Decision Making in Dynamic Environments: Fixation Errors and Their Causes

Optimal maintenance over a finite time horizon for a system under imperfect inspection and dynamic working environment

The construction of a practical nanorobot is a definite futuristic reality. However development of a Nanorobot is associated with a multitude of challenges and limitations related mainly to its control and behavior aspects in different dynamic work environments. In this chapter a novel Nanorobot movement control algorithms in dynamic environment has being introduced. To avoid obstacles during movement trajectory, swarm intelligence based approach and for sensing, path planning, obstacle avoidance and target detection of nano-robot Quorum and RFID based approach has been utilized. Major proportion of work has been done on Microsoft Robotics Developer Studio 2008 (MSRD, 2008) along with two kinds of programming environment VPL and SPL. The chapter also includes a description of how nanorobotics technology has been applied in medical field. In this context, a non invasive method to treat a brain blood clot using nanorobots has being explained. Various other aspects of application of nanorobots has also been briefly mentioned.

PurposeIn situ 3D reconstruction is the basis for measuring and monitoring large-scale working environments such as construction sites and coal mining surfaces. The purpose of this paper is to address the difficulties of on-site 3D reconstruction in large-scale dynamic environments. Based on panoramic rotating light detection and ranging sensors, a dynamic environment 3D reconstruction method combining occupancy grid and point cloud segmentation is proposed.Design/methodology/approachThe algorithm fully combines the information between point clouds to process the points in the region of interest, improving the processing speed of the occupancy grid method and the accuracy of dynamic object filtering. Furthermore, this paper also proposes an incremental long-short horizon segmentation and reconstruction workflow, which performs different levels of point cloud differential segmentation for various types of dynamic objects.FindingsThis paper designs detailed physical and simulation experiments in different environments to verify the advantages and reliability of the algorithm. The entire system showed satisfactory performance in experiments.Originality/valueThe proposed dynamic environment 3D reconstruction method can effectively complete the 3D reconstruction of complex work environments, and the proposed incremental long-short horizon segmentation and reconstruction workflow further improves the accuracy of dynamic object removal.

Industry 4.0 is creating a radically more dynamic work environment, which calls for considerable changes in the role of industry professionals. As industries need to respond to evolving trends quickly, as well professionals need to be able to work and constantly learning in this new work environment. Besides, due to the continuous advances in technology and the adoption of these technologies in the industries processes, the level of complexity in the workplace is increasing, which results in the need for a new professional role. However, the main challenge is how to prepare and qualify these professionals to acquire these competences. In order to provide a better understanding of the new professional role and their relationship with the industry 4.0 working environment, this paper introduces an ontology for Competence Management in the Fourth Industrial Revolution. Considering the recent scientific and business developments for preparing the industries and workers for this new working era, competences and skills needed for professionals in industry 4.0 were reviewed, as well as challenges and opportunities. Based on a systematic literature review in scientific sources and grey literature, this work identified what technologies are being adopted and what the professional competences are for working in this working environment. Since Industry 4.0 is spreading all over the world, this study contributes to this understanding and also provides a starting point for further research regarding workforce competence management for Industry 4.0.KeywordsIndustry 4.0Workforce skillsetCompetence managementOntology

This study aims to analyze the influence of leadership, work environment, work motivation, organizational communication, and training on employee performance at PT XYZ, ABC International Airport. As a strategic national sector, the aviation industry demands effective human resource management to ensure service excellence and organizational competitiveness. This research employs a quantitative approach with descriptive and verificative methods, using Structural Equation Modeling (SEM) AMOS involving 155 respondents. The analysis results indicate that only organizational communication positively and significantly affects employee performance (p < 0.05), while leadership, work environment, motivation, and training show no direct significant effect. These findings highlight the critical role of effective internal communication in enhancing performance within complex and dynamic work environments such as airports. The managerial implication is the need for the company to prioritize the development of robust internal communication systems both vertically and horizontally to support efficient coordination, prompt decision-making, and overall productivity improvement. This study contributes both theoretically and practically to the development of human resource strategies in the air transportation service sector.

Normal Distribution Transform (NDT) algorithm plays the role of detecting the relative pose of the vehicle in high-precision map. In this paper, a method of setting downsampling factor and grid factor for NDT relocation algorithm in dynamic environment is proposed, which can solve the problems of excessive NDT relocation error and location loss caused by dynamic objects accounting for 1 % to 35 % of the volume of scanning point cloud in vehicle environment. To simulate a real dynamic point cloud environment, the single-frame LiDAR point cloud space is voxelized into a mesh. Each grid is assigned a random number evenly distributed between 0 and 1. The threshold value for whether to add a Gaussian noise point is also set. Seven representative dynamic objects on the highway are selected. The threshold value of probability distribution function of Gaussian noise object needs to be set. Then the volume content of the dynamic object in the single frame point cloud space is calculated according to the set threshold value by using the definite integral. By changing the content and volume of dynamic obstacles in a dynamic environment, the effects of the downsampling factor and the grid factor on the accuracy of the repositioning trajectory are obtained. The resampling and mesh coefficients are optimized based on the analysis of the repositioning trajectory accuracy. The results show that When the current sampling factor is fixed, the grid factor of the NDT algorithm is proportional to the RMSE factor. When the NDT grid factor is fixed and the down sampling factor is equal to the side length of the obstacle, the NDT relocation accuracy is the highest and reaches the local optimum.

In order to be able to deliver efficient and effective decision support technologies within healthcare, it is important to be able to understand and describe decision making in medical diagnosis, treatment and administrative processes. This paper outlines how information can be synthesized, interpreted and used during decision making in dynamic healthcare environments. We intend to develop a set of modeling constructs that describe the decision requirements forming the basis for adequate situation awareness in clinical processes. We propose that a separate decision perspective will 1) enhance the shared understanding of the decision context among clinical staff, and 2) provide a better understanding of how we can design information system support for complex cognitive tasks in dynamic work environments.

The purpose of the research is to understand the factors that affect employer branding, particularly in the context of Generation Z employees in startup companies. Startups have emerged as a prominent career option for Generation Z in the current globalization era, due to their innovative and dynamic work environments. The goal of this study is to determine which aspects of employer attractiveness align with the aspirations and values of Generation Z, specifically analyzing PT Eximku Teknologi Indonesia (Andalin). The study used a qualitative methodology, involving in-depth interviews with internal Andalin and external startup employees. The purpose of the data collection is to identify how employees vary in their responses to the various aspects of employer attractiveness, such as Social Value, Development Value, Application Value, Safety Value, and Economic Value. According to the study, Andalin employees are largely satisfied on most criteria except Economic Value, where some respondents believe their workload is not appropriately provided. External respondents are dissatisfied with most characteristics, except for social, developmental, and economic values, demonstrating a lack of organizational belonging and long-term job stability in startups. Notable results indicate that social media efficiently showcases the working environment to Generation Z and attracts their attention, demonstrating how it is so important for employer branding. Another suggested strategy to increase awareness of the company's culture, vision, mission, and core values of the company is to improve the career website. Furthermore, offering complimentary educational or developing skills courses is suggested as an efficient way of underlying continuous development within the organization, which results in attracting potential employees.

Office layout arrangements have an important role in increasing employee effectiveness in a dynamic work environment. This research explores the impact of smart office layout arrangements on increasing employee productivity at PT. Chunsan Group Indonesia. The goal is to provide an in-depth understanding of office layout settings that can increase productivity. The research method involves data collection and in-depth interviews in an office layout setting. The research findings emphasize the importance of applying office layout theory efficiently to increase productivity. The conclusion is that smart office layout settings can play a role in increasing employee productivity and comfort in the company. The recommendation from this research is that organizations, including PT. Chunsan Group Indonesia pays close attention to office layout design to create an optimal work environment. It is hoped that the implications of this research can help organizations design office layouts that support employee productivity and achieve company goals.

This paper aims to provide an in-depth understanding of how the combination of intuitive leadership and mentoring can be a key factor in achieving competitive advantage and sustainable growth in the modern business context. The method used is qualitative where the source of findings comes from articles related to the variables in this paper, with a time span of ten years and this proof to strengthen and provide an implementation result in a result in a scientific paper or article. Intuitive leadership and mentoring on employee performance, it can be concluded that these two elements play an important role in shaping a productive work environment that supports individual growth. Intuitive leadership, with its emphasis on instinct-based decision-making and emotional intelligence, creates responsive and adaptive leaders. This dynamic work environment allows employees to thrive, creating a culture of flexibility and innovation. Mentoring also contributes significantly to employee performance, through personalized and ongoing mentoring. With mentors in place, employees can experience increased job satisfaction, engagement and development of specialized skills.

The Human Resource Management plays a vital role in an academic institution particularly ensuring the welfare of its employees. However, in a dynamic work environment and a fast-changing landscape of labor, industry and education, there are challenges that need to be discovered to provide a remedy that will serve as a catalyst of change for the improvement of its function and effectiveness. These will transcend barriers of ambiguity and complexity and initiate value and principles augmenting to the gap between the top management and employees. The researchers aimed to answer the following: Functions of the Human Resource Department, challenges, coping and its quality assurance mechanisms. To explore the experiences and insights of instituting quality assurance mechanisms of the HRDO directors, a narrative analysis was used. Results have revealed that the Human Resource is a complex work environment, and a genuine commitment is necessary, challenges are emanating from both internal and external factors, and one should adapt to provide a continuing and nurturing commitment that will ensure the well-being of employees. Recommendations focuses on fostering interpersonal relationships, providing regular faculty and staff development opportunities, ensuring accountability and responsibility and a sense of security.

When a robot manipulator performs tasks in a dynamic unstructured environment, it not only should account for where and how it should move, but also ensure that the robot can effectively avoid collisions with static and moving obstacles. Planning in absolutely unstructured and dynamic environment is much more challenging, up-to-date there is no universal solution to this problem. In this paper, we believed the concept that for motion planning in real dynamic environments, usually there is only a part of a path invalidated by obstacles, and only this part needs replanning. Thus, in this paper a practical strategy was presented for motion planning in dynamic environments. First, a variant dynamic Rapidly-exploring Random Tree (RRT) planner was designed to combine global planning with local replanning. Then, the proposed dynamic RRT algorithm was implemented under Robotic Operation System (ROS) framework and applied to a 7-degree-of-freedom manipulator. Experimental results have shown that the proposed dynamic RRT planner can plan and execute movement of robot manipulator between a starting and target position while preserving task constraints and reacting to environment changes in real time.

Health-care organizations are now moving toward integrated delivery systems to provide high-quality care, as they are being held to an ever-increasing scope of accountabilities. Distributed applications such as telemedicine and electronic patient records (EPR) are seen as key requirements for the future to deliver cost effective and high-quality health-care services. This initiative would provide dynamic environments for health professionals to access patient information and thereby increase the decision-making capacities on patient care procedures. Although telemedicine applications and EPR contribute to the improvement of healthcare services, poor communication mechanisms and practices negatively impact on quality of service (QoS) in teamwork environments of patient care. Awareness and responsiveness are becoming important factors in dynamic group collaborative work environments in healthcare facilities. This paper reports on a detailed case study of group communication patterns in a patient service environment. Further, an ethnographic approach that addresses group communications patterns, identifies tools and techniques in light of Computer-Supported Collaborative Work (CSCW), which requires the application of a number of disciplines including sociology, organizational science, psychology, and computer science. In cooperative work environments, it is important to understand the activities of others for human interaction and communication in general. This is very important for future development of CSCW-based distributed architectures that focus on the challenges of improving QoS in healthcare environments.

Electric vehicles are a key alternative to fossil fuel-based transportation but face challenges in safety and driving range. Blade battery technology, with its long and flat shape, offers improved heat distribution and safety. This study focuses on the thermal performance of a blade-shaped Lithium Iron Phosphate (LFP) battery enhanced with manganese (LMFP), using a water-based cooling system to ensure temperature stability during operation. Effective thermal management, including the use of cooling systems, is crucial for maintaining battery performance and reliability. This study modeled a blade-shaped battery with a water-cooling system using ANSYS Fluent. The process involves designing 3D geometry and meshing to simulate thermal behavior accurately. The simulation was conducted under varying operating conditions by applying different inlet temperatures for the cooling system (14.85°C, 26.85°C, and 34.85°C ) combined with different discharge rates (0.5C, 1C, 2C, and 5C). These parameter variations were designed to evaluate the thermal response of the battery under realistic and dynamic working environments. The results indicate that the cooling system can maintain the battery temperature within the optimal thermal range, with the maximum temperature remaining below 35°C across all tested conditions. Higher C-rates resulted in increased internal heat generation, leading to higher cell temperatures. This study contributes to the development of thermally stable, higher-energy-density batteries, offering practical insights for designing safer and more efficient battery packs in electric vehicles.

The challenge of complex multi-attribute large group decision-making (CMALGDM) is reflected from three perspectives: interrelated attributes, large group decision makers (DMs) and dynamic decision environments. However, there are few decision techniques that can address the three perspectives simultaneously. This paper proposes a random intuitionistic fuzzy factor analysis model, aiming to address the challenge of CMALGDM from the three perspectives. The proposed method effectively reduces the dimensionality of the original data and takes into account the underlying random environmental factors which may affect the performances of alternatives. The development of this method follows three steps. First, the random intuitionistic fuzzy variables are developed to deal with a hybrid uncertain situation where fuzziness and randomness co-exist. Second, a novel factor analysis model for random intuitionistic fuzzy variables is proposed. This model uses specific mappings or functions to define the way in which evaluations are affected by the dynamic environment vector through data learning or prior distributions. Third, multiple correlated attribute variables and DM variables are transformed into fewer independent factors by a two-step procedure using the proposed model. In addition, the objective classifications and weights for attributes and DMs are obtained from the results of orthogonal rotated factor loading. An illustrative case and detailed comparisons of decision results in different environmental conditions are demonstrated to test the feasibility and validity of the proposed method.