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1 – 9 of 9
Article
Publication date: 1 August 2004

B. Beydoun, M. Zoaeter, A. Alaeddine, I. Rachidi, F. Bahsoun, J‐J. Charlot and J‐P. Charles

Modifications of physical and electrical properties of the vertical double‐diffused metal oxide semiconductor (VDMOS) transistor are observed on using the device under some…

Abstract

Modifications of physical and electrical properties of the vertical double‐diffused metal oxide semiconductor (VDMOS) transistor are observed on using the device under some conditions of “functional” stress. This paper presents the characterization and the 2D simulation for the pre‐ and post‐stressed device, to point out the degraded parameters due to the functional stress, and to analyze their effects on the degradation of the VDMOS static and dynamic characteristics.

Details

Microelectronics International, vol. 21 no. 2
Type: Research Article
ISSN: 1356-5362

Keywords

Article
Publication date: 4 October 2022

Jing Chen, Lu Zhang and Wenhai Qian

Attentive to task-related information is the prerequisite for task completion. Comparing the cognition between attentive readers (AR) and inattentive readers (IAR) is of great…

Abstract

Purpose

Attentive to task-related information is the prerequisite for task completion. Comparing the cognition between attentive readers (AR) and inattentive readers (IAR) is of great value for improving reading services which has seldom been studied. To explore their cognitive differences, this study investigates the effectiveness, efficiency and cognitive resource allocation strategy by eye-tracking technology.

Design/methodology/approach

A controlled user study of two types of task, fact-finding (FF) and content understanding (CU) tasks was conducted to collect data including answer for task, fixation duration (FD), fixation count (FC), fixation duration proportion (FDP), and fixation count proportion (FCP). 24 participants were placed into AR or IAR group according to their fixation duration on paragraphs related to task.

Findings

Two types of cognitive resource allocation strategies, question-oriented (QO) and navigation-assistant (NA) were identified according to the differences in FDP and FCP. In FF task, although QO strategy was applied by the two groups, AR group was significantly more effective and efficient. In CU task, although the two groups were similar in effectiveness and efficiency, AR group promoted their strategies to NA while IAR group sticked to applying QO strategy. Furthermore, an interesting phenomenon “win by uncertainty”, which implies IAR group may get correct answer through uncertain means, such as clue, domain knowledge or guess, rather than task-related information, was observed.

Originality/value

This study takes a deep insight into cognition from the prospect of attentive and inattentive to task-related information. Identifying indicators about cognition helps to distinguish attentive and inattentive readers in various tasks automatically. The cognitive resource allocation strategy applied by readers sheds new light on reading skill training. A typical reading phenomenon “win by uncertainty” was found and defined. Understanding the phenomenon is of great value for satisfying reader information need and enhancing their deep learning.

Article
Publication date: 14 March 2019

Ali Daher, Amine Ammar and Abbas Hijazi

The purpose of this paper is to develop a numerical model for the simulation of the dynamics of nanoparticles (NPs) at liquid–liquid interfaces. Two cases have been studied, NPs…

Abstract

Purpose

The purpose of this paper is to develop a numerical model for the simulation of the dynamics of nanoparticles (NPs) at liquid–liquid interfaces. Two cases have been studied, NPs smaller than the interfacial thickness, and NPs greater than the interfacial thickness.

Design/methodology/approach

The model is based on the molecular dynamics (MD) simulation in addition to phase field (PF) method, through which the discrete model of particles motion is superimposed on the continuum model of fluids which is a new ide a in numerical modeling. The liquid–liquid interface is modeled using the diffuse interface model.

Findings

For NPs smaller than the interfacial thickness, the results obtained show that the concentration gradient of one fluid in the other gives rise to a hydrodynamic drag force that drives the NPs to agglomerate at the interface. Whereas, for spherical NPs greater than the interfacial thickness, the results show that such NPs oscillate at the interface which agrees with some experimental studies.

Practical implications

The results are important in the field of numerical modeling, especially that the model is general and can be used to study different systems. This will be of great interest in the field of studying the behavior of NPs inside fluids and near interfaces, which enters in many industrial applications.

Originality/value

The idea of superimposing the molecular dynamic method on the PF method is a new idea in numerical modeling.

Details

Engineering Computations, vol. 36 no. 3
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 7 June 2021

Amir Hosein Keyhanipour and Farhad Oroumchian

Incorporating users’ behavior patterns could help in the ranking process. Different click models (CMs) are introduced to model the sophisticated search-time behavior of users…

Abstract

Purpose

Incorporating users’ behavior patterns could help in the ranking process. Different click models (CMs) are introduced to model the sophisticated search-time behavior of users among which commonly used the triple of attractiveness, examination and satisfaction. Inspired by this fact and considering the psychological definitions of these concepts, this paper aims to propose a novel learning to rank by redefining these concepts. The attractiveness and examination factors could be calculated using a limited subset of information retrieval (IR) features by the random forest algorithm, and then they are combined with each other to predicate the satisfaction factor which is considered as the relevance level.

Design/methodology/approach

The attractiveness and examination factors of a given document are usually considered as its perceived relevance and the fast scan of its snippet, respectively. Here, attractiveness and examination factors are regarded as the click-count and the investigation rate, respectively. Also, the satisfaction of a document is supposed to be the same as its relevance level for a given query. This idea is supported by the strong correlation between attractiveness-satisfaction and the examination-satisfaction. Applying random forest algorithm, the attractiveness and examination factors are calculated using a very limited set of the primitive features of query-document pairs. Then, by using the ordered weighted averaging operator, these factors are aggregated to estimate the satisfaction.

Findings

Experimental results on MSLR-WEB10K and WCL2R data sets show the superiority of this algorithm over the state-of-the-art ranking algorithms in terms of P@n and NDCG criteria. The enhancement is more noticeable in top-ranked items which are reviewed more by the users.

Originality/value

This paper proposes a novel learning to rank based on the redefinition of major building blocks of the CMs which are the attractiveness, examination and satisfactory. It proposes a method to use a very limited number of selected IR features to estimate the attractiveness and examination factors and then combines these factors to predicate the satisfactory which is regarded as the relevance level of a document with respect to a given query.

Details

International Journal of Web Information Systems, vol. 17 no. 4
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 24 May 2013

N. Abboud, R. Habch, Y. Cuminal, A. Foucaran and C. Salame

The purpose of this paper is to apply a negative gate bias stress in order to study instabilities of threshold voltage in N‐channel power vertical double‐diffused…

Abstract

Purpose

The purpose of this paper is to apply a negative gate bias stress in order to study instabilities of threshold voltage in N‐channel power vertical double‐diffused metal‐oxide‐semiconductor field effect transistor (VDMOSFET). Variations in gate oxide trapped charge and interface trap densities are also calculated.

Design/methodology/approach

A threshold voltage shift is detected; the oxide and interface trap densities were evaluated based on a direct measurement of the gate to source capacitance and conductance.

Findings

Results presented show that the threshold voltage is decreasing with stress time, the capacitance and conductance curves are altered by applied stress, also the oxide traps and the interface traps densities are increasing with stress time.

Originality/value

The positive bias stress seems to be more destructive in the case of the studied devices.

Details

International Journal of Structural Integrity, vol. 4 no. 2
Type: Research Article
ISSN: 1757-9864

Keywords

Article
Publication date: 26 April 2019

Jacqueline Sachse

Web search is more and more moving into mobile contexts. However, screen size of mobile devices is limited and search engine result pages face a trade-off between offering…

Abstract

Purpose

Web search is more and more moving into mobile contexts. However, screen size of mobile devices is limited and search engine result pages face a trade-off between offering informative snippets and optimal use of space. One factor clearly influencing this trade-off is snippet length. The purpose of this paper is to find out what snippet size to use in mobile web search.

Design/methodology/approach

For this purpose, an eye-tracking experiment was conducted showing participants search interfaces with snippets of one, three or five lines on a mobile device to analyze 17 dependent variables. In total, 31 participants took part in the study. Each of the participants solved informational and navigational tasks.

Findings

Results indicate a strong influence of page fold on scrolling behavior and attention distribution across search results. Regardless of query type, short snippets seem to provide too little information about the result, so that search performance and subjective measures are negatively affected. Long snippets of five lines lead to better performance than medium snippets for navigational queries, but to worse performance for informational queries.

Originality/value

Although space in mobile search is limited, this study shows that longer snippets improve usability and user experience. It further emphasizes that page fold plays a stronger role in mobile than in desktop search for attention distribution.

Details

Aslib Journal of Information Management, vol. 71 no. 3
Type: Research Article
ISSN: 2050-3806

Keywords

Article
Publication date: 8 September 2022

Amir Hosein Keyhanipour and Farhad Oroumchian

User feedback inferred from the user's search-time behavior could improve the learning to rank (L2R) algorithms. Click models (CMs) present probabilistic frameworks for describing…

Abstract

Purpose

User feedback inferred from the user's search-time behavior could improve the learning to rank (L2R) algorithms. Click models (CMs) present probabilistic frameworks for describing and predicting the user's clicks during search sessions. Most of these CMs are based on common assumptions such as Attractiveness, Examination and User Satisfaction. CMs usually consider the Attractiveness and Examination as pre- and post-estimators of the actual relevance. They also assume that User Satisfaction is a function of the actual relevance. This paper extends the authors' previous work by building a reinforcement learning (RL) model to predict the relevance. The Attractiveness, Examination and User Satisfaction are estimated using a limited number of the features of the utilized benchmark data set and then they are incorporated in the construction of an RL agent. The proposed RL model learns to predict the relevance label of documents with respect to a given query more effectively than the baseline RL models for those data sets.

Design/methodology/approach

In this paper, User Satisfaction is used as an indication of the relevance level of a query to a document. User Satisfaction itself is estimated through Attractiveness and Examination, and in turn, Attractiveness and Examination are calculated by the random forest algorithm. In this process, only a small subset of top information retrieval (IR) features are used, which are selected based on their mean average precision and normalized discounted cumulative gain values. Based on the authors' observations, the multiplication of the Attractiveness and Examination values of a given query–document pair closely approximates the User Satisfaction and hence the relevance level. Besides, an RL model is designed in such a way that the current state of the RL agent is determined by discretization of the estimated Attractiveness and Examination values. In this way, each query–document pair would be mapped into a specific state based on its Attractiveness and Examination values. Then, based on the reward function, the RL agent would try to choose an action (relevance label) which maximizes the received reward in its current state. Using temporal difference (TD) learning algorithms, such as Q-learning and SARSA, the learning agent gradually learns to identify an appropriate relevance label in each state. The reward that is used in the RL agent is proportional to the difference between the User Satisfaction and the selected action.

Findings

Experimental results on MSLR-WEB10K and WCL2R benchmark data sets demonstrate that the proposed algorithm, named as SeaRank, outperforms baseline algorithms. Improvement is more noticeable in top-ranked results, which usually receive more attention from users.

Originality/value

This research provides a mapping from IR features to the CM features and thereafter utilizes these newly generated features to build an RL model. This RL model is proposed with the definition of the states, actions and reward function. By applying TD learning algorithms, such as the Q-learning and SARSA, within several learning episodes, the RL agent would be able to learn how to choose the most appropriate relevance label for a given pair of query–document.

Details

Data Technologies and Applications, vol. 57 no. 4
Type: Research Article
ISSN: 2514-9288

Keywords

Article
Publication date: 31 May 2019

Dirk Lewandowski and Sebastian Sünkler

The purpose of this paper is to describe a new method to improve the analysis of search engine results by considering the provider level as well as the domain level. This approach…

1406

Abstract

Purpose

The purpose of this paper is to describe a new method to improve the analysis of search engine results by considering the provider level as well as the domain level. This approach is tested by conducting a study using queries on the topic of insurance comparisons.

Design/methodology/approach

The authors conducted an empirical study that analyses the results of search queries aimed at comparing insurance companies. The authors used a self-developed software system that automatically queries commercial search engines and automatically extracts the content of the returned result pages for further data analysis. The data analysis was carried out using the KNIME Analytics Platform.

Findings

Google’s top search results are served by only a few providers that frequently appear in these results. The authors show that some providers operate several domains on the same topic and that these domains appear for the same queries in the result lists.

Research limitations/implications

The authors demonstrate the feasibility of this approach and draw conclusions for further investigations from the empirical study. However, the study is a limited use case based on a limited number of search queries.

Originality/value

The proposed method allows large-scale analysis of the composition of the top results from commercial search engines. It allows using valid empirical data to determine what users actually see on the search engine result pages.

Details

Aslib Journal of Information Management, vol. 71 no. 3
Type: Research Article
ISSN: 2050-3806

Keywords

Article
Publication date: 7 August 2017

Annie Tubadji, Masood Gheasi and Peter Nijkamp

An interest in social transmission as a source of welfare and income inequality in a society has re-emerged recently with new vigour in leading economic research (see Piketty, 2014

Abstract

Purpose

An interest in social transmission as a source of welfare and income inequality in a society has re-emerged recently with new vigour in leading economic research (see Piketty, 2014). This paper presents a mixed Bourdieu-Mincer (B-M) type micro-economic model which provides a testable mechanism for culturally biased socio-economic inter-generational transmission. In particular, the operationalisation of this mixed B-M type model seeks to find evidence for individual and local cultural capital effects on the economic achievements, in addition to the human capital effect, for both migrants and locals in the Netherlands. The purpose of this paper is to examine two sources of wage differential in the local labour market, namely: individual cultural capital (approximated by immigrant background), which affects schooling results; and the local cultural capital (approximated with the cultural milieu), which directly biases the selection of employees.

Design/methodology/approach

The study utilises the 2007-2009 data set for higher professional education (in Dutch termed HBO) graduates registered in the Maastricht database. The Mincer-type equation is augmented with a control variable for the local cultural milieu. The authors cope with this model empirically by means of 2SLS and 3SLS methods.

Findings

The authors find convincing evidence for the existence of both an individual cultural capital and a local cultural capital effect on schooling and wage differentials. This can be interpreted as a migrant background effect leading to a disadvantaged position on the labour market due to less frequently attending high-quality secondary schools.

Originality/value

More importantly, the authors find evidence for a classical Myrdalian effect of self-fulfilling prophecy, in which graduates with second-generation migrant background have a disadvantaged position due to access only to poorer quality of schooling.

Details

International Journal of Manpower, vol. 38 no. 5
Type: Research Article
ISSN: 0143-7720

Keywords

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