Task Management and Timekeeping, Classic API

Author(s):  
Gedare Bloom ◽  
Joel Sherrill ◽  
Tingting Hu ◽  
Ivan Cibrario Bertolotti
Keyword(s):  
Author(s):  
Cristina Iani ◽  
Christopher D. Wickens

2020 ◽  
Vol 1 (100) ◽  
pp. 42-49
Author(s):  
A.M. Pysarenko ◽  

The article anylyses the theoretical and methodological basis for the study of the problem of team leadership in the student environment: the importance of team formation in the student environment, the essence of the concept of "leadership", the psychological components of effective team leadership. Team leadership is seen as the ability of a leader to gain authority in one’s group, thereby gaining the primary right to make group decisions, as well as to recognize the strengths of others and delegate task management functions to others. Also, command leadership is seen as a process of allocating authoritative personalities in a group and facilitating them to develop leadership qualities of other members of the group, which leads to the emergence of coordinated teamwork. It is noted that tactics of the leader’s influence on the group can determine the effectiveness of team leadership. His typical actions, internal psychological features, ability to update the desired features in a specific situation. The authors consider the internal psychological features of students, which determine the command style of leadership, as follows: flexibility, originality, critical thinking, orientation to solving problems in difficult situations; desire for cooperation, diplomacy, ability to manage and resolve conflicts, organizational skills, communication skills; striving for self-development and self-improvement. The essence of the empirical study of the psychological components of effective team leadership in a student environment is highlighted.


Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1788
Author(s):  
Gomatheeshwari Balasekaran ◽  
Selvakumar Jayakumar ◽  
Rocío Pérez de Prado

With the rapid development of the Internet of Things (IoT) and artificial intelligence, autonomous vehicles have received much attention in recent years. Safe driving is one of the essential concerns of self-driving cars. The main problem in providing better safe driving requires an efficient inference system for real-time task management and autonomous control. Due to limited battery life and computing power, reducing execution time and resource consumption can be a daunting process. This paper addressed these challenges and developed an intelligent task management system for IoT-based autonomous vehicles. For each task processing, a supervised resource predictor is invoked for optimal hardware cluster selection. Tasks are executed based on the earliest hyper period first (EHF) scheduler to achieve optimal task error rate and schedule length performance. The single-layer feedforward neural network (SLFN) and lightweight learning approaches are designed to distribute each task to the appropriate processor based on their emergency and CPU utilization. We developed this intelligent task management module in python and experimentally tested it on multicore SoCs (Odroid Xu4 and NVIDIA Jetson embedded platforms).Connected Autonomous Vehicles (CAV) and Internet of Medical Things (IoMT) benchmarks are used for training and testing purposes. The proposed modules are validated by observing the task miss rate, resource utilization, and energy consumption metrics compared with state-of-art heuristics. SLFN-EHF task scheduler achieved better results in an average of 98% accuracy, and in an average of 20–27% reduced in execution time and 32–45% in task miss rate metric than conventional methods.


Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 341
Author(s):  
Carolina Rodriguez-Paras ◽  
Johnathan T. McKenzie ◽  
Pasakorn Choterungruengkorn ◽  
Thomas K. Ferris

Despite the increasing availability of technologies that provide access to aviation weather information in the cockpit, weather remains a prominent contributor to general aviation (GA) accidents. Pilots fail to detect the presence of new weather information, misinterpret it, or otherwise fail to act appropriately on it. When cognitive demands imposed by concurrent flight tasks are high, the risks increase for each of these failure modes. Previous research shows how introducing vibrotactile cues can help ease or redistribute some of these demands, but there is untapped potential in exploring how vibratory cues can facilitate “interruption management”, i.e., fitting the processing of available weather information into flight task workflow. In the current study, GA pilots flew a mountainous terrain scenario in a flight training device while receiving, processing, and acting on various weather information messages that were displayed visually, in graphical and text formats, on an experimental weather display. Half of the participants additionally received vibrotactile cues via a connected smartwatch with patterns that conveyed the “severity” of the message, allowing pilots to make informed decisions about when to fully attend to and process the message. Results indicate that weather messages were acknowledged more often and faster when accompanied by the vibrotactile cues, but the time after acknowledgment to fully process the messages was not significantly affected by vibrotactile cuing, nor was overall situation awareness. These findings illustrate that severity-encoded vibrotactile cues can support pilot awareness of updated weather as well as task management in processing weather messages while managing concurrent flight demands.


2021 ◽  
pp. 106815
Author(s):  
Tao Zhang ◽  
Chengchao Li ◽  
Dongying Ma ◽  
Xiaodong Wang ◽  
Chaoyong Li

BJS Open ◽  
2021 ◽  
Vol 5 (Supplement_1) ◽  
Author(s):  
Alex Tebbett ◽  
Ian Purcell ◽  
Shereen Watton ◽  
Rathinavel Shanmugham ◽  
Alexandra Tebbett

Abstract Introduction During Covid-19 many staff members were redeployed to the Intensive Care Unit (ICU) with little opportunity to train in the new skills they would require. One such skill was the transfer of a critically ill, and contagious, patient from ICU; a risky and complicated procedure which requires planning, preparation, risk assessment, situational awareness and, ideally, experience. To assist our colleagues in this skill an existing ICU transfer course has been adapted to cover the Covid-19 situation, or any similar contagious pandemic, in patient transfer. Methods An in-situ simulation method was chosen as the most realistic method of immersing our participants into the environment of ICU and to highlight real-life complexities and issues they may face. A multidisciplinary training session was devised so that novice anaesthetists, ACCPs and nurses could learn together, reflective of the usual team. Human factors such as communication, team leadership, task management and situational awareness are the focus of the post-simulation debrief, and human factors sheets have been created to guide the participants in analysing these skills. Pre- and post-simulation confidence, knowledge and attitudes will be assessed using validated appraisal tools and questionnaires to gather both quantitative and qualitative data about the experience. Discussion Multidisciplinary training is often difficult to arrange, due to the different requirements, processes, and procedures each department demands. A hidden blessing of Covid-19 is the realisation that this barrier can be broken, for the benefit of our patients and colleagues alike, and training sessions like this implemented.


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