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
فیلترهای جستجو: فیلتری انتخاب نشده است.
نمایش ۱۸۱ تا ۲۰۰ مورد از کل ۲٬۹۳۵ مورد.
۱۸۱.

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

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue, ۲۰۲۳ 34 - 51
حوزه‌های تخصصی:
تعداد بازدید : ۶۹۵ تعداد دانلود : ۳۵۰
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.
۱۸۲.

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

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue, ۲۰۲۳ 72 - 91
حوزه‌های تخصصی:
تعداد بازدید : ۴۱۲ تعداد دانلود : ۲۶۷
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.
۱۸۳.

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
حوزه‌های تخصصی:
تعداد بازدید : ۳۶۱ تعداد دانلود : ۳۸۴
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.
۱۸۴.

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

نویسنده:
منبع: مدیریت دانش سازمانی سال ششم تابستان ۱۴۰۲ شماره ۲۱ 53 - 82
حوزه‌های تخصصی:
تعداد بازدید : ۳۳۶ تعداد دانلود : ۳۵۵
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.
۱۸۵.

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
حوزه‌های تخصصی:
تعداد بازدید : ۳۸۰ تعداد دانلود : ۲۶۸
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.
۱۸۶.

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
حوزه‌های تخصصی:
تعداد بازدید : ۴۸۰ تعداد دانلود : ۲۶۰
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.
۱۸۷.

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
حوزه‌های تخصصی:
تعداد بازدید : ۴۴۰ تعداد دانلود : ۲۶۰
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.
۱۸۸.

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
حوزه‌های تخصصی:
تعداد بازدید : ۳۳۳ تعداد دانلود : ۲۳۹
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.
۱۸۹.

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
حوزه‌های تخصصی:
تعداد بازدید : ۴۲۷ تعداد دانلود : ۲۴۸
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.
۱۹۰.

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
حوزه‌های تخصصی:
تعداد بازدید : ۴۶۱ تعداد دانلود : ۲۷۵
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.
۱۹۱.

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
حوزه‌های تخصصی:
تعداد بازدید : ۳۷۷ تعداد دانلود : ۲۵۷
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.
۱۹۲.

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
حوزه‌های تخصصی:
تعداد بازدید : ۴۷۵ تعداد دانلود : ۲۰۶
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.
۱۹۳.

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
حوزه‌های تخصصی:
تعداد بازدید : ۴۲۱ تعداد دانلود : ۲۰۷
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.
۱۹۴.

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
حوزه‌های تخصصی:
تعداد بازدید : ۴۷۸ تعداد دانلود : ۲۴۹
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.
۱۹۵.

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
حوزه‌های تخصصی:
تعداد بازدید : ۷۵۲ تعداد دانلود : ۳۸۲
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.
۱۹۶.

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

نویسنده:
منبع: مدیریت دانش سازمانی سال ششم تابستان ۱۴۰۲ شماره ۲۱ 11-19
حوزه‌های تخصصی:
تعداد بازدید : ۶۲۵ تعداد دانلود : ۴۷۷
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.
۱۹۷.

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
حوزه‌های تخصصی:
تعداد بازدید : ۵۰۱ تعداد دانلود : ۳۵۹
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.
۱۹۸.

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
حوزه‌های تخصصی:
تعداد بازدید : ۵۱۵ تعداد دانلود : ۳۲۸
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.
۱۹۹.

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
حوزه‌های تخصصی:
تعداد بازدید : ۵۴۴ تعداد دانلود : ۳۷۳
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.
۲۰۰.

The Influence of the Shadow Economy on the Financial Security of Ukraine in the Conditions of Informatization of Society(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۴, ۲۰۲۳ 1 - 17
حوزه‌های تخصصی:
تعداد بازدید : ۳۳۹ تعداد دانلود : ۲۳۳
The article presents the results of the analysis of the indicators of the level of the shadow economy in Ukraine in the period from 2010 to 2020. The level of shadow economy calculated on the basis of such methods as: unprofitable enterprises, monetary, population expenditures - retail trade - services and electricity was used for the analysis. The causes and consequences of shadow economic activity in Ukraine are given. The study found that the downward trend in the shadow economy persists despite the spread of the negative effects of the COVID - 19 pandemic and declining real GDP. In particular, three of the four methods used to assess the level of the shadow economy recorded a decrease in the level of the shadow economy (the method of "population expenditure - retail trade and services"; the electric method; the monetary method). At the same time, the method of enterprise losses showed an increase in the shadow economy, which is largely due to a significant deterioration in the financial situation of enterprises under the restrictions imposed to prevent the rapid spread of the coronavirus pandemic in the world and Ukraine, as well as logistical problems. The practical value of the results is determined by the fact that the conclusions and proposals can be used to more accurately and objectively calculate the level of the shadow economy, which in turn can be the basis for effective decisions to de-shadow and legalize Ukraine's economy.

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