scholarly journals Launching of a New Product with the Co-Branding Strategy: A Case Study of Indian Brands

2020 ◽  
Vol 8 (2) ◽  
pp. 28-33
Author(s):  
A Ananda Kumar ◽  
R Sakthivel
Keyword(s):  
New Product ◽  
Brand Names ◽  
Research Articles ◽  
Marketing Plan ◽  
Brand Associations ◽  
Single Product ◽  
General Classification ◽  
Brand Association

In recent years, the practice of co-branding has attracted a large number of research scholars and practitioners. Many of the researchers are also done their research articles with branding or co-branding. Commonly co-branding deals with the combination of two or more brands into a single product. Where co-branding is concerned with a marketing plan to associate with multiple brand names in a single product. The researcher discussed the general classification of brand associations. The paper reveals two classifications of the  statements. The first is to form the general classification of Co-branding. The second aims of this paper are to promote the model of co-branding. The paper is also dealing with analyzing the theories of brand association and brand extension. The paper discussed, along with various case studies of co-branding of products and services.

scholarly journals Determining and Establishing A General Classification of Prefixes and Prefixoids for Nouns in Multistructural Languages (A Case Study of Russian, German, and Thai Languages)

2020 ◽  
pp. 91-110
Author(s):  
Kritsada Chusuwan ◽  
◽  
Andrey Ivanov ◽  
Keyword(s):  
Word Formation ◽  
Comparative Approach ◽  
Relevant Research ◽  
Compound Words ◽  
General Classification ◽  
Points Of View ◽  
Selective Analysis ◽  
Derivatives Of

This article examines the problem of classifying prefixes and prefixoids or half-prefixes for nouns in multistructural languages. The concept of prefixes and prefixoids in multistructural languages is debatable due linguists’ different points of view, therefore, the same word-formation formant (prefix for nouns, in this context) can receive different names, such as prefix, prefixoid, confix, preconfix, initial or the first part of compound words or an element of compound words; in addition, in multistructural languages the same word-formation formant of foreign origin, especially Greek and Latin, may be considered and classified according to many other different criteria, proposed by linguists. The relevance of the study is enhanced by the need to define and classify prefixes and prefixoids for nouns in multistructural languages (namely in Russian, Thai, and German) in a new way. The authors seek to determine and classify prefixes and prefixoids by establishing the most suitable criteria in the languages under analysis after an in-depth review of existing systems proposed by other linguists. As material for selective analysis, they use lexemes recorded in word-formation and explanatory dictionaries as well as data from relevant research by Russian and foreign linguists. Using the comparative approach, they attempt to establish the general criteria that would enable scholars to define and classify noun prefixes and prefixoids in multistructural languages, thus simplifying the existing system of analysis and classification. The results of this study may be used both as a tool for modeling prefixal derivatives of nouns in multistructural languages and as a constructive stepping stone for further similar research in word formation of multistructural languages.

FUNDAMENTAL NATURE AND CLASSIFICATION OF LABOR MIGRATION

2020 ◽  
Vol 1 (3) ◽  
pp. 14-23
Author(s):  
Tulkin Chulliev ◽  
Keyword(s):  
Labor Migration ◽  
General Classification ◽  
Fundamental Nature

The article explains the fundamental nature of migration by combining the definitions given by other scholars. The issue of labor migration is analyzed. One of the most important problems in contemporary migration processes - the problem of classification- is researched and a general classification is provided

scholarly journals Assessment of health/functioning of older adults who consume psychoactive substances

2018 ◽  
Vol 71 (3) ◽  
pp. 942-950
Author(s):  
Vania Dias Cruz ◽  
Silvana Sidney Costa Santos ◽  
Jamila Geri Tomaschewski-Barlem ◽  
Bárbara Tarouco da Silva ◽  
Celmira Lange ◽  
...  
Keyword(s):  
Older Adults ◽  
Qualitative Case Study ◽  
International Classification Of Functioning ◽  
Psychoactive Substances ◽  
Systematic Observation ◽  
Health Functioning ◽  
Final Consideration ◽  
Theory Of Complexity

ABSTRACT Objective: To assess the health/functioning of the older adult who consumes psychoactive substances through the International Classification of Functioning, Disability and Health, considering the theory of complexity. Method: Qualitative case study, with 11 older adults, held between December 2015 and February 2016 in the state of Rio Grande do Sul, using interviews, documents and non-systematic observation. It was approved by the ethics committee. The analysis followed the propositions of the case study, using the complexity of Morin as theoretical basis. Results: We identified older adults who consider themselves healthy and show alterations - the alterations can be exacerbated by the use of psychoactive substances - of health/functioning expected according to the natural course of aging such as: systemic arterial hypertension; depressive symptoms; dizziness; tinnitus; harmed sleep/rest; and inadequate food and water consumption. Final consideration: The assessment of health/functioning of older adults who use psychoactive substances, guided by complex thinking, exceeds the accuracy limits to risk the understanding of the phenomena in its complexity.

scholarly journals Sparse Autoencoder-based Multi-head Deep Neural Networks for Machinery Fault Diagnostics with Detection of Novelties

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Zhe Yang ◽  
Dejan Gjorgjevikj ◽  
Jianyu Long ◽  
Yanyang Zi ◽  
Shaohui Zhang ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Supervised Classification ◽  
Deep Neural Networks ◽  
Activation Function ◽  
Reconstruction Error ◽  
Fine Tuning ◽  
Fault Diagnostics ◽  
Sparse Autoencoder

AbstractSupervised fault diagnosis typically assumes that all the types of machinery failures are known. However, in practice unknown types of defect, i.e., novelties, may occur, whose detection is a challenging task. In this paper, a novel fault diagnostic method is developed for both diagnostics and detection of novelties. To this end, a sparse autoencoder-based multi-head Deep Neural Network (DNN) is presented to jointly learn a shared encoding representation for both unsupervised reconstruction and supervised classification of the monitoring data. The detection of novelties is based on the reconstruction error. Moreover, the computational burden is reduced by directly training the multi-head DNN with rectified linear unit activation function, instead of performing the pre-training and fine-tuning phases required for classical DNNs. The addressed method is applied to a benchmark bearing case study and to experimental data acquired from a delta 3D printer. The results show that its performance is satisfactory both in detection of novelties and fault diagnosis, outperforming other state-of-the-art methods. This research proposes a novel fault diagnostics method which can not only diagnose the known type of defect, but also detect unknown types of defects.

scholarly journals CNN-Based Acoustic Scene Classification System

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 371
Author(s):  
Yerin Lee ◽  
Soyoung Lim ◽  
Il-Youp Kwak
Keyword(s):  
Low Complexity ◽  
Classification Model ◽  
Weight Class ◽  
Scene Classification ◽  
Audio File ◽  
General Classification ◽  
Team Task ◽  
Real World Applications ◽  
Activation Mapping

Acoustic scene classification (ASC) categorizes an audio file based on the environment in which it has been recorded. This has long been studied in the detection and classification of acoustic scenes and events (DCASE). This presents the solution to Task 1 of the DCASE 2020 challenge submitted by the Chung-Ang University team. Task 1 addressed two challenges that ASC faces in real-world applications. One is that the audio recorded using different recording devices should be classified in general, and the other is that the model used should have low-complexity. We proposed two models to overcome the aforementioned problems. First, a more general classification model was proposed by combining the harmonic-percussive source separation (HPSS) and deltas-deltadeltas features with four different models. Second, using the same feature, depthwise separable convolution was applied to the Convolutional layer to develop a low-complexity model. Moreover, using gradient-weight class activation mapping (Grad-CAM), we investigated what part of the feature our model sees and identifies. Our proposed system ranked 9th and 7th in the competition for these two subtasks, respectively.

scholarly journals Neither a Novel Tau Proteinopathy nor an Expansion of a Phenotype: Reappraising Clinicopathology-Based Nosology

2021 ◽  
Vol 22 (14) ◽  
pp. 7292
Author(s):  
Luca Marsili ◽  
Jennifer Sharma ◽  
Alberto J. Espay ◽  
Alice Migazzi ◽  
Elhusseini Abdelghany ◽  
...  
Keyword(s):  
Spinocerebellar Ataxia Type ◽  
Niemann Pick Disease ◽  
Whole Exome ◽  
Heterozygous Variant ◽  
History Of ◽  
Ataxia Syndrome ◽  
Niemann Pick

The gold standard for classification of neurodegenerative diseases is postmortem histopathology; however, the diagnostic odyssey of this case challenges such a clinicopathologic model. We evaluated a 60-year-old woman with a 7-year history of a progressive dystonia–ataxia syndrome with supranuclear gaze palsy, suspected to represent Niemann–Pick disease Type C. Postmortem evaluation unexpectedly demonstrated neurodegeneration with 4-repeat tau deposition in a distribution diagnostic of progressive supranuclear palsy (PSP). Whole-exome sequencing revealed a new heterozygous variant in TGM6, associated with spinocerebellar ataxia type 35 (SCA35). This novel TGM6 variant reduced transglutaminase activity in vitro, suggesting it was pathogenic. This case could be interpreted as expanding: (1) the PSP phenotype to include a spinocerebellar variant; (2) SCA35 as a tau proteinopathy; or (3) TGM6 as a novel genetic variant underlying a SCA35 phenotype with PSP pathology. None of these interpretations seem adequate. We instead hypothesize that impairment in the crosslinking of tau by the TGM6-encoded transglutaminase enzyme may compromise tau functionally and structurally, leading to its aggregation in a pattern currently classified as PSP. The lessons from this case study encourage a reassessment of our clinicopathology-based nosology.

scholarly journals Natural language processing (NLP) tools in extracting biomedical concepts from research articles: a case study on autism spectrum disorder

2020 ◽  
Vol 20 (S11) ◽  
Author(s):  
Jacqueline Peng ◽  
Mengge Zhao ◽  
James Havrilla ◽  
Cong Liu ◽  
Chunhua Weng ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Clinical Manifestations ◽  
Predictive Performance ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Research Articles

Abstract Background Natural language processing (NLP) tools can facilitate the extraction of biomedical concepts from unstructured free texts, such as research articles or clinical notes. The NLP software tools CLAMP, cTAKES, and MetaMap are among the most widely used tools to extract biomedical concept entities. However, their performance in extracting disease-specific terminology from literature has not been compared extensively, especially for complex neuropsychiatric disorders with a diverse set of phenotypic and clinical manifestations. Methods We comparatively evaluated these NLP tools using autism spectrum disorder (ASD) as a case study. We collected 827 ASD-related terms based on previous literature as the benchmark list for performance evaluation. Then, we applied CLAMP, cTAKES, and MetaMap on 544 full-text articles and 20,408 abstracts from PubMed to extract ASD-related terms. We evaluated the predictive performance using precision, recall, and F1 score. Results We found that CLAMP has the best performance in terms of F1 score followed by cTAKES and then MetaMap. Our results show that CLAMP has much higher precision than cTAKES and MetaMap, while cTAKES and MetaMap have higher recall than CLAMP. Conclusion The analysis protocols used in this study can be applied to other neuropsychiatric or neurodevelopmental disorders that lack well-defined terminology sets to describe their phenotypic presentations.

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