Pedestrian Heading Estimation Methods Based on Multiple Phone Carrying Modes

The development of smartphone Micro-Electro-Mechanical Systems (MEMS) inertial sensors has provided opportunities to improve indoor navigation and positioning for location-based services. One area of indoor navigation research uses pedestrian dead reckoning (PDR) technology, in which the mobile phone must typically be held to the pedestrian’s chest. In this paper, we consider navigation in three other mobile phone carrying modes: “calling,” “pocket,” and “swinging.” For the calling mode, in which the pedestrian holds the phone to their face, the rotation matrix method is used to convert the phone’s gyroscope data from the calling state to the holding state, allowing calculation of the stable pedestrian forward direction. For a phone carried in a pedestrian’s trouser pocket, a heading complementary equation is established based on principal component analysis and rotation approach methods. In this case, the pedestrian heading is calculated by determining a subset of data that avoid 180° directional ambiguity and improve the heading accuracy. For the swinging mode, a heading capture method is used to obtain the heading of the lowest point of the pedestrian’s arm swing as they hold the phone. The direction of travel is then determined by successively adding the heading offsets each time the arm droops. Experimental analysis shows that 95% of the heading errors of the above three methods are less than 5.81°, 10.73°, and 9.22°, respectively. These results present better heading accuracy and reliability.

Sigmoid generalized complementary equation for wet surface evaporation at the scale with changing advections

<p>Understandings the processes and estimating the amount of wet surface evaporation across various scales are crucial to the evaporation research. The Penman (1948) and Priestley-Taylor (1972) equations are derived for a wet patches and an extensive wet surface respectively, with an obviously different effects of advection. However, the evaporation for a wet surface between these two scales is difficult to estimate because of the changing advections. The sigmoid generalized complementary (SGC) equation, which expresses the ratio of actual evaporation (E) to Penman potential evaporation (E<sub>Pen</sub>) as a function of the proportion of the radiation term (E<sub>rad</sub>) in E<sub>Pen</sub>, is used to model the wet surface evaporation process by setting the symmetric parameter to be infinity, and was validated by data from flux sites over a lake site (CN-MLW) from China, a wetland site (US-WPT) from the United State, and a paddy site (JP-MSE) from Japan. The SGC equation robustly describes the growth of E/E<sub>Pen</sub> upon E<sub>rad</sub>/E<sub>Pen</sub> with upper flatness part over the wet surface with significant changing advection effects, and could account for the variation of the Priestley-Taylor coefficient directly. Thus, the SGC equation outperforms the Priestley-Taylor equation with a constant coefficient for estimating wet surface evaporation at the scale with changing advections.</p>

An Improved Analytical Solution of Population Balance Equation Involving Aggregation and Breakage via Fibonacci and Lucas Approximation Method

This study presents a novel analytical solution for the Population Balance Equation (PBE) involving particulate aggregation and breakage by making use of the appropriate solution(s) of the associated complementary equation of a nonlinear PBE via Fibonacci and Lucas Approximation Method (FLAM). In a previously related study, travelling wave solutions of the complementary equation of the PBE using Auxiliary Equation Method (AEM) with sixth order nonlinearity was taken to be analogous to the description of the dynamic behavior of the particulate processes. However, in this study, the class of auxiliary equations is extended to Fibonacci and Lucas type equations with given transformations to solve the PBE. As a proof-of-concept for the novel approach, the general case when the number of particles varies with respect to time is chosen. Three cases i. e. balanced aggregation and breakage and when either aggregation or breakage can dominate are selected and solved for their corresponding analytical solution and compared with the available analytical approaches. The solution obtained using FLAM is found to be closer to the exact solution and requiring lesser parameters compared to the AEM and thereby being a more robust and reliable framework.

Numerical modeling of the thermoelectric cooler with a complementary equation for heat circulation in air gaps

In this paper, a numerical model is developed by combining thermodynamics with heat transfer theory. Taking inner and external multi-irreversibility into account, it is with a complementary equation for heat circulation in air gaps of a steady cooling system with commercial thermoelectric modules operating in refrigeration mode. With two modes concerned, the equation presents the heat flowing through air gaps which forms heat circulations between both sides of thermoelectric coolers (TECs). In numerical modelling, a TEC is separated as two temperature controlled constant heat flux reservoirs in a thermal resistance network. In order to obtain the parameter values, an experimental apparatus with a commercial thermoelectric cooler was built to characterize the performance of a TEC with heat source and sink assembly. At constant power dissipation, steady temperatures of heat source and both sides of the thermoelectric cooler were compared with those in a standard numerical model. The method displayed that the relationship betweenΦfand the ratio$\varPhi_{{\text c}}'/\varPhi_{{\text c}}$was linear as expected. Then, for verifying the accuracy of proposed numerical model, the data in another system were recorded. It is evident that the experimental results are in good agreement with simulation(proposed model) data at different heat transfer rates. The error is small and mainly results from the instabilities of thermal resistances with temperature change and heat flux, heat loss of the device vertical surfaces and measurements.

Construct Linear Polynomial Complementary Transformation for NP-Completeness Using Parallel Genetic Algorithm

This paper examines the correlation between numbers of computer cores in parallel genetic algorithms. The objective to determine the linear polynomial complementary equation in order represent the relation between number of parallel processing and optimum solutions. Model this relation as optimization function (f(x)) which able to produce many simulation results. F(x) performance is outperform genetic algorithms. Compression results between genetic algorithm and optimization function is done. Also the optimization function give model to speed up genetic algorithm. Optimization function is a complementary transformation which maps a TSP given to linear without changing the roots of the polynomials.

The Doubly Nonlinear Limit Load Analysis of Space Grid Structure

This paper first adopts variational inequation—the method of linear complementary equation. We use this method to analyses the elastoplastic limit load of space grid structure. This is a way to resolve the nonlinear question. Adopting this method to resolve the limit load of space grid structure avoid some drawback caused by adopting iteration method. We only need do some limited compute to a load-increment then we can obtain consequence, which fit in with all condition. Particularly, though adopting the method of linear complementary equation, we can control the value of limit load, make the calculated load can not exceed the limit load. Once exceeding, computer can decrease load- increment automatically and load again till getting the limit load of structure. Based on elastoplastic limit load analysis, this paper has considered big deformation impact on the limit load of bspace grid structure. We have made analysis of doubly nonlinear limit loads under the condition of coupling out of elastoplastic big deformation. The method and theory of this paper can combine with all kinds of single rod mechanics model.

Bayesian simultaneous equation models for the analysis of energy intake and partitioning in growing pigs

SUMMARYThe objective of the current study was to develop Bayesian simultaneous equation models for modelling energy intake and partitioning in growing pigs. A key feature of the Bayesian approach is that parameters are assigned prior distributions, which may reflect the current state of nature. In the models, rates of metabolizable energy (ME) intake, protein deposition (PD) and lipid deposition (LD) were treated as dependent variables accounting for residuals being correlated. Two complementary equation systems were used to model ME intake (MEI), PD and LD. Informative priors were developed, reflecting current knowledge about metabolic scaling and partial efficiencies of PD and LD rates, whereas flat non-informative priors were used for the reminder of the parameters. The experimental data analysed originate from a balance and respiration trial with 17 cross-bred pigs of three genders (barrows, boars and gilts) selected on the basis of similar birth weight. The pigs were fed four diets based on barley, wheat and soybean meal supplemented with crystalline amino acids to meet or exceed Danish nutrient requirement standards. Nutrient balances and gas exchanges were measured at c. 25, 75, 120 and 150 kg body weight (BW) using metabolic cages and open circuit respiration chambers. A total of 56 measurements were performed. The sensitivity analysis showed that only the maintenance component was sensitive to the prior specification, and hence the maintenance estimate of 0·91 MJ ME/kg0·60 per day (0·95 credible interval (CrI): 0·78–1·09) should be interpreted with caution. It was shown that boars’ ability to deposit protein was superior to that of barrows and gilts, as these had an estimated maximum PD (PDmax) of 250 g/day (0·95 CrI: 237–263), whereas the barrows and gilts had a PDmax of 210 g/day (0·95 CrI: 198–220). Furthermore, boars reached PDmax at 109 kg BW (0·95 CrI: 93·6–130), whereas barrows and gilts maximized PD at 81·7 kg BW (0·95 CrI: 75·6–89·5). At 25 kg BW, the boars partitioned on average 5–6% more of the ME above maintenance into PD than barrows and gilts, and this was progressively increased to 10–11% more than barrows and gilts at 150 kg BW. The Bayesian modelling framework can be used to further refine the analysis of data from metabolic studies in growing pigs.