Initial Classification Scheme Research Articles

The Predatory Journal: Victimizer or Victim?

Aim/Purpose: Labeling a journal as “predatory” can do great damage to the journal and the individuals that have contributed to it. This paper considers whether the predatory classification has outlived its usefulness and what might replace it. Background: With the advent of open access publishing, the term “predatory” has increasingly been used to identify academic journals, conferences, and publishers whose practices are driven by profit or self-interest rather than the advancement of science. Absent clear standards for determining what is predatory and what is not, concerns have been raised about the misuse of the label. Methodology: Mixed methods: A brief review of the literature, some illustrative case studies, and conceptual analysis. Contribution: The paper provides recommendations for reducing the impact of illegitimate journals. Findings: Current predatory classifications are being assigned with little or no systematic research and virtually no accountability. The predatory/not predatory distinction does not accommodate alternative journal missions. Recommendations for Researchers: The distinction between legitimate and illegitimate journals requires consideration of each journal’s mission. To serve as a useful guide, a process akin to that used for accrediting institutions needs to be put in place. Impact on Society: Avoiding unnecessary damage to the careers of researchers starting out. Future Research: Refining the initial classification scheme proposed in the paper.

Consensus statement on surgical pathology of the aorta from the Society for Cardiovascular Pathology and the Association for European Cardiovascular Pathology: I. Inflammatory diseases.

Inflammatory diseases of the aorta include routine atherosclerosis, aortitis, periaortitis, and atherosclerosis with excessive inflammatory responses, such as inflammatory atherosclerotic aneurysms. The nomenclature and histologic features of these disorders are reviewed and discussed. In addition, diagnostic criteria are provided to distinguish between these disorders in surgical pathology specimens. An initial classification scheme is provided for aortitis and periaortitis based on the pattern of the inflammatory infiltrate: granulomatous/giant cell pattern, lymphoplasmacytic pattern, mixed inflammatory pattern, and the suppurative pattern. These inflammatory patterns are discussed in relation to specific systemic diseases including giant cell arteritis, Takayasu arteritis, granulomatosis with polyangiitis (Wegener's), rheumatoid arthritis, sarcoidosis, ankylosing spondylitis, Cogan syndrome, Behçet's disease, relapsing polychondritis, syphilitic aortitis, and bacterial and fungal infections.

THE USE OF NEURAL NETWORKS IN RARE VEGETATION COMMUNITIES CLASSIFICATION

This paper describes training of Multilayer Perceptron Neural classifier to extract rare vegetation objects from high spatial resolution IKONOS satellite imagery. There have been considered three options of training of the Multilayer Perceptron Neural according to three different classification schemes. At first 12 type of rare vegetation community types were defined, a main classification scheme (“Initial classification scheme”) was designed on that base. After prelim statistical tests on training samples two modification algorithms of the classification scheme were defined: the first one led to creating of scheme consisting of 7 classes (“Modified classification scheme”) and second one led us to creating of 5-classes scheme (“Optimized classification scheme“). The learning procedures of these classifiers are described as well as analysis and post processing of extraction results of objects of interest using Geoinformation Technologies in details.

Remote Sensing and GIS as an Advance Space Technologies for Rare Vegetation Monitoring in Gobustan State National Park, Azerbaijan

This paper describes remote sensing methodologies for monitoring rare vegetation with special emphasis on the Image Statistic Analysis for set of training samples and classification. At first 5 types of Rare Vegetation communities were defined and the Initial classification scheme was designed on that base. After preliminary Statistic Analysis for training samples, a modification algorithm of the classification scheme was defined: one led us to creating a 4 class’s scheme (Final classification scheme). The different methods analysis such as signature statistics, signature separability and scatter plots are used. According to the results, the average separability (Transformed Divergence) is 1951.14, minimum is 1732.44 and maximum is 2000 which shows an acceptable level of accuracy. Contingency Matrix computed on the results of the training on Final classi- fication scheme achieves better results, in terms of overall accuracy, than the training on Initial classification scheme.

Unconscious linguistic referents to race: analysis and methodological frameworks

Recent years have seen considerable development in methodological designs for accessing and eliciting unconscious cognitive schemata in response to social stimuli, including race. One design is experimental and involves the priming and automatic activation of schemata. Another design is a specifically developed psycho-linguistic and logico-mathematic method for recognizing, analyzing, and validating unconsciously expressed meaning in verbal narratives, referred to as sub-literal (SubLit). Unconscious references to race found in verbal discourse from both laboratory and everyday settings, including the mass media, are illustrated and analyzed utilizing these two complementary methodological designs. Along with suggested procedures, an initial classification scheme for attributions of racial stereotypes and prejudice are presented. Given the historical and current state of race relations both nationally and globally, the paper has significant social implications.

Object‐based land‐cover classification for the Phoenix metropolitan area: optimization vs. transportability

An object‐based approach was utilized in the development of two urban land‐cover classification schemes on high‐resolution (0.6 m), true‐colour aerial photography of the Phoenix metropolitan area, USA. An initial classification scheme was heavily weighted by standard nearest‐neighbour (SNN) functions generated by samples from each of the classes, which produced an enhanced accuracy (84%). A second classification was developed from the initial classification scheme in which SNN functions were transformed into a fuzzy‐rule set, creating a product transportable to different areas of the same imagery, or for land‐cover change detection with similar imagery. A comprehensive accuracy assessment revealed a slightly lower overall accuracy (79%) for the rule‐based classification. We conclude that the transportable classification scheme is satisfactory for general land‐cover analyses; yet classification accuracy can be enhanced at site‐specific venues with the incorporation of nearest‐neighbour functions using class samples.

Taxonomy of Group Chat: A Basis for Understanding and Design

Instant messaging, or online chat, has existed for almost a decade. Today, more individuals are using chat in the work place as organizations increasingly acknowledge chat as a useful collaborative tool, particularly in distributed work environments. One organization where chat has seen overwhelming adoption is the military. Chat is ideally suited for military domains as it consumes low-bandwidth and provides nearly synchronous communication. In addition, military chat users can simultaneously monitor multiple group conversations, making chat an important situation awareness tool. Despite its extensive use, little research exists on chat use in the workplace, particularly the military, and almost none is devoted to making the chat environment more attuned to user needs. Before extensive studies on and possible improvements to chat environments can occur, an understanding of the different chat environments is needed. This paper provides an initial classification scheme for different types of chat.

Texture imperfections

Self-similarity is the generic property of the class of homogenous image textures. The concept of texture with respect to a similarity relation is introduced. The minimum patch constraint included in the concept leads to an ambiguity inherent in texture segmentation. Local imperfections (defects) in surface textures are also viewed as ambiguity zones or discontinuity regions which locally break the homogeneity of a pattern. Some general principles of imperfection analysis are discussed and an initial classification scheme for the types of imperfections suggested. Finally, the possible approaches to the detection of imperfections are outlined.

Graduate Student-Faculty Relationships: A Classification Scheme

The trend in graduate education in political science in the last few years has been one of retrenchment and constriction. This trend, combined with the shrinking job market for new Ph.D.s, has forced many departments to face the dilemma of maintaining a quality Ph. D. program. The authors believe that one of the best ways to meet the demands of this new situation is to increase and enhance the interaction between faculty and graduate students outside the classroom. Before one can outline how this could be done, however, there is a need to better understand the nature and dimensions of these noncourse related student-professorial relationships. This article sets out an initial classification scheme of what is believed to be the main types of graduate student-faculty relationships in political science. It discusses the conditions under which we expect the various relationships to develop and analyzes the costs and benefits a graduate student can incur as a partner in each relationship.