Search results for: peak estimation

Authors: Yuzhi Cai

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This talk presents a Bayesian approach to quantile autoregressive (QAR) time series model estimation and forecasting. We establish that the joint posterior distribution of the model parameters and future values is well defined. The associated MCMC algorithm for parameter estimation and forecasting converges to the posterior distribution quickly. We also present a combining forecasts technique to produce more accurate out-of-sample forecasts by using a weighted sequence of fitted QAR models. A moving window method to check the quality of the estimated conditional quantiles is developed. We verify our methodology using simulation studies and then apply it to currency exchange rate data. An application of the method to the USD to GBP daily currency exchange rates will also be discussed. The results obtained show that an unequally weighted combining method performs better than other forecasting methodology.

Keywords: combining forecasts, MCMC, quantile modelling, quantile forecasting, predictive density functions

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Authors: Suresh Palla

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This research paper presents the results of the study on the estimation of fly ash, slag and cement contents in blended and composite cements by novel selective dissolution method. Types of cement samples investigated include OPC with fly ash as performance improver, OPC with slag as performance improver, PPC, PSC and Composite cement confirming to respective Indian Standards. Slag and OPC contents in PSC were estimated by selectively dissolving OPC in stage 1 and selectively dissolving slag in stage 2. In the case of composite cement sample, the percentage of cement, slag and fly ash were estimated systematically by selective dissolution of cement, slag and fly ash in three stages. In the first stage, cement dissolved and separated by leaving the residue of slag and fly ash, designated as R1. The second stage involves gravimetric estimation of fractions of OPC, residue and selective dissolution of fly ash and slag contents. Fly ash content, R2 was estimated through gravimetric analysis. Thereafter, the difference between the R1 and R2 is considered as slag content. The obtained results of cement, fly ash and slag using selective dissolution method showed 10% of standard deviation with the corresponding percentage of respective constituents. The results suggest that this novel selective dissolution method can be successfully used for estimation of OPC and SCMs contents in different types of cements.

Keywords: selective dissolution method , fly ash, ggbfs slag, edta

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Authors: S. B. Provost, Susan Sheng

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An alternative bivariate density estimation methodology is introduced in this presentation. The proposed approach involves estimating the density function associated with the marginal distribution of each of the two variables by means of the saddlepoint approximation technique and applying a bivariate polynomial adjustment to the product of these density estimates. Since the saddlepoint approximation is utilized in the context of density estimation, such estimates are determined from empirical cumulant-generating functions. In the univariate case, the saddlepoint density estimate is itself adjusted by a polynomial. Given a set of observations, the coefficients of the polynomial adjustments are obtained from the sample moments. Several illustrative applications of the proposed methodology shall be presented. Since this approach relies essentially on a determinate number of sample moments, it is particularly well suited for modeling massive data sets.

Keywords: density estimation, empirical cumulant-generating function, moments, saddlepoint approximation

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Authors: Seongsoo Lee

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Motion estimation occupies the heaviest computation in HEVC (high efficiency video coding). Many fast algorithms such as TZS (test zone search) have been proposed to reduce the computation. Still the huge computation of the motion estimation is a critical issue in the implementation of HEVC video codec. In this paper, motion estimator architecture with optimized number of PEs (processing element) is presented by exploiting early termination. It also reduces hardware size by exploiting parallel processing. The presented motion estimator architecture has 8 PEs, and it can efficiently perform TZS with very high utilization of PEs.

Keywords: motion estimation, test zone search, high efficiency video coding, processing element, optimization

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.

Keywords: multi-view, pose estimation, ST-GCN, joint fusion

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Authors: Majid Yazdandoust

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This study, tries to suggest a design method based on displacement using finite difference numerical modeling in reinforcing soil retaining wall with steel strip. In this case, dynamic loading characteristics such as duration, frequency, peak ground acceleration, geometrical characteristics of reinforced soil structure and type of the site are considered to correct the pseudo static method and finally introduce the pseudo static coefficient as a function of seismic performance level and peak ground acceleration. For this purpose, the influence of dynamic loading characteristics, reinforcement length, height of reinforced system and type of the site are investigated on seismic behavior of reinforcing soil retaining wall with steel strip. Numerical results illustrate that the seismic response of this type of wall is highly dependent to cumulative absolute velocity, maximum acceleration, and height and reinforcement length so that the reinforcement length can be introduced as the main factor in shape of failure. Considering the loading parameters, mechanically stabilized earth wall parameters and type of the site showed that the used method in this study leads to most efficient designs in comparison with other methods which are generally suggested in cods that are usually based on limit-equilibrium concept. The outputs show the over-estimation of equilibrium design methods in comparison with proposed displacement based methods here.

Keywords: pseudo static coefficient, seismic performance design, numerical modeling, steel strip reinforcement, retaining walls, cumulative absolute velocity, failure shape

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Authors: Tsui-Tsai Lin

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Cooperative orthogonal frequency division multiplexing (OFDM) transmission, which possesses the advantages of better connectivity, expanded coverage, and resistance to frequency selective fading, has been a more powerful solution for the physical layer in wireless communications. However, such a hybrid scheme suffers from the carrier frequency offset (CFO) effects inherited from the OFDM-based systems, which lead to a significant degradation in performance. In addition, insertion of a cyclic prefix (CP) at each symbol block head for combating inter-symbol interference will lead to a reduction in spectral efficiency. The design on the CFO estimation for the cooperative OFDM system without CP is a suspended problem. This motivates us to develop a low complexity CFO estimator for the cooperative OFDM decode-and-forward (DF) communication system without CP over the multipath fading channel. Especially, using a block-type pilot, the CFO estimation is first derived in accordance with the least square criterion. A reliable performance can be obtained through an exhaustive two-dimensional (2D) search with a penalty of heavy computational complexity. As a remedy, an alternative solution realized with an iteration approach is proposed for the CFO estimation. In contrast to the 2D-search estimator, the iterative method enjoys the advantage of the substantially reduced implementation complexity without sacrificing the estimate performance. Computer simulations have been presented to demonstrate the efficacy of the proposed CFO estimation.

Keywords: cooperative transmission, orthogonal frequency division multiplexing (OFDM), carrier frequency offset, iteration

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Authors: Dalvinder Kaur Mangal

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For the past decade, noise corrupted output measurements have been a fundamental research problem to be investigated. On the other hand, the estimation of the parameters for linear dynamic systems when also the input is affected by noise is recognized as more difficult problem which only recently has received increasing attention. Representations where errors or measurement noises/disturbances are present on both the inputs and outputs are usually called errors-in-variables (EIV) models. These disturbances may also have additive effects which are also considered in this paper. Parameter estimation of false EIV problem using equation error, output error and iterative prefiltering identification schemes with and without additive uncertainty, when only the output observation is corrupted by noise has been dealt in this paper. The comparative study of these three schemes has also been carried out.

Keywords: errors-in-variable (EIV), false EIV, equation error, output error, iterative prefiltering, Gaussian noise

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Authors: Manasa Kalla, Narasimha Raju Chebrolu, Ashok Chatterjee

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We have studied the quantum transport properties of a single molecular transistor in the presence of an external magnetic field using the Keldysh Green function technique. We also used the Anderson-Holstein-Caldeira-Leggett Model to describe the single molecular transistor that consists of a molecular quantum dot (QD) coupled to two metallic leads and placed on a substrate that acts as a heat bath. The phonons are eliminated by the Lang-Firsov transformation and the effective Hamiltonian is used to study the effect of an external magnetic field on the spectral density function, Tunneling Current, Differential Conductance and Spin polarization. A peak in the spectral function corresponds to a possible excitation. In the presence of a magnetic field, the spin-up and spin-down states are degenerate and this degeneracy is lifted by the magnetic field leading to the splitting of the central peak of the spectral function. The tunneling current decreases with increasing magnetic field. We have observed that even the differential conductance peak in the zero magnetic field curve is split in the presence electron-phonon interaction. As the magnetic field is increased, each peak splits into two peaks. And each peak indicates the existence of an energy level. Thus the number of energy levels for transport in the bias window increases with the magnetic field. In the presence of the electron-phonon interaction, Differential Conductance in general gets reduced and decreases faster with the magnetic field. As magnetic field strength increases, the spin polarization of the current is increasing. Our results show that a strongly interacting QD coupled to metallic leads in the presence of external magnetic field parallel to the plane of QD acts as a spin filter at zero temperature.

Keywords: Anderson-Holstein model, Caldeira-Leggett model, spin-polarization, quantum dots

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Authors: Guangyuan Zhao, Nan Huang, Xuesong Han, Xu Huang

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In order to solve the problem of sample dilution in the traditional particle filter algorithm and achieve accurate state estimation in a nonlinear system, a particle filter method based on an improved artificial bee colony (ABC) algorithm was proposed. The algorithm simulated the process of bee foraging and optimization and made the high likelihood region of the backward probability of particles moving to improve the rationality of particle distribution. The opposition-based learning (OBL) strategy is introduced to optimize the initial population of the artificial bee colony algorithm. The convergence factor is introduced into the neighborhood search strategy to limit the search range and improve the convergence speed. Finally, the crossover and mutation operations of the genetic algorithm are introduced into the search mechanism of the following bee, which makes the algorithm jump out of the local extreme value quickly and continue to search the global extreme value to improve its optimization ability. The simulation results show that the improved method can improve the estimation accuracy of particle filters, ensure the diversity of particles, and improve the rationality of particle distribution.

Keywords: particle filter, impoverishment, state estimation, artificial bee colony algorithm

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Authors: Babatunde Dosumu, Obuks Ejohwomu, Akilu Yunusa-Kaltungo

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Cost estimation in construction is often difficult, particularly when dealing with risks and uncertainties, which are inevitable and peculiar to developing countries like Nigeria. Direct consequences of these are major deviations in cost, duration, and quality. The fundamental aim of this study is to develop a framework for assessing the impacts of risk on cost estimation, which in turn causes variabilities between contract sum and final account. This is very important, as initial estimates given to clients should reflect the certain magnitude of consistency and accuracy, which the client builds other planning-related activities upon, and also enhance the capabilities of construction industry professionals by enabling better prediction of the final account from the contract sum. In achieving this, a systematic literature review was conducted with cost variability and construction projects as search string within three databases: Scopus, Web of science, and Ebsco (Business source premium), which are further analyzed and gap(s) in knowledge or research discovered. From the extensive review, it was found that factors causing deviation between final accounts and contract sum ranged between 1 and 45. Besides, it was discovered that a cost estimation framework similar to Building Cost Information Services (BCIS) is unavailable in Nigeria, which is a major reason why initial estimates are very often inconsistent, leading to project delay, abandonment, or determination at the expense of the huge sum of money invested. It was concluded that the development of a cost estimation framework that is adjudged an important tool in risk shedding rather than risk-sharing in project risk management would be a panacea to cost estimation problems, leading to cost variability in the Nigerian construction industry by the time this ongoing Ph.D. research is completed. It was recommended that practitioners in the construction industry should always take into account risk in order to facilitate the rapid development of the construction industry in Nigeria, which should give stakeholders a more in-depth understanding of the estimation effectiveness and efficiency to be adopted by stakeholders in both the private and public sectors.

Keywords: cost variability, construction projects, future studies, Nigeria

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Authors: Kelsey Scanlon

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Introduction: With the rate of female collegiate and professional athletes on the rise in recent decades, fluctuations in physical performance in relation to the menstrual cycle is an important area of study. PURPOSE: The purpose of this research was to compare differences in upper and lower body maximal anaerobic capacities across a single menstrual cycle. Methode: Participants (n=11) met a total of four times; once for familiarization and again on day 1 of menses (follicular phase), day 14 (ovulation), and day 21 (luteal phase) respectively. Upper body power was assessed using a bench press weight of ~50% of the participant’s predetermined 1-repetition maximum (1-RM) on a ballistic measurement system and variables included peak force (N), mean force (N), peak power (W), mean power (W), and peak velocity (m/s). Lower body power output was collected using a standard Wingate test. The variables of interest were anaerobic capacity (w/kg), peak power (W), mean power (W), fatigue index (W/s), and total work (J). Result: Statistical significance was not observed (p > 0.05) in any of the aforementioned variables after completing multiple one ways of analyses of variances (ANOVAs) with repeated measures on time. Conclusion: Within the parameters of this research, neither female upper nor lower body power output differed across the menstrual cycle when analyzed using 50% of one repetition (1RM) maximal bench press and the 30-second maximal effort cycle ergometer Wingate test. Therefore, researchers should not alter their subject populations due to the incorrect assumption that power output may be influenced by the menstrual cycle.

Keywords: anaerobic, athlete, female, power

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Authors: Naoya Ozaki, Takuya Watanabe, Ryosuke Matsumoto, Noriko Fukasawa

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In the metropolitan areas in Japan, in many stations, shopping areas are set up, and escalators and elevators are installed to make the stations be barrier-free. Further, many areas around the stations are being redeveloped. Railway business operators want to know how much effect these circumstances have on attractiveness of the station or number of passengers using the station. So, we performed a questionnaire survey of the station users in the metropolitan areas for finding factors to affect the attractiveness of stations. Then, based on the analysis of the survey, we developed a method to quantitatively evaluate attractiveness of the stations. We also developed an estimation method for number of passengers based on combination of attractiveness of the station quantitatively evaluated and the residential and labor population around the station. Then, we derived precise linear regression models estimating the attractiveness of the station and number of passengers of the station.

Keywords: attractiveness of the station, estimation method, number of passengers of the station, redevelopment around the station, renovation of the station

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Authors: I. V. Pinto, M. R. Sooriyarachchi

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It can be frequently observed that the data arising in our environment have a hierarchical or a nested structure attached with the data. Multilevel modelling is a modern approach to handle this kind of data. When multilevel modelling is combined with a binary response, the estimation methods get complex in nature and the usual techniques are derived from quasi-likelihood method. The estimation methods which are compared in this study are, marginal quasi-likelihood (order 1 & order 2) (MQL1, MQL2) and penalized quasi-likelihood (order 1 & order 2) (PQL1, PQL2). A statistical model is of no use if it does not reflect the given dataset. Therefore, checking the adequacy of the fitted model through a goodness-of-fit (GOF) test is an essential stage in any modelling procedure. However, prior to usage, it is also equally important to confirm that the GOF test performs well and is suitable for the given model. This study assesses the suitability of the GOF test developed for binary response multilevel models with respect to the method used in model estimation. An extensive set of simulations was conducted using MLwiN (v 2.19) with varying number of clusters, cluster sizes and intra cluster correlations. The test maintained the desirable Type-I error for models estimated using PQL2 and it failed for almost all the combinations of MQL. Power of the test was adequate for most of the combinations in all estimation methods except MQL1. Moreover, models were fitted using the four methods to a real-life dataset and performance of the test was compared for each model.

Keywords: goodness-of-fit test, marginal quasi-likelihood, multilevel modelling, penalized quasi-likelihood, power, quasi-likelihood, type-I error

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Authors: Sung Hyun Yoo, In Hwan Choi, Jun Ho Jung, Choon Ki Ahn, Myo Taeg Lim

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Home energy management system (HEMS) has been issued to reduce the power consumption. The HEMS performs electric power control for the indoor electric device. However, HEMS commonly treats the smart devices. In this paper, we suggest the output estimation of home legacy device using the artificial neural fuzzy inference system (ANFIS). This paper discusses the overview and the architecture of the system. In addition, accurate performance of the output estimation using the ANFIS inference system is shown via a numerical example.

Keywords: artificial neural fuzzy inference system (ANFIS), home energy management system (HEMS), smart device, legacy device

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Authors: Renjie Liu, Junshuai Xue, Jiajia Yao, Guanlin Wu, Zumao L, Xueyan Yang, Fang Liu, Zhuang Guo

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Here, we report the study of the performance of AlN/GaN bipolar resonance tunneling diodes (BRTDs) using numerical simulations. The I-V characteristics of BRTDs show double negative differential resistance regions, which exhibit similar peak current density and peak-to-valley current ratio (PVCR). Investigations show that the PVCR can approach 4.6 for the first and 5.75 for the second negative resistance region. The appearance of the two negative differential resistance regions is realized by changing the collector material of conventional GaN RTD to P-doped GaN. As the bias increases, holes in the P-region and electrons in the N-region undergo resonant tunneling, respectively, resulting in two negative resistance regions. The appearance of two negative resistance regions benefits from the high AlN barrier and the precise regulation of the potential well thickness. This result shows the promise of GaN BRTDs in the development of multi-valued logic circuits.

Keywords: GaN bipolar resonant tunneling diode, double negative differential resistance regions, peak to valley current ratio, multi-valued logic

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Authors: Jefferson Hernandez, Juan Padilla

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Estimation of price elasticity of demand is a valuable tool for the task of price settling. Given its relevance, it is an active field for microeconomic and statistical research. Price elasticity in the industry of oil and gas, in particular for fuels sold in gas stations, has shown to be a challenging topic given the market and state restrictions, and underlying correlations structures between the types of fuels sold by the same gas station. This paper explores the Lotka-Volterra model for the problem for price elasticity estimation in the context of fuels; in addition, it is introduced multivariate random effects with the purpose of dealing with errors, e.g., measurement or missing data errors. In order to model the underlying correlation structures, the Inverse-Wishart, Hierarchical Half-t and LKJ distributions are studied. Here, the Bayesian paradigm through Markov Chain Monte Carlo (MCMC) algorithms for model estimation is considered. Simulation studies covering a wide range of situations were performed in order to evaluate parameter recovery for the proposed models and algorithms. Results revealed that the proposed algorithms recovered quite well all model parameters. Also, a real data set analysis was performed in order to illustrate the proposed approach.

Keywords: price elasticity, volume, correlation structures, Bayesian models

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Authors: Gichun Cha, Byoungjoon Yu, Jihwan Park, Minsoo Park, Junghyun Im, Sehwan Park, Sujung Sin, Seunghee Park

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The goal of this research is to estimate a structural shape change using terrestrial laser scanning. This study proceeds with development of data reduction and shape change estimation algorithm for large-capacity scan data. The point cloud of scan data was converted to voxel and sampled. Technique of shape estimation is studied to detect changes in structure patterns, such as skyscrapers, bridges, and tunnels based on large point cloud data. The point cloud analysis applies the octree data structure to speed up the post-processing process for change detection. The point cloud data is the relative representative value of shape information, and it used as a model for detecting point cloud changes in a data structure. Shape estimation model is to develop a technology that can detect not only normal but also immediate structural changes in the event of disasters such as earthquakes, typhoons, and fires, thereby preventing major accidents caused by aging and disasters. The study will be expected to improve the efficiency of structural health monitoring and maintenance.

Keywords: terrestrial laser scanning, point cloud, shape information model, displacement measurement

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Authors: Ranojoy Dutta

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HVAC equipment capacity has a direct impact on occupant comfort and energy consumption of a building. Glazing gains, especially in buildings with high window area, can be a significant contributor to the total peak load on the HVAC system, leading to over-sized systems that mostly operate at poor part load efficiency. In addition, radiant temperature, which largely drives occupant comfort in glazed perimeter zones, is often not effectively controlled despite the HVAC being designed to meet the air temperature set-point. This is due to short wave solar radiation transmitted through windows, that is not sensed by the thermostat until much later when the thermal mass in the room releases the absorbed solar heat to the indoor air. The implication of this phenomenon is increased cooling energy despite poor occupant comfort. EC glazing can significantly eliminate direct solar transmission through windows, reducing both the space cooling loads for the building and improving comfort for occupants near glazing. This paper will review the exact mechanism of how EC glazing would reduce the peak load under design day conditions, leading to reduced cooling capacity vs regular high-performance glazing. Since glazing heat transfer only affects the sensible load, system sizing will be evaluated both with and without the availability of a DOAS to isolate the downsizing potential of the primary cooling equipment when outdoor air is conditioned separately. Given the dynamic nature of glazing gains due to the sun’s movement, effective peak load mitigation with EC requires an automated control system that can predict solar movement and radiation levels so that the right tint state with the appropriate SHGC is utilized at any given time for a given façade orientation. Such an automated EC product will be evaluated for a prototype commercial office model situated in four distinct climate zones.

Keywords: electrochromic glazing, peak sizing, thermal comfort, glazing load

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Authors: Jing Wu, Wei Lv, Yibing Li, Yuanfan You

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The separation of speech signals has become a research hotspot in the field of signal processing in recent years. It has many applications and influences in teleconferencing, hearing aids, speech recognition of machines and so on. The sounds received are usually noisy. The issue of identifying the sounds of interest and obtaining clear sounds in such an environment becomes a problem worth exploring, that is, the problem of blind source separation. This paper focuses on the under-determined blind source separation (UBSS). Sparse component analysis is generally used for the problem of under-determined blind source separation. The method is mainly divided into two parts. Firstly, the clustering algorithm is used to estimate the mixing matrix according to the observed signals. Then the signal is separated based on the known mixing matrix. In this paper, the problem of mixing matrix estimation is studied. This paper proposes an improved algorithm to estimate the mixing matrix for speech signals in the UBSS model. The traditional potential algorithm is not accurate for the mixing matrix estimation, especially for low signal-to noise ratio (SNR).In response to this problem, this paper considers the idea of an improved potential function method to estimate the mixing matrix. The algorithm not only avoids the inuence of insufficient prior information in traditional clustering algorithm, but also improves the estimation accuracy of mixing matrix. This paper takes the mixing of four speech signals into two channels as an example. The results of simulations show that the approach in this paper not only improves the accuracy of estimation, but also applies to any mixing matrix.

Keywords: DBSCAN, potential function, speech signal, the UBSS model

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Authors: Fariza Yunus, Jasmee Jaafar, Zamalia Mahmud, Nurul Nisa’ Khairul Azmi, Nursalleh K. Chang, Nursalleh K. Chang

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Variation of air temperature from one place to another is cause by air temperature controls. In general, the most important control of air temperature is elevation. Another significant independent variable in estimating air temperature is the location of meteorological stations. Distances to coastline and land use type are also contributed to significant variations in the air temperature. On the other hand, in homogeneous terrain direct interpolation of discrete points of air temperature work well to estimate air temperature values in un-sampled area. In this process the estimation is solely based on discrete points of air temperature. However, this study presents that air temperature controls also play significant roles in estimating air temperature over homogenous terrain of Peninsular Malaysia. An Inverse Distance Weighting (IDW) interpolation technique was adopted to generate continuous data of air temperature. This study compared two different datasets, observed mean monthly data of T, and estimation error of T–T’, where T’ estimated value from a multiple regression model. The multiple regression model considered eight independent variables of elevation, latitude, longitude, coastline, and four land use types of water bodies, forest, agriculture and build up areas, to represent the role of air temperature controls. Cross validation analysis was conducted to review accuracy of the estimation values. Final results show, estimation values of T–T’ produced lower errors for mean monthly mean air temperature over homogeneous terrain in Peninsular Malaysia.

Keywords: air temperature control, interpolation analysis, peninsular Malaysia, regression model, air temperature

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Authors: Juliana C. Alencar, Monica Ferreira do Amaral Porto

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The blue-green infrastructure in recent years has been pointed out as a possibility to increase the environmental quality of watersheds. The regulation ecosystem services brought by these areas are many, such as the improvement of the air quality of the air, water, soil, microclimate, besides helping to control the peak flows and to promote the quality of life of the population. This study proposes a blue-green infrastructure scenario for the Jaguaré watershed, located in the western zone of the São Paulo city in Brazil. Based on the proposed scenario, it was verified the impact of the adoption of the blue and green infrastructure in the control of the peak flow of the basin, the benefits for the avifauna that are also reflected in the flora and finally, the quantification of the regulation ecosystem services brought by the adoption of the scenario proposed. A survey of existing green areas and potential areas for expansion and connection of these areas to form a network in the watershed was carried out. Based on this proposed new network of green areas, the peak flow for the proposed scenario was calculated with the help of software, ABC6. Finally, a survey of the ecosystem services contemplated in the proposed scenario was made. It was possible to conclude that the blue and green infrastructure would provide several regulation ecosystem services for the watershed, such as the control of the peak flow, the connection frame between the forest fragments that promoted the environmental enrichment of these fragments, improvement of the microclimate and the provision of leisure areas for the population.

Keywords: green and blue infrastructure, sustainable drainage, urban waters, ecosystem services

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Authors: Muhammad Nouman Qureshi, Muhammad Hanif

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Adaptive cluster sampling (ACS) is specifically developed for the estimation of highly clumped populations and applied to a wide range of situations like animals of rare and endangered species, uneven minerals, HIV patients and drug users. In this paper, we proposed a generalized semi-exponential estimator with two auxiliary variables under the framework of ACS design. The expressions of approximate bias and mean square error (MSE) of the proposed estimator are derived. Theoretical comparisons of the proposed estimator have been made with existing estimators. A numerical study is conducted on real and artificial populations to demonstrate and compare the efficiencies of the proposed estimator. The results indicate that the proposed generalized semi-exponential estimator performed considerably better than all the adaptive and non-adaptive estimators considered in this paper.

Keywords: auxiliary information, adaptive cluster sampling, clustered populations, Hansen-Hurwitz estimation

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Authors: Shaher A. I. Shalfawi, Fredrik Hviding, Bjornar Kjellstadli

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The main purpose of this study was to measure the effect of two different strength training methods on muscle strength, muscle mass, fat mass and endurance factors. Fourteen physical education students accepted to participate in this study. The participants were then randomly divided into three groups, traditional training group (TTG), cluster training group (CTG) and control group (CG). TTG consisted of 4 participants aged ( ± SD) (22.3 ± 1.5 years), body mass (79.2 ± 15.4 kg) and height (178.3 ± 11.9 cm). CTG consisted of 5 participants aged (22.2 ± 3.5 years), body mass (81.0 ± 24.0 kg) and height (180.2 ± 12.3 cm). CG consisted of 5 participants aged (22 ± 2.8 years), body mass (77 ± 19 kg) and height (174 ± 6.7 cm). The participants underwent a hypertrophy strength training program twice a week consisting of 4 sets of 10 reps at 70% of one-repetition maximum (1RM), using barbell squat and barbell bench press for 8 weeks. The CTG performed 2 x 5 reps using 10 s recovery in between repetitions and 50 s recovery between sets, while TTG performed 4 sets of 10 reps with 90 s recovery in between sets. Pre- and post-tests were administrated to assess body composition (weight, muscle mass, and fat mass), 1RM (bench press and barbell squat) and a laboratory endurance test (Bruce Protocol). Instruments used to collect the data were Tanita BC-601 scale (Tanita, Illinois, USA), Woodway treadmill (Woodway, Wisconsin, USA) and Vyntus CPX breath-to-breath system (Jaeger, Hoechberg, Germany). Analysis was conducted at all measured variables including time to peak VO2, peak VO2, heart rate (HR) at peak VO2, respiratory exchange ratio (RER) at peak VO2, and number of breaths per minute. The results indicate an increase in 1RM performance after 8 weeks of training. The change in 1RM squat was for the TTG = 30 ± 3.8 kg, CTG = 28.6 ± 8.3 kg and CG = 10.3 ± 13.8 kg. Similarly, the change in 1RM bench press was for the TTG = 9.8 ± 2.8 kg, CTG = 7.4 ± 3.4 kg and CG = 4.4 ± 3.4 kg. The within-group analysis from the oxygen consumption measured during the incremental exercise indicated that the TTG had only a statistical significant increase in their RER from 1.16 ± 0.04 to 1.23 ± 0.05 (P < 0.05). The CTG had a statistical significant improvement in their HR at peak VO2 from 186 ± 24 to 191 ± 12 Beats Per Minute (P < 0.05) and their RER at peak VO2 from 1.11 ± 0.06 to 1.18 ±0.05 (P < 0.05). Finally, the CG had only a statistical significant increase in their RER at peak VO2 from 1.11 ± 0.07 to 1.21 ± 0.05 (P < 0.05). The between-group analysis showed no statistical differences between all groups in all the measured variables from the oxygen consumption test during the incremental exercise including changes in muscle mass, fat mass, and weight (kg). The results indicate a similar effect of hypertrophy strength training irrespective of the methods of the training used on untrained subjects. Because there were no notable changes in body-composition measures, the results suggest that the improvements in performance observed in all groups is most probably due to neuro-muscular adaptation to training.

Keywords: hypertrophy strength training, cluster set, Bruce protocol, peak VO2

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Authors: Linhang Zhu, Hongyu Zhu, Jiahe Liu

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This paper investigated a method of indoor real-time positioning and mapping based on the Manhattan world assumption. In indoor environments, relying solely on feature matching techniques or other geometric algorithms for sensor pose estimation inevitably resulted in cumulative errors, posing a significant challenge to indoor positioning. To address this issue, we adopt the Manhattan world hypothesis to optimize the camera pose algorithm based on feature matching, which improves the accuracy of camera pose estimation. A special processing method was applied to image data frames that conformed to the Manhattan world assumption. When similar data frames appeared subsequently, this could be used to eliminate drift in sensor pose estimation, thereby reducing cumulative errors in estimation and optimizing mapping and positioning. Through experimental verification, it is found that our method achieves high-precision real-time positioning in indoor environments and successfully generates maps of indoor environments. This provides effective technical support for applications such as indoor navigation and robot control.

Keywords: Manhattan world hypothesis, real-time positioning and mapping, feature matching, loopback detection

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Authors: Mudafara Bengleil

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Estimation of the magnitude and causes of poisoning was the objective of the current study. A retrospective study of medical records of all poisoning children admitted to Benghazi Children Hospital in Libya from January 2008 up to December 2010. Number of children admitted was 244; the age ranged from less than one to 13 years old. Most of cases were admitted with mild symptom and the majority of them were boys. Only few cases admitted to intensive care unit and there was no mortality recorded through the period of study. Age group 1 to 3 years (50.8%) had the highest frequency of admission and the peak of admission was during summer. The most common cause of admission was due to ingestion of medication (53.69%), House hold product exposure (26.64%) was the second causes of admission while, 19.67% of admissions were due to Food poisoning. Almost all admitted cases were accidental and medicines were the most consumed substances in addition, improper storage of toxic agents were the first risk factor of poisoning. Present results indicated that, children poisoning seems to be a common pediatric care problem which need to control and prevent.

Keywords: poisoning, children, hospital, medical

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Authors: Akinola Ikudayisi, Josiah Adeyemo

Abstract:

The correct estimation of reference evapotranspiration (ETₒ) is required for effective irrigation water resources planning and management. However, there are some variables that must be considered while estimating and modeling ETₒ. This study therefore determines the multivariate analysis of correlated variables involved in the estimation and modeling of ETₒ at Vaalharts irrigation scheme (VIS) in South Africa using Principal Component Analysis (PCA) technique. Weather and meteorological data between 1994 and 2014 were obtained both from South African Weather Service (SAWS) and Agricultural Research Council (ARC) in South Africa for this study. Average monthly data of minimum and maximum temperature (°C), rainfall (mm), relative humidity (%), and wind speed (m/s) were the inputs to the PCA-based model, while ETₒ is the output. PCA technique was adopted to extract the most important information from the dataset and also to analyze the relationship between the five variables and ETₒ. This is to determine the most significant variables affecting ETₒ estimation at VIS. From the model performances, two principal components with a variance of 82.7% were retained after the eigenvector extraction. The results of the two principal components were compared and the model output shows that minimum temperature, maximum temperature and windspeed are the most important variables in ETₒ estimation and modeling at VIS. In order words, ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity are less important and cannot be used to provide enough information about ETₒ estimation at VIS. The outcome of this study has helped to reduce input variable dimensionality from five to the three most significant variables in ETₒ modelling at VIS, South Africa.

Keywords: irrigation, principal component analysis, reference evapotranspiration, Vaalharts

Procedia PDF Downloads 233

Authors: Rachmat Mudiyono, Siti Sumiati

Abstract:

In the next few years, traffic will happen most of the time. This was triggered by the growing rate of vehicles againts the road capacity which is not balance. All the time the congestion in the city of Semarang has been occured at peak hours. Congestion also occured in between Teuku Umar and Setia Budi road Jatingaleh because of a plot intersection (Kesatrian intersection, PLN intersection and Jatingaleh intersection) with the Toll Road. Jatingaleh is located in the southern city of Semarang which is a central meeting point between the upper and lower Semarang where the vehicle flows in through a combination of local current and regional traffic, and the flow of vehicles coming in and out from highway. The main cause of the problems that occurred in the area of Jatingaleh is due to the numbers of vehicles movement that occurs at the intersections. With the above issues, it is necessary to analyse the existing conditions and look into some solutions. Before carrying out an analysis of field surveys at peak hours for example morning (06:00 to 08:00 am) and for the afternoon (04:00 to 06:00 pm)should be conducted, then the number of vehicles is counted manually with “short-breakcounting” according to types of vehicles. From the analysis we found that the degree of saturation (DS) is 1.61 between Teuku Umar and Setia Budi road during the morning peak hours and 1.56 during the afternoon peak hours. This means that the capacity of the existing road is no longer able to accommodate the traffic flow. One of the solutions for the congestion that occurs at the intersection of Jatingaleh is to apply the efficiency of the intersection that is not in a plot with a Fly over, Underpass and the combination of Fly Over-Underpass. Base on the flow reduction calculation with 3 comparative modeling it shows that the Fly Over is the most technically efficient to be applied in this research.

Keywords: single fly over, congestion, intersection, interchange

Procedia PDF Downloads 375

Authors: Kuei-Yu Chien, Hsiu-Yu Chiu, Chia-Nan Chen, Shu-Chen Chen

Abstract:

Background: Frailty is associated with decreased physical performances that affect mobility of the elderly. Time up and go test (TUG) was the common method to evaluate mobility in the community. The purpose of this study was to compare the parameters in different stages of Time up and go test (TUG) and physical performance between pre-frail elderly (PFE) and non-frail elderly (NFE). We also investigated the relationship between TUG parameters and physical performance. Methods: Ninety-two community-dwelling older adults were as participants in this study. Based on Canadian Study of Health and Aging Clinical Frailty Scale, 22 older adults were classified as PFE (71.77 ± 6.05 yrs.) and 70 were classified as NFE (71.2 ± 5.02 yrs.). We performed body composition and physical performance, including balance, muscular strength/endurance, mobility, cardiorespiratory endurance, and flexibility. Results: Pre-frail elderly took significantly longer time than NFE in TUG test (p=.004). Pre-frail elderly had lower turning average angular velocity (p = .017), turning peak angular velocity (p = .041) and turning-stand to sit peak angular velocity (p = .037) than NFE. The turning related parameters related to open-eye stand on right foot, 30-second chair stand test, back scratch, and 2-min step tests. Conclusions: Turning average angular velocity, turning peak angular velocity and turning-stand to sit peak angular velocity mainly affected the TUG performance. We suggested that static/dynamic balance, agility, flexibility, and muscle strengthening of lower limbs exercise were important to PFE.

Keywords: mobility, aglity, active ageing, functional fitness

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Authors: H. Bakhshi, E. Khayyamian

Abstract:

Cognitive radios have been recognized as one of the most promising technologies dealing with the scarcity of the radio spectrum. In cognitive radio systems, secondary users are allowed to utilize the frequency bands of primary users when the bands are idle. Hence, how to accurately detect the idle frequency bands has attracted many researchers’ interest. Detection performance is sensitive toward noise power and gain fluctuation. Since signal to noise ratio (SNR) between primary user and secondary users are not the same and change over the time, SNR and noise power estimation is essential. In this paper, we present a cooperative spectrum sensing algorithm using SNR estimation to improve detection performance in the real situation.

Keywords: cognitive radio, cooperative spectrum sensing, energy detection, SNR estimation, spectrum sensing, rayleigh fading channel

Procedia PDF Downloads 434