Types Of Tasks Research Articles

TabMoE: A General Framework for Diverse Table-Based Reasoning with Mixture-of-Experts

Tables serve as a widely adopted data format, attracting considerable academic interest concerning semantic understanding and logical inference of tables. In recent years, the prevailing paradigm of pre-training and fine-tuning on tabular data has become increasingly prominent in research on table understanding. However, existing table-based pre-training methods frequently exhibit constraints, supporting only single tasks while requiring substantial computational resources, which hinders their efficiency and applicability. In this paper, we introduce the TabMoE, a novel framework based on mixture-of-experts, designed to handle a wide range of tasks involving logical reasoning over tabular data. Each expert within the model specializes in a distinct logical function and is trained through the utilization of a hard Expectation–Maximization algorithm. Remarkably, this framework eliminates the necessity of dependency on tabular pre-training, instead exclusively employing limited task-specific data to significantly enhance models’ inferential capabilities. We conduct empirical experiments across three typical tasks related to tabular data: table-based question answering, table-based fact verification, and table-to-text generation. The experimental results underscore the innovation and feasibility of our framework.

The Role of Task Type in Enhancing Writing Fluency: A Study of Saudi Female University Students

The Role of Task Type in Enhancing Writing Fluency: A Study of Saudi Female University Students

Specific and shared cognitive predictors of drawing and block building in typically developing children.

Spatial construction is a complex ability involving attention, global/local visual processing, mental representation, visuo-motor coordination and, to varying extent, working memory and executive functions, and verbal abilities. In developmental neuropsychology, little attention has been paid to comprehend whether and to what extent the above cognitive processes are involved in two main spatial construction tasks, that is drawing and block building. We used path analysis to test shared and specific effects of verbal and spatial working memory, spatial attention, inhibition, verbal abilities (vocabulary and naming), figure disembedding, mental rotation, and visual-motor coordination, as well as of demographics (sex, age and socio-economic status), on two classical drawing (Rey-Osterrieth Complex Figure; ROCF) and block building (Block design; BD) tasks in a sample of 195 typically developing children (age range: 7-11 years). Figure disembedding and visuo-motor coordination were the only shared predictors of both spatial construction tasks. Moreover, ROCF score was directly related with spatial attention and inhibition, while BD score was directly related with sex, vocabulary, mental rotation and backward spatial working memory. These findings distinguish between abilities involved in spatial construction regardless of the type of task and those specifically related to ROCF or Block Design, thus providing clues relevant to neuropsychological assessment and intervention in children with spatial construction disorders.

IDENTIFYING CYBERTHREATS THROUGH SOCIAL MEDIA RESEARCH

The work provides an overview of the main methods of social network analysis used to identify cyber threats. The main types of threats in social networks are indicated and some protection methods for their prevention are described. Typical tasks of social network analysis aimed at detecting cyber threats are, for example, identifying online communities, identifying leaders and experts in communities, analyzing the stability of communities, clustering textual information, etc. With increasing digitization and active use of social networks as a means of communication, the importance of effective monitoring and data analysis to ensure cyber security is becoming more and more relevant. Complexities and challenges associated with processing large amounts of data in social networks are also analyzed, including privacy issues and ethical aspects of user data control. The study provides a holistic view of the use of social media as a tool to proactively identify and prevent cyberthreats, highlighting the importance of integrating analytical systems into the overall cybersecurity framework of organizations and individuals. The study provides a holistic view of the use of social media as a tool for proactive detection and prevention of cyber threats, highlighting the importance of integrating analytical systems into the overall cybersecurity posture of organizations and individuals, while emphasizing the need to improve machine learning and artificial intelligence techniques for deeper and more accurate analysis of user behavior and community dynamics, which can contribute to more effective prevention and neutralization of threats in the digital environment.

Stochastic models for time complexity of computing tasks: II. Description of interaction with databases

The paper contains the second part of an investigation devoted to the design of the mathematical models for the execution time of user tasks carried out on the virtual calculating nodes. We provide the performance of the proposed model for the description of the data processing fulfilled in the databases. As a testbed for stress testing, we choose a prototype of the anonymization system of the passengers’ personal data. There are stochastic models describing two types of user tasks: personal data anonymization procedure and calculation of the sample statistical characteristics. The paper contains a detailed description of the stress test planning and fulfillment for both models. The obtained mathematical models developed by the real data demonstrate high performance.

Load-balanced offloading of multiple task types for mobile edge computing in IoT

The continuous development of mobile networks poses new challenges for end devices with limited computing power. Mobile or multi-access edge computing (MEC) has been proposed for providing the computing resources close to the end devices that need them. However, in real network environments, MEC servers also have limited computing resources that need to be shared among many devices and efficient resource allocation is critical to ensure that the limited resources are optimally used. In view of this, we propose the Balanced Offload for Multi-type Tasks (BOMT) algorithm. The tasks to be offloaded are first prioritized according to their type, size and maximum tolerable delay; then different offloading algorithms are executed for different priority tasks according to the level of the priority and the current load on the MEC server. Following which, the optimal offloading policy is determined iteratively. Simulation results show that BOMT can effectively reduce system delay, increase user coverage and offload task completion rates.

A Systematic Review on Fostering Appropriate Trust in Human-AI Interaction: Trends, Opportunities and Challenges

Appropriate Trust in Artificial Intelligence (AI) systems has rapidly become an important area of focus for both researchers and practitioners. Various approaches have been used to achieve it, such as confidence scores, explanations, trustworthiness cues, or uncertainty communication. However, a comprehensive understanding of the field is lacking due to the diversity of perspectives arising from various backgrounds that influence it and the lack of a single definition for appropriate trust. To investigate this topic, this paper presents a systematic review to identify current practices in building appropriate trust, different ways to measure it, types of tasks used, and potential challenges associated with it. We also propose a Belief, Intentions, and Actions (BIA) mapping to study commonalities and differences in the concepts related to appropriate trust by (a) describing the existing disagreements on defining appropriate trust, and (b) providing an overview of the concepts and definitions related to appropriate trust in AI from the existing literature. Finally, the challenges identified in studying appropriate trust are discussed, and observations are summarized as current trends, potential gaps, and research opportunities for future work. Overall, the paper provides insights into the complex concept of appropriate trust in human-AI interaction and presents research opportunities to advance our understanding on this topic.

A problem-based approach in the formation of the self-educational competence of schoolchildren (based on the use of digital technology resources)

The article reveals the possibilities of the problem-based approach in solving the problem of the formation of the self-educational competence of schoolchildren. Various ways of influencing the development of their self-educational competence through the preparation of specially selected tasks are offered in lessons, in homework and in individual work with schoolchildren. It is substantiated that in lessons it is expedient from the point of view of the formation of self-educational competence to use typical tasks similar to typical tasks for independent work and creative tasks. It is shown that the use of educational, training and research tasks is productive for organizing homework. It has been revealed that in individual work it will be effective to perform preparatory, trial, basic tasks. At the same time, it has been proven that all the specified types of tasks involve the active use of digital technologies, which will allow for effective organization of educational activities, improve the motivation and cognitive interest of schoolchildren, ensure individualization of learning and create prerequisites for the development of independence of schoolchildren. In lessons, it is advisable to use simple digital applications, digital resources for creating your own content, digital activity environments and digital resources for online communication. It is effective to use digital resources-sources of educational information, tools for self-monitoring and self-diagnosis, as well as resources for creating your own digital content in homework. Digital resources-sources of information, tools for self-monitoring and self-diagnosis, digital activity environments and resources for personalized learning are useful for the individual work of schoolchildren. The article examines the potential of the problem-based approach to the formation of the self-educational competence of schoolchildren. The main components of self-educational competence are considered, namely: motivational-value, substantive-procedural and control-reflective. The impact of the problem-based approach on the development of each of these components is analyzed. It has been determined that the problem-based approach helps to increase students' motivation to study, stimulates their cognitive activity and develops critical thinking

Difficult cases of punctuation in the tasks of the All-Russian Olympiad of schoolchildren in the Russian language

The article examines those All-Russian Olympiad assignments in the Russian language that include questions on punctuation. It is noted that punctuation as a separate section is not included in the methodological recommendations for compiling Olympiad assignments. There are several reasons accounting for the small number of punctuation Olympiad tasks. Firstly, modern Russian punctuation is variable. Thus, the use of one or another punctuation mark can be determined not only by the main structural-grammatical principle of punctuation, but by the semantic and intonation ones as well. Secondly, the absence of unified prescriptive rules leads to discrepancies in the explanation of a particular punctuation case. Nevertheless, assignments on difficult cases of punctuation are appropriate in the Russian language Olympiad since they are the type of research tasks that form textual analysis skills in the aspect of the norm variation processes.

The effect of object perception on event integration and segregation.

The perceptual system must integrate information from various points in time and space to interpret continuous sensory input into meaningful units, such as visual objects or events. To explore the relationship between the perception of spatial objects and temporal events, we modified the missing element task, a typical temporal integration task, by inserting a simple spatial object. The aim was to determine whether the perceptual processing of the object would have an impact on the frequency of temporal integration and segregation. Temporal integration was most successful when the missing element was located within the object, less successful when there was no object, and least successful when the missing element appeared outside the object. The advantage of the location of the missing element within the object was observed at display durations from 30 ms to 150 ms. Interestingly, the object provided the same benefit for integration and segregation despite their opposing perceptual demands. This study demonstrates the relationship that exists between the processing of temporal events and spatial objects, and shows how such spatial information can facilitate temporal integration.

Impaired emotion recognition in Cntnap2-deficient mice is associated with hyper-synchronous prefrontal cortex neuronal activity.

Individuals diagnosed with autism spectrum disorder (ASD) show difficulty in recognizing emotions in others, a process termed emotion recognition. While human fMRI studies linked multiple brain areas to emotion recognition, the specific mechanisms underlying impaired emotion recognition in ASD are not clear. Here, we employed an emotional state preference (ESP) task to show that Cntnap2-knockout (KO) mice, an established ASD model, do not distinguish between conspecifics according to their emotional state. We assessed brain-wide local-field potential (LFP) signals during various social behavior tasks and found that Cntnap2-KO mice exhibited higher LFP theta and gamma rhythmicity than did C57BL/6J mice, even at rest. Specifically, Cntnap2-KO mice showed increased theta coherence, especially between the prelimbic cortex (PrL) and the hypothalamic paraventricular nucleus, during social behavior. Moreover, we observed significantly increased Granger causality of theta rhythmicity between these two brain areas, across several types of social behavior tasks. Finally, optogenetic stimulation of PrL pyramidal neurons in C57BL/6J mice impaired their social discrimination abilities, including in ESP. Together, these results suggest that increased rhythmicity of PrL pyramidal neuronal activity and its hyper-synchronization with specific brain regions are involved in the impaired emotion recognition exhibited by Cntnap2-KO mice.

汉语二语者写作研究回顾与展望——基于CiteSpace的知识图谱分析

<p>This study uses CiteSpace to analyze research trends in writing for Chinese as a Second Language (CSL) in the CNKI database. The field of CSL writing is currently rapidly evolving. Writing assessment research primarily examines linguistic differentiation features and their predictive ability on writing quality. Writing teaching research encompasses empirical summaries, teaching methods, and teaching materials. The articles explore teaching methods and their effectiveness in practical applications. It also analyzes Chinese learners' writing features and errors from a linguistic perspective. Additionally, it investigates the influencing factors on writing, such as task type, task complexity, and genre. The article concludes by offering insights into future research directions in CSL writing.</p>

Social-sum-Mal: A Dataset for Abstractive Text Summarization in Malayalam

Abstractive text summarization techniques for Malayalam language is still in its infancy. The lack of benchmarked datasets for this task is one of the constraints in developing and testing good models. Malayalam has seven nominal case forms, two nominal number forms, and three gender forms. It is subjected to extreme agglutination and inflection. Due to this, the translation of other text summarization datasets to Malayalam may not capture these case forms effectively. Therefore curation of datasets from scratch is highly demanded for specific text-processing applications in Malayalam. This paper introduces a novel dataset designed specifically for advancing the field of automatic abstractive text summarization in Malayalam language. The dataset is curated to address the unique linguistic characteristics of the Malayalam language. It is named as Social-sum-Mal dataset, capable of addressing three different types of summarization tasks- long, extreme, and query-based summarizations. In addition, Social-sum-Mal can be extended for other applications like text classification, multi-document summarization, and question answering. To enhance the dataset transparency, a datasheet is created for Social-sum-Mal. Data accuracy and annotator biases are evaluated using proper testing strategies including Jaccard, cosine, and overlap similarities. The correctness of the dataset is further evaluated by comparing it with a deep-learning-based text summarization model.

Caregivers as experimenters: Reducing unfamiliarity helps shy children learn words.

Previous work has found that shy children show chance-level disambiguation and retention of novel word meanings in a typical lab-based word learning task. This effect could be explained in terms of shy children's aversion to unfamiliarity disrupting the requisite attentional processes, because the task is marked by a high degree of unfamiliarity. To test this argument, we examined whether increasing the familiarity of the task facilitates shy children's ability to form and retain word meanings. Two-year-old children (N=23) took part in a word learning task in which their caregiver acted as the experimenter. On referent selection trials, children were presented with sets of three objects, one novel and two familiar, and were asked for either a familiar object using its known label, or a novel object using a novel word. Children were then tested on their retention of the previously formed novel word-object mappings. In this context of increased familiarity, shyness was unrelated to performance on referent selection trials. However, shyness was positively related to children's retention of the word-object mappings, meaning that shyer children outperformed less-shy children on this measure of word learning. These findings show that context-based familiarity interacts with intrinsic individual differences to affect word learning performance.

Practically implementing an LLM-supported collaborative vulnerability remediation process: A team-based approach

Incorporating LLM into cybersecurity operations, a typical real-world high-stakes task, is critical but non-trivial in practice. Using cybersecurity as the study context, we conduct a three-step mix-method study to incorporate LLM into the vulnerability remediation process effectively. Specifically, we deconstruct the deficiencies in user satisfaction within the existing process (Study 1). This inspires us to design, implement, and empirically validate an LLM-supported collaborative vulnerability remediation process through a field study (Study 2). Given LLM’s diverse contributions, we further investigate LLM’s double-edge roles through the analysis of remediation reports and follow-up interviews (Study 3). In essence, our contribution lies in promoting an efficient LLM-supported collaborative vulnerability remediation process. These first-hand, real-world pieces of evidence suggest that when incorporating LLMs into practical processes, facilitating the collaborations among all associated stakeholders, reshaping LLMs’ roles according to task complexity, as well as approaching the short-term side effects of improved user engagement facilitated by LLMs with a rational mindset.

Episodic memory impairment and its influencing factors in individuals with autism spectrum disorder: systematic review and meta-analysis.

Individuals with autism spectrum disorders (ASD) are considered to experience difficulties with episodic memory (EM), while studies on EM in ASD have shown inconsistent results. A meta-analysis of 65 episodic memory studies with a combined sample size of 1652 individuals with ASD and 1626 typically developing individuals was conducted to analyze factors that may affect EM in ASD. The results showed that ASD had a significant medium to large effect size decrease in EM ability. Age period, task type, and reporting method significantly reduced the observed heterogeneity while EM type did not reduce the observed heterogeneity. The results of the meta-regression revealed that it was verbal IQ rather than full-scale IQ that was significantly correlated with EM in individuals with ASD. These findings suggest that individuals with ASD have reduced EM abilities and the potential factors is still needed to be explored.

Evaluation of forces applied to tissues during robotic-assisted surgical tasks using a novel force feedback technology

BackgroundThe absence of force feedback (FFB) is considered a technical limitation in robotic-assisted surgery (RAS). This pre-clinical study aims to evaluate the forces applied to tissues using a novel integrated FFB technology, which allows surgeons to sense forces exerted at the instrument tips.MethodsTwenty-eight surgeons with varying experience levels employed FFB instruments to perform three robotic-assisted surgical tasks, including retraction, dissection, and suturing, on inanimate or ex-vivo models, while the instrument sensors recorded and conveyed the applied forces to the surgeon hand controllers of the robotic system. Generalized Estimating Equations (GEE) models were used to analyze the mean and maximal forces applied during each task with the FFB sensor at the “Off” setting compared to the “High” sensitivity setting for retraction and to the “Low”, “Medium”, and “High” sensitivity settings for dissection and suturing. Sub-analysis was also performed on surgeon experience levels.ResultsThe use of FFB at any of the sensitivity settings resulted in a significant reduction in both the mean and maximal forces exerted on tissue during all three robotic-assisted surgical tasks (p < 0.0001). The maximal force exerted, potentially associated with tissue damage, was decreased by 36%, 41%, and 55% with the use of FFB at the “High” sensitivity setting while performing retraction, dissection, and interrupted suturing tasks, respectively. Further, the use of FFB resulted in substantial reductions in force variance during the performance of all three types of tasks. In general, reductions in mean and maximal forces were observed among surgeons at all experience levels. The degree of force reduction depends on the sensitivity setting selected and the types of surgical tasks evaluated.ConclusionsOur findings demonstrate that the utilization of FFB technology integrated in the robotic surgical system significantly reduced the forces exerted on tissue during the performance of surgical tasks at all surgeon experience levels. The reduction in the force applied and a consistency of force application achieved with FFB use, could result in decreases in tissue trauma and blood loss, potentially leading to better clinical outcomes in patients undergoing RAS. Future studies will be important to determine the impact of FFB instruments in a live clinical environment.

A - 13 Cognitive Correlates of Technology-Based Instrumental Activities of Daily Living Performance in Older Adults Presenting for Cognitive Evaluations

Abstract Objective Rapid advances in technology have altered how daily activities are performed. Accumulating evidence suggests technology-based instrumental activities of daily living (iADLs) are increasingly common in older adults’ lives, and assessing these skills may improve diagnostic identification of individuals with Alzheimer’s disease and related dementias (ADRD). While iADLs are complex tasks reliant on multiple cognitive processes, prior work suggests memory and executive functioning are the cognitive processes most strongly predictive of iADL performance in ADRD. However, whether similar associations exist with technology-based iADLs has not been established. The goal of the present study was to evaluate the cognitive correlates of technology-based compared to traditional iADL items. Method One hundred seventy-eight individuals (mean age: 75.35 ± 7.30) presenting for evaluation of cognitive status completed tests of memory, executive functioning, language, and processing speed. Care partners completed the Functional Activities Questionnaire (FAQ) and 11 technology-based iADL items. Associations between cognition and traditional and technology-based FAQ items were examined through Pearson’s correlations and multiple regression analyses. Results Cognition was significantly correlated with both traditional and technology-based iADLs (|r’s| &amp;gt; 0.30, p’s.44). In multiple regression models, executive functioning and processing speed but not memory were the strongest predictors of traditional iADL performance (p’s &amp;lt; 0.02), but for independence with technology-based iADLs, executive functioning alone (p &amp;lt; 0.001) emerged. Conclusions Relations between cognition and daily functioning are similar for both traditional and technology-based FAQ items, with executive functioning particularly relevant for both types of tasks. Implications for clinical practice and technology-based interventions are discussed.

OneTip: A Soft Tactile Interface for 6-D Fingertip Pose Acquisition in Human-Computer Interaction

Advances in display technology have created the need for more efficient and natural multi-degree-of-freedom interaction devices. The movement of a single fingertip has six degrees of freedom (DOFs), but traditional rigid touchscreens usually sense only 2-D information. This article proposes a new deformable tactile interface, OneTip, for single-fingertip human-computer interaction with 6 DOFs. It is manufactured based on the principle of vision-based tactile sensing using virtual stereoscopic cameras, and its size is about twice that of a thumb. The contact surface of OneTip has a specially designed structure and material to mimic the sensitivity and softness of human skin. Also, OneTip employs a new sensing method to address the problem of soft fingertip pose estimation (measuring relative change only) with incipient slip effects. Experiments show that OneTip has good 6-D pose estimation accuracy, with root mean square errors (RMSE) of translation and rotation not exceeding 0.1mm and 2.6°, respectively, within the linear interval (x and y: −1.2 to 1.2mm; z: 0 to 3mm; yaw: −15 to 15deg; pitch and roll: −40 to 40deg). Experiments were also conducted to explore the application of OneTip in typical virtual manipulation tasks and the possibility of combining it with other interaction devices.

A comprehensive study on the impacts of thermal comfort on occupants’ thermophysiology and cognitive performances in a radiant cooling environment using physiological measurements

Radiant cooling (RC) systems are increasingly implemented in public buildings to enhance human thermal comfort and reduce building energy consumption. The quality of the indoor thermal environment significantly impacts occupants’ learning and work performance. This investigation explores indoor occupants’ dynamic physiological regulation, thermal comfort, and cognitive performance under radiant whole-wall cooling (RWWC) systems. Twenty-eight participants underwent a summer exposure test task at varying ambient temperatures, yielding four collected data types: indoor physical parameters, physiological parameters (including skin temperature (ST), heart rate (HR)/heart rate variability (HRV), and electroencephalography (EEG)), performance index (PI), and thermal perception. Results indicate that the RWWC system notably improves thermal perception and comfort, with 93 % of participants reporting comfort at a target temperature of 24℃. Air temperature (AT) exerted the most significant effect on changes in ST on the right upper arm (p < 0.01) and left hand back (p < 0.01) at 30℃ compared to the 22℃. The difference in whole-body mean skin temperature (MST) is 2.68℃. The HR decline was more pronounced in higher temperatures, and the HRV representativeness index approached ‘1′ at 24℃. PI was affected by temperature and task type, displaying a non-linear correlation with AT (R2 = 0.6056) and an inverted “U” shaped curve with TSV (R2 = 0.9523). Thermal perception correlates with MST, HRV, and EEG. The study carries implications for the reasonable design of comfortable and healthy RC environments.