درخت حوزه‌های تخصصی

مدیریت دانش و IT

حوزه‌های تخصصی
ادبیات اقتصاد تاریخ تربیت بدنی جغرافیا حقوق روانشناسی زبان شناسی علم اطلاعات و دانش‌شناسی علوم اجتماعی علوم اسلامی علوم انسانی علوم تربیتی علوم سیاسی فلسفه و منطق مدیریت مطالعات زنان هنر و معماری
اخبار مدیریت تئوری های مدیریت گروههای ویژه مدیریت آموزشی مدیریت استراتژیک مدیریت بازرگانی مدیریت دانش و IT مدیریت دولتی مدیریت سازمانی و منابع انسانی مدیریت صنعتی مدیریت مالی – حسابداری نقد و بررسی کتاب
پیش بینی، اجرا و ارزیابی تکنولوژی تکنولوژی و توسعه حقوق مالکیت سرمایه گذاریهای خارجی و انتقال تکنولوژی سیستم های پشتیبانی تصمیم گیری سیستمهای خبره کلیات مدلهای انتقال تکنولوژی مدیریت دانش مدیریت فناوری اطلاعات منطق فازی و هوش مصنوعی
ترتیب بر اساس: جدیدترینپربازدید‌ترین
فیلتر های جستجو: فیلتری انتخاب نشده است.
نمایش ۴۱ تا ۶۰ مورد از کل ۲٬۷۹۴ مورد.
۴۱.

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

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۲, ۲۰۲۳ 164 - 182

کلید واژه ها: Government Public e-services bibliometric analysis Network analysis E-government Researchv

حوزه های تخصصی:
تعداد بازدید : ۵۲ تعداد دانلود : ۴۷
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.
۴۲.

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)

نویسنده:
منبع: مدیریت دانش سازمانی سال ششم تابستان ۱۴۰۲ شماره ۲۱ 21 - 52

کلید واژه ها: چابکی سازمانی سازمان های پروژه محور دفاعی مدیریت دانش نوآوری سازمانی

حوزه های تخصصی:
تعداد بازدید : ۱۰۰ تعداد دانلود : ۱۴۷
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.
۴۳.

شناسایی و اولویت بندی پیشایندهای عدم اشتراک گذاری دانش در بین کارکنان شرکت مجتمع صنعتی رفسنجان(مقاله علمی وزارت علوم)

نویسنده:
منبع: مدیریت دانش سازمانی سال ششم تابستان ۱۴۰۲ شماره ۲۱ 141 - 182

کلید واژه ها: دانش مدیریت دانش اشتراک گذاری دانش مجتمع صنعتی رفسنجان

حوزه های تخصصی:
تعداد بازدید : ۱۱۱ تعداد دانلود : ۹۰
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.
۴۴.

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

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue: EIntelligent and Security for Communication, Computing Application (ISCCA-۲۰۲۲), ۲۰۲۳ 35 - 56

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

حوزه های تخصصی:
تعداد بازدید : ۳۳ تعداد دانلود : ۲۵
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.
۴۵.

Efficient Machine Learning Algorithms in Hybrid Filtering Based Recommendation System(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۳, ۲۰۲۳ 134 - 161

کلید واژه ها: Recommender System Content-Based Filtering collaborative filtering Movie Recommendation deep learning

حوزه های تخصصی:
تعداد بازدید : ۳۸ تعداد دانلود : ۳۰
The widespread use of E-commerce websites has drastically increased the need for automatic recommendation systems with machine learning. In recent years, many ML-based recommenders and analysers have been built; however, their scope is limited to using a single filtering technique and processing with clustering-based predictions. This paper aims to provide a systematic year-wise survey and evolution of these existing recommenders and analysers in specific deep learning-based hybrid filtering categories using movie datasets. They are compared to others based on their problem analysis, learning factors, data sets, performance, and limitations. Most contributions are found with collaborative filtering using user or item similarity and deep learning for the IMDB datasets. In this direction, this paper introduces a new and efficient Hybrid Filtering based Recommendation System using Deep Learning (HFRS-DL), which includes multiple layers and stages to provide a better solution for generating recommendations.
۴۶.

F-MIM: Feature-based Masking Iterative Method to Generate the Adversarial Images against the Face Recognition Systems(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue: EIntelligent and Security for Communication, Computing Application (ISCCA-۲۰۲۲), ۲۰۲۳ 80 - 93

کلید واژه ها: Adversarial attack Black-box attack Dodging attack Face Recognition Feature based attack

حوزه های تخصصی:
تعداد بازدید : ۴۱ تعداد دانلود : ۲۲
Numerous face recognition systems employ deep learning techniques to identify individuals in public areas such as shopping malls, airports, and other high-security zones. However, adversarial attacks are susceptible to deep learning-based systems. The adversarial attacks are intentionally generated by the attacker to mislead the systems. These attacks are imperceptible to the human eye. In this paper, we proposed a feature-based masking iterative method (F-MIM) to generate the adversarial images. In this method, we utilize the features of the face to misclassify the models. The proposed approach is based on a black-box attack technique where the attacker does not have the information related to target models. In this black box attack strategy, the face landmark points are modified using the binary masking technique. In the proposed method, we have used the momentum iterative method to increase the transferability of existing attacks. The proposed method is generated using the ArcFace face recognition model that is trained on the Labeled Face in the Wild (LFW) dataset and evaluated the performance of different face recognition models namely ArcFace, MobileFace, MobileNet, CosFace and SphereFace under the dodging and impersonate attack. The F-MIM attack is outperformed in comparison to the existing attacks based on Attack Success Rate evaluation metrics and further improves the transferability.
۴۷.

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

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۲, ۲۰۲۳ 25 - 45

کلید واژه ها: Investment Pro-Technology Altman Z-Score Model Prediction Tool Sustainability

حوزه های تخصصی:
تعداد بازدید : ۵۵ تعداد دانلود : ۴۵
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.
۴۸.

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

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue: EIntelligent and Security for Communication, Computing Application (ISCCA-۲۰۲۲), ۲۰۲۳ 94 - 110

کلید واژه ها: DCNNs (Deep Convolution Neural Network) CNNs (Convolution Neural Network) Classification

حوزه های تخصصی:
تعداد بازدید : ۳۲ تعداد دانلود : ۳۱
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.
۴۹.

Forensic Research of the Computer Tools and Systems in the Fight against Cybercrime(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۱, ۲۰۲۳ 135 - 162

کلید واژه ها: Forensic research Computer tools and systems cybercrime

حوزه های تخصصی:
تعداد بازدید : ۱۵۶ تعداد دانلود : ۱۵۷
The cybersecurity in the modern world has become global, and cyber attacks are becoming more complex and large-scale. In the system of civil and criminal justice, computer forensics helps to ensure the integrity of digital evidence presented in court cases. The purpose of this study is to develop scientifically sound proposals and recommendations for the implementation of tools for forensic research of computer tools and systems in the fight against cybercrime. The relevance of this study is due to the need to implement active ways to protect and combat cybercrime. To achieve the goal of the study, methodological principles and approaches of legal science were used. It is proposed to use computer forensic methods more widely research in the fight against cybercrime.This study identifies the types of computer forensics: forensics database; electronic forensics; malware forensics; criminology of memory; mobile forensics; network forensics. The authors foundlack of a regulatory mechanism to regulate cybersecurity, capture and use of digital evidence and the regulatory framework for international cooperation. To brought need in strengthening international cooperation and in developing appropriate policies and legislative initiatives of security and network and information systems, improvement legislation in the field countering cybercrime.
۵۰.

نقش تفکر انتقادی در فرایند مدیریت دانش(مقاله علمی وزارت علوم)

نویسنده:
منبع: مدیریت دانش سازمانی سال ششم تابستان ۱۴۰۲ شماره ۲۱ 11-19

کلید واژه ها: مدیریت دانش تفکر انتقادی مرور انتقادی

حوزه های تخصصی:
تعداد بازدید : ۱۲۲ تعداد دانلود : ۱۴۷
مدیریت دانش[1] و تفکر انتقادی[2] دو پدیده گسترده و مهم برای سازمان ها و جامعه معاصر هستند و به خوبی مفاهیم مرتبط با آنها در ادبیات نظری علم مدیریت دانش و تفکر انتقادی بحث شده است. بااین حال، پیوندهای مفهومی موجود بین مدیریت دانش و تفکر انتقادی کمتر مورد تجزیه وتحلیل قرار گرفته و نقش تفکر انتقادی در فرایند مدیریت دانش به خوبی تبیین نشده است. هدف از این نوشتار، پر کردن این شکاف نظری و ارائه ارتباطات مفهومی بین مدیریت دانش و تفکر انتقادی است. تجزیه وتحلیل مفاهیم تفکر انتقادی و مدیریت دانش امکان شناسایی پیوندها را در سه بعد فراهم می کند.
۵۱.

Real-Time Deep Intelligence Analysis and Visualization of COVID-19 Using FCNN Mechanism(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue, ۲۰۲۳ 102 - 119

کلید واژه ها: DNA RNA sequence COVID-19 SARS-CoV-2 Coronavirus pandemic

حوزه های تخصصی:
تعداد بازدید : ۲۰۰ تعداد دانلود : ۱۲۶
The Analytic visualization suggests representing knowledge during a visual type that may be charts, graphs, lists, or maps. The COVID 19 detection and analysis of spreading is very important for countries. Database management with respect to virus deep analysis is a critical task to the researcher through conventional algorithms. The RNA, DNA, and biological data are helping to the bio-inspired algorithm but its implementation can be complex by software tools. Therefore, an effective technique is required to cross over the above limitations. So that covid 19 pandemic data analysis is performed through FCNN (Fully conventional Neural Network) pre-training network. The dataset is collected from social media, Kaggle, and GitHub databases. At 1st stage, the auto stack encoding process is applied later same data is processed with FCNN deep learning classifier. In this research work, covid-pandemic affects parameters like infected persons, deaths, active cases, and recovering cases. The FCNN is take care of feature extraction, training, testing, and classification. Finally using a confusion matrix accuracy of 98.34%, sensitivity 97.63%, Recall 98.26%, and F measure 98.83% had been estimated.
۵۲.

Generation of Syntax Parser on South Indian Language using Bottom-Up Parsing Technique and PCFG(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue, ۲۰۲۳ 19 - 33

کلید واژه ها: Natural Language Processing Artificial Intelligence Syntax Parser CYK Parsing Algorithm Probabilistic Context Free Grammar

حوزه های تخصصی:
تعداد بازدید : ۱۶۶ تعداد دانلود : ۹۴
In our research, we provide a statistical syntax parsing method experimented on Kannada texts, which is an official language of Karnataka, India. The dataset is downloaded from TDIL website. Using the Cocke-Younger-Kasami (CYK) parsing technique, we generated Kannada Treebank dataset from 1000 annotated sentences in the first stage. The Treebank generated in this stage contains 1000 syntactically structured sentences and it is used as input to train the syntax parser model in the second stage. We have adopted Probabilistic Context Free Grammar (PCFG) while training the parser model and extracting the Chmosky Normal Form (CNF) grammar from a Treebank dataset. The developed syntax parser model is tested on 150 raw Kannada sentences. It outputs with the most likely parse tree for each sentence and this is verified with golden Treebank. The syntax parser model generated 74.2% precision, 79.4% recall, and 75.3% F1-score respectively. The similar technique may be adopted for other low resource languages.
۵۳.

Exemplary Growth Through Online Shopping With Satisfied Consumers In Vellore District(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue, ۲۰۲۳ 92 - 101

کلید واژه ها: Consumer behavior Fondness factors Online shopping Repurchase Satisfaction and Technology development

حوزه های تخصصی:
تعداد بازدید : ۱۴۸ تعداد دانلود : ۱۰۲
The rapid emergence and evolution of technology have greatly impacted the way people live their lives. The internet has become a vital part of our daily lives. E-commerce is a type of technology development that enables customers to buy and sell products online. It is a unique form of transaction that connects people from all around the world. Today, many consumers shop for products online and present their products along with their specifications. This is becoming more prevalent. This increases the number of consumers online, which can result in a drop in growth. This is one of the main factors that a company uses to measure its success. Growing business success is revealed with retained customers. Satisfied consumers are the assets for a growing business. The study investigates the factors that influence people's decisions when it comes to buying items online. It shows that the experiences they have while shopping online can affect their decisions. The following statistical tools were applied for this study: percentage analysis, mean score with rank correlation, and t-Test. The results reveal that the factors quality, cost, product variety, uniqueness, and safety payments were highlighted as important indicators of performance and that the companies that do online businesses had to take care of their main goal as per the proposal.
۵۴.

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

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue: EIntelligent and Security for Communication, Computing Application (ISCCA-۲۰۲۲), ۲۰۲۳ 111 - 138

کلید واژه ها: Net Asset Value NAV prediction Mutual Funds N-BEATS FLANN LSTM

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تعداد بازدید : ۴۳ تعداد دانلود : ۲۶
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.
۵۵.

Informational and Analytical Systems for Forecasting the Indicators of Financial Security of the Banking System of Ukraine(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۲, ۲۰۲۳ 1 - 13

کلید واژه ها: Financial security Information–Analytical System banking system Banking Security Forecast Models Financial Stability State

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تعداد بازدید : ۴۳ تعداد دانلود : ۴۳
The article is devoted to the modern development of high technologies and computer technology greatly enhanced the development of automated banking systems of banking sector organizations and allowed the synthesis of information and communication technologies for their formation. The main purpose of the article is to select the main indicators for assessing the level of financial security of the banking system of the state and identify promising areas of its development using forecasting models. In the process of research such analytical functions have been used: polynomial, exponential, power and logarithmic. The authors believe that the information and analytical provision of the financial security of the bank is an information provision that combines, on the one hand, information work, that is, ways, means and methods of collecting the necessary information, and on the other - analytical work, which includes forms and methods of information analysis and processing, which ensures an objective assessment of the situation and the adoption of a balanced management decision. As a result, forecast models were built for each of the indicators and also, it has been found that most indicators of the banking system of Ukraine in 2021-2023 will remain at “unsatisfactory” and “critical” levels. In conclusions it was proposed to introduce measures that would be aimed at improving the reliability and stability of the banking system of Ukraine.
۵۶.

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

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۲, ۲۰۲۳ 116 - 137

کلید واژه ها: Health information technology Patient satisfaction Kano Model AHP technique QFD model

حوزه های تخصصی:
تعداد بازدید : ۴۳ تعداد دانلود : ۴۹
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.
۵۷.

State Regulation Improvement of the Military-Industrial Complex Development in Ukraine in Terms of Transition to Modern Information Technologies(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۴, ۲۰۲۳ 18 - 46

کلید واژه ها: Defense and Security of the State State Regulation military-industrial complex information technologies Scientific and Technical Potential Innovative development

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تعداد بازدید : ۴۳ تعداد دانلود : ۳۰
The military and political leadership of Ukraine considers the domestic military-industrial complex as an important component of the country's national security and defense strategy and pays special attention to increasing the efficiency of production and scientific and technical activities of defense industry enterprises and organizations. The study represents directions for improving the state regulation for the further development of the military-industrial complex in Ukraine under the conditions of the transition to modern information technologies. Proposals have been made for the formation of the organizational and economic mechanism for state regulation development of the military-industrial complex, aimed at ensuring its innovativeness, stimulating scientific and technical activity, and implementing modern information technologies systematically during the production of weapons, ammunition and military goods.
۵۸.

The Digital Transformation of Creative Industries as a Management Imperative of Information Security of Society on a Parity-Legal Basis(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۴, ۲۰۲۳ 47 - 63

کلید واژه ها: Digital Transformation Creative Industries Imperatives System-Reflexive Management Information security

حوزه های تخصصی:
تعداد بازدید : ۳۹ تعداد دانلود : ۲۶
The article defines that the composition and structure of creative industries, their branch specialization and cooperation, the scale and directions of development of industrial and other relations are determined by means of solving spatial problems and are conditioned by the level of digital transformation as imperative system-reflex management of information security of society at parity-legal principles. The process of formation of digital transformation of creative industries as an imperative of system-reflexive management of information security of society on a parity-legal basis in modern conditions today must meet globalization challenges that dictate the development of the country's economy as a whole. This should be manifested in the application of modern integration models for the formation and development of creative industries. It is substantiated that the main tasks of the strategy of financial capacity for digital transformation of creative industries as an imperative of system-reflexive management of information security of society on a parity-legal basis are to achieve balance of financial opportunities and needs of industries, efficiency of their financial relations, efficiency of processes of formation, movement, allocation and use of financial resources, rational structure of sources of financial resources, under which is possible stable financial support of digital transformation.
۵۹.

Brain Computer Interface using Genetic Algorithm with modified Genome and Phenotype Structures(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۳, ۲۰۲۳ 47 - 68

کلید واژه ها: Motor Imagery (M.I.) Genetic Algorithm (GA) Three Dimensional Population Support Vector Machine (SVM)

حوزه های تخصصی:
تعداد بازدید : ۸۹ تعداد دانلود : ۲۹
The human machine interface research in the light of modern fast computers and advanced sensors is taking new heights. The classification and processing of neural activity in the brain accessed by Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), functional Magnetic Resonance Imaging (fMRI), Electrocorticography (ECoG), EEG Electroencephalogram (EEG) etc., are peeling off new paradigms for pattern recognition in human brain-machine interaction applications. In the present paper, an effective novel scheme based upon a synergetic approach employing the Genetic Algorithm (GA), Support Vector Machine and Wavelet packet transform for motor imagery classification and optimal Channel selection is proposed. GA with SVM acting as the objective function is employed for simultaneous selection of features and channels optimally. The binary population of GA is uniquely represented in three-dimensional structure and a new cross-over operator for GA are introduced. The new modified cross-over operator is proposed for the modified three-dimensional population. The ‘data set I’ of ‘BCI Competition IV’ is taken for evaluation of the efficacy of the proposed scheme. For subject ‘a’ accuracy is 88.9 6.9 with 10 channels, for subject ‘b’ accuracy is 79.20±5.36with 11 channels, for subject ‘f’ accuracy is 90.50±3.56 with 13 channels, and for subject ‘g’ accuracy is 92.23±3.21with 12 channels. The proposed scheme outperforms in terms of classification accuracy for subjects ‘a, b, f, g’ and in terms of number of channels for subject ‘a’ and that for subject ‘b’ is same as reported earlier in literature. Therefore, proposed scheme contributes a significant development in terms of new three-dimensional representation of binary population for GA as well as significant new modification to the GA operators. The efficacy of the scheme is evident from the results presented in the paper for dataset under consideration.
۶۰.

Automated Novel Heterogeneous Meditation Tradition Classification via Optimized Chi-Squared 1DCNN Method(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue: EIntelligent and Security for Communication, Computing Application (ISCCA-۲۰۲۲), ۲۰۲۳ 1 - 22

کلید واژه ها: EEG 1DCNN Meditation Tradition Chi-Square dimension reduction

حوزه های تخصصی:
تعداد بازدید : ۳۴ تعداد دانلود : ۲۳
The realm of human-computer interaction delves deep into understanding how individuals acquire knowledge and integrate technology into their everyday lives. Among the various methods for measuring brain signals, electroencephalography (EEG) stands out for its non-invasive, portable, affordable, and highly time-sensitive capabilities. Some researchers have revealed a consistent correlation between meditation practices and changes in the EEG frequency range, observed across a wide array of meditation techniques. Furthermore, the availability of EEG datasets has facilitated research in this field. This study explores the effectiveness of the One-Dimensional Convolutional Neural Network (CNN-1D) based novel classification method, which impressively achieved an 62% training accuracy, showcasing the robustness of these models in meditation classification tasks. The proposed methodology unveiling a novel method to differentiate neural oscillations in 4 types of meditators and control. This approach analyzes an EEG dataset of highly experienced meditators practicing Vipassana (VIP), Isha Shoonya (SYN), Himalayan Yoga (HYT), and untrained control subjects (CTR) by employing chi-square, CNN, hyperparameter models for data analysis, The outcomes indicate that different meditation types exhibit distinct cognitive features, enabling effective differentiation and classification.

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