Neural network and multiple linear regression to predict school children dimensions for ergonomic school furniture design

The current study investigates the possibility of obtaining the anthropometric dimensions, critical to school furniture design, without measuring all of them. The study first selects some anthropometric dimensions that are easy to measure. Two methods are then used to check if these easy-to-measure dimensions can predict the dimensions critical to the furniture design. These methods are multiple linear regression and neural networks. Each dimension that is deemed necessary to ergonomically design school furniture is expressed as a function of some other measured anthropometric dimensions. Results show that out of the five dimensions needed for chair design, four can be related to other dimensions that can be measured while children are standing. Therefore, the method suggested here would definitely save time and effort and avoid the difficulty of dealing with students while measuring these dimensions. In general, it was found that neural networks perform better than multiple linear regression in the current study.     

计算机辅助图像分类信息挖掘与应用探讨*

以沿海地区TM图像应用为例,通过量化方法由计算机对训练区的分离度进行确定与比较,进行最佳信息维数的确定与最佳信息维组合的选择,并将信息维数对分类精度的影响进行探讨。结果证明,这种方法可以得到能满足工作需要的分类精度,组合维数以6维最佳。     

Turning Organizational Culture from Fad into Management Tool*

Talking about a company's culture has become a fad. To turn the concept into something of practical managerial use, we need to know how to assess a company's culture in ways that permit realistic proposals for actions with some chance of moving the company in a desired direction. The author has found six dimensions of corporate culture, some of which are consistent with earlier work. He shows how the dimensions can be a framework for introducing and monitoring proposed organizational changes.     

Perceptions about the quality of web sites: a survey amongst students at Northeastern University and Erasmus University

A survey was undertaken to identify the quality aspects perceived to be most important in the design and use of web sites. The questionnaire utilized was based on preliminary research by Cox and Dale who had previously developed a model for assessing the quality of web sites. The results were compared to the SERVQUAL dimensions as developed by Zeithaml, Parasuraman, and Berry for bricks-and-mortar service environments. Our results indicated that the quality dimensions found applicable in the service sector are also applicable to web sites.No major differences have been found between the attitudes of students at Erasmus University Rotterdam (EUR) and those at Northeastern University (NEU), Boston on web quality aspects. Minor differences can be explained by age, gender and field of study. Overall, NEU students make more use of the Internet than EUR students.     

Anthropometric study of Algerian farmers

An anthropometric study of Algerian date-palm farmers was carried out. Thirty-six body dimensions were measured. Mean, variation measures, percentiles, 4 indices, and correlation coefficients between body dimensions were calculated. Effects of age were studied. Data of Algerian farmers and farmers from both developed and developing countries are compared. Body dimensions results were presented in one table so that they can easily be used by designers. It has been found that both stature and weight correlated significantly with many body dimensions. In addition, age was found to affect body height and weight. Moreover, it was found that stature and weight have increased with time. These days farmers are taller and heavier than farmers of the 1960s. Algerian farmers are also taller and heavier than farmers of many developing countries. However, when Algerians are compared with the farmers of developed countries, they are shorter and lighter.

Relevance to industry

The physical dimensions of the workplace are very important because small changes can have a considerable impact on worker health, safety, and productivity. Therefore, this study was completed to provide anthropometric data that can be used to design or redesign agricultural machines, tools and equipment. Date-palm agriculture is still done traditionally in most of the date-palm producing countries. The introduction of ergonomically designed technology will improve the date-palm industry.     

A fractal analysis of shadowed and sunlit areas

Analyses of remote-sensing imagery from a fractal perspective have become more frequent in the literature. However, one aspect which has not been considered specifically is how images integrate a mix of several, possibly very different, fractal processes. In this exploratory investigation, the fractal dimensions of sunlit and shadowed areas of surfaces of known fractal dimensions were determined. It was found that the shadowed areas lend to have fractal dimensions approaching 2.0, whereas, surprisingly, sunlit areas have fractal dimensions which are inversely related to the fractal dimension of the surface.     

Evidence for the need to update the Chilean standard for school furniture dimension specifications

Some countries decide to use standards to define the type of furniture dimensions that should be used according to students' anthropometric characteristics. The aim of this paper is to generate data to update the standard for Chilean school furniture using student anthropometric data. The sample used involved 3078 students. Data collection included eight anthropometric dimensions. A strict procedure was followed to define six furniture school dimensions. The definition of the compatibility between students' characteristics and furniture dimensions was done using the concept of mismatch computed through a set of equations. The results showed differences in mismatch levels between the two compared approaches, with lower mismatch found using the new proposed approach – the updated standard (UpS). Seat depth presents the greatest difference in mismatch, with values of 43% for the current Chilean standard (ChS) and 17% for the UpS. Also, seat height match values are almost the same (100%); however, it is important to mention that the level of match could drop to 82% in the ChS if the furniture selection was already carried out, as suggested in the standard itself, by using the Stature. Finally the UpS presents a higher covered range in the six furniture dimensions. The obtained results reflect the need to update the data and the procedure for school furniture selection presented by the current Chilean standard. Relevance for industry: this paper presents relevant data to be used by both school furniture designers, as well as by those responsible for the furniture selection at schools. In addition, proof is presented that school furniture standards need to be updated periodically in order to better fit the students’ anthropometric characteristics.     

Estimation of critical dimensions for a trapezoidal-shaped steel fin using hybrid differential evolution algorithm

This paper deals with the inverse prediction of parameters in a trapezoidal fin with temperature-dependent thermal conductivity and heat transfer coefficient. Three critical dimensions along with the relevant heat transfer coefficient at the fin base have been simultaneously predicted for satisfying a given temperature distribution on the surface of the trapezoidal fin. The inverse problem is solved by a hybrid differential evolution-nonlinear programming (DE-NLP) optimization method. For a given fin material which is considered to be stainless steel, it is found from the present study that many feasible dimensions exist which satisfy a given temperature distribution, thereby providing flexibility in selecting any dimensions from the available alternatives by appropriately regulating the base heat transfer coefficient. A very good estimation of the unknown parameters has been obtained even for temperature distribution involving random measurement errors which is confirmed by the comparisons of the reconstructed distributions. It is concluded that for a given fin material, the hybrid DE-NLP algorithm satisfactorily estimates feasible dimensions of a trapezoidal fin even with random measurement error of 11 %.

     

Tool wear monitoring using artificial neural network based on extended Kalman filter weight updation with transformed input patterns

The condition of the tool in a turning operation is monitored by using artificial neural network (ANN). The recursive Kalman filter algorithm is used for weight updation of the ANN. To monitor the status of the tool, tool wear patterns are collected. The patterns are transformed from n-dimensional feature space to a lower dimensional space (two dimensions). This is done by using two discriminant vectors j₁ {\varphi_{1 }} and j₂{\varphi_{2}}. These discriminant vectors are found by optimal discriminant plane method. Thirty patterns are used for training the ANN. A comparison between the classification performances of the ANN trained without reducing the dimensions of the input patterns and with reduced dimensions of the input patterns is done. The ANN trained with transformed tool wear patterns gives better results in terms of improved classification performance in less iteration, when compared with the results of the ANN trained without transforming the dimensions of the input patterns to a lower dimension.     

ICT Research in Africa: Need for a Strategic Developmental Focus

This paper argues the need to expand the research agenda on the use of ICT in African countries to include a stronger strategic developmental focus than is evident in much of the literature to date. Four strategic dimensions are identified, where ICT arguably has potential as a significant enabler for transformational development in Africa: institutional infrastructure; governance, accountability, and civil society; service production and economic activity; and access to global markets and resources. A representative set of literature on IS in Africa is classified along these dimensions, but an explicit focus on development is found to be lacking in most of this work. The four dimensions are then discussed in turn to describe their importance in the African context, to discuss some pathfinding research examples to date and to identify some directions for future research. The paper concludes with a call for IS researchers working on Africa to become involved in debate on national and international policy from an ICT perspective and to engage with other research communities in doing this, notably with those concerned with the field of African development.     

Outlier identification in high dimensions

A computationally fast procedure for identifying outliers is presented that is particularly effective in high dimensions. This algorithm utilizes simple properties of principal components to identify outliers in the transformed space, leading to significant computational advantages for high-dimensional data. This approach requires considerably less computational time than existing methods for outlier detection, and is suitable for use on very large data sets. It is also capable of analyzing the data situation commonly found in certain biological applications in which the number of dimensions is several orders of magnitude larger than the number of observations. The performance of this method is illustrated on real and simulated data with dimension ranging in the thousands.     

The determination of optimum accelerating factors for successive overrelaxation on an equidistant and non-equidistant rectangular net

A modification to the successive overrelaxation iterative procedure for solving elliptic partial differential equations is presented. The modified method is based on an extension of Brazier's nodal overrelaxation method in one dimension, characterised by the use of a different overrelaxation factor for each point in the net. The extension to several dimensions make use of the separability of the variables for the error distribution. Thus the optimum one dimensional results are directly used in the several dimensional problem.The present method has been examined in one and two dimensions, for equidistant and non-equidistant nets. The computational time required to obtain a given accuracy for a solution was found for all two dimensional cases to be half (or less) of that required by conventional methods.     

Taiwanese adult foot shape classification using 3D scanning data

This study classifies the foot shapes of Taiwanese using 3D foot scanning data from 2000 males and 1000 females. Nine foot dimensions relative to foot length and absolute measures in the common foot length categories were applied to compare the gender differences. Using foot breadth in % foot length (% FL), ball of foot length in % FL and arch height in % FL as feature parameters, three foot shape types for males and females can be classified. Significant gender differences were found in seven of the nine foot dimensions. Females had greater ball of foot length than males (0.2% FL). When comparing feet of the same foot length, males had greater breadth, girth and height dimensions than females, except for toe height. In addition, ethnic differences in foot shape were also observed. The findings can provide very useful information for building gender-specific shoe lasts and designing footwear insoles.     

Learner readiness for online learning: Scale development and student perceptions

The purpose of this study was to develop and validate a multidimensional instrument for college students’ readiness for online learning. Through a confirmatory factor analysis, the Online Learning Readiness Scale (OLRS) was validated in five dimensions: self-directed learning, motivation for learning, computer/Internet self-efficacy, learner control, and online communication self-efficacy. Research data gathered from 1051 college students in five online courses in Taiwan revealed that students’ levels of readiness were high in computer/Internet self-efficacy, motivation for learning, and online communication self-efficacy and were low in learner control and self-directed learning. This study found that gender made no statistical differences in the five OLRS dimensions, but that higher grade (junior and senior) students exhibited significantly greater readiness in the dimensions of self-directed learning, online communication self-efficacy, motivation for learning, and learner control than did lower grade (freshman and sophomore) students.     

A multidimensional analysis of data quality for credit risk management: New insights and challenges

Recent studies have indicated that companies are increasingly experiencing Data Quality (DQ) related problems as more complex data are being collected. To address such problems, the literature suggests the implementation of a Total Data Quality Management Program (TDQM) that should consist of the following phases: DQ definition, measurement, analysis and improvement. As such, this paper performs an empirical study using a questionnaire that was distributed to financial institutions worldwide to identify the most important DQ dimensions, to assess the DQ level of credit risk databases using the identified DQ dimensions, to analyze DQ issues and to suggest improvement actions in a credit risk assessment context. This questionnaire is structured according to the framework of Wang and Strong and incorporates three additional DQ dimensions that were found to be important to the current context (i.e., actionable, alignment and traceable). Additionally, this paper contributes to the literature by developing a scorecard index to assess the DQ level of credit risk databases using the DQ dimensions that were identified as most important. Finally, this study explores the key DQ challenges and causes of DQ problems and suggests improvement actions. The findings from the statistical analysis of the empirical study delineate the nine most important DQ dimensions, which include accuracy and security for assessing the DQ level.     

基于混合粒子群算法的高维优化问题求解

为解决高维复杂函数的优化问题，克服标准粒子群算法早熟收敛、局部搜索能力弱等缺点，在标准粒子群优化算法中融合了遗传算法的设计思想，提出了一种新颖的混合粒子群算法。高维函数个别维上的差解导致算法最终无法找到全局最优解，而通常的优化算法很难寻找到每一维上的最佳值。受遗传算法思想的启发，在粒子的进化过程中，通过对最优粒子的每一维进行评价，找到导致最终解质量差的维度，对其维上的数据进行变异，进而有针对性地改进，寻找到每一维上的最佳位置。对典型高维复杂函数的仿真表明：算法在求解质量和求解速度两方面都得到了好的结果。     

Anisotropic human performance in six degree-of-freedom tracking: anevaluation of three-dimensional display and control interfaces

Motivated by the need for human performance evaluations of advanced interface technologies, this paper presents an empirical evaluation of a 3D interface, from the point of view of both display and control, in a pursuit tracking experiment. The paper derives methods for decomposing tracking performance into six dimensions (three in translation and three in rotation). This dimensional decomposition approach has the advantage of revealing overall performance levels in the depth dimension relative to performance in the horizontal and vertical dimensions. With interposition, linear perspective, stereoscopic disparity and partial occlusion cues incorporated into a single 3D display system, subjects' tracking errors in the depth dimension were about 35% (with no practice) to 35% (with practice) larger than those in the horizontal and vertical dimensions. It was also found that subjects initially had larger tracking errors along the vertical axis than along the horizontal axis, likely due to their attention allocation strategy. Analysis of rotation errors generated a similar anisotropic pattern     

Metrics for characterizing the form of security policies

Security policies are widely used tools for the implementation of organizational security, however neither do we have metrics for measuring their effectiveness, nor are there universal standards that can serve as benchmarks. There is considerable variability in security policies based on the way they are written but we have no quantifiable evidence to determine if one kind of policy is better than another. This paper examines the literature on policies and identifies three dimensions (breadth, clarity and brevity) that could be used to characterize how well a security policy is written. These dimensions are validated through a survey of user perceptions. Informed by this empirical evidence, we propose objective metrics (along with algorithms for calculating these metrics), that can be used to assess each of these dimensions. The objective metrics are cross validated with user perceptions and found to be consistent, thus providing a standardized process to characterize the form of a security policy. Such a set of metrics would facilitate the process of evaluating the effectiveness of security policies.     

The mediating role of the dimensions of the perceived risk in the effect of customers’ awareness on the adoption of Internet banking in Iran

One of the major issues banks are faced with in providing Internet Banking (IB) services is the adoption of these services by the customers. This study seeks answer to the question that whether bank customers’ awareness of the services and advantages of IB is effective in reducing the negative effect of customers’ perceived risk on their intention of IB adoption. To this end, the two constructs of the dimensions of the perceived risk and IB awareness are simultaneously considered. Besides, in the research model, the effect of IB awareness on each dimension of the perceived risk and the effect of these dimensions on intention of IB adoption by the customers are investigated. The results indicate that IB awareness acts as a factor reducing all dimensions of the perceived risk (including time, financial, performance, social, security, and privacy). In addition, it was found out that except for social risk, other dimensions of the perceived risk have significantly negative effect on the intention of IB adoption. Finally, proving the direct and positive effect of IB awareness on adoption intention, it was concluded that the dimensions of customers’ perceived risk plays a mediating role in the positive effect of IB awareness on IB adoption intention. In this respect, management approaches centered on the concept of IB awareness are offered for reducing the dimensions of customers’ perceived risk.