Multiplexing modulation design optimization and quality evaluation of BDS-3 PPP service signal

The Precise Point Positioning (PPP) service of BeiDou-3 Navigation Satellite System (BDS-3) is implemented on its Geostationary Earth Orbit (GEO) satellites. However, its signal design is limited by the actual power of satellite and other conditions. Furthermore, the design needs to fully consider the compatibility of different service phases. Starting from the actual state of the BDS-3 GEO satellite, this paper studies the multiplexing modulation of the BDS PPP service signal that is based on the Asymmetric Constant Envelope Binary Offset Carrier (ACE-BOC) technique and proposes several feasible schemes for this signal. Comparison and optimization of these techniques are made from the aspects of transmission efficiency, multiplexing efficiency, and service forward compatibility. Based on the Type-III ACE-BOC multiplexing modulation technique, phase rotation and intermodulation reconstruction techniques are proposed to suppress the intermodulation interference issue. Finally, a signal based on improved ACE-BOC multiplexing is designed. The quality of the proposed signal was continuously monitored and tested using large-diameter antennas. The evaluation results show that the power spectrum deviation of the signal is 0.228 dB, the correlation loss is 0.110 dB, the S-curve slope deviation is 1.558% on average, the average length difference between the positive/negative chip and the ideal chip is only 0.0006 ns, and the coherence between the carrier and the pseudo code is 0.082°. All quality indicators are satisfactory, indicating that the proposed signal multiplexing modulation technique is an ideal solution that meets all the requirements of the design constraints, and can achieve efficient information broadcasting and forward compatibility of the BDS PPP service.

Technology Forecasting of Unmanned Aerial Vehicle Technologies through Hierarchical S Curves

This study aims to propose a technology forecasting approach based on hierarchical S-curves. The proposed approach uses holistic forecasting by evaluating the S-curves of sub-technologies as well as the main technology under concern. A case study of unmanned aerial vehicle (UAV) technologies is conducted to demonstrate how the proposed approach works in practice. This is the first study that applies hierarchical S-curves to technology forecasting of unmanned aerial vehicle technologies in the literature. The future trend of the UAV technologies is analysed in detail through a hierarchical S-curve approach. Hierarchical S-curves are also utilised to investigate the sub-technologies of the UAV. In addition, the technology development life cycle of technology is assessed by using the three indexes namely, (1) the current technological maturity ratio (TMR), (2) estimating the number of potential patents that could be granted in the future (PPA), and (3) forecasting the expected remaining life (ERL). The results of this study indicate that the UAV technologies and their sub-technologies are at the growth stage in the technology life cycle, and most of the developments in UAV technology will have been completed by 2048. Hence, these technologies can be considered emerging technologies.

Determination of the Uncertainties in S-Curve Logistic Fits

Look-up tables and graphs are provided for determining the uncertainties during logistic fits, on the three parameters M, α and to describing an S-curve of the form: S(t) = M/(1+exp(-α(t-t0))).The uncertainties and the associated confidence levels are given as a function of the uncertainty on the data points and the length of the historical period. Correlations between these variables are also examined; they make “what-if” games possible even before doing the fit.The study is based on some 35,000 S-curve fits on simulated data covering a variety of conditions and carried out via a χ2 minimization technique. A rule-of-thumb general result is that, given at least half of the S-curve range and a precision of better than 10% on each historical point, the uncertainty on M will be less than 20% with 90% confidence level.

Vertical Bearing Capacity of Precast Pier Foundation Filled with Demolished Concrete Lumps

The application of recycled compound concrete made of demolished concrete lumps (DCLs) and fresh normal concrete in pier foundation can effectively improve the utilization efficiency of construction waste resources. In this study, two prefabricated pier foundations based on recycled compound concrete (dimension of Ø800 × 2500 mm and Ø1000 × 2500 mm) and two cast-in-place pier foundations based on ordinary concrete (dimension of Ø800 × 2500 mm and Ø1000 × 2500 mm) were tested. Special attention was devoted to the load-settlement curve characteristics of the precast pier foundation of compound concrete, the load transfer law of the pier-soil system, the soil pressure distribution at the bottom of the pier, and the failure mode. The results showed that the Q-S curve of precast concrete pier foundation made of recycled compound concrete is slow deformation at loading, which is consistent with that of cast-in-place concrete pier foundation. The load transfer theory of pier-soil system is established, and its accuracy is verified by experimental analysis. The precast foundation of recycled compound concrete is the same as the cast-in-place foundation of ordinary concrete. The failure form of prefabricated pier foundation made of recycled compound concrete was a local shear failure, while the failure form of ordinary concrete cast-in-place pier foundation was piercing-type shear failure. The feasibility of relevant theoretical methods for calculating the vertical ultimate bearing capacity is examined.

Why the Singularity Cannot Happen

The concept of a Singularity as described in Ray Kurzweil’s book cannot happen for a number of reasons. One reason is that all natural growth processes that follow exponential patterns eventually reveal themselves to be following S-curves thus excluding runaway situations. The remaining growth potential from Kurzweil’s “knee”, which could be approximated as the moment when an S-curve pattern begins deviating from the corresponding exponential, is a factor of only one order of magnitude greater than the growth already achieved. A second reason is that there is already evidence of a slowdown in some important trends. The growth pattern of the U.S. GDP is no longer exponential. Had Kurzweil been more rigorous in his fitting procedures, he would have recognized it. Moore’s law and the Microsoft Windows operating systems are both approaching end-of-life limits. The Internet rush has also ended — for the time being — as the number of users stopped growing; in the western world because of saturation and in the underdeveloped countries because infrastructures, education, and the standard of living there are not yet up to speed. A third reason is that society is capable of auto-regulating runaway trends as was the case with deadly car accidents, the AIDS threat, and rampant overpopulation. This control goes beyond government decisions and conscious intervention. Environmentalists who fought nuclear energy in the 1980s, may have been reacting only to nuclear energy’s excessive rate of growth, not nuclear energy per se, which is making a comeback now.What may happen instead of a Singularity is that the rate of change soon begins slowing down. The exponential pattern of change witnessed up to now dictates more milestone events during year 2025 than witnessed throughout the entire 20th century! But such events are already overdue today. If, on the other hand, the change growth pattern has indeed been following an S-curve, then the rate of change is about to enter a declining trajectory; the baby boom generation will have witnessed more change during their lives than anyone else before or after them.

US Nobel laureates: Logistic growth versus Volterra–Lotka

The logistic-growth equation is a special case of the Volterra-Lotka equations. The former describes competition only between members of the same species whereas the latter describes competition also with other species. In the study of US Nobel laureates considering laureates per population improves the quality of the logistic fit but the Volterra-Lotka approach suggests that a logistic description would be a good approximation for data per unit of time rather than cumulative data. Fitting logistic S curves on cumulative data — although proven successful in many business and other applications — constitutes treacherous terrain for inexperienced S-curve enthusiasts. The Volterra-Lotka analysis of Nobel laureates reveals other insights such as that Americans and other nationalities are locked in a win-win struggle with Americans drawing more of a benefit, and also that American Nobel laureates “incubate” new Nobel laureates to a lesser extent than other nationalities.

Used Car Price Estimation: Moving from Linear Regression towards a New S-Curve Model

A simple linear regression is commonly used as a practical predictive model on a used car price. It is a useful model which carry smaller prediction errors around its central mean. Practically, real data will hardly produce a linear relationship. A non-linear model has been observed to better forecast any price appreciation and manage prediction errors in real-life phenomena. In this paper, an S-curve model shall be proposed as an alternative non-linear model in estimating the price of used cars. A dynamic S-shaped Membership Function (SMF) is used as a basis to build an S-curve pricing model in this research study. Real used car price data has been collected from a popular website. Comparisons against linear regression and cubic regression are made. An S-curve model has produced smaller error than linear regression while its residual is closer to a cubic regression. Overall, an S-curve model is anticipated to provide a better and more practical estimate on used car prices in Malaysia.

Research and application of K/S value in stain identification

Purpose The intelligent identification of stains can quickly and accurately identify stains. At present, stains are identified subjectively by appearance, color, taste, feel, location, etc. Color is an important factor in identifying stains. K/S value is used to analyze the color of textile fabric, and it has additivity. The purpose of the study is to explore its application in stain recognition is of great significance to intelligent washing. Design/methodology/approach A certain method used to stain the textile, then the K/S value of the textile before and after the stain was analyzed and tested by the color difference instrument. The K/S curve of the stain was calculated by the addition of K/S, and then the stain was identified and distinguished. Findings The K/S value of the textile stained with stains could be deducted by the K/S value of the color difference meter. After deducting the base cloth, the K/S curve of the same stain is basically the same. Then the stain can be identified and analyzed. Research limitations/implications The K/S value can be used for stain analysis, but it needs to be analyzed and tested in the laboratory. Practical implications This study provides a simple method for stains identification. Originality/value In addition to common methods of stain identification, such as appearance, color, feel, smell, location, stain removal materials, breaking the substrate, IR, etc., K/S value can be used for stain analysis. Identifying stains and washing them in a targeted way to achieve a better washing effect could provide certain technical support for the development of smart washing and smart home appliances.

Measurement and modeling of a flexible manipulator for vibration control using five-segment S-curve motion

User designed manipulators are widely used in industry as a part of automation. The design of lighter robotic arms is required for less energy consumption. Joints, structural features, and payload affect the dynamic behavior of manipulators. Even if the arms have sufficient structural rigidity, joints, or payloads further increase their flexibility. These factors should be considered at the design stage. Flexibility causes vibrations, and these vibrations negatively affect robot repeatability and processing speed. Reducing the vibration levels of flexible manipulators is an attractive issue for engineers and researchers. Accurate estimation of the mathematical model of flexible manipulators increases the success of vibration control. In this paper, the modeling and experiments for vibration control of a single-axis flexible curved manipulator with payload are considered. The experimental system is introduced to collect vibration responses synchronously at the tip of the curved manipulator for angular velocity input. The mathematical model of the manipulator is estimated using the continuous-time system identification (CTSI) method with a black-box model based on the experimental input/output (I/O) signals. A five-segment S-curve motion input based on the modal parameters is designed to suppress residual vibrations. Vibration control is successfully performed for different deceleration times of the designed S-curve motion input. The results showed that the residual vibrations from experiments and predicted models matched well for different cases depending on payload, angular position, and motion time.

A Polynomial Method Approximating S-Curve with Limited Availability of Reliable Rainfall Data

A methodology named the step response separation (SRS) method for deriving S-curves solely from the data for basin runoff and the associated instantaneous unit hydrograph (IUH) is presented. The SRS method extends the root selection (RS) method to generate a clearly separated S-curve from runoff incorporated in mathematical procedure utilizing the step response function. Significant improvements in performance are observed in separating the S-curve with rainfall. A procedure to evaluate the hydrologic stability provides ways to minimize the oscillation of the S-curve associated with the determination of infiltration and baseflow. The applicability of the SRS method to runoff reproduction is examined by comparison with observed basin runoff based on the RS method. The SRS method applied to storm events for the Nenagh basin resulted in acceptable S-curves and showed its general applicability to optimization for rainfall-runoff modeling.