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The purpose of this research is to achieve multi-task autonomous driving by adjusting the network architecture of the model. Meanwhile, after achieving multi-task autonomous driving, the authors found that the trained neural network model performs poorly in untrained scenarios. Therefore, the authors proposed to improve the transfer efficiency of the model for new scenarios through transfer learning.

First, the authors achieved multi-task autonomous driving by training a model combining convolutional neural network and different structured long short-term memory (LSTM) layers. Second, the authors achieved fast transfer of neural network models in new scenarios by cross-model transfer learning. Finally, the authors combined data collection and data labeling to improve the efficiency of deep learning. Furthermore, the authors verified that the model has good robustness through light and shadow test.

This research achieved road tracking, real-time acceleration–deceleration, obstacle avoidance and left/right sign recognition. The model proposed by the authors (UniBiCLSTM) outperforms the existing models tested with model cars in terms of autonomous driving performance. Furthermore, the CMTL-UniBiCL-RL model trained by the authors through cross-model transfer learning improves the efficiency of model adaptation to new scenarios. Meanwhile, this research proposed an automatic data annotation method, which can save 1/4 of the time for deep learning.

This research provided novel solutions in the achievement of multi-task autonomous driving and neural network model scenario for transfer learning. The experiment was achieved on a single camera with an embedded chip and a scale model car, which is expected to simplify the hardware for autonomous driving.

The purpose of this research paper is to recover the autonomous flight performance of a mini unmanned aerial vehicle (UAV) via stochastically optimizing the wing over certain parameters (i.e. wing taper ratio and wing aspect ratio) while there are lower and upper constraints on these redesign parameters.

A mini UAV is produced in the Iskenderun Technical University (ISTE) Unmanned Aerial Vehicle Laboratory. Its complete wing can vary passively before the flight with respect to the result of the stochastic redesign of the wing while maximizing autonomous flight performance. Flight control system (FCS) parameters (i.e. gains of longitudinal and lateral proportional-integral-derivative controllers) and wing redesign parameters mentioned before are simultaneously designed to maximize autonomous flight performance index using a certain stochastic optimization strategy named as simultaneous perturbation stochastic approximation (SPSA). Found results are used while composing UAV flight simulations.

Using stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV over previously mentioned wing parameters and FCS, it obtained a maximum UAV autonomous flight performance.

Permission of the directorate general of civil aviation in the Republic of Türkiye is essential for real-time UAV autonomous flights.

Stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV wing parameters and FCS approach is very useful for improving any mini UAV autonomous flight performance cost index.

Stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV wing parameters and FCS approach succeeds confidence, highly improved autonomous flight performance cost index and easy service demands of mini UAV operators.

Creating a new approach to recover autonomous flight performance cost index (e.g. satisfying less settling time and less rise time, less overshoot during flight trajectory tracking) of a mini UAV and composing a novel procedure performing simultaneous mini UAV having passively morphing wing over certain parameters while there are upper and lower constraints and FCS design idea.

Previous sales control research has limited the definition of outcome controls exclusively to sales outcomes in an outside sales context. In addition to sales outcome controls, inside sales managers use phone operational outcomes to influence inside sales agent performance, supporting the need to expand the broader definition of outcome controls. Hence, the purpose of this paper is to explore the need to bifurcate outcome controls into two distinct variables: sales and phone operational controls. Researchers know little about the application of sales outcome controls beyond sales-only outcomes, which, in turn, limits the definition of outcome controls.

Through the utilization of survey, secondary operational data and sales manager’s feedback, this paper demonstrates that the definition of outcome controls needs to be divided into two distinct areas, sales and phone operational controls for inside sales agents, which, in turn, acts collectively to impact an inside sales agent’s job performance and satisfaction.

This research demonstrates that inside sales managers depend on both sales and phone operational outcome controls to drive sales agent performance, varying in degrees by industry. Even as inside sales managers focus on creating an employee-centric autonomous motivational work culture, the overarching controlling factors associated with phone operational outcomes dampen an inside sales agent’s performance and job satisfaction.

To the best of the authors’ knowledge, as the first sales control research to examine an inside sales context, this study provides support to further study sales controls in an inside sales context. This research can be enhanced by examining business-to-consumer inside sales environments, behavior controls, greater sample size and additional work outcomes such as turnover and tenure.

The findings have important implications because they can help practitioners understand the effect that both sales and phone operational outcomes have on sales agent performance. It also illuminates the need for inside sales managers to be less controlling in their focus on phone operational outcomes, as such a practice has a negative influence on key sales agent job outcomes.

To the best of the authors’ knowledge, this study is the first to triangulate multiple data sources to illustrate the need to evaluate both sales and phone operational outcomes as broader components of sales outcome controls. The study of sales controls in a different sales context suggests that sales management controls may differ by sales context, opening the door to extend the vast sales control literature beyond its current context of outside sales.

Numerous studies have focused on the effect of motivation on performance in the workplace. The purpose of this paper is to evaluate the somewhat overlooked role of positive and negative emotions as potential mediators of this critical association.

The longitudinal study employed multilevel modeling for assessing the effects of motivation, emotions and work satisfaction on job performance. In total, 116 respondents provided 1,044 responses at nine consecutive measurement points.

Findings indicated that positive emotions and job satisfaction mediate the positive association between autonomous motivation and performance. Concurrently, negative emotions and decreased job satisfaction mediated the negative associations between controlled motivation and job performance.

The results address only the within-subject and between-subject analysis of temporal variations in emotions and behavior. Future studies can include higher levels of analysis, such as group, team and organizational contexts.

This research contributes to self-determination theory by highlighting the role of emotions in understanding how motivation shapes workplace performance.

The purpose of this paper is to develop a simplified atmospheric model including constant wind, turbulence, gusts, and wind shear to provide simulation tools for unmanned aerial vehicle (UAV) design, testing, and evaluation within the West Virginia University (WVU) UAV simulation environment.

Analytical methods and experimental data are used to develop the simplified model for air mass motion as a superposition of four major components. Spatial gradients of relative air velocity vector projections are considered for modeling wind shear effects. The total contribution to relative air velocity from the four components in vehicle body axes is used within the WVU UAV simulation environment to calculate aerodynamic forces and moments. The simplified wind model is also interfaced with aircraft sub-system upset conditions models and different autonomous flight scenarios.

The simplified wind model developed provides simulation of different upset environment flight conditions with desirable levels of realism. It allows the testing, comparison, and evaluation of different trajectory tracking solutions for autonomous flight.

The proposed simplified wind model facilitates the investigation of the effects of different atmospheric scenarios on the performance of trajectory generation algorithms and trajectory tracking control laws.

The proposed simplified wind model has been proved to be a high flexibility tool for simulation of UAVs under normal and abnormal flight conditions. It is expected to provide valuable support for the design and analysis of autonomous flight control laws.

This research effort provides a new capability for the advanced simulation of UAV autonomous flight with practically no additional computational cost. It adds an unprecedented level of detail and versatility to the UAV simulation toolkit within a very user-friendly framework aimed at supporting UAV design and analysis for optimal performance and safety under normal and abnormal flight conditions.

In this paper, the authors take an amorphous flattened air-ground wireless self-assembling network system as the research object and focus on solving the wireless self-assembling network topology instability problem caused by unknown control communication faults during the operation of this system.

In the paper, the authors propose a neural network-based direct robust adaptive non-fragile fault-tolerant control algorithm suitable for the air-ground integrated wireless ad hoc network integrated system.

The simulation results show that the system eventually tends to be asymptotically stable, and the estimation error asymptotically tends to zero with the feedback adjustment of the designed controller. The system as a whole has good fault tolerance performance and autonomous learning approximation performance. The experimental results show that the wireless self-assembled network topology has good stability performance and can change flexibly and adaptively with scene changes. The stability performance of the wireless self-assembled network topology is improved by 66.7% at maximum.

The research results may lack generalisability because of the chosen research approach. Therefore, researchers are encouraged to test the proposed propositions further.

This paper designs a direct, robust, non-fragile adaptive neural network fault-tolerant controller based on the Lyapunov stability principle and neural network learning capability. By directly optimizing the feedback matrix K to approximate the robust fault-tolerant correction factor, the neural network adaptive adjustment factor enables the system as a whole to resist unknown control and communication failures during operation, thus achieving the goal of stable wireless self-assembled network topology.

This research study aims to minimize autonomous flight cost and maximize autonomous flight performance of a slung load carrying rotary wing mini unmanned aerial vehicle (i.e. UAV) by stochastically optimizing autonomous flight control system (AFCS) parameters. For minimizing autonomous flight cost and maximizing autonomous flight performance, a stochastic design approach is benefitted over certain parameters (i.e. gains of longitudinal PID controller of a hierarchical autopilot system) meanwhile lower and upper constraints exist on these design parameters.

A rotary wing mini UAV is produced in drone Laboratory of Iskenderun Technical University. This rotary wing UAV has three blades main rotor, fuselage, landing gear and tail rotor. It is also able to carry slung loads. AFCS variables (i.e. gains of longitudinal PID controller of hierarchical autopilot system) are stochastically optimized to minimize autonomous flight cost capturing rise time, settling time and overshoot during longitudinal flight and to maximize autonomous flight performance. Found outcomes are applied during composing rotary wing mini UAV autonomous flight simulations.

By using stochastic optimization of AFCS for rotary wing mini UAVs carrying slung loads over previously mentioned gains longitudinal PID controller when there are lower and upper constraints on these variables, a high autonomous performance having rotary wing mini UAV is obtained.

Approval of Directorate General of Civil Aviation in Republic of Türkiye is essential for real-time rotary wing mini UAV autonomous flights.

Stochastic optimization of AFCS for rotary wing mini UAVs carrying slung loads is properly valuable for recovering autonomous flight performance cost of any rotary wing mini UAV.

Establishing a novel procedure for improving autonomous flight performance cost of a rotary wing mini UAV carrying slung loads and introducing a new process performing stochastic optimization of AFCS for rotary wing mini UAVs carrying slung loads meanwhile there exists upper and lower bounds on design variables.

We examine how input- (vs. output-) based performance evaluation and incentive intensity impact employees’ autonomous motivation, thereby influence their proactive work behaviors.

We collected survey responses from 309 employees of different firms. Multi-group Structural Equation Modeling analyses were used to analyze the data.

Input-based evaluation had a positive effect on autonomous motivation and proactive work behaviors when task uncertainty was high, but a negative effect when it was low. Autonomous motivation had a positive effect on proactive work behaviors.

Our results on the moderating effect of task uncertainty provide insights into inconsistencies in earlier studies. Moreover, applying self-determination theory of motivation to incentive research can provide some insights into why sometimes, incentives can negatively affect performance.

The study of proactive work behaviors is important because despite their necessity in the fast-changing business environment, they are relatively unexplored in the incentive literature. Proactivity is especially important for tasks that are high in uncertainty because the exact tasks to achieve those goals are hard to specify.

We investigate the effect of performance management system on proactive work behaviors, mediated by autonomous motivation and moderated by task uncertainty.

Previous sales research remains limited to analyzing the influence of sales activities with sales agent tenure. To date, research on this subject has focused on the downstream direct or indirect impact of sales activities to sales performance, failing to consider whether sales activities impact a sales agent’s tenure. This paper aims to assess the effect of sales activities on sales performance and sales agent engagement on sales agent tenure through the lens of autonomous motivation to better understand sales activities as an overall sales process antecedent

Through the utilization of secondary sales operational data, this research demonstrates the influence of sales activities on multiple sales agent outcomes, while depicting the importance of sales managers creating an autonomous motivational climate.

This research demonstrates the direct relationship between sales activities to job engagement and sales performance. However, sales activities have a negative relationship to sales agent tenure, which require a sales manager to create an autonomous motivation to mediate the relationship between sales activities and sales agent tenure.

Organizations are provided with sample methodology and analysis to better determine how a culture grounded in autonomous motivation mediates sales activities and can be a catalyst for improving sales agent tenure. Then, provide a better understanding of the effect of actual sales activities on important sales department work outcomes.

The model is the first to test holistically the influence of sales activities on sales performance, sales agent engagement and tenure jointly by using actual secondary operational data. This study provides a glimpse of the real world balance a sales manager must consider between climate and activities. Plus, this study takes initial steps to study sales agent engagement, an under-researched construct in sales research.

The purpose of this study is to extend sales control research to inside sales. Aside from a few notable exceptions (Conde et al., 2022) much of the sales control literature has focused on a single control mechanism rather than a sales control portfolio perspective. The authors add multiple layers to Conde et al. (2022) by capturing secondary operational data and manager interviews to access sales control theory in practice.

With operational data from a Fortune 100 financial services company and sales manager interviews, the authors present evidence that managers apply a portfolio of controls to ensure sales agents’ overall performance.

Findings support that cultural controls have a greater influence on overall performance than a focus solely on process and outcome controls. Inside sales managers can generate better results when they focus on creating an employee-centric culture rather than controlling sales agents with formal sales controls.

This study extends sales control research by examining inside sales managers’ formal and informal sales controls. Historically, inside sales had sales leaders balance a myriad of sales controls grounded in strict oversight. With a few notable exceptions, the limited inside sales control research provides the opportunity to display an inside sales manager’s need to jointly focus on operational results and sales outcomes, illustrating the importance of cultural controls compared to other sales process and outcome controls. This research considerably extends sales controls research by focusing on inside sales.