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The purpose of this paper is to present a novel approach based on the artificial bee colony (ABC) algorithm aiming to achieve maximum acceleration and maximum endurance for morphing unmanned aerial vehicle (UAV) design.

Some of the most important issues in the design of UAV are the design of thrust system and determination of the endurance of the UAV. Although propeller selection is very important for the thrust system design, battery selection has the utmost importance for the determination of UAV endurance. In this study, the calculations of maximum acceleration and endurance required by ZANKA-II during the flight are considered simultaneously. For this purpose, a model based on the ABC algorithm is proposed for the morphing UAV design, aiming to achieve the maximum acceleration and endurance. In the proposed model, the propeller diameter, propeller pitch and battery values used in morphing UAV's power system design are selected as the input parameters; maximum acceleration and endurance are selected as the output parameters. To obtain the maximum acceleration and endurance, the optimum input parameters are determined through the ABC algorithm-based model.

Considerable improvements on maximum acceleration and endurance of morphing UAV with ABC algorithm-based model are obtained.

The endurance and acceleration due to the thrust are two separate parameters that are not normally proportional to each other. In this study, optimization of UAV’s endurance and acceleration is considered with equal importance.

Using artificial intelligence techniques causes fast and simple optimization for determination of UAV’s endurance and acceleration with equal importance. In the simulation studies with ABC algorithm, satisfactory results are obtained.

The results of the study have showed that the proposed approach could be an alternative method for UAV designers.

Providing a new and efficient method saves time and reduces cost in calculations of maximum acceleration and endurance of the UAV.

The purpose of this paper is to create an endurance index of housing investor sentiment and use it to forecast housing stock returns. This study performs not only in-sample and out-of-sample forecasting, like many previous studies did, but also a true forecasting by using all lag terms of independent variables. In addition, an evaluation procedure is applied to quantify the quality of forecasts.

Using a binomial probability distribution model, this paper creates an endurance index of housing investor sentiment. The index reflects the probability of the high or low stock price being the close price for the Philadelphia Stock Exchange Housing Sector Index. This housing investor sentiment endurance index directly uses housing stock price differentials to measure housing investor reactions to all relevant news. Empirical results in this study suggest that the index can not only play a significant role in explaining variations in housing stock returns but also have decent forecasting ability.

Results of this study reveal the considerable forecasting ability of the index. Monthly forecasts of housing stock returns have an overall accuracy of 51 per cent, while the overall accuracy of 8-quarter rolling forecasts even reaches 84 per cent. In addition, the index has decent forecasting ability on changes in housing prices as suggested by the strong evidence of one-direction causal relations running from the endurance index to housing prices. However, extreme volatility of housing stock returns may impair the forecasting quality.

The endurance index of housing investor sentiment is easy to construct and use for forecasting housing stock returns. The demonstrated predictability of the index on housing stock returns in this study can have broad implications on housing-related business practices through providing an effective forecasting tool to investors and analysts of housing stocks, as well as housing policy-makers.

Despite different investor sentiment proxies suggested in the previous studies, few of them can effectively predict stock returns, due to some embedded limitations. Many increases and decreases inn prices cancel out each other during the trading day, as many unreliable sentiments cancel out each other. This dynamic process reveals not only investor sentiment but also resilience or endurance of sentiment. It is only long-lasting resilient sentiment that can be built in the closing price. It means that the only feasible way to use investor sentiment contained in stock prices to forecast future stock prices is to detach resilient investor sentiment from stock prices and construct an index of endurance of investor sentiment.

This study aims to optimize autonomous performance (i.e. both longitudinal and lateral) and endurance of the quadrotor type aerial vehicle simultaneously depending on the autopilot gain coefficients and battery weight.

Quadrotor design processes are critical to performance. Unmanned aerial vehicle durability is an important performance parameter. One of the factors affecting durability is the battery. Battery weight, energy capacity and discharge rate are important design parameters of the battery. In this study, proper autopilot gain coefficients and battery weight are obtained by using a stochastic optimization method named as simultaneous perturbation stochastic approximation (SPSA). Because there is no direct correlation between battery weight and battery energy density, artificial neural network (ANN) is benefited to obtain battery energy density corresponding to resulted battery weight found from SPSA algorithm. By using the SPSA algorithm optimum performance index is obtained, then obtained data is used for longitudinal and lateral autonomous flight simulations.

With SPSA, the best proportional integrator and derivative (PID) coefficients and battery weight, energy efficiency and endurance were obtained in case of morphing.

It takes a long time to find the most suitable battery values depending on quadrotor endurance. However, this situation can be overcome with the proposed SPSA.

It is very useful to determine quadrotor endurance, PID coefficients and morphing rate using the optimization method.

Determining quadrotor endurance, PID coefficients and morphing rate using the optimization method provides advantages in terms of time, cost and practicality.

The proposed method improves quadrotor endurance. In addition, with the SPSA optimization method and ANN, the parameters required for endurance will be obtained faster and more securely. In addition, the energy density according to the battery weight also contributes to the clean environment and energy efficiency.

The purpose of this paper is finding the optimal geometric parameters and developing of a method for optimizing a light unmanned aerial vehicle (UAV) wing, maximizing, at the same time, its endurance with the assumed parameters of aircraft mission.

The research is based on the experience gained by the author’s contribution to the project of building medium-altitude, long-endurance class, light UAV called “Samonit”. The author was responsible for the structure design, wind tunnel tests and flight tests of the “Samonit” aircraft. Based on the experience, the author was able to develop an optimization process considering various disciplines involved in the whole aircraft design topics such as aerodynamics, flight mechanics, structural stiffness and weight, aircraft stability and maneuverability. The presented methodology has a multidisciplinary nature, as in the process of optimization both aerodynamic aspects and the influence of wing geometric parameters on the wing structure and weight and the aircraft payload were taken into account. The optimal wing configuration was obtained using the genetic algorithms.

As a result, a set of wing geometrical parameters has been obtained that allowed for achieving twice as long endurance as compared with the initial one.

Using the methodology presented in the paper, an aircraft designer can easily find the optimum wing configuration of a designed aircraft, satisfying the mission requirements in a best way.

An original procedure has been developed, based on the actual design, wind tunnel tests and numerical calculations of “Samonit” aircraft, enabling the determination of optimum wing configuration for a small unmanned aircraft.

White tea is an unfermented tea made from young shoots of Camellia sinensis protected from sunlight to avoid polyphenol degradation. White tea contains a high level of polyphenolic compounds known as catechins. Several types of evidence have suggested that tea consumption has benefits in body weight and endurance maintenance. This study was designed to evaluate the effect of white tea on body weight and endurance of animal models.

This research was an intervention design using 20 Wistar white rats (Rattus Norvegicus) in body weight between 150 and 200 g. The rats were randomized into four groups, three groups receiving white tea drink (WTD) with different doses and the other group receiving plain water in equal volume as a control group for four weeks. The forced swim test (FST) was done to measure their struggling capacity, and digital bodyweight to measure the weight.

Intervention (WTD Groups and Control) caused weight gain among except G3 with the highest doses of white tea. The result showed that WTD intake in G3 had a significant difference (p < 0.05) on body weight gain compared to control. The authors found that WTD in a specific dose (G3: 0.22 mg) tends to maintain the body weight of animals (219.2 ± 41.96; 212.6 ± 46.90, respectively), while other doses caused weight gain. WTD also significantly increased the swimming and struggling capacity of rats that represented improvements the endurance along with the test. There was a statistically significant difference in endurance among all groups (p < 0.05).

The results of this study can be followed as human intervention research as an input for nutritionists and sports scientists to explore the beneficial effect of white tea.

The results of this study can be followed as human intervention research as an input for nutritionists and sports scientists to explore the beneficial effect of white tea.

This study adds more evidence and information about the advantages of white tea as potential beverages in future healthy lifestyles.

This paper aims to determine the influence of physical ability on initial emergency response performance among emergency response teams.

In an emergency incident, emergency responders are involved in vigorous physical activities. Previous attempts have demonstrated that job performance of emergency responders depends a great deal on their ability to perform strenuous physical activity. This paper examines the influence of physical ability namely weight, height, and cardiovascular endurance on emergency response performance among fire fighting teams in Malaysia. Emergency response performance was defined as team member's speed in responding to emergency situations. Data on team member's physical ability and emergency response time were collected for the duration of five months. The distance from the waiting room to the fire truck in each selected fire station was used to measure performance.

This study found that the team with higher average weight and cardiovascular endurance level had better initial response to emergency situations, contrary to the research hypothesis. But it is speculated that the relationship could be further understood by considering the proportion of fat in the body. The relationship between cardiovascular endurance and initial emergency response performance further validates and justifies the use of physical fitness test as a criterion for job performance of fire fighters.

This paper offers empirical evidence of emergency response performance in Malaysia. Specifically, it presents findings on the influence of physical ability measures on initial emergency response performance from a team perspective. In addition, the emergency response performance was measured by the distance traveled by the responders, which serves as a meaningful performance indicator.

In recent years, high‐altitude/long‐endurance airship platforms have generated great interest as a means to provide communications and surveillance capabilities. The purpose of this paper is to develop a model for airship conceptual design and help provide insight into the viability of high‐altitude/long‐endurance airships.

A configuration analysis model with the consideration of pressure difference, temperature difference, and helium purity, etc. was developed. The influences of the airship payload, size and area required of solar cell with environment and operation parameters, such as operation latitude, pressure difference, temperature difference, helium purity, seasons, latitude, and wind speed, etc. were analyzed.

The results show that the area of solar cell required for stratospheric airship is very large under the condition of low altitude, high latitude, wind, and in winter, etc. which might make the design of high‐altitude/long‐endurance airship an elusive goal. They also show that the solar cell efficiency is the key technology in the control of solar cell area required for airships, and the technology advances in regenerative fuel cells and propeller efficiency have significant effects among on the airship payload, size, and solar cell area required for airship.

The paper analyses the energy balance of the high‐altitude/long‐endurance airship.

The endurance of small unmanned air vehicles (UAVs) is directly associated with the energy density of the propulsion system used. As the batteries commonly used in small UAVs have a relatively low energy density, they are not sufficient for long-term endurance tasks. The purpose of this paper is to offer a solution to increase the endurance of a concept small UAV with combination of different power sources. The design, construction and ground tests of fuel cell-powered hybrid propulsion systems are presented in this paper.

The power requirements of a concept UAV were calculated according to aerodynamic calculations and then, hybrid propulsion system sources are determined. The hybrid system consists of a 100 W scale proton-exchange membrane (PEM) type fuel cell stack, lithium-polymer battery, solar cells and power management system (PMS). Subsequently, this hybrid power system was integrated with the new design of PMS and then series of ground tests were carried out.

This experimental study proved that it is theoretically possible to obtain an endurance of around 3 h for concept UAV with the proposed hybrid system.

The research study shows that fuel cell-based hybrid propulsion system with the proposed PMS can be widely used to obtain extended endurance in small UAVs.

A hybrid propulsion system with a novel PMS unit is proposed for small UAVs and the ground tests were implemented.

THE method used at present in fatigue testing aircraft joints and components by applying cycles of constant stress amplitude of a magnitude considered to be the most damaging is based on the assumption that Miner's cumulative damage rule, Σ(n/N)&equals l, holds good. This rule is known to be true only under certain conditions which may not apply to those under which fatigue damage is accumulated in aircraft.