A theoretical framework and empirical examination of the effects of foreign and translated interface language

Given the increased globalization and popularization of computer applications, translating a system's human interface into the local language has become a major consideration for software vendors and distributors. In this paper, we suggest a theoretical framework for the study of user interface translation. The framework includes recognizing vendors' and users' costs of, and benefits from, software translation. An experiment was conducted, based on this framework, to test user performance and preferences regarding interface translations. The experiment manipulated the translation of two interface components: documentation language and manipulation language. The results indicate that users are sensitive to different combinations of interface translation in a way that is commensurate with the instruction-following process (Terwilliger and Polson 1997). Users performed best when a fully translated interface was used and worst when only the manipulation language was translated. Users' preferences were in line with their performance, indicating that a cost benefit approach can serve as a promising starting point to the study of interface translation.     

Reading and writing mathematics: The MAVIS1 Project

One of the greatest challenges to the visually impaired student in science and mathematics disciplines is the reading and writing of complex mathematical equations or have convenient access to information based tools such as the world wide web. In research currently underway at New Mexico State University, tools are being built using logic programming to facilitate access to complex information in a variety of formats. On top of the logic based tools, new interfaces are being designed to permit more convenient access to information by our visually impaired students.     

数据库自然语言接口研究

使用自然语言对数据库进行操作,有利于数据库技术的进一步推广应用。本文首先对语音识别的主要技术隐马尔可夫模型进行了综述,对数据库操作的词法和语义进行了研究,分析给出了基本的操作语句框架。     

Combining natural language with direct manipulation: the conceptual framework for a hybrid human-computer interface

This paper describes the development of a conceptual model of an interaction system for future human-computer interaction. It is suggested that an integrated system is the most promising solution for diverse users and tasks. A ' hybrid interaction system' is considered, which tries to efficiently direct manipulation, menu selection, and natural language. The mechanism of the natural language interface module is described in more detail. Finally, the allocation of functionalities for generalized tasks on the conceptual model is considered from the taxonomic approach.     

Combining natural language with direct manipulation: the conceptual framework for a hybrid human-computer interface

Abstract

This paper describes the development of a conceptual model of an interaction system for future human-computer interaction. It is suggested that an integrated system is the most promising solution for diverse users and tasks. A ‘ hybrid interaction system’ is considered, which tries to efficiently direct manipulation, menu selection, and natural language. The mechanism of the natural language interface module is described in more detail. Finally, the allocation of functionalities for generalized tasks on the conceptual model is considered from the taxonomic approach.     

浅谈现代教育技术在《高等数学》教学中的应用

介绍现代教育技术在《高等数学》教学中的重要性,现代教育技术被越来越多的学校所利用,也给《高等数学》的教学带来巨大的生机,成为高等数学教师必不可少的工具。分析现代教育技术应用在高等数学教学中存在的一些问题,针对这些问题,结合笔者的教学经验,提出一些改进的方法。     

Quitting the use of a habituated hedonic information system: a theoretical model and empirical examination of Facebook users

Much research has been devoted to the early adoption and the continued and habituated use of information systems (IS). Nevertheless, less is known about quitting the use of IS by individuals, especially in habituated hedonic settings, that is, IS discontinuance. This study focuses on this phenomenon, and argues that in hedonic IS use contexts (1) IS continuance and discontinuance can be considered simultaneously yet independently by current users, and that (2) IS continuance and discontinuance drivers can have differential effects on the respective behavioral intentions. Specifically, social cognitive theory is used to point to key unique drivers of website discontinuance intentions: guilt feelings regarding the use of the website and website-specific discontinuance self-efficacy, which counterbalance the effects of continuance drivers: habit and satisfaction. The distinctiveness of continuance and discontinuance intentions and their respective nomological networks, as well as the proposed research model, were then empirically validated in a study of 510 Facebook users. The findings indicate that satisfaction reduces discontinuance intentions directly and indirectly through habit formation. However, habit can also facilitate the development of ‘addiction’ to the use of the website, which produces guilt feelings and reduces one’s self-efficacy to quit using the website. These factors, in turn, drive discontinuance intentions and possibly the quitting of the use of the website.     

Ann: A domain-specific language for the effective design and validation of Java annotations

This paper describes a new modelling language for the effective design and validation of Java annotations. Since their inclusion in the 5th edition of Java, annotations have grown from a useful tool for the addition of meta-data to play a central role in many popular software projects. Usually they are not conceived in isolation, but in groups, with dependency and integrity constraints between them. However, the native support provided by Java for expressing this design is very limited.To overcome its deficiencies and make explicit the rich conceptual model which lies behind a set of annotations, we propose a domain-specific modelling language. The proposal has been implemented as an Eclipse plug-in, including an editor and an integrated code generator that synthesises annotation processors. The environment also integrates a model finder, able to detect unsatisfiable constraints between different annotations, and to provide examples of correct annotation usages for validation. The language has been tested using a real set of annotations from the Java Persistence API (JPA). Within this subset we have found enough rich semantics expressible with Ann and omitted nowadays by the Java language, which shows the benefits of Ann in a relevant field of application.     

An insight into the dispersion of changes in cloned and non-cloned code: A genealogy based empirical study

In this paper, we present an in-depth empirical study of a new metric, change dispersion, that measures the extent changes are scattered throughout the code of a software system. Intuitively, highly dispersed changes, the changes that are scattered throughout many software entities (such as files, classes, methods, and variables), should require more maintenance effort than the changes that only affect a few entities. In our research we investigate change dispersion on the code-base of a number of subject systems as a whole, and separately on each system's cloned and non-cloned code. Our central objective is to determine whether cloned code negatively affects software evolution and maintenance. The granularity of our focus is at the method level.Our experimental results on 16 open source subject systems written in four different programming languages (Java, C, C#, and Python) involving two clone detection tools (CCFinderX and NiCad) and considering three major types of clones (Type 1: exact, Type 2: dissimilar naming, and Type 3: some dissimilar code) suggests that change dispersion has a positive and statistically significant correlation with the change-proneness (or instability) of source code. Cloned code, especially in Java and C systems, often exhibits a higher change dispersion than non-cloned code. Also, changes to Type 3 clones are more dispersed compared to changes to Type 1 and Type 2 clones. According to our analysis, a primary cause of high change dispersion in cloned code is that clones from the same clone class often require corresponding changes to ensure they remain consistent.     

On the economic effects of the text completion interface: empirical analysis of financial markets

Electronic Markets - In financial markets, investment options are relatively fixed but may occasionally change as new securities (tickers) are introduced to the markets. Theory on exploratory...     

A framework for empirical evaluation of conceptual modeling techniques

The paper presents a framework for the empirical evaluation of conceptual modeling techniques used in requirements engineering. The framework is based on the notion that modeling techniques should be compared via their underlying grammars. The framework identifies two types of dimensions in empirical comparisons—affecting and affected dimensions. The affecting dimensions provide guidance for task definition, independent variables and controls, while the affected dimensions define the possible mediating variables and dependent variables. In particular, the framework addresses the dependence between the modeling task—model creation and model interpretation—and the performance measures of the modeling grammar. The utility of the framework is demonstrated by using it to categorize existing work on evaluating modeling techniques. The paper also discusses theoretical foundations that can guide hypothesis generation and measurement of variables. Finally, the paper addresses possible levels for categorical variables and ways to measure interval variables, especially the grammar performance measures.     

A theoretical framework to improve the quality of manually acquired data

We present a framework for organisations to prevent errors in data entry. It states that data entry errors can be prevented by a strong intention of data producers to enter data correctly and by a high task-technology fit. Two empirical studies support the framework and demonstrate that a high task-technology fit is relatively more important than the data producers’ intention. The framework refines the theory of planned behaviour, and extends the explanatory domain of the task-technology fit construct. The empirical evidence underlines the importance of the task-technology fit construct, an often-neglected construct in information systems research.     

A framework for and empirical study of algorithms for traffic assignment

Traffic congestion is an issue in most cities worldwide. Transportation engineers and urban planners develop various traffic management projects in order to solve this issue. One way to evaluate such projects is traffic assignment (TA). The goal of TA is to predict the behaviour of road users for a given period of time (morning and evening peaks, for example). Once such a model is created, it can be used to analyse the usage of a road network and to predict the impact of implementing a potential project. The most commonly used TA model is known as user equilibrium, which is based on the assumption that all drivers minimise their travel time or generalised cost. In this study, we consider the static deterministic user equilibrium TA model.The constant growth of road networks and the need of highly precise solutions (required for select link analysis, network design, etc.) motivate researchers to propose numerous methods to solve this problem. Our study aims to provide a recommendation on what methods are more suitable depending on available computational resources, time and requirements on the solution. In order to achieve this goal, we implement a flexible software framework that maximises the usage of common code and, hence, ensures comparison of algorithms on common ground. In order to identify similarities and differences of the methods, we analyse groups of algorithms that are based on common principles. In addition, we implement and compare several different methods for solving sub-problems and discuss issues related to accumulated numerical errors that might occur when highly accurate solutions are required.     

User switching of information technology: A theoretical synthesis and empirical test

As competing technological choices emerge in the marketplace, an inevitable consequence is user switching from one IT product or service to another. However, we know very little of this phenomenon or the key drivers of user switching. We examined the reasons for IT switching by proposing a model that synthesized and extended current theories of IT acceptance and customer satisfaction. We believed that IT switching was driven by user dissatisfaction with an incumbent product or service and the fact that the customer was aware of the availability of a potentially superior product or service. Further, to explain differential switching patterns across an adopter population, we posited personal innovativeness as an individual difference variable that moderated the effect of user dissatisfaction and relative advantage of a new IT on users’ switching intention. Our model was empirically validated using a longitudinal survey of web browser switching among student subjects. We hope that our study will generate researchers’ interest in an understudied area of research and that the model will serve as a starting point for furthering our understanding of IT switching.     

On the empirical justification of theoretical heuristic transference and learning

The solution of intractable problems implies the use of heuristics. Quantum computers may find use for optimization problems, but have yet to solve any NP-hard problems. This paper demonstrates results in game theory for domain transference and the reuse of problem-solving knowledge through the application of learned heuristics. It goes on to explore the possibilities for the acquisition of heuristics for the solution of the NP-hard TSP problem. Here, it is found that simple heuristics (e.g., pairwise exchange) often work best in the context of more or less sophisticated experimental designs. Often, these problems are not amenable to exclusive logic solutions; but rather, require the application of hybrid approaches predicated on search. In general, such approaches are based on randomization and supported by parallel processing. This means that heuristic solutions emerge from attempts to randomize the search space. The paper goes on to present a constructive proof of the unbounded density of knowledge in support of the Semantic Randomization Theorem (SRT). It highlights this result and its potential impact upon the community of machine learning researchers.     

The effects of feedback on performance and retention of skill for a natural language interface

This study investigated the effectiveness of different types of on-line feedback following user errors for informing users of the information and functions available in a system with a natural language interface. Twenty-four individuals performed a task based on an industry cost savings program, in which they were given general goals to pursue with regard to the task. Three feedback levels which differed according to the type and amount of feedback provided, along with two levels of system complexity, were examined. In addition, subjects performed the task again after one week to determine the effects of feedback on retention. Results indicated that the subjects in the second level of feedback generally performed better with respect to accessing system functions and information than those in the first level. Although there was some performance improvement from the second to third level, it was not significant. However, the third level of feedback did significantly improve the efficiency with which subjects used information to complete the task during the return condition. Overall, feedback did not affect the errors made, though at certain more limited stages of the tasks this effect was observed.     

A theoretical framework for quantum image representation and data loading scheme

Two fundamental problems exist in the use of quantum computation to process an image or signal.The first one is how to represent giant data,such as image data,using quantum state without losing information.The second one is how to load a colossal volume of data into the quantum registers of a quantum CPU from classical electronic memory.Researches on these two questions are rarely reported.Here an entangled state is used to represent an image(or vector)for which two entangled registers are used to store a vector component and its classical address.Using the representation,n1+n2+8 qubits are used to store the whole information of the gray image that has a 2n1×2n2 size at a superposition of states,a feat is not possible with a classic computer.The way of designing a unitary operation to load data,such as a vector(or image),into the quantum registers of a quantum CPU from electronic memory is defined herein as a quantum loading scheme(QLS).In this paper,the QLS with time complexity O(log2N)is presented where N denotes the number of vector components,a solution that would break through the efciency bottleneck of loading data.QLS would enable a quantum CPU to be compatible with electronic memory and make possible quantum image compression and quantum signal processing that has classical input and output.     

Remote sensing of phytoplankton pigments: A comparison of empirical and theoretical approaches

Algorithms that have been used on a routine basis for remote sensing of the phytoplankton pigment, chlorophyll- a, from ocean colour data from satellite sensors such as the CZCS (Coastal Zone Color Scanner), SeaWiFS (Sea Viewing Wide Field-of-View Sensor) and OCTS (Ocean Colour and Temperature Scanner) are all of an empirical nature. However, there exist theoretical models that allow ocean colour to be expressed as a function of the inherent optical properties of seawater, such as the absorption coefficient and the backscattering coefficient. These properties can in turn be expressed as functions of chlorophyll- a, at least for the so-called Case 1 waters in which phytoplankton may be considered to be the single, independent variable responsible for most of the variations in the marine optical properties. Here, we use such a theoretical approach to model variations in ocean colour as a function of chlorophyll- a concentration, and compare the results with some empirical models in routine use. The parameters of phytoplankton absorption necessary for the implementation of the ocean colour model are derived from our database of over 700 observations of phytoplankton absorption spectra and concurrent measurements of phytoplankton pigments by HPLC (High Performance Liquid Chromatography) techniques. Since there are reports in the literature that significant differences exist in the performance of the algorithms in polar regions compared with lower latitudes, the model is first implemented using observations made at latitudes less than 50. It is then applied to the Labrador Sea, a high-latitude environment. Our results show that there are indeed differences in the performance of the algorithm at high latitudes, and that these differences may be attributed to changes in the optical characteristics of phytoplankton that accompany changes in the taxonomic composition of their assemblages. The sensitivities of the model to assumptions made regarding absorption by coloured dissolved organic matter (or yellow substances) and backscattering by particles are examined. The importance of Raman scattering on ocean colour and its influence on the algorithms are also investigated.     

A unified model of knowledge sharing behaviours: theoretical development and empirical test

Research and practice on knowledge management (KM) have shown that information technology alone cannot guarantee that employees will volunteer and share knowledge. While previous studies have linked motivational factors to knowledge sharing (KS), we took a further step to thoroughly examine this theoretically and empirically. We developed a unified model that is comprehensive and yet parsimonious, based on the decomposed theory of planned behaviour (DTPB) with three sets of critical antecedents: psychological, organisational and technological that are theorised to influence KS behaviours. Results of a field survey of knowledge workers support the majority of hypothesised relationships, and explained 41.3% of the variance in the actual KS behaviours and 60.8% of the variance in the intention to share knowledge. These results far exceed the predictive powers achieved by previous studies. Among our significant findings include a strong positive influence of perceived enjoyment in helping others (PEH) and a strong negative influence of perceived loss of knowledge power (PLK). Based on the findings, we discussed the study's implications for research and practice.