Designing a Novel high-speed ternary-logic multiplier using GNRFET Technology

Abstract:This paper presents a novel design of a ternary multiplierbased on graphene nanoribbon field-effect transistor(GNRFET). GNRFET, as a new material with superiorphysical and electronic properties, can be a good choiceinstead of conventional devices such as metal–oxide–semiconductor field-effect transistor (MOSFET) andCNTFET. Moreover, multiple-valued logic (MVL) canhelp to reduce area and decrease the computational stepcompared with binary logic. We proposed a ternarymultiplier with the resistors to produce ternary logic. Theproposed multiplier performances are analyzed byevaluating the delay, power, and power-delay product(PDP), with 15 nm process technologies based onGNRFET. The simulation results with HSPICEdemonstrate that the proposed design frameworkoutperforms state-of-the-art designs in circuit parameters

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts’ Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth-first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2–100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms

Study of Mapping Iran Machine Readable Cataloging (Iran MARC) Data Elements to Functional Requirements for Bibliographic Records (FRBR) Entities and Attributes

The main goal of this research is to determine mapping of Iran MARC data elements to Functional Requirement for Bibliographic Records (FRBR) model group one entities and attributes. FRBR group one entities are work, expression, manifestation and item and each one has special attributes. Therefore all fields and data elements of Iran MARC were examined via comparative method to the entities and attributes of the first group. In first segment a table was made and all of the data elements were mapped based on similar research conducted on MARC 21 by U.S Congress Library. Research findings showed that from the total of 1558 data elements that exist in Iran MARC, 531 data elements are manifestation, 73 data elements are Work y, 65 data elements are expression and 33 data elements are Item. Totally 702 data elements in Iran MARC(45.05%) have adaption capability. Among attributes of every entity, the Form of work for Work entity, language of Expression attribute for expression, Manifestation identifier attribute for Manifestation and Item identifier for item entity have the major frequency in Iran MARC structure and totally 692 data elements (44.41%) adopted this pattern

Rapid extraction of the hottest or coldest regions of medical thermographic images

Early detection of breast tumors, feet pre-ulcers diagnosing in diabetic patients, and identifying the location of pain in patients are essential to physicians. Hot or cold regions in medical thermographic images have potential to be suspicious. Hence extracting the hottest or coldest regions in the body thermographic images is an important task. Lazy snapping is an interactive image cutout algorithm that can be applied to extract the hottest or coldest regions in the body thermographic images quickly with easy detailed adjustment. The most important advantage of this technique is that it can provide the results for physicians in real time readily. In other words, it is a good interactive image segmentation algorithm since it has two basic characteristics: (1) the algorithm produces intuitive segmentation that reflects the user intent with given a certain user input and (2) the algorithm is efficient enough to provide instant visual feedback. Comparing to other methods used by the authors for segmentation of breast thermograms such as K-means, fuzzy c-means, level set, and mean shift algorithms, lazy snapping was more user-friendly and could provide instant visual feedback. In this study, twelve test cases were presented and by applying lazy snapping algorithm, the hottest or coldest regions were extracted from the corresponding body thermographic images. The time taken to see the results varied from 7 to 30 s for these twelve cases. It was concluded that lazy snapping was much faster than other methods applied by the authors such as K-means, fuzzy c-means, level set, and mean shift algorithms for segmentation. Graphical abstract Time taken to implement lazy snapping algorithm to extract suspicious regions in different presented thermograms (in seconds). In this study, ten test cases are presented that by applying lazy snapping algorithm, the hottest or coldest regions were extracted from the corresponding body thermographic images. The time taken to see the results varied from 7 to 30 s for the ten cases. It concludes lazy snapping is much faster than other methods applied by the authors.Accepted versio

Nailfold Capillaroscopy in Rheumatic Diseases : Which Parameters Should Be Evaluated?

Video nailfold capillaroscopy (NFC), considered as an extension of the widefield technique, allows a more accurate measuring andstoring of capillary data and a better defining, analyzing, and quantifying of capillary abnormalities. Capillaroscopic study is oftenperformed on the patients suspected of having microcirculation problems such as Raynaud’s phenomenon as the main indicationfor nailfold capillaroscopy. Capillaroscopic findings based on microcirculation studies can provide useful information in the fieldsof pathophysiology, differential diagnosis, and monitoring therapy. Nailfold capillaroscopy provides a vital assessment in clinicalpractices and research; for example, its reputation in the early diagnosis of systemic sclerosis is well established and it is also usedas a classification criterion in this regard. This review focuses on the manner of performing video nailfold capillaroscopy and on acommon approach for measuring capillary dimensions in fingers and toes.QC 20150903</p

Payment systems for dialysis and their effects: a scoping review

Abstract Background End stage renal disease (ESRD) is a major health concern and a large drain on healthcare resources. A wide range of payment methods are used for management of ESRD. The main aim of this study is to identify current payment methods for dialysis and their effects. Method In this scoping review Pubmed, Scopus, and Google Scholar were searched from 2000 until 2021 using appropriate search strategies. Retrieved articles were screened according to predefined inclusion criteria. Data about the study characteristics and study results were extracted by a pre-structured data extraction form; and were analyzed by a thematic analysis approach. Results Fifty-nine articles were included, the majority of them were published after 2011 (66%); all of them were from high and upper middle-income countries, especially USA (64% of papers). Fee for services, global budget, capitation (bundled) payments, and pay for performance (P4P) were the main reimbursement methods for dialysis centers; and FFS, salary, and capitation were the main methods to reimburse the nephrologists. Countries have usually used a combination of methods depending on their situations; and their methods have been further developed over time specially from the retrospective payment systems (RPS) towards the prospective payment systems (PPS) and pay for performance methods. The main effects of the RPS were undertreatment of unpaid and inexpensive services, and over treatment of payable services. The main effects of the PPS were cost saving, shifting the service cost outside the bundle, change in quality of care, risk of provider, and modality choice. Conclusion This study provides useful insights about the current payment systems for dialysis and the effects of each payment system; that might be helpful for improving the quality and efficiency of healthcare

Association between a western diet and asthma among children and adolescents

Abstract Several risk factors including environmental exposures, socioeconomic status, and dietary factors including dietary patterns have been considered for childhood Asthma. The present study tried to examine the association between a western-style pattern and the likelihood of asthma and its symptoms in Yazd, Iran. In the present cross-sectional study, dietary intakes of elementary and high-school children were obtained through a validated GAN questionnaire. The GAN questionnaire, derived from the ISAAC questionnaire was used to assess the symptoms of allergic diseases and their related risk factors. A western dietary pattern score considered 9 food groups including chicken eggs, margarine, butter, sugar, fast foods, soft drinks, snacks, sauce, and chocolate. In total 7667 children aged 10.9 ± 3.35 years were included in the current investigation. Boys with higher adherence to western dietary pattern had a higher risk of wheezing in the past 12 months (OR 1.37, 5% CI 1.01–1.87, P = 0.04) and this association was also observed in the whole population (OR 1.30, 5% CI 1.05–1.60, P = 0.01). However, after adjustment for confounders this relation did not remain significant in boys. Our results support the hypothesis that a western dietary pattern is associated with an increased risk of wheezing in the past 12 months in children with asthma. Future prospective studies are needed to confirm this finding

Prediction of type 2 diabetes mellitus using hematological factors based on machine learning approaches: a cohort study analysis

Abstract Type 2 Diabetes Mellitus (T2DM) is a significant public health problem globally. The diagnosis and management of diabetes are critical to reduce the diabetes complications including cardiovascular disease and cancer. This study was designed to assess the potential association between T2DM and routinely measured hematological parameters. This study was a subsample of 9000 adults aged 35–65 years recruited as part of Mashhad stroke and heart atherosclerotic disorder (MASHAD) cohort study. Machine learning techniques including logistic regression (LR), decision tree (DT) and bootstrap forest (BF) algorithms were applied to analyze data. All data analyses were performed using SPSS version 22 and SAS JMP Pro version 13 at a significant level of 0.05. Based on the performance indices, the BF model gave high accuracy, precision, specificity, and AUC. Previous studies suggested the positive relationship of triglyceride-glucose (TyG) index with T2DM, so we considered the association of TyG index with hematological factors. We found this association was aligned with their results regarding T2DM, except MCHC. The most effective factors in the BF model were age and WBC (white blood cell). The BF model represented a better performance to predict T2DM. Our model provides valuable information to predict T2DM like age and WBC