A Cooperative Positioning Method of Connected and Automated Vehicles with Direction-of-Arrival and Relative Distance Fusion

The rapid development of science and technology has created favorable conditions for Connected and Automated Vehicles (CAVs). Accurate localization is one of the fundamental functions of CAV to realize some advanced operations such as vehicle platooning. However, complicated urban traffic environments, such as the flyover, significantly influence vehicular positioning accuracy. The inability of CAV to accurately perceive self-localization information has become an urgent issue to be addressed. This paper proposed a novel cooperative localization method by introducing the relative Direction-of-Arrival (DOA) and Relative Distance (RD) into CAV to improve the localization accuracy of CAV in the multivehicle environment. First, the three-dimensional positioning error model of the host vehicle concerning adjacent vehicles in azimuth angle and pitch angle and intervehicle distances under the vehicle-to-vehicle communication was established. Second, two least-squares estimation algorithms, linear and nonlinear, are established to decrease the position errors by combining relative DOA and RD measurement information. To verify the proposed algorithm's effect, the PreScan-Simulink joint simulation is carried out. The results show that the host vehicle's localization accuracy by the proposed method can be improved by 25% compared with direct linearization. Besides, by combining relative DOA and relative RD measurement, the locating capability of the least-square-based nonlinear optimization method can be enhanced by 22%.

Sustainability of weight loss from a family-centered pediatric weight management program integrated in primary care

Background A 6-month pediatric weight loss program showed modest success, but the sustainability of this success after 12 months was unclear. The present study aims tomeasure the medium-term effectiveness of family-based weight management in pediatric primary care to reduce body weight in children living with obesity. Methods In a retrospective cohort study, children ages 3 to 17 years with obesity in Kaiser Permanente Orange County, California, who enrolled in a weight management program between April 2014 and December 2018 (FB-WMG, n = 341) were compared to children referred but not enrolled (Ref-CG, n = 317) and controls matched by sex, age, zip code and BMI (Area-CG, n = 801). The relative distance from the median BMI-for-age at months 0, 6, and 12 were expressed as difference-in-differences (DID) using multivariable linear regressions with robust standard error. Results The baseline BMI-for-age was 98.6 (SD 1.08) percentile in FB-WMG, 98.2 (SD 1.22) percentile in Ref-CG, and 98.6 (1.13 in Area-CG). FB-WMG had a median of 3 visits (P25 1 visit, P75 5 visits) in the first 6 months. Despite a more considerable decrease in the relative distance to the median BMI-for-age in FB-WMG children with 3+ visits after 6 months, the success obtained was not sustained at 12 months (DID FB-WMG vs Area-CG -0.34, 95% CI − 3.00 to 2.33%, FB-WMG vs Ref-CG -0.39, 95% CI − 3.14 to 2.35%). At 12 months, there was no statistical significant difference between the three groups (FB-WWG, Ref-CG, Area-CG). Conclusions The initial success in weight management was not sustained in the absence of continued support for healthy lifestyle changes. Based on current evidence, continued support is necessary to maintain and promote success beyond a brief 6 month intervention. Long-term pediatric weight management programs are needed to promote continuing progress.

A Distance Increment Smoothing Method and Its Application on the Detection of NLOS in the Cooperative Positioning

The wide use of cooperative missions using multiple unmanned platforms has made relative distance information an essential factor for cooperative positioning and formation control. Reducing the range error effectively in real time has become the main technical challenge. We present a new method to deal with ranging errors based on the distance increment (DI). The DI calculated by dead reckoning is used to smooth the DI obtained by the cooperative positioning, and the smoothed DI is then used to detect and estimate the non-line-of-sight (NLOS) error as well as to smooth the observed values containing random noise in the filtering process. Simulation and experimental results show that the relative accuracy of NLOS estimation is 8.17%, with the maximum random error reduced by 40.27%. The algorithm weakens the influence of NLOS and random errors on the measurement distance, thus improving the relative distance precision and enhancing the stability and reliability of cooperative positioning.

The framework of data-driven and multi-criteria decision-making for detecting unbalanced bidding

PurposeUnbalanced bidding can seriously imposed the government from obtaining the best value for the taxpayers' money in public procurement since it increases the owner's cost and decreases the fairness of the competitive bidding process. How to detect an unbalanced bid is a challenging task faced by theoretical researchers and practical actors. This study aims to develop an identification method of unbalanced bidding in the construction industry.Design/methodology/approachThe identification of unbalanced bidding is considered as a multi-criteria decision-making (MCDM) problem. A data-driven unit price database from the historical bidding document is built to present the reference unit prices as benchmarks. According to the proposed extended TOPSIS method, the data-driven unit price is chosen as the positive ideal solution, and the unit price that has the furthest absolute distance measure as the negative ideal solution. The concept of relative distance is introduced to measure the distances between positive and negative ideal solutions and each bidding unit price. The unbalanced bidding degree is ranked by means of relative distance.FindingsThe proposed model can be used for the quantitative evaluation of unbalanced bidding from a decision-making perspective. The identification process is developed according to the decision-making process. The finding shows that the model will support owners to efficiently and effectively identify unbalanced bidding in the bid evaluation stage.Originality/valueThe data-driven reference unit prices improve the accuracy of the benchmark to evaluate the unbalanced bidding. The extended TOPSIS model is applied to identify unbalanced bidding; the owners can undertake objective decision-making to identify and prevent unbalanced bidding at the stage of procurement.

Design of Orbit Controls for a Multiple CubeSat Mission Using Drift Rate Modulation

For the low-cost improvement of laser communication, which is critical for various applications such as surveillance systems, a study was conducted on relative distance control based on orbital drift rate modulations for multiple CubeSats during formation flying. The VISION mission covered in this paper comprises two CubeSats to demonstrate laser communication technology in space. During the mission, the deputy CubeSat changes the relative distance to execute mission objectives within various scenarios. Impulsive controls decrease, maintain, and increase the relative distance between the CubeSats by changing the orbital drift rates. The simulation results indicated that the desired orbital operation can be conducted within a given ΔV budget. In addition, the errors in the orbit determination, thrust maneuvers, and time synchronization were analyzed to satisfy the mission requirements. The mass-to-area ratio should be matched to adjust the relative distance between satellites with different properties by drift rate modulation. The proposed orbit control method appropriately operated the VISION mission by adjusting the drift rate modulation. The results of this study serve as a basis for the development of complex orbit control simulations and detailed designs that reflect the characteristics of the thrust module and operational aspects.

Molecular identification and prevalence of trypanosomes in cattle distributed within the Jebba axis of the River Niger, Kwara state, Nigeria

Background Trypanosomiasis is a fatal disease that threatens the economy of at least 37 countries in sub-Saharan Africa, particularly with regard to livestock farming. In this study, we investigated the prevalence of trypanosome infection in cattle, and molecularly identified the species of trypanosomes in infected cattle and the spatial distribution of trypanosome-infected herds along the Jebba axis of the River Niger. Methods A randomized cross-sectional study was conducted along the Jebba axis of the River Niger by screening cattle from 36 herd clusters by nested PCR using ITS-1 generic primers. Data generated were analysed using the Chi-square test at a 95% confidence interval. Results Microscopic examination revealed three infected cattle out of 398 examined, representing 0.8% prevalence. Twelve animals (3.0%) were positive by PCR. Our results showed a decline in the packed cell volume of infected animals (24.7%). The infection rates were categorized as single infection in 11/12 (91.7%) and mixed infection in 1/12 (8.3%). Animals were most frequently infected by Trypanosoma congolense (50.0%), with T. congolense Savannah being the most prevalent subspecies (71.4%). Aside from the infection rate by age (10.0%) and relative distance of animals from the River Niger (56.2%), statistical differences in every other parameter tested were based on mere probabilistic chance. Spatial data showed that the disease was prevalent among herds located less than 3 km from the River Niger. Conclusions Six species of trypanosomes were identified in cattle herds along the Jebba axis of the River Niger, with T. congolense being the most prevalent. Age and relative distance of herds from the River Niger may be risk factors for trypanosome infection in cattle herds in this area. Graphical abstract