Attention Limitations in the Detection and Identification of Alarms in Close Temporal Proximity

Objective The aim of this study was to establish the effects of simultaneous and asynchronous masking on the detection and identification of visual and auditory alarms in close temporal proximity. Background In complex and highly coupled systems, malfunctions can trigger numerous alarms within a short period of time. During such alarm floods, operators may fail to detect and identify alarms due to asynchronous and simultaneous masking. To date, the effects of masking on detection and identification have been studied almost exclusively for two alarms during single-task performance. This research examines 1) how masking affects alarm detection and identification in multitask environments and 2) whether those effects increase as a function of the number of alarms. Method Two experiments were conducted using a simulation of a drone-based package delivery service. Participants were required to ensure package delivery and respond to visual and auditory alarms associated with eight drones. The alarms were presented at various stimulus onset asynchronies (SOAs). The dependent measures included alarm detection rate, identification accuracy, and response time. Results Masking was observed intramodally and cross-modally for visual and auditory alarms. The SOAs at which asynchronous masking occurred were longer than reported in basic research on masking. The effects of asynchronous and, even more so, simultaneous masking became stronger as the number of alarms increased. Conclusion Masking can lead to breakdowns in the detection and identification of alarms in close temporal proximity in complex data-rich domains. Application The findings from this research provide guidance for the design of alarm systems.

“Compoundless Anaesthesia”, Controlled Administration, and Post-Operative Recovery Acceleration: Musings on Theoretical Nanomedicine Applications

Much research has been conducted on how patients may be served through new advances in perioperative anaesthetic care. However, adaptations of standardised care methodologies can only provide so many novel solutions for patients and caregivers alike. Similarly, unique methods such as nanoscopic liposomal package delivery for analgesics and affective numbing agents pose a similar issue—specifically that we are still left with the dilemma of patients for whom analgesics and numbing agents are ineffective or harmful. An examination of the potential gains that may result from the targeted development of nanorobotics for anaesthesia in perioperative care will be presented in this essay to help resolve this pending conflict for the research community. This examination should therefore serve as a “call to action” for such research and a “primer” for those for whom the method’s implementation would most directly impact.

A Literature Review of Drone-Based Package Delivery Logistics Systems and Their Implementation Feasibility

In recent years, e-commerce businesses have seen an increase in the daily volume of packages to be delivered, as well as an increase in the number of particularly demanding customer expectations. In this respect, the delivery mechanism became prohibitively expensive, particularly for the final kilometer. To stay competitive and meet the increased demand, businesses began to look for innovative autonomous delivery options for the last mile, such as autonomous unmanned aerial vehicles/drones, which are a promising alternative for the logistics industry. Following the success of drones in surveillance and remote sensing, drone delivery systems have begun to emerge as a new solution to reduce delivery costs and delivery time. In the coming years, autonomous drone sharing systems will be an unavoidable logistical solution, especially with the new laws/recommendations introduced by the Flight World Organization on how to organize the operations of these special unmanned airline systems. This paper provides a comprehensive literature survey on a set of relevant research issues and highlights the representative solutions and concepts that have been proposed thus far in the design and modeling of the logistics of drone delivery systems, with the purpose of discussing the respective performance levels reached by the various suggested approaches. Furthermore, the paper also investigates the central problems to be addressed and briefly discusses and outlines a series of interesting new research avenues of relevance for drone-based package delivery systems.

Application of Pythagorean Fuzzy Digraphs in Package Delivery Robots

The fuzzy set concept was developed to cope with uncertainty, whereas traditional sets are intended to deal with certainty. To address flaws in fuzzy set theory, extensions such as Intuitionistic Fuzzy Set (IFS), neutrosophic fuzzy sets, image fuzzy sets, and Pythagorean fuzzy set (PyFS) were developed. Pythagorean fuzzy set is useful tool for more clearly defining hazy concepts. In comparison to other fuzzy models, Pythagorean fuzzy set-based models allow more flexibility in handling human judgement information. The fuzzy graph structure is used to deal with the uncertainty in a network and to characterize its relationship with the non-empty vertex set. Pythagorean fuzzy graph (PyFG) was one of the Intuitionistic Fuzzy Graph (IFG) extensions. PyFG was created to cope with the uncertainty of an object and its relationship with other objects. PyFS and PyFG are the driving forces behind this innovative concept. This work defines Pythagorean Fuzzy Digraph (PyFDG), and PyFDG's score function. An algorithm is proposed for an issue to find the Pythagorean shortest path in package delivery robots.

Analisis Pengaruh Experiental Marketing terhadap Kepuasan dan Loyalitas Pelanggan di PT Pos Indonesia Pekanbaru

The development of technology and information today makes the domestic goods delivery service business increase every year. This causes the opportunity for the entry of courier service companies to be wide open so that it can result in a business in the field of courier services that is increasingly competitive. Competition to compete for potential customers and retain existing customers is an increasing challenge and must be faced by PT Pos Indonesia (Persero) in marketing its delivery services. PT Pos Indonesia (Persero) especially PT Pos Indonesia (Persero) Pekanbaru has implemented Experience Marketing in it’s business processes. However, in the last 3 years, based on Consumer Complain Handling (CCH) at PT Pos Indonesia (Persero) Pekanbaru, it has tended to increase, meanwhile Revenue from the Mail and Package Delivery Business tends to decrease. The purpose of this study is to analyze and find out how much influence Experiential Marketing has on Customer Satisfaction and Loyalty at PT Pos Indonesia (Persero) Pekanbaru. The population taken in this study were customers who had transacted more than 3 times at PT Pos Indonesia (Persero) Pekanbaru. The sample selection technique used is non-probability sampling, with the number of samples used as many as 180 samples. The data analysis method used is Structural Equation Modeling (SEM). From the results of research that has been done, it can be concluded that Experiential Marketing has a significant and positive effect on Customer Satisfaction. Experiential Marketing also has a significant and positive effect on Customer Loyalty, and Customer Satisfaction has a positive and significant effect on Customer Loyalty.

A 3D Vision Cone Based Method for Collision Free Navigation of a Quadcopter UAV among Moving Obstacles

In the near future, it’s expected that unmanned aerial vehicles (UAVs) will become ubiquitous surrogates for human-crewed vehicles in the field of border patrol, package delivery, etc. Therefore, many three-dimensional (3D) navigation algorithms based on different techniques, e.g., model predictive control (MPC)-based, navigation potential field-based, sliding mode control-based, and reinforcement learning-based, have been extensively studied in recent years to help achieve collision-free navigation. The vast majority of the 3D navigation algorithms perform well when obstacles are sparsely spaced, but fail when facing crowd-spaced obstacles, which causes a potential threat to UAV operations. In this paper, a 3D vision cone-based reactive navigation algorithm is proposed to enable small quadcopter UAVs to seek a path through crowd-spaced 3D obstacles to the destination without collisions. The proposed algorithm is simulated in MATLAB with different 3D obstacles settings to demonstrate its feasibility and compared with the other two existing 3D navigation algorithms to exhibit its superiority. Furthermore, a modified version of the proposed algorithm is also introduced and compared with the initially proposed algorithm to lay the foundation for future work.