Ensemble clustering for result diversification

This paper describes the participation of the University of Twente in the Web track of TREC 2012. Our baseline approach uses the Mirex toolkit, an open source tool that sequantially scans all the documents. For result diversification, we experimented with improving the quality of clusters through ensemble clustering. We combined clusters obtained by different clustering methods (such as LDA and K-means) and clusters obtained by using different types of data (such as document text and anchor text). Our two-layer ensemble run performed better than the LDA based diversification and also better than a non-diversification run

Toward Robots with Peripersonal Space Representation for Adaptive Behaviors

The abilities to adapt and act autonomously in an unstructured and human-oriented environment are necessarily vital for the next generation of robots, which aim to safely cooperate with humans. While this adaptability is natural and feasible for humans, it is still very complex and challenging for robots. Observations and findings from psychology and neuroscience in respect to the development of the human sensorimotor system can inform the development of novel approaches to adaptive robotics. Among these is the formation of the representation of space closely surrounding the body, the Peripersonal Space (PPS) , from multisensory sources like vision, hearing, touch and proprioception, which helps to facilitate human activities within their surroundings. Taking inspiration from the virtual safety margin formed by the PPS representation in humans, this thesis first constructs an equivalent model of the safety zone for each body part of the iCub humanoid robot. This PPS layer serves as a distributed collision predictor, which translates visually detected objects approaching a robot\u2019s body parts (e.g., arm, hand) into the probabilities of a collision between those objects and body parts. This leads to adaptive avoidance behaviors in the robot via an optimization-based reactive controller. Notably, this visual reactive control pipeline can also seamlessly incorporate tactile input to guarantee safety in both pre- and post-collision phases in physical Human-Robot Interaction (pHRI). Concurrently, the controller is also able to take into account multiple targets (of manipulation reaching tasks) generated by a multiple Cartesian point planner. All components, namely the PPS, the multi-target motion planner (for manipulation reaching tasks), the reaching-with-avoidance controller and the humancentred visual perception, are combined harmoniously to form a hybrid control framework designed to provide safety for robots\u2019 interactions in a cluttered environment shared with human partners. Later, motivated by the development of manipulation skills in infants, in which the multisensory integration is thought to play an important role, a learning framework is proposed to allow a robot to learn the processes of forming sensory representations, namely visuomotor and visuotactile, from their own motor activities in the environment. Both multisensory integration models are constructed with Deep Neural Networks (DNNs) in such a way that their outputs are represented in motor space to facilitate the robot\u2019s subsequent actions

Understanding Organizational Citizenship Behaviour through Organizational Justice and its Consequences among Vietnamese’s Universities Employees

This paper aims to investigate the impact of organizational justice components on job satisfaction, organizational commitment, and organizational citizenship behaviours (OCB) of employees in the higher education sector of Vietnam. Although many research studies have been conducted in organizations on the topics of organizational justice, as well as organizational commitment, and organizational citizenship behaviour, there is a shortage of these topics in higher education institutions as well as in Asian context. Therefore, this article attempts to fill this literature gap. A total of 317 employees from various universities in Vietnam participated in this study, and a self-administered survey was conducted, which was modified based on suggestions from the universities' management team following interviews. The collected data were analyzed using the partial least squares structural equation modeling (PLS-SEM) technique. The results showed that procedural justice and interactional justice had a significant impact on both job satisfaction and organizational commitment, while distributive justice only affected job satisfaction. Furthermore, the study found that job satisfaction and organizational commitment significantly affected OCB. However, this study had a limitation in terms of the narrow sample size, which only included participants from universities. Future studies should broaden the sample size to include participants from vocational colleges. On paper, the study shows the effects of organizational justice on OCB through the mediating roles of individual work outputs, which received inadequate attention in previous studies. Doi: 10.28991/ESJ-2023-SIED2-08 Full Text: PD

Learning to extract folktale keywords

Manually assigned keywords provide a valuable means for accessing large document collections. They can serve as a shallow document summary and enable more efficient retrieval and aggregation of information. In this paper we investigate keywords in the context of the Dutch Folktale Database, a large collection of stories including fairy tales, jokes and urban legends. We carry out a quantitative and qualitative analysis of the keywords in the collection. Up to 80% of the assigned keywords (or a minor variation) appear in the text itself. Human annotators show moderate to substantial agreement in their judgment of keywords. Finally, we evaluate a learning to rank approach to extract and rank keyword candidates. We conclude that this is a promising approach to automate this time intensive task

Direct embryogenesis from anther culture of hot chilli Capsicum annuum L.

In Viet Nam, local varieties of chili have a distinctive aroma and pungency. However, the generation of pure lines from pollen culture in local hot chilli has been very limited reported. Therefore, this study was to relate flower bud size with microspore developmental stages and the culture media have concentration changed of growth regulator effects on the in vitro androgenesis. Flower buds were randomly collected and visually divided into three stage based on both petal and sepal size. Then anther was cultured on MS basal medium with different concentration of hormones NAA changed 0.1 - 0.7 mg/L and kinetin changed 1.0 - 3.0 mg/L, BA changed 0.5 - 1.5 mg/L. The results showed that bud flower have anthers are light violet in color, 2.5 mm long, consisted of anthers with 80 % uni-nucleate and 20 % bi-nucleate microspores were selected. In induction culture media, it was observed that MS medium with 2.0 mg/L Kinetin and 0.5 mg/L NAA gave higher embryo frequency. MS medium with 1 mg/L BA is the best medium for embryo germination and inducting shoots. And ½ MS medium for shoot elongation and rooting

Audience and the Use of Minority Languages on Twitter

On Twitter, many users tweet in more than one language. In this study, we examine the use of two Dutch minority languages. Users can engage with different audiences and by analyzing different types of tweets, we find that characteristics of the audience influence whether a minority language is used. Furthermore, while most tweets are written in Dutch, in conversations users often switch to the minority language

Vietnamese Version of Cornell Scale for Depression in Dementia at an Outpatient Memory Clinic: A Reliability and Validity Study

Background: In Vietnam, there has been, currently, no standardized tool for depression assessment for people with dementia (PWD). Cornell Scale for Depression in Dementia (CSDD) is a widely studied and used scale for PWD worldwide. Objectives: The aim of this study was to standardize the Vietnamese version of the CSDD (V-CSDD) in depression assessment in PWD through reliability and validity examination. Methods: V-CSDD was rated in terms of reliability and validity with gold standard regarding "major depressive episode"and "major depressive-like episode"of DSM-5. Cronbach's α, ICC, exploratory factor analysis (EFA), and receiver operating characteristic analysis were performed. Results: V-CSDD was found to have a high internal consistency reliability (Cronbach's α = 0.80), inter-rater reliability at sound ranking (ICC = 0.89; 95% CI = 0.81-0.94), maximum cut-off mark of 13 (sensitivity = 70%, specificity = 92%), and EFA, which suggested that V-CSDD may comprise 5 factors. Conclusions: Results indicate the V-CSDD to be a reliable and valid assessment and to be beneficial in classifying and diagnosing depression in dementia outpatients in clinical contexts

TweetGenie: automatic age prediction from tweets

A person’s language use reveals much about the person’s social identity, which is based on the social categories a person belongs to including age and gender. We discuss the development of TweetGenie, a computer program that predicts the age of Twitter users based on their language use. We explore age prediction in three different ways: classifying users into age categories, by life stages, and predicting their exact age. An automatic system achieves better performance than humans on these tasks. Both humans and the automatic systems tend to underpredict the age of older people. We find that most linguistic changes occur when people are young, and that after around 30 years the studied variables show little change, making it difficult to predict the ages of older Twitter users