فیلترهای جستجو:
فیلتری انتخاب نشده است.
نمایش ۱۴۱ تا ۱۶۰ مورد از کل ۲٬۹۱۷ مورد.
حوزههای تخصصی:
Nowadays, many companies cannot see the digital investment that plays a main role in the IR 4.0. Therefore, this study is investigating the study of investment as plays a critical role in an analytical activity to assess the benefits and costs of an investment and can be used as an investment justification. Traditional investment appraisal uses a financial approach where the benefits and costs are quantified in a certain amount of value for money and then compared in value. Moreover, this study is revealed the fruitful outcomes because revealed the investment valuation method with NPV (Net Present Value) and ROV (Real Option Valuation). ROV is an alternative to financial valuation. Seeding from the same philosophy as Financial Option, ROV has advantages in handling the flexibility, risk, and volatility that may occur from an investment. Thus, ROV is considered more able to appreciate an investment that has these characteristics. Investment appraisal with ROV is better able to appreciate investment than traditional financial methods, as shown by ROV's NPV results in the case of marketing with Loyalty points through email communication as a digital investment that are greater than ordinary NPV. This is because ROV can appreciate flexibility in investments that have choices of investment plans in the future
Predicting Court Judgment in Criminal Cases by Text Mining Techniques(مقاله علمی وزارت علوم)
حوزههای تخصصی:
What is clear is that judges usually judge cases based on their knowledge, experience, personality, and sentiment. Due to high pressures and stress, it may be difficult for them to carefully examine documents and evidence, which leads to more subjective judgments. Legal judgment prediction with artificial intelligence algorithms can benefit judicial bodies, legal experts, and litigants as well as judges. In this research, we are looking at predicting legal sentences in drug cases involving the purchase, possession, concealment, or transportation of illicit drugs, using machine learning methods, and the effect of sentiment and emotions in case texts on predicting the severity of whipping, fines, and imprisonment. So, the text documents of 6000 Persian drug-related cases were pre-processed and then the translation of the NRC Glossary of Emotions and sentiment was used to give each item a score for positive or negative sentiment and a score for emotion. Then machine learning methods were used for modeling. BERT, TFIDF+Adaboost, and Skipgram+LSTM+CNN methods had the highest accuracy, respectively. Also, evaluation criteria were analyzed in situations where sentiment scores, emotional scores, or both were used in the prediction process along with judicial texts. Finally, it was found that the use of sentiment and emotion scores improves the accuracy of legal judgment predictions for all three types of sentences and that sentiments have a greater impact on the accuracy of legal judgment predictions than emotions
بررسی تاثیر رهبری دانش محور بر توسعه منابع انسانی با نقش میانجی رفتارهای کاری نوآورانه (مورد مطالعه: سازمان هاي دانش بنیان فعال در پارك علم فناوري لرستان)(مقاله علمی وزارت علوم)
منبع:
مدیریت دانش سازمانی سال ششم پاییز ۱۴۰۲ شماره ۲۲
21 - 48
حوزههای تخصصی:
پژوهش حاضر به بررسی تاثیر رهبری دانش محور بر توسعه منابع انسانی با نقش میانجی رفتارهای کاری نوآورانه می پردازد. این پژوهش در زمره پژوهش های کمی و همچنین از حیث فلسفه تحقیق دارای رویکرد قیاسی است. جامعه آماری این پژوهش 120 نفر از کارشناسان سازمان های دانش بنیان فعال در پارک علم فناوری لرستان هستند که با استفاده از جدول مورگان 92 نفر به روش تصادفی ساده به عنوان نمونه انتخاب شدند. ابزار گردآوری اطلاعات در این پژوهش پرسشنامه استاندارد ویتالا (2004)، شای و همکاران (2004) و جانسن (200) است که روایی و پایایی آن با استفاده از روش اعتبار محتوا و آلفای کرونباخ تایید شده است. در این پژوهش برای بررسی و آزمون فرضیه ها، رویکرد مدل سازی معادلات ساختاری و نرم افزار spss و pls به کار رفت. یافته ها نشان داد که در سطح اطمینان0/95 رهبری دانش محور تاثیر مثبت و معنادار بر توسعه منابع انسانی دارد. همچنین رهبری دانش محور تاثیر مثبت و معنادار بر رفتارهای کاری نوآورانه دارد. نتایج پژوهش مبین آن است که رفتارهای کاری نوآورانه نقش میانجی در تاثیر رهبری دانش محور بر توسعه منابع انسانی دارد
تحلیل علی هم افزایی دانش در شرکت های دانش بنیان با رویکرد تلفیقی مدل سازی ساختاری تفسیری و معادلات ساختاری (مورد مطالعه: پارک علم و فناوری یزد)(مقاله علمی وزارت علوم)
منبع:
مدیریت دانش سازمانی سال ششم پاییز ۱۴۰۲ شماره ۲۲
49 - 80
حوزههای تخصصی:
امروزه شرکت های دانش بنیان می توانند با هم افزایی دانش در مراحل ادغام و اکتساب دانش، قابلیت های پویا را در خود ایجاد و تقویت نمایند. از این رو هدف از انجام این پژوهش تحلیل و بررسی عوامل اثرگذار بر هم افزایی دانش در شرکت های دانش بنیان پارک علم و فناوری یزد است. به منظور انجام پژوهش در ابتدا عوامل تاثیرگذار بر شکل گیری هم افزایی دانش در درون شرکت های دانش بنیان شناسایی گردید. در ادامه با استفاده از رویکرد مدل سازی ساختاری تفسیری، عوامل شناسایی شده ساختاربندی شدند. به منظور اعتبارسنجی مدل مفهومی تحقیق، از رویکرد معادلات ساختاری و از نرم افزار SmartPls3 استفاده گردید جامعه آماری این پژوهش را متخصصین، خبرگان و کارکنان شرکت های دانش بنیان در پارک علم و فناوری یزد تشکیل داده اند. روش نمونه گیری در این پژوهش در بخش معادلات ساختاری، روش نمونه گیری در دسترس بوده است. در این پژوهش در بخش معادلات ساختاری، تعداد 186 پرسشنامه تکمیل و مورد تجزیه و تحلیل قرار گرفت. در سطح ششم و آغازین مدل، عامل زمینه های محیطی، در سطح پنجم عامل رهبری مدیریت و در سطح چهارم عامل فرهنگ سازمانی قرار گرفته اند. در سطح سوم مدل عوامل منابع، چشم انداز و استراتژی و سرمایه اجتماعی جای گرفته اند. در سطح دوم عوامل آموزش و تعهد کارمندان و نهایتاً در سطح پایانی عامل فناوری اطلاعات قرار گرفته اند. زمینه های دیگر نتایج این پژوهش می-توان به تأثیر آموزش و تعهد کارکنان شرکت های دانش بنیان پارک علم و فناوری یزد بر فناوری اطلاعات اشاره کرد.
Application of Grouped MCDM Technique for Ranking and Selection of Laptops in the Current Scenario of COVID-19(مقاله علمی وزارت علوم)
حوزههای تخصصی:
In the modern technological age, laptops are widely used for doing various day-to-day activities and getting updates all around us. The COVID-19 situation is playing a vital role in a dynamic shift in buyer behavior with multiple personal computing devices at home. Prioritizing and selecting appropriate laptop devices is difficult because there are several options of laptops that are available in the market, and these are equipped with the latest features to do gaming, designing, attending online classes, and performing office and other everyday tasks. There are multiple selection criteria that are complex in nature. MCDM (Multiple Criteria Decision Making) approaches can handle and analyze these complicated criteria. By using MCDM techniques, decision-making can be done to select the top-ranked alternative from among the available alternatives. This paper exhibits a group of two MCDM techniques; Best Worst Method (BWM) and Analytical Hierarchy Process (AHP), which have been used to evaluate relative weights of considered conflicting criteria such as brand, price, storage capacity, RAM, processor, weight, touch screen, Bluetooth, and screen size, and these weights are used in the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for ranking and selecting the best product of laptops.
Digital Tools of Marketing Strategies in Hotel Branding(مقاله علمی وزارت علوم)
حوزههای تخصصی:
The condition of the hotel's competitiveness is a strong brand. The introduction of digital marketing in the strategy of hotel branding creates new opportunities for hotels when interacting with guests through digital channels. The purpose of this study is to develop theoretical and practical measures to improve the effectiveness of marketing strategies in hotel branding using digital tools. To achieve the goal of the study was conducted research on targeted branding some of the largest hotel chains. The results of the analysis showed that in the process of branding at each stage the corresponding goals have achieved by means of advertising, marketing, public relations management, personnel selection, corporate culture.This study substantiates the main tools of the strategy of the Digital Marketing and Sales. The brands need to constantly monitor changes in market positions and audience sentiment using all the features and channels. The priorities should be implemented by performing key tasks, in particular such astimely measurements as far as brand experience has a positive effect on customer satisfaction and loyalty.
Energy-Efficient and Reliable Deployment of IoT Applications in a Fog Infrastructure Based on Enhanced Water Strider Algorithm(مقاله علمی وزارت علوم)
حوزههای تخصصی:
Fog computing is considered a promising solution to minimize processing and networking demands of the Internet of things (IoT) devices. In this work, a model based on the energy consumption evaluation criteria is provided to address the deployment issue in fog computing. Numerous factors, including processing loads, communication protocols, the distance between each connection of fog nodes, and the amount of traffic that is exchanged, all have an impact on the re-search system's overall energy consumption. The power consumption for implementing each com-ponent on the fog node as well as the power consumption for information exchange between the fog nodes are taken into account when calculating each fog node's energy use. Each fog node's energy consumption is closely correlated to how its resources are used, and as a result, to the average normalized resource utilization of a fog node. When the dependent components are spread across two distinct fog nodes, the transfer energy is taken into account in the computations. The sum of the energy used for transmission and the energy used for computational resources is the entire amount of energy consumed by a fog node. The goal is to reduce the energy consumption of the fog network while deploying components using a novel metaheuristic method. Therefore, this work presents an enhanced water strider algorithm (EWSA) to address the problem of deploying application components with minimum energy consumption. Simulation experiments with two scenarios have been conducted based on the proposed EWSA algorithm. The results show that the EWSA algorithm achieved better performance with 0.01364 and 0.01004 optimal energy consumption rates.
Comparative study on Functional Machine learning and Statistical Methods in Disease detection and Weed Removal for Enhanced Agricultural Yield(مقاله علمی وزارت علوم)
حوزههای تخصصی:
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.
Analyzing Hybrid C4.5 Algorithm for Sentiment Extraction over Lexical and Semantic Interpretation(مقاله علمی وزارت علوم)
حوزههای تخصصی:
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.
Unpacking the Dynamics of Digital Entrepreneurship: Managing Work-Family Boundaries among Women Entrepreneurs(مقاله علمی وزارت علوم)
حوزههای تخصصی:
The global spread of internet technology and the associated advancements are making it easier for women entrepreneurs to manage the work-family boundary. However, there is a need for more research on digital entrepreneurship (DE), especially on how different degrees of DE influence the success of work-family boundary management (WFBM). This study explores the effect of extreme, moderate, and mild pursuit of DE on women’s abilities to manage the boundary between work and family. This study uses a quantitative research method and collected data from 312 women entrepreneurs. The results show that DE enables women entrepreneurs to manage the work-family boundary. We found that with extreme DE, women are more likely to experience high levels of cross-role interruption behaviours and perceived boundary control, while with moderate DE, women experience high levels of identity centrality of work and family roles. Therefore, this study contributes to the literature on women’s DE by investigating different degrees of DE and its effects on work-family boundary management. The study also contributes to the literature on WFBM through examining the dynamics of DE in enabling women entrepreneurs to manage work-family boundaries to different extents. Therefore, this study captures the interplay between DE and managing work-family boundaries, which facilitates our understanding of women entrepreneurship and the role DE has in enabling the agentic potential of entrepreneurial actors.
Multi- Objective Fuzzy Software Release Problem with learning capacities for fault detection and correction processes(مقاله علمی وزارت علوم)
حوزههای تخصصی:
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.
Assessment of E-Learning Readiness in the Primary Education Sector in Libya: A Case of Yefren(مقاله علمی وزارت علوم)
حوزههای تخصصی:
Over the last few decades, both developed and developing countries have an increasing trend in technology but with an enormous gap, particularly in the education sector. The e-learning following institutions can achieve benefits by evaluating their e-learning readiness through up-front analysis. Moreover, several models have been introduced to measure e-learning readiness for developed countries but these are not adequate for developing countries. This paper introduced the e-learning readiness evaluation model for the developing country, Libya, by considering the primary education sector. Furthermore, this study examines the e-learning level of readiness in the staff of the primary school. The purpose of this study is to evaluate the e-learning readiness of staff by directing factors of e-learning readiness i.e. cultural readiness, content readiness, and technology readiness. To achieve this objective, this paper collects data through questionnaires, and respondents are 110 staff member of primary schools in Yefren, Libya. Therefore, the multivariate analysis shows that the e-learning readiness factors have e significant relationship with the adoption of e-learning because most teachers are well prepared and ready. Likewise, results indicate that technology is the most significant factor instead of other e-learning readiness factors. According to the views of staff, there should be more content development training required for primary school staff. Thus, the demographic structure is inadequate to enhance the e-learning but the staff is ready for e-learning. Consequently, this study emphasizes the significance of cultural readiness and its relationship with the adoption of e-learning in primary education sectors’ development in Yefren, Libya.
Exploring the Influence of Microfinance on Entrepreneurship using machine learning techniques(مقاله علمی وزارت علوم)
حوزههای تخصصی:
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.
شناسایی و اولویت بندی پیشایندهای عدم اشتراک گذاری دانش در بین کارکنان شرکت مجتمع صنعتی رفسنجان(مقاله علمی وزارت علوم)
منبع:
مدیریت دانش سازمانی سال ششم تابستان ۱۴۰۲ شماره ۲۱
141 - 182
حوزههای تخصصی:
هدف این پژوهش شناسایی و اولویت بندی پیشایندهای عدم اشتراک گذاری دانش در بین کارکنان شرکت مجتمع صنعتی رفسنجان بوده است. این پژوهش از نظر هدف، پژوهش کاربردی و بر اساس ماهیت و روش یک پژوهش توصیفی- پیمایشی می باشد. در این پژوهش ابتدا با استفاده از مطالعات کتابخانه ای عوامل شناسایی شده و در ادامه با استفاده از پرسشنامه به تائید و اولویت گذاری پرداخته شده است. خبرگان تحقیق حاضر 13 نفر بودند که به صورت غیراحتمالی انتخاب شدند و شامل مدیران و کارکنان ارشد شرکت مجتمع صنعتی رفسنجان بوده اند. با استفاده از نرم افزارهای SPSS 23 و Expert Choice به تجزیه و تحلیل داده ها پرداخته شد و از نرم افزار روش فرآیند سلسله مراتبی برای اولویت بندی عوامل استفاده شد. یافته های حاصل از داده های تحقیق نشان داد که پیشایندهای عدم اشتراک گذاری دانش عبارتند از: موانع فناورانه که دارای چهار زیرمولفه است و عدم وجود سامانه ها مهمترین زیرمولفه موثر بر عدم اشتراک گذاری دانش است. موانع سازمانی از جمله عوامل موثر دیگر است که دارای یازده زیرمولفه است و زیرمولفه عدم وجود مسئله یابی و حل مسئله موثرترین عامل بر عدم اشتراک دانش است. موانع مدیریتی نیز از جمله موانع عدم اشتراک دانش است که شامل شش زیرمولفه است و عدم حمایت از به اشتراک گذاری دانش جزو مهمترین عوامل موثر بر آن است. موانع فردی نیز از جمله موانع عدم اشتراک گذاری دانش است که شامل یازده زیرمولفه است و بی اعتمادی مهمترین زیرمولفه موثر بر عدم به اشتراک گذاری دانش شناسایی شده است. با توجه به نتایج می توان گفت که موانع فناورانه و نبود زیرساخت ها و فناوری ها مورد نیاز از جمله مهمترین عوامل موثر بر عدم اشتراک گذاری دانش است در حالی که عوامل فردی کمترین تاثیر را داشته یعنی کارکنان در عدم به اشتراک گذاری دانش کمترین تاثیر را دارند.
Range of Publications for E-Government Services: a Review and Bibliometric Analysis(مقاله علمی وزارت علوم)
حوزههای تخصصی:
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.
Exploring the Perceived online Review Credibility and Management Response Influence on Purchase Intention(مقاله علمی وزارت علوم)
حوزههای تخصصی:
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
Understanding Customer Satisfaction of Chatbots Service and System Quality in Banking Services(مقاله علمی وزارت علوم)
حوزههای تخصصی:
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.
In-Depth Analysis of Various Artificial Intelligence Techniques in Software Engineering: Experimental Study(مقاله علمی وزارت علوم)
حوزههای تخصصی:
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
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)
منبع:
مدیریت دانش سازمانی سال ششم تابستان ۱۴۰۲ شماره ۲۱
21 - 52
حوزههای تخصصی:
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.
Metaheuristic Algorithms for Optimization and Feature Selection in Cloud Data Classification Using Convolutional Neural Network(مقاله علمی وزارت علوم)
حوزههای تخصصی:
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.