Search results

The purpose of this paper is to present computer‐aided simultaneous signal and noise modeling and analysis for mm‐wave field‐effect transistors (FETs) based on scattering parameters approach.

A mm‐wave FET is modeled as three active‐coupled transmission lines, and the developed wave approach is applied to this model to calculate both signal and noise performances of the device.

The measurements show a good match with the calculated data from the point of view of both signal and noise performances of the device.

This CAD‐oriented analysis and modeling can be easily applied to the mm‐wave simulators to improve the simultaneous signal and noise optimization, modeling and analysis of mm‐wave devices, especially for traveling wave transistors in which the distributed model seems to be more exact than the usual lumped models. Also the proposed routine compared to the admittance approach is conceptually more compatible with scattering representations of active and passive circuits. The developed algorithm has been applied successfully to mm‐wave MESFETs and HEMTs.

This paper proposes a novel deep learning based method towards the identification of a pistachio tree cultivar from its image.

The investigated scope of this study includes Iranian commercial pistachios (Jumbo, Long, Round and Super long) trees. Effective use of high-resolution images with standard deep models is addressed in this study. A novel image patches extraction method is also used to boost the number of samples and dataset augmentation. In the proposed method, handcrafted ORB features are used to detect and extract patches which may contain identifiable information. An innovative algorithm is proposed for searching and extracting these patches. After extracting patches from initial images, a Convolutional Neural Network, named EfficientNet-B1, was fine-tuned on it. In the testing phase, several patches were extracted from the prompted image using the ORB-based method, and the results of their prediction were consolidated. In this method, patch prediction scores were in descending order, sorted by the highest score in a list, and finally, the average of a few list tops was calculated and the final decision was made.

Examining the proposed method on the test images led to an achievement of a recognition rate of 97.2% accuracy. Investigation of decision-making in the test dataset could reveal that this method outperformed human experts.

Cultivar identification using deep learning methods, due to their high recognition speed, lack of specialist requirement, and independence from human decision-making error is considered as a breakthrough in horticultural science. Variety cultivars of pistachio trees possess variant characteristics or traits, accordingly recognising cultivars is crucial to reduce the costs, prevent damages and harvest the optimal yields.

Key performance indicators (KPIs) play a pivotal role in evaluating the level of success of an organization in achieving its business objectives. The objective of the current research is to identify and prioritize effective KPIs in branding products and construction projects, which contribute to the success of construction companies in a competitive environment.

The present research is of an inferential, descriptive and survey nature. In this study, we identified the influential key performance indicators of construction companies in branding products and construction projects for success in a competitive environment through a literature review and expert opinions. The data were collected using a questionnaire, and a combination of the one-sample t-test method with a 95% confidence level and the fuzzy multiple attribute decision-making (FMADM) method was employed for analysis.

The results indicate that the most influential key performance indicators for construction companies in branding products and construction projects for success in a competitive environment are, in order of significance, the following indices: “Marketing and Advertising,” “Financial,” “Creativity,” “Technical and Operational” and “Social and Political.”

The present research examines the importance of branding construction products and projects for the success of construction companies by improving their business objectives and utilizing key performance indicators throughout the product lifecycle (production and construction). This study provides solutions on how construction companies can increase their competitive advantage through branding and achieve long-term success in the global construction industry.

Currently, the health system is a treatment-oriented system focused on service providers. In this system, the main focus is on the health market, with little attention on insured. One way to get out of existing conditions is to empower the insured in order to involve them actively in maintaining and improving health. The paper aims to discuss these issues.

This qualitative study was done using the content analysis method. Based on the purposive sampling method and theoretical saturation criterion, 24 individuals including 12 health insurance experts and 12 insured participated in the study in 2018. The semi-structured interview method was used to collect data. Data were analyzed using MAXQDA10 software.

Having analyzed the interviews, 750 codes were obtained. These codes were categorized into two categories of “insurance experts” and “insured” and ten subcategories of “informing and educating, cost reduction, intersectional activities, expectations from the insured, services package, access to services, inability to pay costs, participation, and expectations from the insurance organization.”

This qualitative study was conducted to assess and determine the effective strategies for empowering the insured under health insurance. The results of this study are helpful to the health insurance organizations and health decision makers to detect the effective ways to develop the quality of insurance services, improve the status of insured, and increase access to health care goods and services.