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.

Exploring the Influence of Microfinance on Entrepreneurship using machine learning techniques(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 139 - 156

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

حوزه های تخصصی:
تعداد بازدید : 760 تعداد دانلود : 182
Microfinance institutions in India provide a set of financial services to the economically weaker sections. Recently, a large number of microfinance institutions have emerged in India and they have favorable impact for poverty reduction. The impact of these institutions on entrepreneurship and society, needs to be explored in greater depth. The objective of this study is to apply machine learning techniques to explore this impact. The research uses a MIX dataset for three successive years, namely 2017, 2018, and 2019. This dataset comprises eight variables centered on gross loan portfolio. Principal Component Analysis (PCM) has been applied on the sample dataset for dimensionality reduction, resulting in two main components and each component consist of fraction from eight variables. Then, the sample dataset has been labelled with the help of clustering using K-means clustering technique. Further, classification models based on K-Nearest Neighbors (KNN) algorithm and Support Vector Machine (SVM) are applied to predict the appropriate category of entrepreneurship. The experiment result shows that the machine learning techniques have been found effective and useful tools for estimating the impact of microfinance on entrepreneurship in India.
۲۲.

Factors Influencing Electronic Brand Love and E-Loyalty(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۲, ۲۰۲۳ 138 - 163

کلید واژه ها: Customer loyalty Brand Love E-trust Customer Satisfaction service quality

حوزه های تخصصی:
تعداد بازدید : 822 تعداد دانلود : 341
This research aims to evaluate the effect of consumer traits, service quality, perception-based factors, customer satisfaction, and e-trust on electronic brand love and e-loyalty. In this study, a cross-sectional survey is conducted based on the questionnaire method to collect data from a sample of 300 customers of the Digikala Website in Isfahan, Iran. Structural equation modeling (SEM) is used to test the research hypotheses. According to the results, the service quality, consumer traits, and perception-based factors significantly affected customer satisfaction. Also, e-brand love had a significant impact on e-trust and e-loyalty; e-trust significantly affected e-brand love and e-loyalty, and e-brand love had a significant impact on e-loyalty. To the best of the authors’ knowledge, this research stands among the first to evaluate the factors affecting electronic brand love and loyalty. The evaluation of brand love on loyalty demonstrated that the greater the amount of love and fascination with a brand, the higher the positive effect on consumer loyalty. Overall, managers are recommended to do their best to eliminate misunderstandings and create an interest in consumers, ultimately leading to greater customer loyalty. Managers should pay more attention to brand experience dimensions, such as sensory marketing. In this regard, creating a brand community by e-retailers is very helpful.
۲۳.

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

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue, ۲۰۲۳ 166 - 188

کلید واژه ها: Venture Capital Government Investments Innovation Entrepreneurship

حوزه های تخصصی:
تعداد بازدید : 251 تعداد دانلود : 749
The bibliometric study aims to map and expand respective knowledge by establishing connections between important actors in academic research regarding the government venture capitals (GVCs). The scope is to analyze documents published on Scopus database starting from 2011 to 2020.  Accordingly, the United States (U.S.) is the top country in all categories with China catching up. Alperovych, Quas, and Colombo are top co-authors. On the other hand, Leleux, Grilli, Lerner and Cumming are prolific authors. Articles by Grilli and Li Y are two most cited documents. Investments, venture capital, economics, public policy, and government are most co-occurrence index keywords. Research policy, venture capital, and journal of technology transfer, journal of business venturing and small business economics are top sources of cited documents. Closely associated themes with respect to the study of GVCs are government role in venture capital support, effective Innovation financing policies, performance differential, performance of portfolio companies, funding challenges and investment strategy, decision making model and critical success factors for IT startups. The analysis generated gaps and directions for future research consisting of fund’s structure and characteristics, key personnel’s work experience and network, geographic location, investment horizon, shareholding rights.
۲۴.

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 : 706 تعداد دانلود : 141
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.
۲۵.

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

کلید واژه ها: Machine Learning Statistical Techniques Hyperspectral Data Image classification and accuracy

حوزه های تخصصی:
تعداد بازدید : 932 تعداد دانلود : 99
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.
۲۶.

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 : 241 تعداد دانلود : 897
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.
۲۷.

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 : 546 تعداد دانلود : 102
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.
۲۸.

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 : 425 تعداد دانلود : 774
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.
۲۹.

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 : 55 تعداد دانلود : 98
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.
۳۰.

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 : 887 تعداد دانلود : 806
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.
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 : 528 تعداد دانلود : 107
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.

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 : 688 تعداد دانلود : 80
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.
۳۳.

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 : 905 تعداد دانلود : 999
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.
۳۴.

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 : 602 تعداد دانلود : 424
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.
۳۵.

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 : 903 تعداد دانلود : 621
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.
۳۶.

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

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تعداد بازدید : 405 تعداد دانلود : 214
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.
۳۷.

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

حوزه های تخصصی:
تعداد بازدید : 691 تعداد دانلود : 503
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.
۳۸.

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 : 544 تعداد دانلود : 606
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.
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 : 709 تعداد دانلود : 679
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.

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 : 571 تعداد دانلود : 35
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.

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