What attracts vehicle consumers’ buying:A Saaty scale-based VIKOR (SSC-VIKOR) approach from after-sales textual perspective?

Purpose: The increasingly booming e-commerce development has stimulated vehicle consumers to express individual reviews through online forum. The purpose of this paper is to probe into the vehicle consumer consumption behavior and make recommendations for potential consumers from textual comments viewpoint. Design/methodology/approach: A big data analytic-based approach is designed to discover vehicle consumer consumption behavior from online perspective. To reduce subjectivity of expert-based approaches, a parallel Naïve Bayes approach is designed to analyze the sentiment analysis, and the Saaty scale-based (SSC) scoring rule is employed to obtain specific sentimental value of attribute class, contributing to the multi-grade sentiment classification. To achieve the intelligent recommendation for potential vehicle customers, a novel SSC-VIKOR approach is developed to prioritize vehicle brand candidates from a big data analytical viewpoint. Findings: The big data analytics argue that “cost-effectiveness” characteristic is the most important factor that vehicle consumers care, and the data mining results enable automakers to better understand consumer consumption behavior. Research limitations/implications: The case study illustrates the effectiveness of the integrated method, contributing to much more precise operations management on marketing strategy, quality improvement and intelligent recommendation. Originality/value: Researches of consumer consumption behavior are usually based on survey-based methods, and mostly previous studies about comments analysis focus on binary analysis. The hybrid SSC-VIKOR approach is developed to fill the gap from the big data perspective

Development of a fuzzy expert system for the control of glycemia in type 1 diabetic patients

The paper describes the structure and the characteristics of an expert system that allows the optimization of postprandial glycemia in type 1 diabetic patients. The expert system is able to provide patients with the number of rapid insulin units that must be taken in order to keep the blood glucose level close to the omeostatic condition in the hours following a meal

Monitoring and detection of agitation in dementia: towards real-time and big-data solutions

The changing demographic profile of the population has potentially challenging social, geopolitical, and financial consequences for individuals, families, the wider society, and governments globally. The demographic change will result in a rapidly growing elderly population with healthcare implications which importantly include Alzheimer type conditions (a leading cause of dementia). Dementia requires long term care to manage the negative behavioral symptoms which are primarily exhibited in terms of agitation and aggression as the condition develops. This paper considers the nature of dementia along with the issues and challenges implicit in its management. The Behavioral and Psychological Symptoms of Dementia (BPSD) are introduced with factors (precursors) to the onset of agitation and aggression. Independent living is considered, health monitoring and implementation in context-aware decision-support systems is discussed with consideration of data analytics. Implicit in health monitoring are technical and ethical constraints, we briefly consider these constraints with the ability to generalize to a range of medical conditions. We postulate that health monitoring offers exciting potential opportunities however the challenges lie in the effective realization of independent assisted living while meeting the ethical challenges, achieving this remains an open research question remains.Peer ReviewedPostprint (author's final draft

Big data analytics for preventive medicine

© 2019, Springer-Verlag London Ltd., part of Springer Nature. Medical data is one of the most rewarding and yet most complicated data to analyze. How can healthcare providers use modern data analytics tools and technologies to analyze and create value from complex data? Data analytics, with its promise to efficiently discover valuable pattern by analyzing large amount of unstructured, heterogeneous, non-standard and incomplete healthcare data. It does not only forecast but also helps in decision making and is increasingly noticed as breakthrough in ongoing advancement with the goal is to improve the quality of patient care and reduces the healthcare cost. The aim of this study is to provide a comprehensive and structured overview of extensive research on the advancement of data analytics methods for disease prevention. This review first introduces disease prevention and its challenges followed by traditional prevention methodologies. We summarize state-of-the-art data analytics algorithms used for classification of disease, clustering (unusually high incidence of a particular disease), anomalies detection (detection of disease) and association as well as their respective advantages, drawbacks and guidelines for selection of specific model followed by discussion on recent development and successful application of disease prevention methods. The article concludes with open research challenges and recommendations

Smart hydroponic based on nutrient film technique and multistep fuzzy logic

Automation in hydroponics is have been a great change. Research with fuzzy logic control it’s designed to add to each parameter one by one. In a way microcontroller will activate one by one relay to regulate the parameters with fuzzy logic. While parameter calibration is done, calibration is needed for the next checking if the parameter were not optimal, until its parameter optimal. Multistep fuzzy is used to counter measure the same activation of the relay. With adding real time data monitoring to the system. From test result evaluating multistep fuzzy logic method were 100% works as expected. with another testing approach for best module for sending real time data monitoring for hydroponics. From the real time data transmission method, the success of sending data is 30% from the ESP82166 and 75% of the NRF24L01 with a shortage of the NRF24L01 data loss. For the relay activation can be accommodate with dynamic programming. As for multistep fuzzy logic for hydroponic tested to reach optimal water condition for kale crops resulting in average 12.8 iterations calibration from condition where researches add water only from the start

Determination of Preference Ranking of Fast Food Companies with Analytic Hierarchy Process: An Application in Dumlupinar University

This study aimed to determine students at Dumlupınar University Faculty of Economics and Administrative Sciences International Trade and Finance of preference ranking of fast food company with Analytic Hierarchy Process (AHP). For this purpose, five criteria was determined and six fast food companies in Sera Kütahya shopping center has been discussed as an alternative. A questionnaire was presented to 169 students who determined by sampling method and selected randomly. According to the scores given by the students, the most important criteria of prefering fast food firms was product taste and freshness and less important than others was advertising. According to the Analytic Hierarchy Process results, Burger King was found as the most preferred company with a rate of 27.54% among students. Keywords: Analytic Hierarchy Process, Preference Ranking, Fast Food Companie

Land suitability assessment for wheat production using analytical hierarchy process in a semi-arid region of Central Anatolia

Rational planning of soil resources based on their capabilities are needed for the sustainable use of agricultural lands. Land suitability classification is an important evaluation tool for the management of soil resources. This study aimed to evaluate the land suitability for wheat (Triticum aestivum) cultivation using an approach that integrates multi-criteria decision making (MCDA) analysis and geographic information systems (GIS). The study area cover 21146 ha land and is located within the land consolidation area in the Çumra Plain, located in Central Anatolia of Turkey, The physical, chemical and fertility properties of the soil samples collected from 342 points in the study area were used as parameters in the wheat suitability assessment. The relative weight values of the soil parameters were determined by the Analytical Hierarchy Process (AHP). Literature and expert opinion were used in the creation of the AHP matrices and the determination of the sub-criteria. The criteria with the highest weight values or which have the highest impact on wheat growth were soil texture (0.30) and pH (0.16), while the lowest weight values were given for micro elements (0.02). Land Suitability Assessment was applied to the maps of soil variables using weighted overlay analysis in the GIS environment by using the relative weights. Thus, the suitability of the study area for wheat cultivation was mapped. The results revealed that 74% of the study area was highly suitable (S1) and 24% was moderately suitable (S2) for wheat cultivation. The coefficient of determination (R2) was 0.81, which indicated a successful prediction of the GIS-MCDA hybrid approach for wheat suitability assessment. Integration of land suitability analyzes specific to plant variety in land consolidation projects can provide a more detailed perspective on the land in the design of planning studies. © 2022 Informa UK Limited, trading as Taylor & Francis Group

Organic and conventional public food procurement for youth in Finland

Public catering in Finland has strong historical roots from the 19th century, connected with the rise of the national state, industrialisation, democracy and modern times in general. The school meal system developed hand in hand with work place meal services, and inherently the aim was to offer lateral support for workers' and pupils' activities by healthy and wholesome nutrition. The public catering had initially a strong label of welfare services and implied economical use of ingredients. Later on, the character of public service of the welfare state was emphasised, as public catering was perceived as a way to promote equality between citizens. The public meal system, and school meal system as part of it, represented not a self-evident and 'natural' developmental path, but can be seen as a result of extensive political, economic and organisational efforts, even fights. Further on, the nutritional and cultural orientations were strengthened when the public school meal system was made a statutory free service for all pupils, first in basic education, and later in secondary education. Today the Finnish welfare state meets the challenge of greying societies and decreasing labour force, and the school meal system, as all public provision systems, in confronted with the trend for increased efficiency and economical operations, including food procurement. Even within these restrictive organisational environments, there is interest in environmentally friendly food and sustainable development by public caterers, municipal officials and politicians of all parties. While the conventional meal system is the prevailing one, there are also movements towards sustainable catering in hundreds of schools around Finland, connected to Education for Sustainable Development (ESD) program. The report is produced within the project “innovative Public Organic food Procurement for Youth”, iPOPY, and will be updated and revised during the project period (2007-2010)