Search results for: frequency response function

Authors: Alicja Reuben, Amira Annabi

Abstract:

In this paper, we explore the relationship between the selection of valuation techniques by investment banks and the banks’ risk perceptions and performance in the context of the theory of performativity. We use inferential statistics to study these relationships by building a unique dataset based on the disclosure of 12 investment banks’ 2012-2015 annual financial statements. Moreover, we create two constructs, namely intensity of use and risk perception. We measure the intensity of use as a frequency metric of how often a particular bank adopts valuation techniques for a particular asset or liability. We measure risk perception based on disclosed ranges of values for unobservable inputs. Our results are twofold: we find a significant negative correlation between (1) intensity of use and investment bank performance and (2) intensity of use and risk perception. These results indicate that a performative process takes place, and the valuation techniques are enacting their environment.

Keywords: language, linguistics, performativity, financial techniques

Procedia PDF Downloads 151

Authors: D. Pogliana, A. Maso, N. Milani, D. Panzin, S. Rivaroli, J. Konin

Abstract:

This case aims to identify the role of movement quality during the final stage of return to sport (RTS) in a male amateur football player 13 years old after passing the acute phase of the bilateral Osgood-Schlatter disease (OSD). The patient, after a year from passing the acute phase of OSD with the abstention of physical activity, reports bilateral anterior knee pain at the beginning of the football sport activity. Interventions: After the orthopedist check, who recommended physiotherapy sessions for the correction of motor patterns and the isometric reinforcement of the muscles of the quadriceps, the rehabilitation intervention was developed in 7 weeks through 14 sessions of neuro-motor training (NMT) with a frequency of two weekly sessions and six sessions of muscle-strengthening with a frequency of one weekly session. The sessions of NMT were carried out through free body exercises (or with overloads) with visual bio-feedback with the help of two cameras (one with anterior vision and one with lateral vision of the subject) and a big touch screen. The aim of these sessions of NMT was to modify the dysfunctional motor patterns evaluated by the 2D motion analysis test. The test was carried out at the beginning and at the end of the rehabilitation course and included five movements: single-leg squat (SLS), drop jump (DJ), single-leg hop (SLH), lateral shuffle (LS), and change of direction (COD). Each of these movements was evaluated through the video analysis of dynamic valgus knee, pelvic tilt, trunk control, shock absorption, and motor strategy. A free image analysis software (Kinovea) was then used to calculate scores. Results: Baseline assessment of the subject showed a total score of 59% on the right limb and 64% on the left limb (considering an optimal score above 85%) with large deficits in shock absorption capabilities, the presence of dynamic valgus knee, and dysfunctional motor strategies defined “quadriceps dominant.” After six weeks of training, the subject achieved a total score of 80% on the right limb and 86% on the left limb, with significant improvements in shock absorption capabilities, the presence of dynamic knee valgus, and the employment of more hip-oriented motor strategies on both lower limbs. The improvements shown in dynamic knee valgus, greater hip-oriented motor strategies, and improved shock absorption identified through six weeks of the NMT program can help a teenager amateur football player to manage the anterior knee pain during sports activity. In conclusion, NMT was a good choice to help a 13 years old male amateur football player to return to performance without pain after OSD and can also be used with all this type of athletes of the other teams' sports.

Keywords: movement analysis, neuro-motor training, knee pain, movement strategies

Procedia PDF Downloads 122

Authors: Yu Chen, Seong-Jin Kim, Jaehoon Chung

Abstract:

High throughput cells counting and sizing are often required for biomedical applications. Here we report design, fabrication and validating of a micro-machined Coulter counter device with multiple-channel to realize such application for low cost. Multiple vertical through-holes were fabricated on a silicon chip, combined with the PDMS micro-fluidics channel that serves as the sensing channel. In order to avoid the crosstalk introduced by the electrical connection, instead of measuring the current passing through, the potential of each channel is monitored, thus the high throughput is possible. A peak of the output potential can be captured when the cell/particle is passing through the microhole. The device was validated by counting and sizing the polystyrene beads with diameter of 6 μm, 10 μm and 15 μm. With the sampling frequency to be set at 100 kHz, up to 5000 counts/sec for each channel can be realized. The counting and enumeration of MCF7 cancer cells are also demonstrated.

Keywords: Coulter counter, cell enumeration, high through-put, cell sizing

Procedia PDF Downloads 605

Authors: Mahesh Suresh Kumawat

Abstract:

Steel concrete composite construction means the concrete slab is connected to the steel beam with the help of shear connectors so that they act as a single unit. In the present work, steel concrete composite with RCC options are considered for comparative study of G+9 story commercial building which is situated in earthquake zone-III and for earthquake loading, the provisions of IS: 1893(Part1)-2002 is considered. A three dimensional modeling and analysis of the structure are carried out with the help of SAP 2000 software. Equivalent Static Method of Analysis and Response spectrum analysis method are used for the analysis of both Composite & R.C.C. structures. The results are compared and it was found that composite structure is more economical.

Keywords: composite beam, column, RCC column, RCC beam, shear connector, SAP 2000 software

Procedia PDF Downloads 445

Authors: Naim Suleyman Ting, Yakup Sahin, Ismail Aksoy

Abstract:

This paper presents a zero voltage transition-zero current transition (ZVT-ZCT)-PWM DC-DC boost converter with direct power transfer. In this converter, the main switch turns on with ZVT and turns off with ZCT. The auxiliary switch turns on and off with zero current switching (ZCS). The main diode turns on with ZVS and turns off with ZCS. Besides, the additional current or voltage stress does not occur on the main device. The converter has features as simple structure, fast dynamic response and easy control. Also, the proposed converter has direct power transfer feature as well as excellent soft switching techniques. In this study, the operating principle of the converter is presented and its operation is verified for 1 kW and 100 kHz model.

Keywords: direct power transfer, boost converter, zero-voltage transition, zero-current transition

Procedia PDF Downloads 811

Authors: J. R. Wang, H. T. Lin, Y. Chiang, H. C. Chen, C. Shih

Abstract:

Kuosheng Nuclear Power Plant (NPP) is located on the northern coast of Taiwan. Its nuclear steam supply system is a type of BWR/6 designed and built by General Electric on a twin unit concept. First, the methodology of Kuosheng NPP SPU (Stretch Power Uprate) safety analysis TRACE/SNAP model was developed in this research. Then, in order to estimate the safety of Kuosheng NPP under the more severe condition, the SBO (Station Blackout) + LOCA (Loss-of-Coolant Accident) transient analysis of Kuosheng NPP SPU TRACE/SNAP model was performed. Besides, the animation model of Kuosheng NPP was presented using the animation function of SNAP with TRACE/SNAP analysis results.

Keywords: TRACE, safety analysis, BWR/6, severe accident

Procedia PDF Downloads 703

Authors: Nancy Ann P. Gonzales, Serafin L. Ngohayon

Abstract:

The Nurturing Indigenous Knowledge Experts (NIKE) among the young generation in Ifugao was a project in Ifugao, Philippines spearheaded by the Ifugao State University (IFSU) and was sponsored by the UNESCO Association in Japan. Through the project, he Ifugao Indigenous Knowledge Workbook was developed. It contains nine chapters. The workbook was pilot-tested to students who had IK classes. The descriptive survey method of research was used. A questionnaire was used to gather data from first year Bachelor of Elementary Education and Bachelor of Political Science students. Frequency count, percentage and mean were computed. T-test was used to determine if there exists significant difference on knowledge gained before and after IK was taught to the students. Results revealed that the respondents have an increased level of IK in all the areas covered in the NIKE workbook after they enrolled in their classes. It is alarming to note that the students are knowledgeable about IK but they are not practicing it. However, according to the respondents, they will apply their IK through teaching after graduation.

Keywords: curriculum, elders, Indigenous knowledge, and students

Procedia PDF Downloads 350

Authors: Najebah Alsaleh, Nirpendra Singh, Udo Schwingenschlogl

Abstract:

The electronic and transport properties of bulk and monolayer CuSbS2 and CuSbSe2 are determined by using density functional theory and semiclassical Boltzmann transport theory, in order to investigate the role of interlayer coupling for the thermoelectric properties. The calculated band gaps of the bulk compounds are in agreement with experiments and significantly higher than those of the monolayers, which thus show lower Seebeck coefficients. Since also the electrical conductivity is lower, the monolayers are characterized by lower power factors. Therefore, interlayer coupling is found to be essential for the excellent thermoelectric response of CuSbS2 and CuSbSe2, even though it is weak.

Keywords: density functional theory, thermoelectric, electronic properties, monolayer

Procedia PDF Downloads 316

Authors: Yusuf S. Dambatta, Ahmed A. D. Sarhan

Abstract:

Fused deposition modelling (FDM) is one of the most prominent rapid prototyping (RP) technologies which is being used to efficiently fabricate CAD 3D geometric models. However, the process is coupled with many drawbacks, of which the surface quality of the manufactured RP parts is among. Hence, studies relating to improving the surface roughness have been a key issue in the field of RP research. In this work, a technique of modelling the surface roughness in FDM is presented. Using experimentally measured surface roughness response of the FDM parts, an ANFIS prediction model was developed to obtain the surface roughness in the FDM parts using the main critical process parameters that affects the surface quality. The ANFIS model was validated and compared with experimental test results.

Keywords: surface roughness, fused deposition modelling (FDM), adaptive neuro fuzzy inference system (ANFIS), orientation

Procedia PDF Downloads 448

Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

Abstract:

As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

Procedia PDF Downloads 48

Authors: Ji Eun Shin, Byung Ho Jung, Dong Hoon Lim

Abstract:

It is almost impossible to store or analyze big data increasing exponentially with traditional technologies. Hadoop is a new technology to make that possible. R programming language is by far the most popular statistical tool for big data analysis based on distributed processing with Hadoop technology. With RHadoop that integrates R and Hadoop environment, we implemented parallel multiple regression analysis with different sizes of actual data. Experimental results showed our RHadoop system was much faster as the number of data nodes increases. We also compared the performance of our RHadoop with lm function and big lm packages available on big memory. The results showed that our RHadoop was faster than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

Keywords: big data, Hadoop, parallel regression analysis, R, RHadoop

Procedia PDF Downloads 429

Authors: Takayuki Konishi, Kakeru Yazawa, Mariko Kondo

Abstract:

This study examines developmental change in the production of epenthetic vowels by Japanese learners of English in relation to acquisition of L2 English speech rhythm. Seventy-two Japanese learners of English in the J-AESOP corpus were divided into lower- and higher-level learners according to their proficiency score and the frequency of vowel epenthesis. Three learners were excluded because no vowel epenthesis was observed in their utterances. The analysis of their read English speech data showed no statistical difference between lower- and higher-level learners, implying the absence of any developmental change in durations of epenthetic vowels. This result, together with the findings of previous studies, will be discussed in relation to the transfer of L1 phonology and manifestation of L2 English rhythm.

Keywords: vowel epenthesis, Japanese learners of English, L2 speech corpus, speech rhythm

Procedia PDF Downloads 260

Authors: Krešimir Begović, Miloš Rydval, Jan Tumajer, Kristyna Svobodová, Thomas Langbehn, Yumei Jiang, Vojtech Čada, Vaclav Treml, Ryszard Kaczka, Miroslav Svoboda

Abstract:

Environmental changes have increased the frequency and intensity of climatic extremes, particularly hotter droughts, leading to altered tree growth patterns and multi-year lags in tree recovery. The effects of shifting climatic conditions on tree growth are inhomogeneous across species’ natural distribution ranges, with large spatial heterogeneity and inter-population variability, but generally have significant consequences for contemporary forest dynamics and future ecosystem functioning. Despite numerous studies on the impacts of regional drought effects, large uncertainties remain regarding the mechanistic basis of drought legacy effects on wood formation and the ability of individual species to cope with increasingly drier growing conditions and rising year-to-year climatic variability. To unravel the complexity of climate-growth interactions and assess species-specific responses to severe droughts, we combined forward modeling of tree growth (VS-lite model) with correlation analyses against climate (temperature, precipitation, and the SPEI-3 moisture index) and growth responses to extreme drought events from multiple tree-ring parameters (tree-width and blue intensity parameters). We used an extensive dataset with over 1000 tree-ring samples from 23 nature forest reserves across an altitudinal range in Czechia and Slovakia. Our results revealed substantial spatiotemporal variability in growth responses to summer season temperature and moisture availability across species and tree-ring parameters. However, a general trend of increasing spring moisture-growth sensitivity in recent decades was observed in the Scots pine mountain forests and lowland forests of both species. The VS-lite model effectively captured nonstationary climate-growth relationships and accurately estimated high-frequency growth variability, indicating a significant incidence of regional drought events and growth reductions. Notably, growth reductions during extreme drought years and discrete legacy effects identified in individual wood components were most pronounced in the lowland forests. Together with the observed growth declines in recent decades, these findings suggest an increasing vulnerability of Norway spruce and Scots pine in dry lowlands under intensifying climatic constraints.

Keywords: dendroclimatology, Vaganova–Shashkin lite, conifers, central Europe, drought, blue intensity

Procedia PDF Downloads 55

Authors: Zhengyi Kong, Seung-Eock Kim

Abstract:

Single angle connections, which are bolted to the beam web and the column flange, are studied to investigate moment-rotation behavior. Elastic–perfectly plastic material behavior is assumed. ABAQUS software is used to analyze the nonlinear behavior of a single angle connection. The same geometric and material conditions with Yanglin Gong’s test are used for verifying finite element models. Since Kishi and Chen’s Power model and Lee and Moon’s Log model are accurate only for a limited range, simpler and more accurate hyperbolic function models are proposed. The equation for calculating rotation at ultimate moment is first proposed.

Keywords: finite element method, moment and rotation, rotation at ultimate moment, single-web angle connections

Procedia PDF Downloads 419

Authors: M. Tiachachat, M. Mihoubi

Abstract:

The Bell polynomials are special polynomials in combinatorial analysis that have a wide range of applications in mathematics. They have interested many authors. The exponential partial Bell polynomials have been well reduced to some special combinatorial sequences. Numerous researchers had already been interested in the above polynomials, as evidenced by many articles in the literature. Inspired by this work, in this work, we propose a family of special polynomials named after the 2-successive partial Bell polynomials. Using the combinatorial approach, we prove the properties of these numbers, derive several identities, and discuss some special cases. This family includes well-known numbers and polynomials such as Stirling numbers, Bell numbers and polynomials, and so on. We investigate their properties by employing generating functions

Keywords: 2-associated r-Stirling numbers, the exponential partial Bell polynomials, generating function, combinatorial interpretation

Procedia PDF Downloads 102

Authors: M. Karami Khorramabadi, A. R. Nezamabadi

Abstract:

This paper studies free vibration of functionally graded beams Subjected to Axial Load that is simply supported at both ends lies on a continuous elastic foundation. The displacement field of beam is assumed based on Engesser-Timoshenko beam theory. The Young's modulus of beam is assumed to be graded continuously across the beam thickness. Applying the Hamilton's principle, the governing equation is established. Resulting equation is solved using the Euler's Equation. The effects of the constituent volume fractions and foundation coefficient on the vibration frequency are presented. To investigate the accuracy of the present analysis, a compression study is carried out with a known data.

Keywords: functionally graded beam, free vibration, elastic foundation, Engesser-Timoshenko beam theory

Procedia PDF Downloads 410

Authors: C. Elavarasi, T. Shanmuganantham

Abstract:

A coplanar waveguide (CPW) feed is presented, and comprising a split ring resonator (SRR) loaded fractal with water lily shape is used for multi band applications. The impedance matching of the antenna is determined by the number of Koch curve fractal unit cells. The antenna is designed on a FR4 substrate with a permittivity of ε_{r =} 4.4 and size of 14 x 16 x 1.6 mm³ to generate multi resonant mode at 3.8 GHz covering S band, 8.68 GHz at X band, 13.96 GHz at Ku band, and 19.74 GHz at K band with reflection coefficient better than -10 dB. Simulation results show that the antenna exhibits the desired voltage standing wave ratio (VSWR) level and radiation patterns across the wide frequency range. The fundamental parameters of the antenna such as return loss, VSWR, good radiation pattern with reasonable gain across the operating bands are obtained.

Keywords: fractal, metamaterial, split ring resonator, waterlily shape

Procedia PDF Downloads 269

Authors: Godwin Chigozie Okpara, William Chimee Nwaoha

Abstract:

The paper set out to stress on how financial inclusion index could be calculated and also investigated the impact of inclusive finance on inclusive growth in an emerging economy. In the light of these objectives, chi-wins method was used to calculate indexes of financial inclusion while co-integration and error correction model were used for evaluation of the impact of financial inclusion on inclusive growth. The result of the analysis revealed that financial inclusion while having a long-run relationship with GDP growth is an insignificant function of the growth of the economy. The speed of adjustment is correctly signed and significant. On the basis of these results, the researchers called for tireless efforts of government and banking sector in promoting financial inclusion in developing countries.

Keywords: chi-wins index, co-integration, error correction model, financial inclusion

Procedia PDF Downloads 644

Authors: Milorad Pavlovic, Sebastiano Trevisani, Antonella Cecchi

Abstract:

In this paper, a procedure for the evaluation of seismic behavior of slender masonry structures (towers, bell towers, chimneys, minarets, etc.) is presented. The presented procedure is based on a full three-dimensional modal analyses and frequency measurements. As well-known, masonry is a composite material formed by bricks, or stone blocks, and mortar arranged more or less regularly and adopted for many centuries as structural material. Dynamic actions may represent the major risk of collapse of brickworks, and despite the progress achieved so far in science and mechanics; the assessment of their seismic performance remains a challenging task. Then, reliable physical and numerical models are worthy of recommendation. In this paper, attention is paid to the historical bell tower of the Basilica of Santa Maria Gloriosa dei Frari - usually called Frari - one of the greatest churches in Venice, Italy.

Keywords: bell tower, FEM, masonry, modal analysis, non-destructive testing

Procedia PDF Downloads 348

Authors: M. El Hajji, A. Hallaoui, L. Bazzi, A. Benlhachemi, Lh. Bazzi, M. Hilali, O. Jbara, A. Tara, B. Bakiz

Abstract:

The cathodic electro deposition of the cuprite Cu2O by chrono potentiometry is performed on two types of electrodes "titanium and stainless steel", in a basic medium containing the precursor of copper. The plot produced vs SCE, shows the formation of a brown layer on the electrode surface. The chrono potentiometric recording made between - 0.2 and - 1 mA/cm2, has allowed us to have a deposit having different morphologies and structural orientation obtained as a function of the variation of many parameters. The morphology, the size of crystals, and the phase of the deposits produced were studied by conventional techniques of analysis of the solid, particularly the X-ray diffraction (XRD), scanning electron microscopy analysis (SEM) and quantitative chemical analysis (EDS). The results will be presented and discussed, they show that the majority of deposits are pure and uniform.

Keywords: cathodic electrodeposition, cuprite Cu2O, XRD, SEM, EDS analysis

Procedia PDF Downloads 416

Authors: Ankita Dixit

Abstract:

A conference call using a mobile refers to a telephonic call in which several people talks to each other simultaneously. This is one of the most eminent features nowadays. This concept is already existing using LTE technology for mobile phones supporting SIM cards. Hence, currently, a conference call is possible only with the support of a SIM card, i.e., a Mobile operator. Bluetooth is a short-range wireless technology that is used for exchanging data between devices placed over short distances (up to 240 meters). This is a booming technology that is easily and freely available and has no dependency on network operators. Our study work proposes a smart system to enable conference calls with more than two mobile users without SIM support to communicate with each other simultaneously. The AI-based proposed solution will be self–governed, self-learned and will be intelligent enough to smartly switch between all callers connected via Bluetooth in a conference call. This proposed solution system will greatly increase the potential of using Bluetooth technology from a wider applicability perspective of conference calls, which is currently only possible over LTE mobiles.

Keywords: conference call, bluetooth, AI, frequency hopping, piconet, scatter net

Procedia PDF Downloads 74

Authors: Elham Sharifineyestani, Mohammad Farshchin

Abstract:

Tropical cyclones are one of the most expensive and deadliest natural disasters. They cause heavy rainfall and serious flash flooding that result in billions of dollars of damage and considerable mortality each year in the United States. Prediction of the frequency of tropical cyclone-induced rainfall events can be helpful in emergency planning and flood risk management. In this study, we have developed a machine-learning model to predict the exceedance frequencies of tropical cyclone-induced rainfall events in the United States. Model results show a satisfactory agreement with available observations. To examine the effectiveness of our approach, we also have compared the result of our predictions with the exceedance frequencies predicted using a physics-based rainfall model by Feldmann.

Keywords: flash flooding, tropical cyclones, frequencies, machine learning, risk management

Procedia PDF Downloads 239

Authors: Liu Shengnan, Sun Liping, Zhu Jianxun

Abstract:

Based on three dimensional potential flow theory and hinged rigid body motion equations, structure RAOs of Pelamis wave energy converter is analyzed. Analysis of numerical simulation is carried out on Pelamis in the irregular wave conditions, and the motion response of structures and total generated power is obtained. The paper analyzes influencing factors on the average power including diameter of floating body, section form of floating body, draft, hinged stiffness and damping. The optimum parameters are achieved in Zhejiang Province. Compared with the results of the pelamis experiment made by Glasgow University, the method applied in this paper is feasible.

Keywords: Pelamis, hinge, floating multibody, wave energy

Procedia PDF Downloads 461

Authors: S. Periyadharshini, K. Ramkumar, S. Jayalalitha, M. GuruPrasath, R. Manikandan

Abstract:

This paper presents a formulation and solution for industrial load management and product grade problem. The formulation is created using linear programming technique thereby optimizing the electricity cost by scheduling the loads satisfying the process, storage, time zone and production constraints which will create an impact of reducing maximum demand and thereby reducing the electricity cost. Product grade problem is formulated using integer linear programming technique of optimization using lingo software and the results show that overall increase in profit margin. In this paper, time of use tariff is utilized and this technique will provide significant reductions in peak electricity consumption.

Keywords: cement industries, integer programming, optimal formulation, objective function, constraints

Procedia PDF Downloads 581

Authors: Ravindra B. Patil, P. Krishnamoorthy, Shriram Sethuraman

Abstract:

This work proposes a novel Gaussian Mixture Model (GMM) based approach for accurate tracking of the arterial wall and subsequent computation of the distension waveform using Radio Frequency (RF) ultrasound signal. The approach was evaluated on ultrasound RF data acquired using a prototype ultrasound system from an artery mimicking flow phantom. The effectiveness of the proposed algorithm is demonstrated by comparing with existing wall tracking algorithms. The experimental results show that the proposed method provides 20% reduction in the error margin compared to the existing approaches in tracking the arterial wall movement. This approach coupled with ultrasound system can be used to estimate the arterial compliance parameters required for screening of cardiovascular related disorders.

Keywords: distension waveform, Gaussian Mixture Model, RF ultrasound, arterial wall movement

Procedia PDF Downloads 496

Authors: Seyedeh Sajedeh Salehi

Abstract:

The Regulation No. 1215/2012/EC also known as the Brussels I Regulation (Recast) deals with jurisdictional disputes in civil and commercial matters. The main aim of the Recast (as in-line with its predecessor Regulation) is to bring a reform in procuring more simplified and faster circulation of civil and commercial judgments within the EU. Hence it is significant to take a closer look at the function of this regulatory tool. Therefore, the main objective of this paper is to analyze a clear understanding of the post-Recast situation on e-commerce relevant jurisdictional matters. The e-consumer protection and the choice-of-court agreements along with the position of the Court of Justice of the European Union in its decisions within the Recast Regulation will be also taken into consideration throughout this paper.

Keywords: choice-of-court agreements, consumer protection, e-commerce, jurisdiction, Recast Brussels I Regulation

Procedia PDF Downloads 302

Authors: Li Dan, Zhao Junsuo, Zhang Wenjun

Abstract:

Aiming at the shortcomings of the Quantum Genetic Algorithm such as the multimodal function optimization problems easily falling into the local optimum, and vulnerable to premature convergence due to no closely relationship between individuals, the paper presents an Improved Many Worlds Quantum Genetic Algorithm (IMWQGA). The paper using the concept of Many Worlds; using the derivative way of parallel worlds’ parallel evolution; putting forward the thought which updating the population according to the main body; adopting the transition methods such as parallel transition, backtracking, travel forth. In addition, the algorithm in the paper also proposes the quantum training operator and the combinatorial optimization operator as new operators of quantum genetic algorithm.

Keywords: quantum genetic algorithm, many worlds, quantum training operator, combinatorial optimization operator

Procedia PDF Downloads 731

Authors: Lubna Naz, Munir Ahmad, G. M. Arif

Abstract:

This study analyzes static and dynamic welfare impacts of food price changes for various landholding groups in Pakistan. The study uses three classifications of land ownership, landless, small landowners and large landowners, for analysis. The study uses Panel Survey, Pakistan Rural Household Survey (PRHS) of Pakistan Institute of Development Economics Islamabad, of rural households from two largest provinces (Sindh and Punjab) of Pakistan. The study uses all three waves (2001, 2004 and 2010) of PRHS. This research work makes three important contributions in literature. First, this study uses Quadratic Almost Ideal Demand System (QUAIDS) to estimate demand functions for eight food groups-cereals, meat, milk and milk products, vegetables, cooking oil, pulses and other food. The study estimates food demand functions with Nonlinear Seemingly Unrelated (NLSUR), and employs Lagrange Multiplier and test on the coefficient of squared expenditure term to determine inclusion of squared expenditure term. Test results support the inclusion of squared expenditure term in the food demand model for each of landholding groups (landless, small landowners and large landowners). This study tests for endogeneity and uses control function for its correction. The problem of observed zero expenditure is dealt with a two-step procedure. Second, it creates low price and high price periods, based on literature review. It uses elasticity coefficients from QUAIDS to analyze static and dynamic welfare effects (first and second order Tylor approximation of expenditure function is used) of food price changes across periods. The study estimates compensation variation (CV), money metric loss from food price changes, for landless, small and large landowners. Third, this study compares the findings on welfare implications of food price changes based on QUAIDS with the earlier research in Pakistan, which used other specification of the demand system. The findings indicate that dynamic welfare impacts of food price changes are lower as compared to static welfare impacts for all landholding groups. The static and dynamic welfare impacts of food price changes are highest for landless. The study suggests that government should extend social security nets to landless poor and categorically to vulnerable landless (without livestock) to redress the short-term impact of food price increase. In addition, the government should stabilize food prices and particularly cereal prices in the long- run.

Keywords: QUAIDS, Lagrange multiplier, NLSUR, and Tylor approximation

Procedia PDF Downloads 360

Authors: K. N. Umesh, K. S. Srinivasan

Abstract:

The influence of rotor rub was studied with respect to light rub and heavy rub conditions. The investigations were carried out for both below and above critical speeds. The time domain waveform has revealed truncation of the waveform during rubbing conditions. The quantum of rubbing has been indicated by the quantum of truncation. The orbits for light rub have indicated a single loop whereas for heavy rub multi looped orbits have been observed. In the heavy rub condition above critical speed both sub harmonics and super harmonics are exhibited. The orbit precess in a direction opposite to the direction of the rotation of the rotor. When the rubbing was created above the critical speed the orbit shape was of '8' shape indicating the rotor instability. Super-harmonics and sub-harmonics of vibration signals have been observed for light rub and heavy rub conditions and for speeds above critical.

Keywords: rotor rub, orbital analysis, frequency analysis, vibration signatures

Procedia PDF Downloads 308

Authors: Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

Abstract:

Time series data consist of successive data points collected over a period of time. Accurate prediction of future values is essential for informed decision-making in several real-world applications, including electricity load demand forecasting, lifetime estimation of industrial machinery, traffic planning, weather prediction, and the stock market. Due to their critical relevance and wide application, there has been considerable interest in time series forecasting in recent years. However, the proliferation of sensors and IoT devices, real-time monitoring systems, and high-frequency trading data introduce significant intricate temporal variations, rapid changes, noise, and non-linearities, making time series forecasting more challenging. Classical methods such as Autoregressive integrated moving average (ARIMA) and Exponential Smoothing aim to extract pre-defined temporal variations, such as trends and seasonality. While these methods are effective for capturing well-defined seasonal patterns and trends, they often struggle with more complex, non-linear patterns present in real-world time series data. In recent years, deep learning has made significant contributions to time series forecasting. Recurrent Neural Networks (RNNs) and their variants, such as Long short-term memory (LSTMs) and Gated Recurrent Units (GRUs), have been widely adopted for modeling sequential data. However, they often suffer from the locality, making it difficult to capture local trends and rapid fluctuations. Convolutional Neural Networks (CNNs), particularly Temporal Convolutional Networks (TCNs), leverage convolutional layers to capture temporal dependencies by applying convolutional filters along the temporal dimension. Despite their advantages, TCNs struggle with capturing relationships between distant time points due to the locality of one-dimensional convolution kernels. Transformers have revolutionized time series forecasting with their powerful attention mechanisms, effectively capturing long-term dependencies and relationships between distant time points. However, the attention mechanism may struggle to discern dependencies directly from scattered time points due to intricate temporal patterns. Lastly, Multi-Layer Perceptrons (MLPs) have also been employed, with models like N-BEATS and LightTS demonstrating success. Despite this, MLPs often face high volatility and computational complexity challenges in long-horizon forecasting. To address intricate temporal variations in time series data, this study introduces Times2D, a novel framework that parallelly integrates 2D spectrogram and derivative heatmap techniques. The spectrogram focuses on the frequency domain, capturing periodicity, while the derivative patterns emphasize the time domain, highlighting sharp fluctuations and turning points. This 2D transformation enables the utilization of powerful computer vision techniques to capture various intricate temporal variations. To evaluate the performance of Times2D, extensive experiments were conducted on standard time series datasets and compared with various state-of-the-art algorithms, including DLinear (2023), TimesNet (2023), Non-stationary Transformer (2022), PatchTST (2023), N-HiTS (2023), Crossformer (2023), MICN (2023), LightTS (2022), FEDformer (2022), FiLM (2022), SCINet (2022a), Autoformer (2021), and Informer (2021) under the same modeling conditions. The initial results demonstrated that Times2D achieves consistent state-of-the-art performance in both short-term and long-term forecasting tasks. Furthermore, the generality of the Times2D framework allows it to be applied to various tasks such as time series imputation, clustering, classification, and anomaly detection, offering potential benefits in any domain that involves sequential data analysis.

Keywords: derivative patterns, spectrogram, time series forecasting, times2D, 2D representation

Procedia PDF Downloads 34