Naturalistic data collection of head posture during smartphone use

Association between smartphone use and head-down tilt posture has not yet been quantitatively evaluated in natural settings. This study aimed to objectively assess the angle and duration of head-down tilt posture of smartphone users during a typical working day via naturalistic data collection. Thirty-one college students conducted their typical school activities while their head posture and smartphone-app usage records were collected simultaneously for 8?hours. Participants spent 125.9?minutes (median usage duration) on their smartphones with significantly larger head-down tilt (p?<?.05) than when they were not using the phone. Head tilt angle greater than 30° was found to be more common when using the phone, while head tilt less than 20° was more common when they were not using the phone. Study findings provide empirical evidence that supports an association between the duration of smartphone use and the intensity of head-down tilt posture.

Practitioner Summary: Head postures of young smartphone users were quantified for 8?hours continuously during a typical workday using a wearable sensor. Participants spent more time in larger head-down tilt postures (greater than 30°) when they were using their smartphones as compared to when they were not using them.     

To the humanities: what does communication studies give?

ABSTRACT

This special issue of Review of Communication presents new offerings of the study of communication, forging present and future humanities. This Introduction engages the six essays in this special issue—which extend and intersect across categories of the humanistic study of communication: communication philosophy and ethics, rhetorical theory, history, pedagogy, criticism, and digital humanities—to explore their contributions in defense of the humanities. Taken together, these essays explore the study of communication as (1) a resource for inquiring and exchanging with concepts, practices, and embodiments of difference, the other, and the posthuman; (2) a means of examining the ontological, epistemological, technological, existential, performative, and ethical implications of our communicative being, our being constituted by symbolic action and mediated exchange in ever-present yet always variant material and affective environments, spaces, and places; (3) a discipline emerging from rhetoric, one of the original liberal arts, yet developing in transdisciplinary ways, transforming the binary of humanities and sciences; (4) a tool for decolonizing knowledge(s); (5) a tool for exploring, critiquing, engaging, and creating with the new media of our digital lives together; (6) a long-standing yet ever inventive method and mode for public humanities; and (7) a praxis of resistance. These essays bring to light what studying communication offers the humanities: a plural, public, reflexive, and ever inventive enterprise for examining being human together on this planet.     

Hierarchical sampling optimization of particle filter for global robot localization in pervasive network environment

This paper presents a hierarchical framework for managing the sampling distribution of a particle filter (PF) that estimates the global positions of mobile robots in a large‐scale area. The key concept is to gradually improve the accuracy of the global localization by fusing sensor information with different characteristics. The sensor observations are the received signal strength indications (RSSIs) of Wi‐Fi devices as network facilities and the range of a laser scanner. First, the RSSI data used for determining certain global areas within which the robot is located are represented as RSSI bins. In addition, the results of the RSSI bins contain the uncertainty of localization, which is utilized for calculating the optimal sampling size of the PF to cover the regions of the RSSI bins. The range data are then used to estimate the precise position of the robot in the regions of the RSSI bins using the core process of the PF. The experimental results demonstrate superior performance compared with other approaches in terms of the success rate of the global localization and the amount of computation for managing the optimal sampling size.     

Correlations between histopathologic and dermoscopic findings in Korean actinic keratosis

Skin biopsy for AK diagnosis is usually performed on only a limited part of the whole lesion. Therefore, a clinical diagnosis is important. According to a study, there is no significant correlation between histopathological and clinical classification system. We examined the correlation between microscopic information and dermoscopic findings to deduce if dermoscopic information reflects histopathologic grade severity. Forty seven patients with histologically confirmed AK were enrolled and positive ratio of red pseudonetwork, rosette, red background and targetoid signs, white‐to‐yellow scale, white structureless area, and pigmentation from dermoscopic findings were investigated. Furthermore, viable epidermal thickness, vessel lumen dimensions, existence and thickness of ortho‐ and parakeratosis, degree of sola elastosis, flag sign existence, and Roewert‐Huber classification were measured as histologic findings. Red background did not show a significant correlation with vascular dimension or viable epidermal thickness. When targetoid sign was present, vascular dimension was significantly larger but showed no correlation with viable epidermal thickness, parakeratosis or orthokeratosis. Solar elastosis level was significantly higher when white‐to‐yellow scale was present. According to Spearman's correlation analysis, ortho/parakeratotic thickness showed correlations with each other. The negative correlation between viable epidermal thickness and vascular dimension was also shown. Roewert‐Huber histologic AK classification showed no correlation with any factors we checked. Factors considered to be characteristic features of AK in dermoscopy seemed unassociated with histologic AK classification and additional research is needed to determine degree of dysplasia of AK lesions using dermoscopy.     

Hierarchical Coherent Phonons in a Superatomic Semiconductor

The coupling of phonons to electrons and other phonons plays a defining role in material properties, such as charge and energy transport, light emission, and superconductivity. In atomic solids, phonons are delocalized over the 3D lattice, in contrast to molecular solids where localized vibrations dominate. Here, a hierarchical semiconductor that expands the phonon space by combining localized 0D modes with delocalized 2D and 3D modes is described. This material consists of superatomic building blocks (Re₆Se₈) covalently linked into 2D sheets that are stacked into a layered van der Waals lattice. Using transient reflectance spectroscopy, three types of coherent phonons are identified: localized 0D breathing modes of isolated superatom, 2D synchronized twisting of superatoms in layers, and 3D acoustic interlayer deformation. These phonons are coupled to the electronic degrees of freedom to varying extents. The presence of local phonon modes in an extended crystal opens the door to controlling material properties from hierarchical phonon engineering.     

Regional-scale rice-yield estimation using stacked auto-encoder with climatic and MODIS data: a case study of South Korea

In South Korea, rice is the most important grain crop that it is crucial to develop yield estimation model for supporting sustainable agriculture and national food security. The main objectives of this paper are (1) to propose a Deep Learning (DL) algorithm, the Stacked Sparse Auto-encoder (SSAE), for rice-yield estimation using climatic and Moderate Resolution Imaging Spectroradiometer (MODIS) data; (2) to choose scenarios showing the best combined performance in terms of length of crop season (before and after harvest) and aggregation periods (7, 10, 15, and 30 days) of climatic data; and (3) to analyse the results in both the temporal and spatial perspectives. In this procedure, the SSAE model was built around the study objectives and compared with the artificial neural network (ANN) model for evaluation of its performance. According to the results, the combined 15-day-aggregated climatic data (between June and August) and MODIS data were selected as the optimal feature set for rice-yield estimation in the study area, Jeolla-do; the SSAE model outperformed ANN, showing root mean square error (RMSE) and RMSE% of 33.09 kg(10a)^?1 (5.21 kg(10a)^?1lower than ANN) and 6.89% (1.14% lower than ANN). Throughout the experiments, the rice-yield-estimation potentiality of a DL algorithm, namely the SSAE, was substantiated.     

Time-sensitivity-aware shared cache architecture for multi-core embedded systems

The Journal of Supercomputing - In embedded systems such as automotive systems, multi-core processors are expected to improve performance and reduce manufacturing cost by integrating multiple...     

Automated delineation of non-small cell lung cancer: A step toward quantitative reasoning in medical decision science

Quantitative reasoning in medical decision science relies on the delineation of pathological objects. For example, evidence-based clinical decisions regarding lung diseases require the segmentation of nodules, tumors, or cancers. Non-small cell lung cancer (NSCLC) tends to be large sized, irregularly shaped, and grows against surrounding structures imposing challenges in the segmentation, even for expert clinicians. An automated delineation tool based on spatial analysis was developed and studied on 25 sets of computed tomography scans of NSCLC. Manual and automated delineations were compared, and the proposed method exhibited robustness in terms of the tumor size (5.32–18.24 mm), shape (spherical or irregular), contouring (lobulated, spiculated, or cavitated), localization (solitary, pleural, mediastinal, endobronchial, or tagging), and laterality (left or right lobe) with accuracy between 80% and 99%. Small discrepancies observed between the manual and automated delineations may arise from the variability in the practitioners' definitions of region of interest or imaging artifacts that reduced the tissue resolution.