scholarly journals Data Mining based Prediction of Demand in Indian Market for Refurbished Electronics

2020 ◽  
Vol 2 (3) ◽  
pp. 153-159
Author(s):  
Dr. V. Suma
Keyword(s):  
Data Mining ◽  
Real World ◽  
Research Work ◽  
Analysis Data ◽  
Business Environment ◽  
Customer Behavior ◽  
The Real ◽  
Market Factors ◽  
Real World Datasets ◽  
The Impact

There has been an increasing demand in the e-commerce market for refurbished products across India during the last decade. Despite these demands, there has been very little research done in this domain. The real-world business environment, market factors and varying customer behavior of the online market are often ignored in the conventional statistical models evaluated by existing research work. In this paper, we do an extensive analysis of the Indian e-commerce market using data-mining approach for prediction of demand of refurbished electronics. The impact of the real-world factors on the demand and the variables are also analyzed. Real-world datasets from three random e-commerce websites are considered for analysis. Data accumulation, processing and validation is carried out by means of efficient algorithms. Based on the results of this analysis, it is evident that highly accurate prediction can be made with the proposed approach despite the impacts of varying customer behavior and market factors. The results of analysis are represented graphically and can be used for further analysis of the market and launch of new products.

scholarly journals Data Mining based Prediction of Demand in Indian Market for Refurbished Electronics

2020 ◽  
Vol 2 (2) ◽  
pp. 101-110
Author(s):  
Dr. Suma V.
Keyword(s):  
Data Mining ◽  
Real World ◽  
Research Work ◽  
Analysis Data ◽  
Business Environment ◽  
Customer Behavior ◽  
The Real ◽  
Market Factors ◽  
Real World Datasets ◽  
The Impact

There has been an increasing demand in the e-commerce market for refurbished products across India during the last decade. Despite these demands, there has been very little research done in this domain. The real-world business environment, market factors and varying customer behavior of the online market are often ignored in the conventional statistical models evaluated by existing research work. In this paper, we do an extensive analysis of the Indian e-commerce market using data-mining approach for prediction of demand of refurbished electronics. The impact of the real-world factors on the demand and the variables are also analyzed. Real-world datasets from three random e-commerce websites are considered for analysis. Data accumulation, processing and validation is carried out by means of efficient algorithms. Based on the results of this analysis, it is evident that highly accurate prediction can be made with the proposed approach despite the impacts of varying customer behavior and market factors. The results of analysis are represented graphically and can be used for further analysis of the market and launch of new products.

PP469 From Theory To Practice: Which Value Framework Is Applied For Onco-Hematology Therapies In Italy? A 5-year Retrospective Analysis

2020 ◽  
Vol 36 (S1) ◽  
pp. 37-37
Author(s):  
Americo Cicchetti ◽  
Rossella Di Bidino ◽  
Entela Xoxi ◽  
Irene Luccarini ◽  
Alessia Brigido
Keyword(s):  
Real World ◽  
Ad Hoc ◽  
Grey Literature ◽  
National Level ◽  
Pharmaceutical Products ◽  
European Medicines Agency ◽  
The Real ◽  
R Process ◽  
The One ◽  
The Impact

IntroductionDifferent value frameworks (VFs) have been proposed in order to translate available evidence on risk-benefit profiles of new treatments into Pricing & Reimbursement (P&R) decisions. However limited evidence is available on the impact of their implementation. It's relevant to distinguish among VFs proposed by scientific societies and providers, which usually are applicable to all treatments, and VFs elaborated by regulatory agencies and health technology assessment (HTA), which focused on specific therapeutic areas. Such heterogeneity in VFs has significant implications in terms of value dimension considered and criteria adopted to define or support a price decision.MethodsA literature research was conducted to identify already proposed or adopted VF for onco-hematology treatments. Both scientific and grey literature were investigated. Then, an ad hoc data collection was conducted for multiple myeloma; breast, prostate and urothelial cancer; and Non Small Cell Lung Cancer (NSCLC) therapies. Pharmaceutical products authorized by European Medicines Agency from January 2014 till December 2019 were identified. Primary sources of data were European Public Assessment Reports and P&R decision taken by the Italian Medicines Agency (AIFA) till September 2019.ResultsThe analysis allowed to define a taxonomy to distinguish categories of VF relevant to onco-hematological treatments. We identified the “real-world” VF that emerged given past P&R decisions taken at the Italian level. Data was collected both for clinical and economical outcomes/indicators, as well as decisions taken on innovativeness of therapies. Relevant differences emerge between the real world value framework and the one that should be applied given the normative framework of the Italian Health System.ConclusionsThe value framework that emerged from the analysis addressed issues of specific aspects of onco-hematological treatments which emerged during an ad hoc analysis conducted on treatment authorized in the last 5 years. The perspective adopted to elaborate the VF was the one of an HTA agency responsible for P&R decisions at a national level. Furthermore, comparing a real-world value framework with the one based on the general criteria defined by the national legislation, our analysis allowed identification of the most critical point of the current national P&R process in terms ofsustainability of current and future therapies as advance therapies and agnostic-tumor therapies.

scholarly journals OFCOD: On the Fly Clustering Based Outlier Detection Framework

Data ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ahmed Elmogy ◽  
Hamada Rizk ◽  
Amany M. Sarhan
Keyword(s):  
Data Mining ◽  
Image Processing ◽  
Intrusion Detection ◽  
Real Time ◽  
Outlier Detection ◽  
Real World ◽  
Medical Data ◽  
Experimental Results ◽  
Real Time Applications ◽  
Real World Datasets

In data mining, outlier detection is a major challenge as it has an important role in many applications such as medical data, image processing, fraud detection, intrusion detection, and so forth. An extensive variety of clustering based approaches have been developed to detect outliers. However they are by nature time consuming which restrict their utilization with real-time applications. Furthermore, outlier detection requests are handled one at a time, which means that each request is initiated individually with a particular set of parameters. In this paper, the first clustering based outlier detection framework, (On the Fly Clustering Based Outlier Detection (OFCOD)) is presented. OFCOD enables analysts to effectively find out outliers on time with request even within huge datasets. The proposed framework has been tested and evaluated using two real world datasets with different features and applications; one with 699 records, and another with five millions records. The experimental results show that the performance of the proposed framework outperforms other existing approaches while considering several evaluation metrics.

scholarly journals Dimension Reduction for Objects Composed of Vector Sets

2017 ◽  
Vol 27 (1) ◽  
pp. 169-180 ◽  
Author(s):  
Marton Szemenyei ◽  
Ferenc Vajda
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Feature Selection ◽  
Discriminant Analysis ◽  
Probability Distribution ◽  
Dimension Reduction ◽  
Pose Estimation ◽  
Real World ◽  
Single Object ◽  
Real World Datasets

Abstract Dimension reduction and feature selection are fundamental tools for machine learning and data mining. Most existing methods, however, assume that objects are represented by a single vectorial descriptor. In reality, some description methods assign unordered sets or graphs of vectors to a single object, where each vector is assumed to have the same number of dimensions, but is drawn from a different probability distribution. Moreover, some applications (such as pose estimation) may require the recognition of individual vectors (nodes) of an object. In such cases it is essential that the nodes within a single object remain distinguishable after dimension reduction. In this paper we propose new discriminant analysis methods that are able to satisfy two criteria at the same time: separating between classes and between the nodes of an object instance. We analyze and evaluate our methods on several different synthetic and real-world datasets.

scholarly journals The Promise of Creativity

2012 ◽  
Vol 6 (1) ◽  
pp. 389-407 ◽  
Author(s):  
Maxine E. Sprague ◽  
Jim Parsons
Keyword(s):  
Real World ◽  
Teaching And Learning ◽  
The Body ◽  
The Real ◽  
Digital World ◽  
Body Of Knowledge ◽  
Imaginative Play ◽  
A Priority ◽  
The Impact

In this paper, the authors discuss creativity and the impact it might have on teaching and learning. The authors believe that imaginative play, at all ages, helps all people (children especially) create healthy environments and spaces that expand their learning. The authors contend that teaching for imagination—which asks little more than creating and trusting an ecological space that engenders it—seldom is considered a priority. Given the emphasis on creativity in the real world and the virtual digital world, the authors believe it is important to add to the body of knowledge through continued research in this field.

scholarly journals Flawed Model Misrepresents the Impact of Anesthesiologists to Patient Safety in the Real World

2012 ◽  
Vol 117 (2) ◽  
pp. 437-438
Author(s):  
Jerry A. Cohen ◽  
Norman A. Cohen ◽  
James D. Grant ◽  
Daniel J. Cole
Keyword(s):  
Patient Safety ◽  
Real World ◽  
The Real ◽  
The Impact

scholarly journals The Role of Written Feedback in Numeracy in the Primary School Classroom

2019 ◽  
Vol 11 (2) ◽  
pp. 52 ◽  
Author(s):  
Miedzo Mutendi ◽  
Chipo Makamure
Keyword(s):  
Primary School ◽  
Learning Process ◽  
Real World ◽  
Learning Goals ◽  
Written Feedback ◽  
Classroom Performance ◽  
The Real ◽  
School Classroom ◽  
The Impact

This study seeks to establish the quality and type of feedback necessary and suitable for learners, understandable by learners and implementable in the learning process by the learners to improve progress in learning numeracy. However, although written feedback is believed to be instrumental in shaping the pupils’ classroom performance, there is less agreement on whether this is workable in the real world of the classroom or has remained an intended goal of feedback. There is limited work in literature on how pupils respond or use written feedback to improve their performance. A questionnaire was administered to a group of Year 5 students at a school in England to solicit the pupils’ perceptions of the usefulness of written feedback and the challenges that were likely to be faced in interpreting and implementing the feedback. In order to measure the impact of feedback on students’ performance, a pre-test was given, pupils’ recommendations from the questionnaire were incorporated, and a second test was given two days later. The two sets of marks were then compared. It was found that pupils find it difficult to understand written feedback at times, mainly because of unfamiliar vocabulary used in the feedback and when they do understand the language, they often find it unhelpful in achieving their learning goals. Teachers are recommended to simplify and add more detail to feedback, making it as informative as possible about what was done well and suggest improvements that could be made.

The Impact of Qualitative Research on the “Real World”

2015 ◽  
Vol 56 (4) ◽  
pp. 414-435 ◽  
Author(s):  
Leeat Granek ◽  
Ora Nakash
Keyword(s):  
Qualitative Research ◽  
Real World ◽  
The Real ◽  
The Impact

scholarly journals TO CONTROL OR NOT TO CONTROL: HOW DO WE LEARN MORE ABOUT HOW AGRONOMIC INNOVATIONS PERFORM ON FARMS?

2017 ◽  
Vol 55 (S1) ◽  
pp. 303-309 ◽  
Author(s):  
RIC COE ◽  
JOYCE NJOLOMA ◽  
FERGUS SINCLAIR
Keyword(s):  
Crop Yield ◽  
Real World ◽  
Crop Management ◽  
Maize Yield ◽  
Scaling Up ◽  
System Response ◽  
Main Concern ◽  
The Real ◽  
Important Variation ◽  
The Impact

SUMMARYOur paper ‘Loading the dice in favour of the farmer: reducing the risk of adopting agronomic innovations’ revealed mean increases but also large variation in the impact of four agroforestry practises on maize yield, as experienced by farmers in Malawi. This prompted a response from Sileshi and Akinnifesi that was critical of the data and methods used. Their main concern was that farmers did not necessarily manage crops identically in plots with and those without trees, so the yield differences that we measured may be partly caused by these differences in crop management. We argue here that it is valid and useful to look at the actual effect on crop yield of farmers having trees intercropped with maize, rather than controlling for how the crop is managed, because this is what happens in the real world. Farmers respond to having trees in their field by treating their crop differently, so this is part of the system response to having trees in fields. Attempts to eliminate this will result in measuring an artefact rather than the real impact of trees on crop yield. By doing this, we revealed important variation in the impact of trees on crop yield amongst farmers, and we argue that it is important to explore, assess and communicate to farmers and development actors the extent and implications of this variation. Understanding the contextual factors that determine who is likely to benefit most from an innovation and for whom it is less suitable can then be incorporated in scaling up, so that targeting of innovations and the appropriateness of messages given to farmers are continuously refined.

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