Determinants of RFID Adoption Intention in the Healthcare Industry for Patient Monitoring

Radio frequency identification (RFID) technology holds tremendous potential in improving the patient management system in hospitals attaining global importance in the healthcare industry due to the spread of the COVID-19 pandemic at present. RFID assists in wireless data storage and automatic retrieval, making systems efficient, improving patient safety, and decreasing costs. Although RFID is an emerging technology in the healthcare industry, its adoption is yet to gather momentum. This chapter will provide a background for healthcare practitioners and researchers about RFID technologies in the healthcare sector. Moreover, an integrated conceptual framework will be proposed consisting of factors that influence RFID technology adoption intention in the healthcare industry. This study will be the first of its kind to identify and classify various factors of RFID adoption intention and provide a comprehensive model using an exploratory method laying the foundation for academicians and industry practitioners for the future scope of its research.

Brain substrates for automatic retrieval of value memory in the primate basal ganglia

Our behavior is often carried out automatically. Automatic behavior can be guided by past experiences, such as learned values associated with objects. Passive-viewing and free-viewing tasks with no immediate outcomes provide a testable condition in which monkeys and humans automatically retrieve value memories and perform habitual searching. Interestingly, in these tasks, caudal regions of the basal ganglia structures are involved in automatic retrieval of learned object values and habitual gaze. In contrast, rostral regions do not participate in these activities but instead monitor the changes in outcomes. These findings indicate that automatic behaviors based on the value memories are processed selectively by the caudal regions of the primate basal ganglia system. Understanding the distinct roles of the caudal basal ganglia may provide insight into finding selective causes of behavioral disorders in basal ganglia disease.

Automatic detection of pupil reactions in cataract surgery videos

In the light of an increased use of premium intraocular lenses (IOL), such as EDOF IOLs, multifocal IOLs or toric IOLs even minor intraoperative complications such as decentrations or an IOL tilt, will hamper the visual performance of these IOLs. Thus, the post-operative analysis of cataract surgeries to detect even minor intraoperative deviations that might explain a lack of a post-operative success becomes more and more important. Up-to-now surgical videos are evaluated by just looking at a very limited number of intraoperative data sets, or as done in studies evaluating the pupil changes that occur during surgeries, in a small number intraoperative picture only. A continuous measurement of pupil changes over the whole surgery, that would achieve clinically more relevant data, has not yet been described. Therefore, the automatic retrieval of such events may be a great support for a post-operative analysis. This would be especially true if large data files could be evaluated automatically. In this work, we automatically detect pupil reactions in cataract surgery videos. We employ a Mask R-CNN architecture as a segmentation algorithm to segment the pupil and iris with pixel-based accuracy and then track their sizes across the entire video. We can detect pupil reactions with a harmonic mean (H) of Recall, Precision, and Ground Truth Coverage Rate (GTCR) of 60.9% and average prediction length (PL) of 18.93 seconds. However, we consider the best configuration for practical use the one with the H value of 59.4% and PL of 10.2 seconds, which is much shorter. We further investigate the generalization ability of this method on a slightly different dataset without retraining the model. In this evaluation, we achieve the H value of 49.3% with the PL of 18.15 seconds.

Spatiotemporal context modulates encoding and retrieval of overlapping events

Overlap between events can lead to interference due to a tradeoff between encoding the present event and retrieving the past event. Temporal context information -- 'when' something occurred, a defining feature of episodic memory -- can cue retrieval of a past event. However, the influence of temporal overlap, or proximity in time, on the mechanisms of interference are unclear. Here, by identifying brain states using scalp electroencephalography (EEG) from male and female human subjects, we show the extent to which temporal overlap promotes interference and induces retrieval. In this experiment, subjects were explicitly directed to either encode the present event or retrieve a past, overlapping event while perceptual input was held constant. We find that the degree of temporal overlap between events leads to selective interference. Specifically, greater temporal overlap between two events leads to impaired memory for the past event selectively when the top-down goal is to encode the present event. Using pattern classification analyses to measure neural evidence for a retrieval state, we find that greater temporal overlap leads to automatic retrieval of a past event, independent of top-down goals. Critically, the retrieval evidence we observe likely reflects a general retrieval mode, rather than retrieval success or effort. Collectively, our findings provide insight into the role of temporal overlap on interference and memory formation.

The level of representation of irrelevant stimuli—Distractor–response binding within and between the senses

Binding theories assume that features of stimuli and executed responses can be integrated together in one event file (Hommel, Visual Cognition, 5, 183–216, 1998; Hommel, Cognitive Sciences, 8, 494–500, 2004). Every reencounter with one or more of the stored features leads to an automatic retrieval of the previously constructed event file and hence of the response—even the repetition of a task-irrelevant distractor stimulus can retrieve a previously encoded response. This so-called distractor–response binding effect is typically investigated using a sequential prime-probe design that allows the orthogonal variation of response relation (response repetition vs. resporrevertnse change) and distractor relation (distractor repetition vs. distractor change), while probe response times and error rates are measured as dependent variable. Previous research has shown that task-relevant stimuli can be represented at different levels (e.g., perceptual and conceptual; see Henson et al., Trends in Cognitive Sciences, 18, 376–384, 2014), yet it is not clear at which level of representation distractor stimuli are processed. In the present study, we focused on the level of representation of response-irrelevant distractor stimuli. To this end, a crossmodal distractor–response binding paradigm was used that enables the differentiation between the perceptual and conceptual representation of the distractor by allowing the systematic repetition and change of conceptual distractor features independent of perceptual repetitions. The results suggest that the repetition of perceptual distractor features is indispensable for the initiation of the retrieval process while the sole repetition of conceptual distractor features is not sufficient to start the retrieval process.

Automatic Retrieval of Shoeprints Using Modified Multi-Block Local Binary Pattern

A shoeprint is a valuable clue found at a crime scene and plays a significant role in forensic investigations. In this paper, in order to maintain the local features of a shoeprint image and place a pattern in a block, a novel automatic method was proposed, referred to as Modified Multi-Block Local Binary Pattern (MMB-LBP). In this method, shoeprint images are divided into blocks according to two different models. The histograms of all blocks of the first and second models are separately measured and stored in the first and second feature matrices, respectively. The performance evaluations of the proposed method were carried out by comparing with state-of-the-art methods. The evaluation criteria are the successful retrieval rates obtained using the best match score at rank one and cumulative match score for the first five matches. The comparison results indicated that the proposed method performs better than other methods, in terms of retrieval of complete and incomplete shoeprints. That is, the proposed method was able to retrieve 97.63% of complete shoeprints, 96.5% of incomplete toe shoeprints, and 91.18% of incomplete heel shoeprints. Moreover, the experiments showed that the proposed method is significantly resistant to the rotation, salt and pepper noise, and Gaussian white noise distortions in comparison with the other methods.

Viewing images of foods evokes taste quality-specific activity in gustatory insular cortex

Previous studies have shown that the conceptual representation of food involves brain regions associated with taste perception. The specificity of this response, however, is unknown. Does viewing pictures of food produce a general, nonspecific response in taste-sensitive regions of the brain? Or is the response specific for how a particular food tastes? Building on recent findings that specific tastes can be decoded from taste-sensitive regions of insular cortex, we asked whether viewing pictures of foods associated with a specific taste (e.g., sweet, salty, and sour) can also be decoded from these same regions, and if so, are the patterns of neural activity elicited by the pictures and their associated tastes similar? Using ultrahigh-resolution functional magnetic resonance imaging at high magnetic field strength (7-Tesla), we were able to decode specific tastes delivered during scanning, as well as the specific taste category associated with food pictures within the dorsal mid-insula, a primary taste responsive region of brain. Thus, merely viewing food pictures triggers an automatic retrieval of specific taste quality information associated with the depicted foods, within gustatory cortex. However, the patterns of activity elicited by pictures and their associated tastes were unrelated, thus suggesting a clear neural distinction between inferred and directly experienced sensory events. These data show how higher-order inferences derived from stimuli in one modality (i.e., vision) can be represented in brain regions typically thought to represent only low-level information about a different modality (i.e., taste).

Real-Time Data Filling and Automatic Retrieval Algorithm of Road Traffic Based on Deep-Learning Method

In order to enhance the real-time and retrieval performance of road traffic data filling, a real-time data filling and automatic retrieval algorithm based on the deep-learning method is proposed. In image detection, the depth representation is extracted according to the detection target area of a general object. The local invariant feature is extracted to describe local attributes in the region, and it is fused with depth representation to complete the real-time data filling of road traffic. According to the results of the database enhancement, the retrieval results of the deep representation level are reordered. In the index stage, unsupervised feature updating is realized by neighborhood information to improve the performance of a feature retrieval. The experimental results show that the proposed method has high recall and precision, a short retrieval time and a low running cost.

From experiment to real-life data

We examine unintentional spelling errors on verb homophones in informal online chat conversations of Flemish adolescents. In experiments, these verb forms yielded an effect of homophone dominance, i.e., most errors occurred on the lower-frequency form (Sandra et al., 1999). Verb homophones are argued to require the conscious application of a spelling rule, which may cause a temporary overload of working memory resources and trigger automatic retrieval of the higher-frequency spelling from the mental lexicon. Unlike most previous research, we investigate homophone intrusions in a natural writing context. Thus, we test the ‘ecological validity’ of psycholinguistic experiments. Importantly, this study relates these psycholinguistic constructs to different social variables in social media writing to test a prediction that directly follows from Sandra et al.’s account. Whereas social factors likely affect the error rates, they should not affect the error pattern: the number of working memory failures occurs at another processing level than the homophone intrusions. Hence, the focus is on the interaction between homophone dominance and the social variables. The errors for two types of verb homophones reveal (a) an impact of all social variables, (b) an effect of homophone dominance, and (c) no interaction between this effect and the social factors.