New software, OLEX2, has been developed for the determination, visualization and analysis of molecular crystal structures. The software has a portable mouse‐driven workflow‐oriented and fully ...comprehensive graphical user interface for structure solution, refinement and report generation, as well as novel tools for structure analysis. OLEX2 seamlessly links all aspects of the structure solution, refinement and publication process and presents them in a single workflow‐driven package, with the ultimate goal of producing an application which will be useful to both chemists and crystallographers.
This paper examines technological acceptance for automated emotion-sensing devices and non-conscious data collection (NCDC). We argue that conventional 20th century scholarship of human-machine ...relations is ill-equipped in the age of intelligent machines that sense, monitor, and tracks human sentiment, emotion, and feeling. We conduct a regression analysis on a dataset of 1015 Generation Z student respondents (age 18–27) from 48 countries and 8 regions worldwide using the Bayesian Hamiltonian Monte Carlo approach. The empirical results highlight the significance of sociocultural factors that influence technological acceptance by this specific generational demographic. Our findings also demonstrate the advantage but also the inherent limitation of traditional theories such as Davis's “Technological Acceptance Model” in accounting for of cross-cultural factors such as religions and regions, given the transfer of new technologies across borders. Moreover, our findings highlight important governance and design implications that need to be addressed to ensure that emotional AI systems and devices serve the best interests of individuals and societies.
•Emotion-sensing devices exacerbate concerns about non-conscious data collection.•Acceptance of emotional data harvesting varies by cultures, sectors, demographics.•It is necessary to extend the Technological Acceptance Model in a systematic and hierarchical manner.
Unmanned Aerial Vehicles (UAVs) are increasingly being used for data harvesting from Wireless Sensor Nodes (SNs). This study aims to minimize the Age of Information (AoI) during data collection, ...while also considering the energy sustainability of the UAVs. Addressing the challenge of optimizing performance in Multi-Agent Reinforcement Learning (MARL) systems as the number of agents increases, our study introduces a MARL approach combined with curriculum learning and evolutionary strategy. This innovation specifically targets the performance issue in traditional MARL setups when scaling up the number of agents. By applying curriculum learning and evolutionary strategies, our method not only enhances MARL scalability but also integrates energy-efficient charging mechanisms, effectively enhancing system performance in large-scale deployments. Numerical results show that our proposed algorithm outperforms baselines in terms of AoI and charging, proving its effectiveness in managing the complexities of large-scale MARL systems.
•MARL with EPC minimizes AoI effectively.•EPC algorithm enhances multi-agent learning.•Energy-efficient trajectories vital for UAV data harvesting.•AoI minimization constant crucial for real-time tasks.
This paper designs energy-efficient trajectories for unmanned aerial vehicles (UAVs) harvesting data sequentially from distributed ground nodes. We propose a novel optimization framework for path ...planning, based on dynamic programming. We develop an optimum backward-forward algorithm that jointly optimizes the hovering locations for each ground node, and the visiting order to those locations. Our algorithm minimizes the total energy consumption of the UAV over its trajectory. Our framework is compatible with various probabilistic wireless communication channel models, and can also be applied to different cost functions, including minimising the total flying time, and allowing for bi-directional communications. We also develop a lower complexity algorithm that approximates the optimum UAV trajectory by decomposing the original problem into two sub-problems, and iterating back and forth between the two. This alternating algorithm has polynomial time complexity, and we show that it produces a near-optimum UAV trajectory, with as little deviation as 5% to 15% from the average energy consumption of the optimum algorithm.
This article advocates for web scraping as an effective method to augment and enhance technical and professional communication (TPC) research practices. Web scraping is used to create consistently ...structured and well-sampled data sets about domains, communities, demographics, and topics of interest to TPC scholars. After providing an extended description of web scraping, the authors identify technical considerations of the method and provide practitioner narratives. They then describe an overview of project-oriented web scraping. Finally, they discuss implications for the concept as a sustainable approach to developing web scraping methods for TPC research.
Video-based noncontact detection of heart rate has a wide range of applications in the field of medicine and health. However, this method is susceptible to noise interference, making it difficult to ...effectively extract blood volume pulse (BVP) signals. To overcome this problem, a new method of noncontact heart rate estimation that can suppress noise interference is proposed in this paper. First, the established data acquisition system conducts video collection, and the captured videos are divided into multiple small regions. Subsequently, the initial signals of BVP are extracted in accordance with the chrominance features extracted through multi-channel data fusion. The BVP signals are separated using the FastICA algorithm. The kurtosis value and signal-to-noise ratios of the power spectrum of the separated signals are analyzed to determine the effective separation component. Results show that this method can extract and process pulse signals, effectively suppressing non-periodic interference. The experiment also proves that the method has good consistency with the measurement of pulse oximeter and has good stability and accuracy in the detection of heart rate of the human body.
•Ricgraph can store many types of items in a single graph.•Ricgraph harvests multiple source systems into a single graph.•Ricgraph Explorer is the exploration tool for Ricgraph.•Ricgraph facilitates ...reasoning about items because it infers new relations between items.•Ricgraph can be tailored for an application area.
Ricgraph, also known as Research in context graph, enables the exploration of researchers, teams, their results, collaborations, skills, projects, and the relations between these items.
Ricgraph can store many types of items into a single graph. These items can be obtained from various systems and from multiple organizations. Ricgraph facilitates reasoning about these items because it infers new relations between items, relations that are not present in any of the separate source systems. Ricgraph is flexible and extensible, and can be adapted to new application areas.
In this article, we illustrate how Ricgraph works by applying it to the application area research information.
Unmanned Aerial Vehicles (UAVs) have been considered to have great potential in supporting reliable and timely data harvesting for Sensor Nodes (SNs) from an Internet of Things (IoT) perspective. ...However, due to physical limitations, UAVs are unable to further process the harvested data and have to rely on terrestrial servers, thus extra spectrum resource is needed to convey the harvested data. To avoid the cost of extra servers and spectrum resources, in this paper, we consider a UAV-based data harvesting network supported by a Cell-Free massive Multiple-Input-Multiple-Output (CF-mMIMO) system, where a UAV is used to collect and transmit data from SNs to the central processing unit of CF-mMIMO system for processing. In order to avoid using additional spectrum resources, the entire bandwidth is shared among radio access networks and wireless fronthaul links. Moreover, considering the limited capacity of the fronthaul links, the compress-and-forward scheme is adopted. In this work, in order to maximize the ergodically achievable sum rate of SNs, the power allocation of ground access points, the compression of fronthaul links, and also the bandwidth fraction between radio access networks and wireless fronthaul links are jointly optimized. To avoid the high overhead introduced by computing ergodically achievable rates, we introduce an approximate problem, using the large-dimensional random matrix theory, which relies only on statistical channel state information. We solve the nontrivial problem in three steps and propose an algorithm based on weighted minimum mean square error and Dinkelbach's methods to find solutions. Finally, simulation results show that the proposed algorithm converges quickly and outperforms the baseline algorithms.
A wireless sensor network assisted by multiple autonomous unmanned aerial vehicles (UAVs) is a promising solution for harvesting data and monitoring the circumstance in various applications. However, ...the complicated path planning problem of each UAV is still problematic. In this paper, we propose an optimal operation strategy based on multi-agent reinforcement learning (MARL) to tackle these hurdles. Various parameters such as the number of deployed UAVs, charging start capacity, and charging complete capacity define a multi-UAV system. This approach is applicable without a time-consuming and costly policy control. We also describe how to balance multiple objectives, such as data harvesting, charging, and collision avoidance, using transfer learning. Finally, learning a policy control that generalizes multiple scenario parameters allows us to analyze the performance of individual parameters in a specific scenario, which helps find the macro-level optimal parameter within a particular scenario. Videos are available at https://github.com/mincheolseong/UAV-Trajectory-Optimizer.
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