scholarly journals Response Time, Visual Search Strategy, and Anticipatory Skills in Volleyball Players

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Alessandro Piras ◽  
Roberto Lobietti ◽  
Salvatore Squatrito
Keyword(s):  
Response Time ◽  
Search Strategy ◽  
Superior Performance ◽  
Specific Information ◽  
Eye Tracker ◽  
Domain Specific ◽  
Visuomotor Task ◽  
Volleyball Players ◽  
Ball Contact ◽  
Gaze Behaviour

This paper aimed at comparing expert and novice volleyball players in a visuomotor task using realistic stimuli. Videos of a volleyball setter performing offensive action were presented to participants, while their eye movements were recorded by a head-mounted video based eye tracker. Participants were asked to foresee the direction (forward or backward) of the setter’s toss by pressing one of two keys. Key-press response time, response accuracy, and gaze behaviour were measured from the first frame showing the setter’s hand-ball contact to the button pressed by the participants. Experts were faster and more accurate in predicting the direction of the setting than novices, showing accurate predictions when they used a search strategy involving fewer fixations of longer duration, as well as spending less time in fixating all display areas from which they extract critical information for the judgment. These results are consistent with the view that superior performance in experts is due to their ability to efficiently encode domain-specific information that is relevant to the task.

Knowledge Enhanced LSTM for Coreference Resolution on Biomedical Texts

2021 ◽  
Author(s):  
Yufei Li ◽  
Xiaoyong Ma ◽  
Xiangyu Zhou ◽  
Pengzhen Cheng ◽  
Kai He ◽  
...  
Keyword(s):  
Information Integration ◽  
Short Term Memory ◽  
Superior Performance ◽  
Supplementary Information ◽  
Specific Information ◽  
Coreference Resolution ◽  
Fine Grained ◽  
Domain Specific ◽  
Memory Network ◽  
Biomedical Texts

Abstract Motivation Bio-entity Coreference Resolution focuses on identifying the coreferential links in biomedical texts, which is crucial to complete bio-events’ attributes and interconnect events into bio-networks. Previously, as one of the most powerful tools, deep neural network-based general domain systems are applied to the biomedical domain with domain-specific information integration. However, such methods may raise much noise due to its insufficiency of combining context and complex domain-specific information. Results In this paper, we explore how to leverage the external knowledge base in a fine-grained way to better resolve coreference by introducing a knowledge-enhanced Long Short Term Memory network (LSTM), which is more flexible to encode the knowledge information inside the LSTM. Moreover, we further propose a knowledge attention module to extract informative knowledge effectively based on contexts. The experimental results on the BioNLP and CRAFT datasets achieve state-of-the-art performance, with a gain of 7.5 F1 on BioNLP and 10.6 F1 on CRAFT. Additional experiments also demonstrate superior performance on the cross-sentence coreferences. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Context-Aware Feature Attention Model for Coreference Resolution on Biomedical Texts

2021 ◽  
Author(s):  
Yufei Li ◽  
Xiangyu Zhou ◽  
Jie Ma ◽  
Xiaoyong Ma ◽  
Chen Li
Keyword(s):  
Information Integration ◽  
Superior Performance ◽  
Specific Information ◽  
Coreference Resolution ◽  
Context Aware ◽  
Attention Model ◽  
Fine Grained ◽  
Domain Specific ◽  
Feature Attention ◽  
Biomedical Texts

Abstract Background: Bio-entity Coreference resolution is an important task to gain a complete understanding of biomedical texts automatically. Previous neural network-based studies on this topic are domain system based methods which rely on some domain-specific information integration. However, for the identical mentions, this may lead to misleading information, as the model tends to get similar or even identical representations, which further leads to wrongful predictions. Results: we propose a new context-aware Feature Attention model to distinguish identical mentions effectively to better resolve coreference. The new model can represent identical mentions based on different contexts by adaptively exploiting features effectively. The proposed model substantially outperforms the state-of-the-art baselines on the BioNLP dataset with a 64.0% F1 score and further demonstrates superior performance on the differential representation and coreferential link of identical mentions. Conclusion: The context-aware Feature Attention model adaptively exploit features and represent identical mentions according to different contexts, which significantly makes the system obtain semantic information effectively and make more accurate predictions. Considering that this approach is still limited when context information is insufficient, we expect to utilize such information more fine-grained with the help of the external knowledge base in coreference resolution.

scholarly journals Into the Eyes of the Referee: A Comparison of Elite and Sub-Elite Football Referees’ On-Field Visual Search Behaviour when making Foul Judgements

2022 ◽  
pp. 174795412110694
Author(s):  
T. van Biemen ◽  
R.R.D. Oudejans ◽  
G.J.P. Savelsbergh ◽  
F. Zwenk ◽  
D.L. Mann
Keyword(s):  
Decision Making ◽  
Visual Search ◽  
Search Rate ◽  
Specific Information ◽  
Eye Tracker ◽  
Skill Levels ◽  
Search Behaviour ◽  
Direct Gaze ◽  
Gaze Patterns ◽  
Gaze Behaviour

In foul decision-making by football referees, visual search is important for gathering task-specific information to determine whether a foul has occurred. Yet, little is known about the visual search behaviours underpinning excellent on-field decisions. The aim of this study was to examine the on-field visual search behaviour of elite and sub-elite football referees when calling a foul during a match. In doing so, we have also compared the accuracy and gaze behaviour for correct and incorrect calls. Elite and sub-elite referees (elite: N = 5, Mage  ±  SD = 29.8 ± 4.7yrs, Mexperience  ±  SD = 14.8 ± 3.7yrs; sub-elite: N = 9, Mage  ±  SD = 23.1 ± 1.6yrs, Mexperience  ±  SD = 8.4 ± 1.8yrs) officiated an actual football game while wearing a mobile eye-tracker, with on-field visual search behaviour compared between skill levels when calling a foul (Nelite = 66; Nsub−elite = 92). Results revealed that elite referees relied on a higher search rate (more fixations of shorter duration) compared to sub-elites, but with no differences in where they allocated their gaze, indicating that elites searched faster but did not necessarily direct gaze towards different locations. Correct decisions were associated with higher gaze entropy (i.e. less structure). In relying on more structured gaze patterns when making incorrect decisions, referees may fail to pick-up information specific to the foul situation. Referee development programmes might benefit by challenging the speed of information pickup but by avoiding pre-determined gaze patterns to improve the interpretation of fouls and increase the decision-making performance of referees.

scholarly journals Simheuristics Approaches for Efficient Decision-Making Support in Materials Trading Networks

Algorithms ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 23
Author(s):  
Markus Rabe ◽  
Majsa Ammouriova ◽  
Dominik Schmitt ◽  
Felix Dross
Keyword(s):  
Reinforcement Learning ◽  
Response Time ◽  
Real World ◽  
Computation Time ◽  
Service Level ◽  
Specific Information ◽  
Real World Data ◽  
Domain Specific ◽  
Distribution Process ◽  
The One

The distribution process in business-to-business materials trading is among the most complex and in transparent ones within logistics. The highly volatile environment requires continuous adaptations by the responsible decision-makers, who face a substantial number of potential improvement actions with conflicting goals, such as simultaneously maintaining a high service level and low costs. Simulation-optimisation approaches have been proposed in this context, for example based on evolutionary algorithms. But, on real-world system dimensions, they face impractically long computation times. This paper addresses this challenge in two principal streams. On the one hand, reinforcement learning is investigated to reduce the response time of the system in a concrete decision situation. On the other hand, domain-specific information and defining equivalent solutions are exploited to support a metaheuristic algorithm. For these approaches, we have developed suitable implementations and evaluated them with subsets of real-world data. The results demonstrate that reinforcement learning exploits the idle time between decision situations to learn which decisions might be most promising, thus adding computation time but significantly reducing the response time. Using domain-specific information reduces the number of required simulation runs and guides the search for promising actions. In our experimentation, defining equivalent solutions decreased the number of required simulation runs up to 15%.

PROTEIN STRUCTURE ALIGNMENT AND FAST SIMILARITY SEARCH USING LOCAL SHAPE SIGNATURES

2004 ◽  
Vol 02 (01) ◽  
pp. 215-239 ◽  
Author(s):  
TOLGA CAN ◽  
YUAN-FANG WANG
Keyword(s):  
Protein Structure ◽  
Protein Structures ◽  
Structure Alignment ◽  
Protein Structure Alignment ◽  
Specific Information ◽  
Alignment Algorithm ◽  
Screening Process ◽  
Domain Specific ◽  
Local Sequence ◽  
Shape Signatures

We present a new method for conducting protein structure similarity searches, which improves on the efficiency of some existing techniques. Our method is grounded in the theory of differential geometry on 3D space curve matching. We generate shape signatures for proteins that are invariant, localized, robust, compact, and biologically meaningful. The invariancy of the shape signatures allows us to improve similarity searching efficiency by adopting a hierarchical coarse-to-fine strategy. We index the shape signatures using an efficient hashing-based technique. With the help of this technique we screen out unlikely candidates and perform detailed pairwise alignments only for a small number of candidates that survive the screening process. Contrary to other hashing based techniques, our technique employs domain specific information (not just geometric information) in constructing the hash key, and hence, is more tuned to the domain of biology. Furthermore, the invariancy, localization, and compactness of the shape signatures allow us to utilize a well-known local sequence alignment algorithm for aligning two protein structures. One measure of the efficacy of the proposed technique is that we were able to perform structure alignment queries 36 times faster (on the average) than a well-known method while keeping the quality of the query results at an approximately similar level.

scholarly journals An Optical Fiber Sensor Based on La2O2S:Eu Scintillator for Detecting Ultraviolet Radiation in Real-Time

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3754 ◽  
Author(s):  
Yongji Yan ◽  
Xu Zhang ◽  
Haopeng Li ◽  
Yu Ma ◽  
Tianci Xie ◽  
...  
Keyword(s):  
Optical Fiber ◽  
Response Time ◽  
Electromagnetic Interference ◽  
Uv Light ◽  
Optical Fiber Sensor ◽  
Temperature Response ◽  
Superior Performance ◽  
Fiber Sensor ◽  
Uv Detectors

A novel ultraviolet (UV) optical fiber sensor (UVOFS) based on the scintillating material La2O2S:Eu has been designed, tested, and its performance compared with other scintillating materials and other conventional UV detectors. The UVOFS is based on PMMA (polymethyl methacrylate) optical fiber which includes a scintillating material. Scintillating materials provide a unique opportunity to measure UV light intensity even in the presence of strong electromagnetic interference. Five scintillating materials were compared in order to select the most appropriate one for the UVOFS. The characteristics of the sensor are reported, including a highly linear response to radiation intensity, reproducibility, temperature response, and response time (to pulsed light) based on emission from a UV source (UV fluorescence tube) centered on a wavelength of 308 nm. A direct comparison with the commercially available semiconductor-based UV sensor proves the UVOFS of this investigation shows superior performance in terms of accuracy, long-term reliability, response time and linearity.

scholarly journals Nanostructured germanium deposited on heated substrates with enhanced photoelectric properties

2016 ◽  
Vol 7 ◽  
pp. 1492-1500 ◽  
Author(s):  
Ionel Stavarache ◽  
Valentin Adrian Maraloiu ◽  
Petronela Prepelita ◽  
Gheorghe Iordache
Keyword(s):  
Optical Properties ◽  
Response Time ◽  
Spectral Width ◽  
Fast Response ◽  
Superior Performance ◽  
X Ray Diffraction ◽  
Electrical Measurements ◽  
Preparation Conditions ◽  
Photoelectric Properties ◽  
Transmission Electron

Obtaining high-quality materials, based on nanocrystals, at low temperatures is one of the current challenges for opening new paths in improving and developing functional devices in nanoscale electronics and optoelectronics. Here we report a detailed investigation of the optimization of parameters for the in situ synthesis of thin films with high Ge content (50 %) into SiO2. Crystalline Ge nanoparticles were directly formed during co-deposition of SiO2 and Ge on substrates at 300, 400 and 500 °C. Using this approach, effects related to Ge–Ge spacing are emphasized through a significant improvement of the spatial distribution of the Ge nanoparticles and by avoiding multi-step fabrication processes or Ge loss. The influence of the preparation conditions on structural, electrical and optical properties of the fabricated nanostructures was studied by X-ray diffraction, transmission electron microscopy, electrical measurements in dark or under illumination and response time investigations. Finally, we demonstrate the feasibility of the procedure by the means of an Al/n-Si/Ge:SiO2/ITO photodetector test structure. The structures, investigated at room temperature, show superior performance, high photoresponse gain, high responsivity (about 7 AW−1), fast response time (0.5 µs at 4 kHz) and great optoelectronic conversion efficiency of 900% in a wide operation bandwidth, from 450 to 1300 nm. The obtained photoresponse gain and the spectral width are attributed mainly to the high Ge content packed into a SiO2 matrix showing the direct connection between synthesis and optical properties of the tested nanostructures. Our deposition approach put in evidence the great potential of Ge nanoparticles embedded in a SiO2 matrix for hybrid integration, as they may be employed in structures and devices individually or with other materials, hence the possibility of fabricating various heterojunctions on Si, glass or flexible substrates for future development of Si-based integrated optoelectronics.

scholarly journals The Relationship between the Number of Emergency Room Patient Visits with Triage Accuracy and Emergency Nurse Response Time in the Covid 19 Pandemic Season

2021 ◽  
Vol 3 (1) ◽  
pp. 21-24
Author(s):  
Ali Humardani ◽  
Yuly Peristiowati ◽  
Agusta D. Ellina
Keyword(s):  
Quality Of Service ◽  
Response Time ◽  
Search Strategy ◽  
The Other ◽  
Bleeding Control ◽  
Electronic Database ◽  
Standard Operating ◽  
The Relationship ◽  
Spine Control

Handling emergency cases must not only be carried out quickly but also must be precise. Standard Operating Procedures (SOP) is one of the instruments to measure the quality of service. the number of patient visits that can affect the quality of service. Triage is a way of sorting patients based on therapy needs and available resources. Therapy is based on ABC conditions (Airway, with cervical spine control, Breathing, and Circulation with bleeding control). On the other hand, the COVID-19 pandemic greatly affects the response time, impacting the number of patient visits. Response time is the time between the beginning of a request being responded to in other words it can be called response time. A good response time for patients is 5 minutes. The purpose of this study was to identify the relationship between the number of patient visits and the accuracy of triage implementation and response time. The electronic database used is PubMed, Springer, and Google Scholar with a search strategy using the PICO (patient, intervention, comparison, and outcome) method.

scholarly journals DISSECT: DISentangle SharablE ConTent for Multimodal Integration and Crosswise-mapping

2020 ◽  
Author(s):  
Geoffrey Schau ◽  
Erik Burlingame ◽  
Young Hwan Chang
Keyword(s):  
Deep Learning ◽  
Complete Information ◽  
Specific Information ◽  
Multimodal Integration ◽  
Specific Data ◽  
Domain Specific ◽  
Cross Domain ◽  
Input Feature ◽  
Novel Approach ◽  
Latent Representations

AbstractDeep learning systems have emerged as powerful mechanisms for learning domain translation models. However, in many cases, complete information in one domain is assumed to be necessary for sufficient cross-domain prediction. In this work, we motivate a formal justification for domain-specific information separation in a simple linear case and illustrate that a self-supervised approach enables domain translation between data domains while filtering out domain-specific data features. We introduce a novel approach to identify domainspecific information from sets of unpaired measurements in complementary data domains by considering a deep learning cross-domain autoencoder architecture designed to learn shared latent representations of data while enabling domain translation. We introduce an orthogonal gate block designed to enforce orthogonality of input feature sets by explicitly removing non-sharable information specific to each domain and illustrate separability of domain-specific information on a toy dataset.

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