Multidimensional Classification Scheme Research Articles

Diversity and Classification of Genetic Variations in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition with symptoms that affect the whole personality and all aspects of life. Although there is a high degree of heterogeneity in both its etiology and its characteristic behavioral patterns, the disorder is well-captured along the autistic triad. Currently, ASD status can be confirmed following an assessment of behavioral features, but there is a growing emphasis on conceptualizing autism as a spectrum, which allows for establishing a diagnosis based on the level of support need, free of discrete categories. Since ASD has a high genetic predominance, the number of genetic variations identified in the background of the condition is increasing exponentially as genetic testing methods are rapidly evolving. However, due to the huge amount of data to be analyzed, grouping the different DNA variations is still challenging. Therefore, in the present review, a multidimensional classification scheme was developed to accommodate most of the currently known genetic variants associated with autism. Genetic variations have been grouped according to six criteria (extent, time of onset, information content, frequency, number of genes involved, inheritance pattern), which are themselves not discrete categories, but form a coherent continuum in line with the autism spectrum approach.

Assessing the impact of technological change on similar occupations: Implications for employment alternatives.

The fast-changing labor market highlights the need for an in-depth understanding of occupational mobility impacted by technological change. However, we lack a multidimensional classification scheme that considers similarities of occupations comprehensively, which prevents us from predicting employment trends and mobility across occupations. This study fills the gap by examining employment trends based on similarities between occupations. We first demonstrated a new method that clusters 756 occupation titles based on knowledge, skills, abilities, education, experience, training, activities, values, and interests. We used the Principal Component Analysis to categorize occupations in the Standard Occupational Classification, which is grouped into a four-level hierarchy. Then, we paired the occupation clusters with the occupational employment projections provided by the U.S. Bureau of Labor Statistics. We analyzed how employment would change and what factors affect the employment changes within occupation groups. Particularly, we specified factors related to technological changes. The results reveal that technological change accounts for significant job losses in some clusters. This poses occupational mobility challenges for workers in these jobs at present. Job losses for nearly 60% of current employment will occur in low-skill, low-wage occupational groups. Meanwhile, many mid-skilled and highly skilled jobs are projected to grow in the next ten years. Our results demonstrate the utility of our occupational classification scheme. Furthermore, it suggests a critical need for skills upgrading and workforce development for workers in declining jobs. Special attention should be paid to vulnerable workers, such as older individuals and minorities.

The development of a classification model of accounting in the digital economy

A multidimensional classification scheme and a semantic multidimensional accounting data model are defined in this article. Instead of accounts, multidimensional accounting uses categories of economic activity. The proposed multidimensional data model is more flexible than the traditional account model and allows you to expand the capabilities of accounting, taking into account the different needs of users of accounting information. The multidimensional data model allows you to expand the capabilities of accounting, taking into account the different needs of users of accounting information. To create a multidimensional accounting system, the categories of economic activity registered in accounting have been determined, the concept of double entry and balance in a multidimensional representation (probalance) has been formulated. The features of planning in a multidimensional accounting system have been described and the implementation of the financial results plan has been considered.

New multidimensional classification scheme of altered igneous rocks from performance comparison of isometric and modified log-ratio transformations of major elements

Nomenclature in any science is of fundamental importance. From performance comparison of isometric and modified or hybrid log-ratio transformations of major elements, we present a complete multidimensional classification scheme for altered igneous rocks for High-Mg rock varieties and magma and rock types. This scheme is efficiently applicable through a computer package called Multidimensional Igneous rock Classification System (MICSys) that encapsulates four new online computer modules (HMgClaMSys_ilr, MagClaMSys_mlr, and IgRoClaMSys_mlr and a robustness evaluation module). We used a major element database of multinormally distributed 33868 samples of relatively fresh igneous rocks and compared the performance of isometric log-ratio and modified log-ratio transformations, both of which were multinormally distributed in terms of the 9 log-transformed variables as confirmed by the DOMUDaF program. The system must be trained from only fresh rocks because the prior class assignment requires an efficient scheme accepted by all, which is available only for fresh rocks. The multivariate technique of linear discriminant analysis (LDA) and canonical analysis applied to the two transformations provided the same percent success or correct classification for the respective databases. With these findings, we reinforce the recently published work on the International Union of Geological Sciences (IUGS)-consistent multidimensional classification of altered igneous rocks. The numerous tests and applications documented earlier on multidimensional classification were applied in the present work. The mathematical properties of log-ratio transformations are no longer important, provided the multidimensional technique involves the LDA and canonical analysis. MICSys available for online application at the web portal http://tlaloc.ier.unam.mx , was successfully applied to 6 new tests and 11 new applications to illustrate the usefulness of our multidimensional classification system to igneous rocks altered from post-emplacement compositional changes. Robustness of the new scheme for altered igneous rock nomenclature as compared to the conventional IUGS procedure for fresh rock nomenclature was confirmed from simulation of post-emplacement alteration of all elements in 28 different rock compositions representative of all rock types. Even greater robustness was demonstrated against analytical uncertainty propagation in 14 geochemical reference materials issued from Canada (3), France (3), Japan (5), and the USA (3). The estimation of robustness against post-emplacement changes and uncertainty propagation was facilitated by the incorporation of a fourth module in MICSys. This work, therefore, clearly shows that, for altered rocks, the new multidimensional scheme should be used, instead of the conventional classification meant for fresh rocks only.

Change detection in urban areas from remote sensing data: a multidimensional classification scheme

ABSTRACT Change detection (CD) from remote sensing data is a very challenging research problem, especially when we analyse an urban scene. Urban scenes are composed of many different types of objects, both natural and man-made. The building class is one of the important and most complex classes to analyse, important because it is useful for so many applications and complex because it exhibits many changes due to human activity and natural catastrophes. For these reasons, we focus our study on building change detection (BCD). In this paper we propose a classification scheme for BCD research according to several important dimensions including objective, input data, temporal resolution, analysis unit, target output unit, building features, processing technique, change categories, and assessment of results. This classification scheme can guide practitioners in choosing appropriate change detection methods to achieve their goals as well as informing new research efforts. Based on this multidimensional characterisation of BCD, we offer a number of suggestions for further work to be done in this field.

On Fair Person Classification Based on Efficient Factor Score Estimates in the Multidimensional Factor Analysis Model.

Since Hooker, Finkelman and Schwartzman (Psychometrika 74(3): 419-442, 2009) it is known that person parameter estimates from multidimensional latent variable models can induce unfair classifications via paradoxical scoring effects. The open question as to whether there is a fair and at the same time multidimensional scoring scheme with adequate statistical properties is addressed in this paper. We develop a theorem on the existence of a fair, multidimensional classification scheme in the context of the classical linear factor analysis model and show how the computation of the scoring scheme can be embedded in the context of linear programming. The procedure is illustrated in the framework of scoring the Wechsler Adult Intelligence Scale (WAIS-IV).

A typological approach to studying policing

ABSTRACTPolicing in the United States has experienced immense change throughout the past quarter-century. Although police agencies have shared their goals of preserving life and protecting property, their philosophies and practices for achieving these goals have differed. The present research, therefore, explores patterns in policing via a novel, typological approach. Using six waves of data (1993, 1997, 2000, 2003, 2007, and 2013) from the Law Enforcement Management and Administrative Statistics (LEMAS) data series, we first employ factor analyses to generate indices for six important policing dimensions: (1) officer diversity, (2) community policing, (3) patrol strategy diversity, (4) militancy, (5) technology, and (6) staffing rigor. Using these indices, we then employ latent class analyses to construct typologies of police agencies, and examine the distribution of such typologies across space at various points in time. Our results reveal several key findings. We detect consistent patterns in typologies across time, including classes with high militancy, high diversity, or low staffing rigor (among others). Within these sets of classes, we also detect micro-heterogeneity amongst patterns of index values: for example, subsets of classes which all score high on one dimension but score high versus low on other dimensions. Finally, we find evidence to suggest spatial convergence of typologies in one large geographic region: Southern California. By offering a multidimensional classification scheme over a 20-year period, we contribute to the policing literature by highlighting the importance and implications of studying multiple policing dimensions simultaneously.

Log‐ratio transformed major element based multidimensional classification for altered High‐Mg igneous rocks

AbstractA new multidimensional classification scheme consistent with the chemical classification of the International Union of Geological Sciences (IUGS) is proposed for the nomenclature of High‐Mg altered rocks. Our procedure is based on an extensive database of major element (SiO2, TiO2, Al2O3, Fe2 , MnO, MgO, CaO, Na2O, K2O, and P2O5) compositions of a total of 33,868 (920 High‐Mg and 32,948 “Common”) relatively fresh igneous rock samples. The database consisting of these multinormally distributed samples in terms of their isometric log‐ratios was used to propose a set of 11 discriminant functions and 6 diagrams to facilitate High‐Mg rock classification. The multinormality required by linear discriminant and canonical analysis was ascertained by a new computer program DOMuDaF. One multidimensional function can distinguish the High‐Mg and Common igneous rocks with high percent success values of about 86.4% and 98.9%, respectively. Similarly, from 10 discriminant functions the High‐Mg rocks can also be classified as one of the four rock types (komatiite, meimechite, picrite, and boninite), with high success values of about 88%–100%. Satisfactory functioning of this new classification scheme was confirmed by seven independent tests. Five further case studies involving application to highly altered rocks illustrate the usefulness of our proposal. A computer program HMgClaMSys was written to efficiently apply the proposed classification scheme, which will be available for online processing of igneous rock compositional data. Monte Carlo simulation modeling and mass‐balance computations confirmed the robustness of our classification with respect to analytical errors and postemplacement compositional changes.

SOA adoption in business networks: do service-oriented architectures really advance inter-organizational integration?

The emergence of the Internet as a global communication infrastructure has dramatically reduced interaction costs within and across organizations, with significant impact on inter-organizational relationships, vertical industry structures, and markets. More recently, service-oriented architectures (SOA) and Web services have introduced the next paradigm shift and foster the idea of dynamic business networks with quick connect and disconnect relationships. However, little research has systematically analyzed how companies leverage SOA to improve their inter-organizational relationships and reshape their business networks. In addition, the mature research stream on inter-organizational information systems (IOS) has not yet sufficiently considered SOA. In order to close this gap, our research seeks to improve the fundamental understanding of how SOA is applied in business networks and how it differs from prior forms of IOS. Using an exploratory research approach, we investigate 33 SOA cases to identify focus areas and patterns of SOA adoption in business networks. Our case analysis builds on a multi-dimensional classification scheme which we derived from prior literature. While our empirical findings do not confirm all promising propositions related to SOA, they underline the specific contribution of SOA compared to prior forms of IOS. We conclude by suggesting five clusters of SOA adoption in the inter-organizational domain, each of those introducing new aspects in the coordination of distributed business networks.

Neonatal seizure classification: A fetal perspective concerning childhood epilepsy

Neonatal seizures are markers for time-specific etiologies during antepartum, intrapartum and neonatal time periods. Seizures with or without encephalopathic signs can represent a continuum of maternal, placental, fetal and neonatal risk factors and disease states. A multi-dimensional classification scheme for neonatal seizures is suggested that will help strategize specific therapeutic interventions to optimize neurologic outcome and anticipate later neurological morbidities including epilepsy risk. This scheme combines “epileptic” and “non-epileptic” seizure descriptions which capture time-specific and brain region-specific mechanisms for seizures. Synchronized video electroencephalographic monitoring provides the most accurate start and endpoints for cortically generated seizures. However, subcortical sites of injury may also initiate abnormal clinical signs with or without the subsequent expression of electrographic seizures. Co-registration of digital neuroimaging techniques such as magnetic resonance imaging with computational electroencephalographic datasets will provide more precise structure–function correlates for neonatal seizures that address both cortical and subcortical sites of injury. Finally, more precise definitions of neonatal status epilepticus need to be established because of the long-term harmful effects on brain development by prolonged seizures expressed as epilepsy and cognitive-behavioral deficits. With this expanded classification scheme for neonatal seizures, novel pharmacologic and surgical strategies can be designed for disease-specific rescue, repair, and regeneration strategies of damaged brain tissue that occur during fetal and neonatal periods, and are later expressed during infancy and childhood. Clinical neuroscientists must strive to develop a classification scheme that bridges bench to bedside concepts of developmental neural plasticity research, recognizing both negative and positive consequences of brain remodeling and repair of the child and adolescent brain. Developmental neural plasticity also extends into adulthood when brain remodeling mechanisms further contribute to epileptogenesis and continues to impair quality of life.

Stuttering and the International Classification of Functioning, Disability, and Health (ICF): An update

The World Health Organization (WHO) recently presented a multidimensional classification scheme for describing health status and the experience of disablement. This new framework, the International Classification of Functioning, Disability, and Health (ICF; WHO, 2001), is a revision of WHO’s prior framework for describing the consequences of disorders, the International Classification of Impairments, Disabilities, and Handicaps (ICIDH; WHO, 1980). In previous papers, Yaruss [J. Speech Lang. Hear. Res. 41 (1998) 249; J. Commun. Disord. 34 (2001) 163] had shown how the original ICIDH could be adapted to describe the consequences of stuttering at several levels that are relevant to the communication and life experiences of the person who stutters. The current manuscript presents an update of the Yaruss (1998) model that accounts for the new structure of the ICF. A comparison of the WHO’s ICIDH and ICF frameworks is presented, followed by an analysis of how the ICF can be adapted to describe the speaker’s experience of the stuttering disorder. Emphasis is placed on the fact that stuttering involves more than just observable behaviors. Specifically, the speaker’s experience of stuttering can involve negative affective, behavioral, and cognitive reactions (both from the speaker and the environment), as well as significant limitations in the speaker’s ability to participate in daily activities and a negative impact on the speaker’s overall quality of life. Learning outcomes As a result of reading this manuscript, participants, will (1) gain an understanding of the updates to the World Health Organization’s original International Classification of Impairments, Disabilities, and Handicaps that are seen in the International Classification of Functioning, Disability, and Health (2) understand how the ICF can be applied to the study of stuttering (3) recognize that health conditions such as stuttering are affected by both internal and external factors, and can involve more than just observable behaviors that are seen on the surface.

Design of a computer-aided user-system dialogue based on an analysis of users' search behaviour

Aspects of needs and values as expressed by users as well as different search strategies applied by librarians and users during the retrieval process are identified. To satisfy the user's requirements, a classification scheme has been developed which reflects the fact that the user's criteria for accepting a document are related to a combination of several different features, such as contents, emotional experience during reading, accessibility, etc. For experimental purposes, different bibliographic databases have been created which contain works of fiction classified according to a multi-dimensional classification scheme. Several different search strategies can be used by searchers when applying this fiction database. Such strategies will be characterized and their different requirements for the design of adequate computer aids will be discussed.