Component-based Analysis of Dynamic Search Performance

In many search scenarios, such as exploratory, comparative, or survey-oriented search, users interact with dynamic search systems to satisfy multi-aspect information needs. These systems utilize different dynamic approaches that exploit various user feedback granularity types. Although studies have provided insights about the role of many components of these systems, they used black-box and isolated experimental setups. Therefore, the effects of these components or their interactions are still not well understood. We address this by following a methodology based on Analysis of Variance (ANOVA). We built a Grid Of Points that consists of systems based on different ways to instantiate three components: initial rankers, dynamic rerankers, and user feedback granularity. Using evaluation scores based on the TREC Dynamic Domain collections, we built several ANOVA models to estimate the effects. We found that (i) although all components significantly affect search effectiveness, the initial ranker has the largest effective size, (ii) the effect sizes of these components vary based on the length of the search session and the used effectiveness metric, and (iii) initial rankers and dynamic rerankers have more prominent effects than user feedback granularity. To improve effectiveness, we recommend improving the quality of initial rankers and dynamic rerankers. This does not require eliciting detailed user feedback, which might be expensive or invasive.

Does More Context Help? Effects of Context Window and Application Source on Retrieval Performance

We study the effect of contextual information obtained from a user’s digital trace on Web search performance. Contextual information is modeled using Dirichlet–Hawkes processes (DHP) and used in augmenting Web search queries. The context is captured by monitoring all naturally occurring user behavior using continuous 24/7 recordings of the screen and associating the context with the queries issued by the users. We report a field study in which 13 participants installed a screen recording and digital activity monitoring system on their laptops for 14 days, resulting in data on all Web search queries and the associated context data. A query augmentation (QAug) model was built to expand the original query with semantically related terms. The effects of context window and source were determined by training context models with temporally varying context windows and varying application sources. The context models were then utilized to re-rank the QAug model. We evaluate the context models by using the Web document rankings of the original query as a control condition compared against various experimental conditions: (1) a search context condition in which the context was sourced from search history; (2) a non-search context condition in which the context was sourced from all interactions excluding search history; (3) a comprehensive context condition in which the context was sourced from both search and non-search histories; and (4) an application-specific condition in which the context was sourced from interaction histories captured on a specific application type. Our results indicated that incorporating more contextual information significantly improved Web search rankings as measured by the positions of the documents on which users clicked in the search result pages. The effects and importance of different context windows and application sources, along with different query types are analyzed, and their impact on Web search performance is discussed.

Rapid detection of social interactions is the result of domain general attentional processes

Using visual search displays of interacting and non-interacting pairs, it has been demonstrated that detection of social interactions is facilitated. For example, two people facing each other are found faster than two people with their backs turned: an effect that may reflect social binding. However, recent work has shown the same effects with non-social arrow stimuli, where towards facing arrows are detected faster than away facing arrows. This latter work suggests a primary mechanism is an attention orienting process driven by basic low-level direction cues. However, evidence for lower level attentional processes does not preclude a potential additional role of higher-level social processes. Therefore, in this series of experiments we test this idea further by directly comparing basic visual features that orient attention with representations of socially interacting individuals. Results confirm the potency of orienting of attention via low-level visual features in the detection of interacting objects. In contrast, there is little evidence for the representation of social interactions influencing initial search performance.

Aird: a computation-oriented mass spectrometry data format enables a higher compression ratio and less decoding time

Background With the precision of the mass spectrometry (MS) going higher, the MS file size increases rapidly. Beyond the widely-used open format mzML, near-lossless or lossless compression algorithms and formats emerged in scenarios with different precision requirements. The data precision is often related to the instrument and subsequent processing algorithms. Unlike storage-oriented formats, which focus more on lossless compression rate, computation-oriented formats concentrate as much on decoding speed as the compression rate. Results Here we introduce “Aird”, an opensource and computation-oriented format with controllable precision, flexible indexing strategies, and high compression rate. Aird provides a novel compressor called Zlib-Diff-PforDelta (ZDPD) for m/z data. Compared with Zlib only, m/z data size is about 55% lower in Aird average. With the high-speed decoding and encoding performance of the single instruction multiple data technology used in the ZDPD, Aird merely takes 33% decoding time compared with Zlib. We have downloaded seven datasets from ProteomeXchange and Metabolights. They are from different SCIEX, Thermo, and Agilent instruments. Then we convert the raw data into mzML, mgf, and mz5 file formats by MSConvert and compare them with Aird format. Aird uses JavaScript Object Notation for metadata storage. Aird-SDK is written in Java, and AirdPro is a GUI client for vendor file converting written in C#. They are freely available at https://github.com/CSi-Studio/Aird-SDK and https://github.com/CSi-Studio/AirdPro. Conclusions With the innovation of MS acquisition mode, MS data characteristics are also constantly changing. New data features can bring more effective compression methods and new index modes to achieve high search performance. The MS data storage mode will also become professional and customized. ZDPD uses multiple MS digital features, and researchers also can use it in other formats like mzML. Aird is designed to become a computing-oriented data format with high scalability, compression rate, and fast decoding speed.

Visual segmentation of complex naturalistic structures in an infant eye-tracking search task

An infant's everyday visual environment is composed of a complex array of entities, some of which are well integrated into their surroundings. Although infants are already sensitive to some categories in their first year of life, it is not clear which visual information supports their detection of meaningful elements within naturalistic scenes. Here we investigated the impact of image characteristics on 8-month-olds' search performance using a gaze contingent eye-tracking search task. Infants had to detect a target patch on a background image. The stimuli consisted of images taken from three categories: vegetation, non-living natural elements (e.g., stones), and manmade artifacts, for which we also assessed target background differences in lower- and higher-level visual properties. Our results showed that larger target-background differences in the statistical properties scaling invariance and entropy, and also stimulus backgrounds including low pictorial depth, predicted better detection performance. Furthermore, category membership only affected search performance if supported by luminance contrast. Data from an adult comparison group also indicated that infants' search performance relied more on lower-order visual properties than adults. Taken together, these results suggest that infants use a combination of property- and category-related information to parse complex visual stimuli.

Landscape Perspective Distance-Included Angle Shape Distribution Analysis Based on 3D CAD Model Retrieval Algorithm

In view of the results obtained in the retrieval process of the 3D CAD model, which can show the differences in the local feature details of the model, the 3D CAD model retrieval algorithm is introduced into the analysis of the perspective distance-angle shape distribution of the garden landscape in this paper. Random sampling is performed on the surface of the constructed 3D CAD model, combined with the test distance between the sampling point and the neighboring points, and the corresponding garden landscape perspective distance-angle shape distribution characteristics in this area are calculated in order to achieve the similarity of the CAD model high-speed retrieval. Finally, experimental research shows that the algorithm proposed in this paper is better than the overall shape distribution algorithm and the spherical harmonic algorithm in the search performance of the CAD model, and it can effectively improve the recognition ability of the local detailed features of the 3D CAD model.

Visual search training benefits from the integrative effect of enhanced covert attention and optimized overt eye movements

Visual search in a complex environment requires efficient discrimination between target and distractors. Training serves as an effective approach to improve visual search performance when the target does not automatically pop out from the distractors. In the present study, we trained subjects on a conjunction visual search task and examined the training effects in behavior and eye movement from Experiments 1 to 4. The results showed that training improved behavioral performance and reduced the number of saccades and overall scanning time. Training also increased the search initiation time before the first saccade and the proportion of trials in which the subjects correctly identified the target without any saccade, but these effects were modulated by stimulus' parameters. In Experiment 5, we replicated these training effects when eye movements and EEG signals were recorded simultaneously. The results revealed significant N2pc components after the stimulus onset (i.e., stimulus-locked) and before the first saccade (i.e., saccade-locked) when the search target was the trained one. These N2pc components can be considered as the neural signatures for the training-induced boost of covert attention to the trained target. The enhanced covert attention led to a beneficial tradeoff between search initiation time and the number of saccades as a small amount of increase in search initiation time could result in a larger reduction in scanning time. These findings suggest that the enhanced covert attention to target and optimized overt eye movements are coordinated together to facilitate visual search training.

Designing Combinations of Pictogram and Text Size for Icons: Effects of Text Size, Pictogram Size, and Familiarity on Older Adults’ Visual Search Performance

Objective This study aimed to determine suitable combinations of text and pictogram sizes for older adults and investigated the visual prioritization of pictogram versus text. Background Icons have become an indispensable part of application (app) design. Pictogram size and text size of icons influence the usability of apps, especially by aged users. However, few studies have investigated the influences of different pictogram and text size combinations on readability, legibility, and visual search performance for older adults. Method This study used eye-tracking technology to investigate the effects of different pictogram and text size combinations as well as familiarity on readability, legibility, and visual search performance for older adults. A 3 (pictogram size) × 3 (text size) × 2 (familiarity) repeated-measures experimental design was used. Results The results of this study suggest that pictogram size and text size significantly affect visual search performance and that familiarity moderates the effect of text size on distribution of fixation duration proportion for text and pictograms. Conclusion Large pictogram and text sizes improved the readability and legibility of icons for older adults. Furthermore, the older adults fixated the area of text prior to pictograms when the pictogram size was larger than 72 × 72 px (1.38° × 1.38°) in the visual search task. Application The results of this study suggest using different combinations of pictogram and text sizes for older adults under different scenarios. The findings of this study act as practical support for designers and developers of mobile apps for older adults.

COACHING TECHNOLOGIES IN EDUCATION: THEORY AND PRACTICE

The article raises the topical problem of innovative activity of pedagogical higher education institutions. The authors take the position that in the context of changing the role of the teacher in the training of pedagogical specialists of the new generation is a popular and modern solution. One of the ways to solve the problem is to introduce into the cycle of general training of applicants for the first (bachelor’s) level of higher education disciplines that will contribute to the formation of students’ ability to solve complex professional problems, quality of teaching and learning, support, motivation, psychological and pedagogical support, their personal and professional development.The purpose of the article is to specify the content of the discipline “Coaching Technologies in Education” for H.S. Skovoroda Kharkiv National Pedagogical University.The authors of the article present the experience of implementation and content of the selective discipline “Coaching Technologies in Education” for applicants for the first (bachelor’s) level of higher education. The list of general and professional competencies that are formed in future teachers during the study of the discipline is given, the program results are specified. Target and content aspects of the elective course are presented through the prism of standardized requirements for general secondary education teachers.Methods of teaching are revealed, including partial search, performance of practical exercises, conversation, discussion, work with the basic and auxiliary literature, information sources, the story, the decision of cases, practical exercises, writing of the essay, business game, drawing up mental maps, storytelling, case study method, World Cafe method.Of particular value is the presented content of the elective course, which consists of two modules “Philosophy, principles and types of coaching”, “Coaching in education”. The thematic plan and forms of lectures and seminars are presented. The peculiarities of conducting classes in the form of coaching sessions are specified.Prospects for further scientific research are to develop practical and methodological complexes for the discipline.