ترتیب بر اساس: جدیدترینپربازدیدترین
فیلترهای جستجو: فیلتری انتخاب نشده است.
نمایش ۱۰۱ تا ۱۲۰ مورد از کل ۲٬۸۶۶ مورد.
۱۰۱.

Exploring the Influence of Microfinance on Entrepreneurship using machine learning techniques(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Microfinance Entrepreneurship Principal Component Analysis (PCM) K-means Clustering K-Nearest Neighbors (KNN) Support Vector Machine (SVM)

حوزه‌های تخصصی:
تعداد بازدید : ۱۰۵ تعداد دانلود : ۸۱
Microfinance institutions in India provide a set of financial services to the economically weaker sections. Recently, a large number of microfinance institutions have emerged in India and they have favorable impact for poverty reduction. The impact of these institutions on entrepreneurship and society, needs to be explored in greater depth. The objective of this study is to apply machine learning techniques to explore this impact. The research uses a MIX dataset for three successive years, namely 2017, 2018, and 2019. This dataset comprises eight variables centered on gross loan portfolio. Principal Component Analysis (PCM) has been applied on the sample dataset for dimensionality reduction, resulting in two main components and each component consist of fraction from eight variables. Then, the sample dataset has been labelled with the help of clustering using K-means clustering technique. Further, classification models based on K-Nearest Neighbors (KNN) algorithm and Support Vector Machine (SVM) are applied to predict the appropriate category of entrepreneurship. The experiment result shows that the machine learning techniques have been found effective and useful tools for estimating the impact of microfinance on entrepreneurship in India.
۱۰۲.

Metaheuristic Algorithms for Optimization and Feature Selection in Cloud Data Classification Using Convolutional Neural Network(مقاله علمی وزارت علوم)

کلیدواژه‌ها: feature selection Classification Cloud Computing Metaheuristic algorithm Convolution neural network

حوزه‌های تخصصی:
تعداد بازدید : ۱۲۱ تعداد دانلود : ۱۱۲
Cloud Computing has drastically simplified the management of IT resources by introducing the concept of resource pooling. It has led to a tremendous improvement in infrastructure planning. The major goals of cloud computing include maximization of computing resources with minimization of cost. But the truth is that everything has a price and cloud computing is no different. With Cloud computing there comes a number of security concerns which need to be addressed. Cloud forensics plays a vital role to address the security issues related to cloud computing by identifying, collecting and studying digital evidence in cloud environment. The aim of the research paper is to explore the concept of cloud forensic by applying optimization for feature selection before classification of data on cloud side. The data is classified as malicious and non-malicious using convolutional neural network. The proposed system makes a comparison of models with and without feature selection algorithms before applying the data to CNN. A comparison of different metaheuristics algorithms- Particle Swarm Optimization, Shuffled Frog Leap Optimization and Fire fly algorithm for feature optimization is done based on convergence rate and efficiency.
۱۰۳.

Investment Project Risk Simulation on the Use of Information Technologies as a Factor for Improving the Financial Safety of the Enterprise(مقاله علمی وزارت علوم)

نویسنده:

کلیدواژه‌ها: Financial security risk Investment Investment project Simulation Modelling information technologies

حوزه‌های تخصصی:
تعداد بازدید : ۱۰۹ تعداد دانلود : ۱۱۳
The article justified the feasibility of an investment project by analysing the performance indicators while taking into account risk and uncertainty of the use of information technologies. The impact of the above calculations of the investment project results is due to the fact that the evaluation of the investment performance depends on the projected cash flows. The purpose of the article is to assess the impact of risks on making investment decisions using information technologies in order to increase the financial security of enterprises. Methodological and practical aspects of risk modelling of the investment project were further developed, using the Monte Carlo method, which allows to construct a model by minimizing data, as well as to maximize the value of data used in the model. This model involves the use of probability theory and random number tables. The results show the distribution of probabilities of the successful project variable and the coefficient of variation of the performance indicator, allowing the investor to take uncertainty into account when making a decision.
۱۰۴.

Exploring the Perceived online Review Credibility and Management Response Influence on Purchase Intention(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Online Review Perceived Credibility Management Response purchase intention

حوزه‌های تخصصی:
تعداد بازدید : ۱۱۶ تعداد دانلود : ۱۱۴
Online reviews play a crucial role in the consumer decision-making process in the glamping industry. Some reviews are misleading; therefore, users need to identify credible reviews to form objective opinions. This study examined dimensions of perceived review credibility and its influence on purchase intention within the glamping business. Online surveys were conducted with respondents with relevant travel experiences to examine the key credibility factors. Findings identified that review length, amount of detail, writing style, and travelers’ images; as well as mixed, moderate, and two-sided reviews influence perceived review credibility. It was also found that perceived review credibility influences purchase intention; that management response impacts perceived company credibility and purchase intention; and that personalized management response is valuable for the perceived credibility and purchase intention. A revised conceptual framework was developed to demonstrate the sources of perceived credible online reviews and the role of management responses in the reviews. In addition to the theoretical contribution, this study can have practical marketing implications for businesses when creating online promotional material for their products and engaging with customers
۱۰۵.

Automatic Prediction and Identification of Smart Women Safety Wearable Device Using Dc-RFO-IoT(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Smart Phone IoT GPS Sensors

حوزه‌های تخصصی:
تعداد بازدید : ۲۵۱ تعداد دانلود : ۱۸۵
Women’s safety is very important for around the world and many anti-women safety incidents are happened in current decades. Women's criminality is on the rise in India, particularly on an hourly basis 1000 criminal cases are filed according to Indraprastha and Kannon organizations. The Internet of Things (IoT) application will assist women in difficult situations. This design with Dc-RFO-IoT has an emergency application that can be useful to provide critical thinking and suggestions to women in rescue time. When the emergency soft button is pushed, notifications are sent to registered contacts as well as to women's hotline lines with GPS and GSM. A GPS sensor is also used to transmit the position with longitude and latitude. Every one minute, the receiver sends a link to your location, updating them on your current position. The attacker may shut the victim's mouth and prevent her from requesting assistance. The speaker on this gadget generates high-frequency sound. It will raise the alarm in the surrounding area and make the attacker fearful. This IoT with deep learning application is giving accurate outcomes and measures are improved. The performance measures like accuracy 93.43%, sensitivity 92.87%, Recall 98.34%, safety ratio 97.34%, and F measure 97,89% had been improved these are outperformance the methodology and compete with present models.
۱۰۶.

Strategic Role of E-Public Procurements in the Formation of Sustainable and Inclusive Economy(مقاله علمی وزارت علوم)

کلیدواژه‌ها: E-Public Procurement Public Procurement Strategy Digital Procurement Government Expenditures Sustainable Inclusive Economy

حوزه‌های تخصصی:
تعداد بازدید : ۲۸۹ تعداد دانلود : ۲۰۱
The purpose of this study is to develop proposals for the introduction of ecological, digital, professional, innovation and social public procurements in the national strategy on E-Public Procurement Reform and the strategy of procurements on the company-customer level. The relevance of this study is due to the need to ensure the development of “smart”, sustainable, inclusive economy, which will help reduce unemployment, poverty, facilitate access for people with disabilities to work, create opportunities for the education of young people and adults, stimulate innovations, meet expectations of citizens, solve environmental problems, carry out digital transformations taking into consideration the best world practices. The share of public procurements in expenditures of the state budget and gross domestic product of Ukraine, the dynamics of the procurement’s participants in the B2G segment is evaluated. In Ukraine, the largest share of expenditures falls on security and social protection, however, the prosperity index in these categories is critical (“red” zone). In order to form The E-Public Procurement Strategy, the best world practices of introducing innovative, environmental and social procurement criteria should be considered. Strategic directions of public procurement, namely – ecological, digital, professional, innovation and social, which provide sustainable and inclusive development of economy, are proposed.
۱۰۷.

In-Depth Analysis of Various Artificial Intelligence Techniques in Software Engineering: Experimental Study(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Software Engineering Defects Prediction Artificial Intelligence ML ANN DNN CNN

حوزه‌های تخصصی:
تعداد بازدید : ۱۲۴ تعداد دانلود : ۱۲۲
In this paper, we have extended our literature survey with experimental implementation. Analyzing numerous Artificial Intelligence (AI) techniques in software engineering (SE) can help understand the field better; the outcomes will be more effective when used with it. Our manuscript shows various AI-based algorithms that include Machine learning techniques (ML), Artificial Neural Networks (ANN), Deep Neural Networks (DNN) and Convolutional Neural Networks (CNN), Natural Language Processing (NLP), Genetic Algorithms (GA) applications. Software testing using Ant Colony Optimization (ACO) approach, predicting software maintainability with Group Method of Data Handling (GMDH), Probabilistic Neural Network (PNN), and Software production with time series analysis technique. Furthermore, data is the fuel for AI-based model testing and validation techniques. We have also used NASA dataset promise repository in our script. There are various applications of AI in SE, and we have experimentally demonstrated one among them, i.e., software defect prediction using AI-based techniques. Moreover, the expected future trends have also been mentioned; these are some significant contributions to the research
۱۰۸.

هنجاریابی پرسشنامه مدیریت دانش سبز در کارشناسان وزارت ورزش و جوانان جمهوری اسلامی ایران(مقاله علمی وزارت علوم)

کلیدواژه‌ها: پرسشنامه مدیریت دانش سبز کارشناس

حوزه‌های تخصصی:
تعداد بازدید : ۱۷۸ تعداد دانلود : ۱۸۲
ترجمه، انطباق و هنجاریابی ابزارهای استاندارد، فرصت سودمندی برای آزمون کاربرد پذیری ابزارها در جوامع دیگر فراهم می آورد و یک گام اساسی در اثبات آن آزمون این مسئله است که آیا الگوی مشکلات همایندی که به وسیله ابزار در یک جامعه شناسایی شده، با الگوهای شناسایی شده توسط آن ابزار در جوامع دیگر برازش دارد. لذا هدف از انجام این پژوهش هنجاریابی پرسشنامه مدیریت دانش سبز در کارشناسان وزارت ورزش و جوانان جمهوری اسلامی ایران است. جامعه آماری این پژوهش را کارشناسان وزارت ورزش و جوانان (320=N) تشکیل دادند که از بین آنها تعداد 273 پرسشنامه به شکل نمونه گیری در دسترس جمع آوری شد. به منظور جمع آوری داده ها از پرسشنامه مدیریت دانش سبز ساخته سیمینگ و همکاران (2022) که مشتمل بر 26 سؤال بود استفاده گردید. به منظور تجزیه و تحلیل داده ها از شاخص های توصیفی و آزمون های آماری ضریب آلفای کرونباخ، ضریب امگا مک دونالد، ضریب تتا، تحلیل عاملی اکتشافی و تحلیل عاملی تأییدی در نرم افزارهای آماری SPSS، lisrel و Stata استفاده شد. نتایج نشان داد پایایی پرسشنامه (983/0=θ، 971/0=Ω، 958/0=α) می باشد. در خصوص روایی سازه و بر اساس میزان روابط و سطح معناداری، تمامی سؤالات رابطه معناداری با مؤلفه ها داشتند و توانستند پیشگوی خوبی برای عامل خود باشند. شاخ ص های نسبت X2 به df برابر با 58/2 و (RMSEA) که برابر با 075/0 بود، بنابراین مدل از برازش لازم برخوردار است. همچنین شاخص های 95/0=NFI، 95/0=CFI، 91/0=GFI، 90/0=AGFI و 96/0=IFI برازش مدل را تأیید کردند. در خصوص روابط مؤلفه ها با مفهوم مدیریت دانش سبز نتایج نشان داد که مؤلفه های ایجاد دانش، کسب دانش، ذخیره دانش، اشتراک دانش و کاربرد دانش توانستند پیشگوی خوبی برای مفهوم مورد نظر باشند و لذا تأثیر معنادار بر دانش محیط زیستی کارشناسان دارند. در نتیجه روایی درونی و بیرونی مدل "مدیریت دانش سبز" مورد تأیید قرار گرفته و می توان از این ابزار برای جمع آوری داده های مورد نیاز از سوی پژوهشگران مورد استفاده قرار گیرد.
۱۰۹.

Analyzing Hybrid C4.5 Algorithm for Sentiment Extraction over Lexical and Semantic Interpretation(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Hybrid C4.5 Lexical Analysis Machine Learning Semantic Analysis Sentiment Analysis Social Media Data

حوزه‌های تخصصی:
تعداد بازدید : ۱۱۷ تعداد دانلود : ۷۸
Internet-based social channels have turned into an important information repository for many people to get an idea about current trends and events happening around the world. As a result of Abundance of raw information on these social media platforms, it has become a crucial platform for businesses and individuals to make decisions based on social media analytics. The ever-expanding volume of online data available on the global network necessitates the use of specialized techniques and methods to effectively analyse and utilize this vast amount of information. This study's objective is to comprehend the textual information at the Lexical and Semantic level and to extract sentiments from this information in the most accurate way possible. To achieve this, the paper proposes to cluster semantically related words by evaluating their lexical similarity with respect to feature and sequence vectors. The proposed method utilizes Natural Language Processing, semantic and lexical clustering and hybrid C4.5 algorithm to extract six subcategories of emotions over three classes of sentiments based on word-based analysis of text. The proposed approach has yielded superior results with seven existing approaches in terms of parametric values, with an accuracy of 0.96, precision of 0.92, sensitivity of 0.94, and an f1-score of 0.92.
۱۱۰.

Comparative study on Functional Machine learning and Statistical Methods in Disease detection and Weed Removal for Enhanced Agricultural Yield(مقاله علمی وزارت علوم)

نویسنده:

کلیدواژه‌ها: Machine Learning Statistical Techniques Hyperspectral Data Image classification and accuracy

حوزه‌های تخصصی:
تعداد بازدید : ۱۹۸ تعداد دانلود : ۱۶۱
Agriculture is one of the essential sources of occupation and revenue in India. Conferring to existing statistics, most agriculturalists are facing severe losses due to poor farming yield. Farming activities are challenged by various environmental factors that affect agricultural productivity to a greater extent. The present farming situation is above the average of the process involves more biochemical bases for managing the diseases and other destructing facts. The foremost problems they are facing in day-to-day farming tasks are crop or plant diseases affecting productivity. Also, the growth of weeds along with field crops has been another challenge.  The technology has developed to rectify the problems using some machine learning algorithms like Random Forest algorithms, Decision trees, Naïve Bayes, KNN, K-Means clustering, Support vector machines. The result has been evaluated and observed through the performance evaluation metrics using confusion matrix, accuracy, precision, Sensitivity, specificity with the observations, research, and studies. The statistics have expressed the overall accuracy of 98% by achieving the detection of diseases in plants and by removing the weeds that ruin the growth of plants.
۱۱۱.

Understanding Customer Satisfaction of Chatbots Service and System Quality in Banking Services(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Chatbots System quality service quality Customer Satisfaction

حوزه‌های تخصصی:
تعداد بازدید : ۳۲۰ تعداد دانلود : ۲۳۸
Chatbots is a computer software powered by artificial intelligence designed to replicate human interaction. It is also possible to refer to them as digital assistants that comprehend the capacities of humans. The bot interprets the user's intent, then processes their queries and provides prompt responses. Chatbots perform their most crucial role: to analyse and detect the intent of the user's request to extract relevant entities. AI-powered chatbots were introduced to improve operational efficiency, eventually saving organisational costs. This study investigates the role of system and service quality in customer satisfaction in banking services. One hundred forty-five usable data were used for analysis. Data were analysed using the Smart PLS. The results revealed that response time, usability, adaptability, empathy and responsiveness were insignificant for customer satisfaction. The result is important as it gave the insight point of customers with regards to the new services. Business organisations may need to introduce chatbots and perhaps make some improvements from time to time to provide better services.
۱۱۲.

Bibliometric Analysis of Government Venture Capital(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Venture Capital Government Investments Innovation Entrepreneurship

حوزه‌های تخصصی:
تعداد بازدید : ۲۴۸ تعداد دانلود : ۱۹۶
The bibliometric study aims to map and expand respective knowledge by establishing connections between important actors in academic research regarding the government venture capitals (GVCs). The scope is to analyze documents published on Scopus database starting from 2011 to 2020.  Accordingly, the United States (U.S.) is the top country in all categories with China catching up. Alperovych, Quas, and Colombo are top co-authors. On the other hand, Leleux, Grilli, Lerner and Cumming are prolific authors. Articles by Grilli and Li Y are two most cited documents. Investments, venture capital, economics, public policy, and government are most co-occurrence index keywords. Research policy, venture capital, and journal of technology transfer, journal of business venturing and small business economics are top sources of cited documents. Closely associated themes with respect to the study of GVCs are government role in venture capital support, effective Innovation financing policies, performance differential, performance of portfolio companies, funding challenges and investment strategy, decision making model and critical success factors for IT startups. The analysis generated gaps and directions for future research consisting of fund’s structure and characteristics, key personnel’s work experience and network, geographic location, investment horizon, shareholding rights.
۱۱۳.

بررسی تأثیر مدیریت دانش بر چابکی سازمانی با تاکید بر نقش میانجی گری نوآوری سازمانی (نمونه پژوهش: سازمان های پروژه محور دفاعی)(مقاله علمی وزارت علوم)

کلیدواژه‌ها: چابکی سازمانی سازمان های پروژه محور دفاعی مدیریت دانش نوآوری سازمانی

حوزه‌های تخصصی:
تعداد بازدید : ۱۷۹ تعداد دانلود : ۲۲۵
چابکی سازمان های پروژه محور دفاعی در انجام پروژه های تحقیقاتی نوآورانه، به منظور افزایش سطح بازدارندگی دفاعی در مقابل تهدیدات ناشی از تولید محصولات نظامی متنوع در دنیا، ضروری می باشد. لذا پژوهش حاضر با هدف بررسی تأثیر بکارگیری مدیریت دانش برچابکی سازمانی با نقش میانجی گری نوآوری در سازمان های پروژه محور دفاعی تدوین گردیده است. این تحقیق از نوع کاربردی بوده و روش آن توصیفی از نوع همبستگی است که به شیوه پیمایشی به انجام رسیده است. جامعه آماری پژوهش را 73 واحد پژوهشی دفاعی تشکیل دادند که تلاش گردید که داده ها از کل جامعه آماری، جمع آوری و مورد تحلیل قرار گیرد. پرسشنامه های لاوسون، جیمنز، و وانگ و شریفی به ترتیب جهت اندازه گیری متغیر های مدیریت دانش، نوآوری سازمانی و چابکی سازمانی بکار گرفته شدند. جهت بررسی روایی پرسشنامه های پژوهش، نظر پنچ نفر از خبرگان اخذ و پس از انجام اصلاحات لازم، روایی صوری و محتوایی آن توسط آنها تایید گردید. همچنین ضریب آلفای کرونباخ محاسبه شده به اندازه 894/0، پایایی پرسشنامه پژوهش را تایید نمود. برای تایید مدل مفهومی پژوهش و فرضیات تحقیق، از تکنیک مدلسازی معادلات ساختاری و نرم افزار Smart-pls، استفاده شده است. یافته های این پژوهش نشان داد که بکارگیری مدیریت دانش، بر چابکی سازمان های پروژه محور دفاعی با ضریب 498/0، تاثیر مستقیم، مثبت و معناداری داشته و همچنین می تواند از طریق نوآوری سازمانی، با اثری غیرمستقیم و با ضریب363/0، چابکی سازمانی را بهبود بخشد. بنابراین سازمان های پروژه محور دفاعی می بایست بر پیاده سازی موثر مدیریت دانش تمرکز بیشتری نمایند تا از طریق تقویت نوآوری و ارتقاء سطح چابکی سازمانی بتوانند به تغییرات سریع محیط دفاعی پاسخی مناسب داده و سطح مناسبی از بازدارندگی دفاعی را ایجاد نمایند.
۱۱۴.

Range of Publications for E-Government Services: a Review and Bibliometric Analysis(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Government Public e-services bibliometric analysis Network analysis E-government Researchv

حوزه‌های تخصصی:
تعداد بازدید : ۱۳۳ تعداد دانلود : ۱۱۳
With the rapid advancement of information and communication technology (ICT), public administration has adopted the concept of e-government. The academic literature produced many studies in the field of E-government (E-GOV) services, however, there is limited research on such services from the perspective of bibliometric and Network analysis. Therefore, this study aims to present a bibliometric and network analysis of the E-government services literature review obtained from the Scopus database, published between 2011 to 2021. This study uses a five-step method including (1) defining keywords, (2) initializing search outcomes, (3) inclusion and exclusion of some elements of the initial result, (4) compiling initial data statistics, and (5) undertaking analysis of data. The analysis starts by identifying more than 4,880 published articles related to E-government services published between 2011 and 2021. The study findings revealed that the highest number of publications on the E-government Service was in 2019 (102 articles), the top contributing affiliation was Brunel University London, the leading influential country was the USA, and the top contributing Source was Electronic Government. Furthermore, Lu J. occupied the first rank in the list of the most influential authors in terms of citations, while Weerakkody V. occupied the list of the top authors with high publications 20 papers. Likewise, this study showed that there is a collaboration among some authors. This research identified four research clusters by which researchers could be encouraged to widen the research of E-government services in the future. The bibliometric and network analysis of E-government services helps to graphically display the publication's assessment over time and identify domains of current studies' interests and potential directions for further studies. Finally, this research draws a roadmap for future investigation into E-government services.
۱۱۵.

Multi- Objective Fuzzy Software Release Problem with learning capacities for fault detection and correction processes(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Software Reliability Software Reliability Growth Models Fuzzy Release Time Problem Software Development Life Cycle

حوزه‌های تخصصی:
تعداد بازدید : ۱۲۱ تعداد دانلود : ۸۷
Without utilization of computer and its related technology, modern day’s life cannot be headway. It has also transformed into an incredibly troublesome task. The genuine challenges included are shorter life cycles, cost effective and higher software quality goals. Despite these challenges the software developers have started to give cautious thought on to the procedure to develop software, testing and reliability investigation of software and to reinforce the method. Developer most fundamental decisions related to the perfect release time of Software. Software development method incorporates a piece of vulnerabilities and ambiguities. We have proposed a multi objective software release time issue under fuzzy environment using a software reliability growth model to overcome such vulnerabilities and ambiguities. Further we have discussed the fuzzy environment framework to deal with the issue. Considering model and issue, we can especially address the issue of when to release software under these conditions. Results are illustrated numerically.
۱۱۶.

Prediction of Type - I and Type –II Diabetes: A Hybrid Approach using Fuzzy Logic and Machine Learning Algorithms(مقاله علمی وزارت علوم)

کلیدواژه‌ها: diabetes Blood sugar Machine Learning Algorithm Fuzzy Logic Disease Management risk factors insulin resistance polynomial regression Support vector regression

حوزه‌های تخصصی:
تعداد بازدید : ۱۰۰ تعداد دانلود : ۸۱
Diseases like diabetes are chronic and require long-term management. Inadequate production of insulin results in high blood sugar levels. Such diseases lead to serious health issues such as heart ailments, blood vessel complaints, eye ailments, kidney function disorders, and nerve ailments. Hence, accurate assessment and management of risk factors are crucial for the onset of diabetes. Our proposed approach combines fuzzy logic & machine learning algorithms for diabetes risk prediction. Three machine learning models were trained to classify patients into two categories of diabetes (Type-I and Type-II) based on their clinical dataset collected from Katihar Medical College & Hospital and Suvadhan Lab. The polynomial regression algorithm achieved a score of 0.947, while the support vector regression algorithm with the rbf kernel achieved a score of 0.954, with a linear kernel achieved a score of 0.73. Our proposed approach performed well with respect to the conventional approaches with improved accuracy by identifying the patients at diabetes risk. In future work, we further analyze the relationship between other ignored factors which contribute to diabetes risk.
۱۱۷.

Analyzing Hospital Services Quality Using a Hybrid Approach: Evidence from Information Technology(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Health information technology Patient satisfaction Kano Model AHP technique QFD model

حوزه‌های تخصصی:
تعداد بازدید : ۱۳۸ تعداد دانلود : ۱۱۸
Hospitals are the most important part of the healthcare system. Statistics show that a significant portion of health budgets are allocated to hospitals. The continuous impact of information technology on hospitals’ performance has led to perfect competition. Accordingly, this study aimed to evaluate the quality indicators of hospital services considering information technology using a hybrid approach of the Kano model, Analytical Hierarchy Process (AHP), and Quality Function Deployment (QFD). In this regard, based on related studies, a total of 18 needs were recognized to evaluate the service quality of a hospital. The statistical population of the study consisted of patients of the hospital and due to the difficulty of access to the patient, a limited sample of 50 patients was selected. After collecting data, the identified needs were classified into three categories called basic, functional, and motivational using the Kano model, and 7 needs were set as basic needs. Then, using the AHP technique, the importance of the basic needs was calculated and considered as the input of the QFD model in the next phase. After providing some solutions based on the literature to meet these 7 needs, solutions were ranked and prioritized using the QFD model. Since the organization had limited resources, the Pareto technique was used to respond to 20% of these strategies and achieve 80% satisfaction. The results of the study showed that the hospitals can achieve 80% satisfaction by implementing the strategies of “holding ethics training courses online” and “creating team spirit and using health information technology in the hospital”, respectively.
۱۱۸.

Cucumber Leaf Disease Detection and Classification Using a Deep Convolutional Neural Network(مقاله علمی وزارت علوم)

کلیدواژه‌ها: DCNNs (Deep Convolution Neural Network) CNNs (Convolution Neural Network) Classification

حوزه‌های تخصصی:
تعداد بازدید : ۱۱۶ تعداد دانلود : ۷۵
Due to obstruction in photosynthesis, the leaves of the plants get affected by the disease. Powdery mildew is the main disease in cucumber plants which generally occurs in the middle and late stages. Cucumber plant leaves are affected by various diseases, such as powdery mildew, downy mildew and Alternaria leaf spot, which ultimately affect the photosynthesis process; that’s why it is necessary to detect diseases at the right time to prevent the loss of plants. This paper aims to identify and classify diseases of cucumber leaves at the right time using a deep convolutional neural network (DCNN). In this work, the Deep-CNN model based on disease classification is used to enhance the performance of the ResNet50 model. The proposed model generates the most accurate results for cucumber disease detection using data enhancement based on a different data set. The data augmentation method plays an important role in enhancing the characteristics of cucumber leaves. Due to the requirements of the large number of parameters and the expensive computations required to modify standard CNNs, the pytorch library was used in this work which provides a wide range of deep learning algorithms. To assess the model accuracy large quantity of four types of healthy and diseased leaves and specific parameters such as batch size and epochs were compared with various machine learning algorithms such as support vector machine method, self-organizing map, convolutional neural network and proposed method in which the proposed DCNN model gave better results.
۱۱۹.

Net Asset Value (NAV) Prediction using Dense Residual Models(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Net Asset Value NAV prediction Mutual Funds N-BEATS FLANN LSTM

حوزه‌های تخصصی:
تعداد بازدید : ۱۲۳ تعداد دانلود : ۸۵
Net Asset Value (NAV) has long been a key performance metric for mutual fund investors. Due to the considerable fluctuation in the NAV value, it is risky for investors to make investment decisions. As a result, accurate and reliable NAV forecasts can help investors make better decisions and profit. In this research, we have analysed and compared the NAV prediction performance of our proposed deep learning models, such as N-BEATS and NBSL, with the FLANN model in both univariate and multivariate settings for five Indian mutual funds for forecast periods of 15, 20, 45, 63, 126, and 252 days using RMSE, MAPE, and R2 as evaluation metrics. A large forecast horizon was chosen to assess the model's consistency, reliability, and accuracy. The result reveals that the N-BEATS model outperforms the FLANN and NBSL models in the univariate setting for all datasets and all prediction horizons. In a multivariate setting, the outcome demonstrates that the N-BEATS model outperforms the FLANN model across all datasets and prediction horizons. The result also shows that, as the number of forecast days grew, our suggested models, notably N-BEATS, maintained consistency and attained the highest R2 value throughout the longest forecast duration.
۱۲۰.

Prediction Financial Distress: The Pro-Technology Technique of Altman Z-Score Model(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Investment Pro-Technology Altman Z-Score Model Prediction Tool Sustainability

حوزه‌های تخصصی:
تعداد بازدید : ۱۳۶ تعداد دانلود : ۱۰۷
The Covid-19 outbreak has had a severe effect on the world economy. The company's business operations and profitability are damaged during the covid 19 outbreak. This deterioration is not only threatening the company’s survival position but also destroy the investor’s investment return. Therefore, it is vital to establish an effective early prediction technical method to foresee a corporate distress by a Pro-technical measurement to enhance the corporate sustainability. This study applies Altman Z-Score Model to as a Pro-Technology technique to the financial distress prediction of Malaysia’s Government Linked Plantation Companies (GLC-P) over a period of 10 years starting from 2012 to 2021. The significant contribution of the study is that the Z-Score Model provides an advanced indication tool regarding the financial stability of the respective GLC-P companies. The findings indicate that Financial Distress Prediction was dependent via in-time application of leverage, liquidity, activity, and profitability to the Altman Z-Score Model. Profitability and leverage were found to be superior prediction tool to financial distress.

پالایش نتایج جستجو

تعداد نتایج در یک صفحه:

درجه علمی

مجله

سال

زبان