With the recent growth and advancement in Information Technology, data has produced at a very high rate in a variety of fields, which have presented to users in a structured, semi-structured, and non-structured mode [1]. New technologies for storing and extracting useful information from this volume of data (big data) have needed because the discovery and extraction of useful information and knowledge from this data volume are difficult, hence, other traditional relational databases cannot meet the needs of users [2]. If you are dealing with data beyond the capabilities of existing software, you are, in fact, dealing with big data. Large data is commonly referred to as a set of data that exceeds the extent to which it can be extracted, refined, managed, and processed by standard management tools and databases. In other words, the term "big data" refers to data that is complex in terms of volume and variety; however, it is not possible to manage them with traditional tools, and therefore, they cannot extract their hidden knowledge and knowledge at predetermined times [3, 4]. Big data is, therefore, defined with three attributes of volume, velocity, and variety that are called Gartner's commentary; some scholars have in addition; IBM cited the
In computer systems, especially with the advancement of the Internet and databases, big data is increasingly expanding and is advancing exponentially [1-4]. This is mostly true in medical big data and images. Therefore, the issue of exploding data shows the concept and power of the big data. In the field of medicine, especially magnetic resonance imaging (MRI) images, the issue of big data with high data dimensions is investigated [5]. As people grow older in the community, an untreated disease would be common, which is called Alzheimer's, and it has been proven that it has no treatment, but it can be prevented from development with timely diagnosis. Alzheimer is known as the most common disease among the various causes of dementia and with each passing decade, the number of people infected with the disease is almost doubled. For this reason, timely
2010),"The moderating effect of business strategy on the relationship between operations strategy and firms' results"If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information.
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AbstractPurpose -The purpose of this paper here is to present an operational model that establishes the necessary relationship between business strategy and operations strategy. Accordingly, managers are enabled to define strategic business elements in the operations unit and align it with the business strategies. Design/methodology/approach -Data were collected from 160 companies using a combination of structured interviews and closed questionnaire. In developing the alignment model, descriptive-survey and correlation methods were used. For selecting the codes and types of alignments, a heuristic data analysis method was developed and applied. Findings -This paper concludes that alignment is significantly different in successful and unsuccessful companies. Considering their performance, 25 alignment types have been identified out of which seven types have been found appropriate for the case. Practical implications -The recommended model here is easy to use and helps managers to improve the performance of their companies by aligning their operation strategy with business strategy. Originality/value -This paper presents a model that includes the content and process of operations strategy, using top-down and resource-based approaches. This model associates alignment with organizations performance, a subject that has been considered as one of the major and challenging issues in the strategic management efforts. Overall, a new and innovative model has been proposed here for building a vertical alignment between the strategies of the firm. The proposed alignment comes in two different levels.
Abstract-Nowadays, Sales Forecasting is vital for any business in competitive atmosphere. For an accurate forecasting, correct variables should be considered. In this paper, we address these problems and a technique is proposed which combines two artificial intelligence algorithms in order to forecast future automobile sales in Saipa group which is a leading Automobile manufacturer in Iran. Anfis is used as the base technique which is combined with GA. GA is used in order to tune the Anfis results.Furthermore, sales forecasting is succeeded with annual data of years between 1990 and 2016. With this in mind, per capita income, inflation rate, housing, Importation, Currency Rate (USD), loan interest rate and automobile import tariffs are selected as effective variables in the proposed model. Finally, we compare our model with ANN model which is a well-known forecasting model.
Background: The kidneys of patients with chronic kidney disease (CKD) do not function well enough and those in end-stage renal
disease (ESRD) of CKD need hemodialysis (HD) as a common renal replacement therapy (RRT) procedure. HD requires a vascular
access (VA), and arteriovenous fistula (AVF) is the common VA choice in the world due to its very few complications. Despite the
widespread use of AVFs, some risk factors maximize AVF failure, which is accompanied by complications of the patient such as repeating
VA surgeries and hospitalization. Therefore, finding effective factors in the success of surgery is highly important and, thus, this
study aimed at measuring the effect of anastomosis angle on the success of AVF surgery.
Methods: This study evaluated the effect of conducted angle in an AVF anastomosis on AVF maturation. The images of 48 created
AVFs for CKD patients was provided over a one-year period (from May 2016 to April 2017). Cross-tab analysis was used, and significance
level was considered meaningful at p-value≤0.001. A centralized database was designed to integrate data. A method for image
processing was developed and geometrical characteristics of the vessels (such as anastomosis angle) and also the diameter of artery and
vein were measured via AutoCAD 2017 software and exported to the database along with other data.
Results: The rate of the AVF failure in the studied patients was 8.96%. The anastomosis angle ≤ 30° is preferable from the AVF status
point of view because most AVF maturation (or least AVF failure) rates are detected at this range.
Conclusion: This study was performed based on a new approach without the need to measure hemodynamic parameters. Moreover, it
signified the important role of anastomosis angle in the function of AVF, showing that the anastomosis angle ≤ 30° is a preferable
intraoperative recommendation for AVF surgery.
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