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 ۲۱ تا ۴۰ مورد از کل ۲٬۷۸۱ مورد.
۲۱.

Analyzing Hybrid C4.5 Algorithm for Sentiment Extraction over Lexical and Semantic Interpretation(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 57 - 79

کلید واژه ها: Hybrid C4.5 Lexical Analysis Machine Learning Semantic Analysis Sentiment Analysis Social Media Data

حوزه های تخصصی:
تعداد بازدید : 370 تعداد دانلود : 68
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.
۲۲.

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 : 977 تعداد دانلود : 855
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.
۲۳.

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

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue, ۲۰۲۳ 142 - 152

کلید واژه ها: Chatbots System quality service quality Customer Satisfaction

حوزه های تخصصی:
تعداد بازدید : 941 تعداد دانلود : 342
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.
۲۴.

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

کلید واژه ها: Smart Phone IoT GPS Sensors

حوزه های تخصصی:
تعداد بازدید : 433 تعداد دانلود : 658
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.
۲۵.

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 : 755 تعداد دانلود : 292
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.
۲۶.

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 : 465 تعداد دانلود : 889
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.
۲۷.

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

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۱, ۲۰۲۲ 113 - 123

کلید واژه ها: E-Public Procurement Public Procurement Strategy Digital Procurement Government Expenditures Sustainable Inclusive Economy

حوزه های تخصصی:
تعداد بازدید : 604 تعداد دانلود : 350
The purpose of this study is to develop proposals for the introduction of ecological, digital, professional, innovation and social public procurements in the national strategy on E-Public Procurement Reform and the strategy of procurements on the company-customer level. The relevance of this study is due to the need to ensure the development of “smart”, sustainable, inclusive economy, which will help reduce unemployment, poverty, facilitate access for people with disabilities to work, create opportunities for the education of young people and adults, stimulate innovations, meet expectations of citizens, solve environmental problems, carry out digital transformations taking into consideration the best world practices. The share of public procurements in expenditures of the state budget and gross domestic product of Ukraine, the dynamics of the procurement’s participants in the B2G segment is evaluated. In Ukraine, the largest share of expenditures falls on security and social protection, however, the prosperity index in these categories is critical (“red” zone). In order to form The E-Public Procurement Strategy, the best world practices of introducing innovative, environmental and social procurement criteria should be considered. Strategic directions of public procurement, namely – ecological, digital, professional, innovation and social, which provide sustainable and inclusive development of economy, are proposed.
۲۸.

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

کلید واژه ها: پرسشنامه مدیریت دانش سبز کارشناس

حوزه های تخصصی:
تعداد بازدید : 211 تعداد دانلود : 566
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.
۲۹.

Assessment of E-Learning Readiness in the Primary Education Sector in Libya: A Case of Yefren(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue, ۲۰۲۳ 153 - 165

کلید واژه ها: Assessment E-Learning Readiness Primary Education

حوزه های تخصصی:
تعداد بازدید : 23 تعداد دانلود : 701
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.
۳۰.

Unpacking the Dynamics of Digital Entrepreneurship: Managing Work-Family Boundaries among Women Entrepreneurs(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue, ۲۰۲۳ 202 - 235

کلید واژه ها: Digital entrepreneurship Women Entrepreneurs Degrees of digitalization Work-Family Boundary management

حوزه های تخصصی:
تعداد بازدید : 770 تعداد دانلود : 440
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.
۳۱.

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 : 610 تعداد دانلود : 602
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.
۳۲.

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 : 603 تعداد دانلود : 374
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.
۳۳.

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

حوزه های تخصصی:
تعداد بازدید : 787 تعداد دانلود : 69
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.
۳۴.

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 : 795 تعداد دانلود : 852
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.
۳۵.

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 : 242 تعداد دانلود : 407
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.
۳۶.

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 : 735 تعداد دانلود : 954
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.
۳۷.

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

حوزه های تخصصی:
تعداد بازدید : 847 تعداد دانلود : 230
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.
۳۸.

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 : 136 تعداد دانلود : 355
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.
۳۹.

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, ۲۰۲۲ 135 - 162

کلید واژه ها: Forensic research Computer tools and systems cybercrime

حوزه های تخصصی:
تعداد بازدید : 441 تعداد دانلود : 475
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.
۴۰.

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 : 183 تعداد دانلود : 698
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.

پالایش نتایج جستجو

تعداد نتایج در یک صفحه:

درجه علمی

مجله

سال

زبان