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 ۱۰۱ تا ۱۲۰ مورد از کل ۲٬۸۴۳ مورد.
۱۰۱.

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 : ۷۹ تعداد دانلود : ۷۵
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.
۱۰۲.

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 : ۱۹۹ تعداد دانلود : ۱۲۲
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.
۱۰۳.

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 : ۱۷۹ تعداد دانلود : ۱۲۰
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.
۱۰۴.

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 : ۲۴۰ تعداد دانلود : ۱۵۹
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.
۱۰۵.

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 : ۶۹ تعداد دانلود : ۶۶
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.
۱۰۶.

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 : ۵۷ تعداد دانلود : ۳۹
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.
۱۰۷.

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

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

کلید واژه ها: Forensic research Computer tools and systems cybercrime

حوزه های تخصصی:
تعداد بازدید : ۱۸۷ تعداد دانلود : ۱۹۳
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.
۱۰۸.

بررسی تاثیر رفتارهای پنهان کننده دانش بر سکوت کارکنان و رفتارهای منحرف سازمانی با نقش میانجی نقض قرارداد روانشناختی (نمونه پژوهش: اداره کل امور مالیاتی مودیان بزرگ)(مقاله علمی وزارت علوم)

نویسنده:
منبع: مدیریت دانش سازمانی سال ششم تابستان ۱۴۰۲ شماره ۲۱ 83 - 140

کلید واژه ها: رفتارهای پنهان کننده دانش سکوت کارکنان رفتارهای منحرف سازمانی

حوزه های تخصصی:
تعداد بازدید : ۱۰۰ تعداد دانلود : ۱۱۶
هدف از پژوهش حاضر، بررسی تاثیر رفتارهای پنهان کننده دانش بر سکوت کارکنان و رفتارهای منحرف سازمانی با نقش میانجی نقض قرارداد روانشناختی می باشد. این پژوهش از نظر نوع هدف، کاربردی و از نظر نوع ماهیت، توصیفی- پیمایشی است. جامعه آماری پژوهش حاضر، شامل کارکنان اداره امور مالیاتی مودیان بزرگ که مشتمل بر 400 نفر می باشند که تعداد 227 نفر به روش تصادفی ساده و به روش تحلیل توان به عنوان نمونه آماری انتخاب گردیدند. جهت گردآوری اطلاعات از پرسشنامه استاندارد استفاده شده است و داده ها بوسیله تحلیل چندمتغیره مبتنی بر مدل سازی معادلات ساختاری با رویکرد کواریانس محور در بستر نرم افزار Amos ورژن 24 مورد تجزیه و تحلیل قرار گرفت. نتایج تحقیق حاکی از تایید تاثیر پنهان کاری منطقی بر سکوت تدافعی، پنهان کاری گریزان بر سکوت رابطه ای، پنهان کاری منطقی بر سکوت رابطه ای، پنهان کاری گریزان بر سکوت بی اثر، پنهان کاری منطقی بر سکوت بی اثر و سکوت تدافعی بر رفتار منحرف سازمانی، سکوت رابطه ای بر رفتار منحرف سازمانی و سکوت بی اثر بر رفتار منحرف سازمانی می باشد و همچنین نتایج حاصل از تحلیل میانجی نشان می دهد که سازه "نقض قرارداد روانشناختی" برای تمامی روابط میان ابعاد پنهان کاری و ابعاد سکوت دارای نقش میانجی است، به طوری که فرآیند میانجی گری مذکور برای روابط علی میان "پنهان کاری خاموش" و "سکوت تدافعی/ سکوت بی اثر" به صورت کامل و برای مابقی روابط به صورت جزئی است. در نهایت، از میان بیست و یک فرضیه مطروحه، هفده فرضیه مورد تائید قرار گرفت که از این بین تاثیر سکوت رابطه ای بر رفتار منحرف سازمانی از بالاترین ضریب مسیر (0.33) برخوردار است.
۱۰۹.

Implementation of Intrusion detection and prevention with Deep Learning in Cloud Computing(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue, ۲۰۲۳ 1 - 18

کلید واژه ها: IDPS (Intrusion Detection and Prevention System) Network Security

حوزه های تخصصی:
تعداد بازدید : ۱۴۳ تعداد دانلود : ۸۴
An administrator is employed to identify network security breaches in their organizations by using a Network Intrusion Detection and Prevention System (NIDPS), which is presented in this paper that can detect and preventing a wide range of well-known network attacks. It is now more important than ever to recognize different cyber-attacks and network abnormalities that build an effective intrusion detection system plays a crucial role in today's security. NSL-KDD benchmark data set is extensively used in literature, although it was created over a decade ago and will not reflect current network traffic and low-footprint attacks. Canadian Institute of Cyber security introduced a new data set, the CICIDS2017 network data set, which solved the NSL-KDD problem. With our approach, we can apply a variety of machine learning techniques like linear regression, Random Forest and ID3. The efficient IDPS is indeed implemented and tested in a network environment utilizing several machine learning methods. A model that simulates an IDS-IPS system by predicting whether a stream of network data is malicious or benign is our objective. An Enhanced ID3 is proposed in this study to identify abnormalities in network activity and classify them. For benchmark purposes, we also develop an auto encoder network, PCA, and K-Means Clustering. On CICIDS2017, a standard dataset for network intrusion, we apply Self-Taught Learning (STL), which is a deep learning approach. To compare, we looked at things like memory, Recall, Accuracy, and Precision.
۱۱۰.

Early Diagnosis of Alzheimer Disease from Mri Using Deep Learning Models(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue, ۲۰۲۳ 52 - 71

کلید واژه ها: Alzheimers disease (AD) Magnetic Resonance Imaging (MRI) Deep Learning (DL) Artificial Neural Network (ANN) and Visual Geometry Group (VGG)

حوزه های تخصصی:
تعداد بازدید : ۱۳۴ تعداد دانلود : ۷۵
On a global scale, one of the prevalent causes of dementia is Alzheimer’s disease (AD). It will cause a steady deterioration in the individual from the mild stage to the severe stage, and thus impair their capacity to finish any tasks with no aid. The diagnosis is done with the utilization of existing methods which include medical history; neuropsychological testing as well as MRI (Magnetic Resonance Imaging), a lack of sensitivity as well as precision does affect the consistency of efficient procedures. With the deep learning network’s utilization, it is possible to create a framework for detecting specific AD characteristics from the MRI images. While automatic diagnosis is done with the application of diverse machine learning techniques, the existing ones do suffer from certain constraints with regards to accuracy. Thus, this work’s key goal is to increase the classification’s accuracy through the inclusion of a pre-processing approach prior to the deep learning model. The Alzheimer's disease Neuroimaging Initiative (ADNI) database of AD patients was used to develop a deep learning approach for AD identification. In addition, this study will present ideas for Haralick features, feature extraction from Local Binary Pattern (LBP), Artificial Neural Network (ANN), and Visual Geometry Group (VGG)-19 network techniques. The results of the experiments show that the deep learners offered are more effective than other systems already in use.
۱۱۱.

Speech Enhancement using Greedy Dictionary Learning and Sparse Recovery(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Special Issue, ۲۰۲۳ 120 - 132

کلید واژه ها: Sparse representation Greedy Dictionary Learning Singular Value Decomposition Orthogonal Matching Pursuit Quantization

حوزه های تخصصی:
تعداد بازدید : ۱۲۳ تعداد دانلود : ۹۲
Most real-time speech signals are frequently disrupted by noise such as traffic, babbling, and background noises, among other things. The goal of speech denoising is to extract the clean speech signal from as many distorted components as possible. For speech denoising, many researchers worked on sparse representation and dictionary learning algorithms. These algorithms, however, have many disadvantages, including being overcomplete, computationally expensive, and susceptible to orthogonality restrictions, as well as a lack of arithmetic precision due to the usage of double-precision. We propose a greedy technique for dictionary learning with sparse representation to overcome these concerns. In this technique, the input signal's singular value decomposition is used to exploit orthogonality, and here the ℓ1-ℓ2 norm is employed to obtain sparsity to learn the dictionary. It improves dictionary learning by overcoming the orthogonality constraint, the three-sigma rule-based number of iterations, and the overcomplete nature. And this technique has resulted in improved performance as well as reduced computing complexity. With a bit-precision of Q7 fixed-point arithmetic, this approach is also used in resource-constrained embedded systems, and the performance is considerably better than other algorithms. The greedy approach outperforms the other two in terms of SNR, Short-Time Objective Intelligibility, and computing time.
۱۱۲.

بررسی نقش مدیریت ارتباط با مشتری در رابطه بین مدیریت دانش مشتری و توسعه محصول جدید (نمونه پژوهش: شرکتهای صنعتی فعال در بخش پلاستیک)(مقاله علمی وزارت علوم)

نویسنده:
منبع: مدیریت دانش سازمانی سال ششم پاییز ۱۴۰۲ شماره ۲۲ 81 - 122

کلید واژه ها: توسعه محصول جدید دانش مشتری مدیریت ارتباط با مشتری مدیریت دانش مشتری

حوزه های تخصصی:
تعداد بازدید : ۱۲۴ تعداد دانلود : ۱۲۰
در این پژوهش تلاش شده است تا تاثیر مدیریت ارتباط با مشتری (CRM) در رابطه بین مدیریت دانش مشتری (CKM) و توسعه محصول جدید (NPD) بررسی شود. این پژوهش از نظر هدف کاربردی و از نظر ماهیت توصیفی-پیمایشی است. جامعه آماری پژوهش شرکت های فعال استان خوزستان و آذربایجان غربی می باشد که از بین آن ها 169 شرکت به عنوان نمونه انتخاب شده اند. ابزار جمع آوری داده ها پرسشنامه استاندارد بوده است. در پرسشنامه مورد استفاده ابعاد متغیر مدیریت دانش مشتری شامل دانش درباره مشتری، از مشتری، و برای مشتری به ترتیب بر اساس مقیاس های بوچنوسکا (2011)، موسی خانی، حقیقت و ترک زاده (2012)، و شامی زنجانی و نجف لو (2011) سنجیده شده است. ابعاد متغیر مدیریت ارتباط با مشتری نیز شامل اطلاعات، ارزش، و ارتباطات چندکاناله به ترتیب بر اساس مقیاس های کوهلی و جاورسکی (1990)، جارویس، و همکاران (2003)، و جیندال، و همکاران (2007) سنجیده شده است. همچنین متغیر محصول جدید بر اساس مقیاس کوپر و کلین اشمیت (1995) سنجیده شده است. جهت تجزیه و تحلیل اطلاعات از روش حداقل مربعات جزئی و نرم افزار SmartPLS استفاده شده است. بررسی پایایی داده ها با استفاده از آزمون ضریب آلفای کرونباخ و پایایی مرکب نشان داد که کمترین مقدار آلفای کرونباخ مربوط به متغیر دانش از مشتری با مقدار 775/0 و کمترین مقدار پایایی مرکب مربوط به متغیر دانش از مشتری با مقدار 843/0شده است و از این رو پایایی همه متغیرهای آزمون مورد تایید قرار گرفته شد. بررسی نتایج پژوهش نشان داد که ضریب مسیر CKM-CRM و CKM-NPD به ترتیب دارای مقادیر 833/0 و 612/0، ضریب مسیر CRM-NPD دارای مقدار 774/0، و اثر میانجی CRM بر رابطه CKM-NPD مقدار 648/0 شده است که همه موارد درسطح خطای 5 درصد معنی دار است. این یافته ها چندین پیامد مهم علمی و عملی دارند و از این رو پیشنهاد می شود شرکت ها اهمیت مدیریت ارتباط با مشتری را در فعال سازی استعداد مدیریت دانش و توسعه محصول جدید مورد توجه ویژه قرار دهند.
۱۱۳.

Digitalization of Biocluster Management on Basis of Balanced Scorecard(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۴, ۲۰۲۳ 80 - 96

کلید واژه ها: Bioeconomy digitalization Biocluster Strategic Management balanced scorecard Forecasting

حوزه های تخصصی:
تعداد بازدید : ۹۵ تعداد دانلود : ۶۶
The article is devoted to the digitalization of biocluster management on the basis of a balanced scorecard. It is proved that a biocluster, as a local model of business concentration that integrates environmentally oriented enterprises, through a combination of traditional and new technologies, resource saving and diversification of the range of environmental products, is able to satisfy various customer requests in one place and time, to ensure competitive advantages and integration into the world economic space. The concept of applying a balanced scorecard in the strategic biocluster management was formed. The technology of formation and mechanism of implementation of the balanced scorecard and digital data processing technologies into the management information system of strategic biocluster management was proposed. The digital outline of the strategic program for transferring the mission and strategy of the biocluster to the mode of effective use, capacity building and development was formed. The scorecard for strategic management of the biocluster was developed, the study of the dynamics of which allows to determine the strengths and weaknesses of the biocluster, to identify tolerance and resilience to changes in the business environment, to identify ways to achieve the set development goals.
۱۱۴.

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

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

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

حوزه های تخصصی:
تعداد بازدید : ۶۲ تعداد دانلود : ۴۸
The realm of human-computer interaction delves deep into understanding how individuals acquire knowledge and integrate technology into their everyday lives. Among the various methods for measuring brain signals, electroencephalography (EEG) stands out for its non-invasive, portable, affordable, and highly time-sensitive capabilities. Some researchers have revealed a consistent correlation between meditation practices and changes in the EEG frequency range, observed across a wide array of meditation techniques. Furthermore, the availability of EEG datasets has facilitated research in this field. This study explores the effectiveness of the One-Dimensional Convolutional Neural Network (CNN-1D) based novel classification method, which impressively achieved an 62% training accuracy, showcasing the robustness of these models in meditation classification tasks. The proposed methodology unveiling a novel method to differentiate neural oscillations in 4 types of meditators and control. This approach analyzes an EEG dataset of highly experienced meditators practicing Vipassana (VIP), Isha Shoonya (SYN), Himalayan Yoga (HYT), and untrained control subjects (CTR) by employing chi-square, CNN, hyperparameter models for data analysis, The outcomes indicate that different meditation types exhibit distinct cognitive features, enabling effective differentiation and classification.
۱۱۵.

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

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

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

حوزه های تخصصی:
تعداد بازدید : ۱۳۱ تعداد دانلود : ۴۷
The human machine interface research in the light of modern fast computers and advanced sensors is taking new heights. The classification and processing of neural activity in the brain accessed by Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), functional Magnetic Resonance Imaging (fMRI), Electrocorticography (ECoG), EEG Electroencephalogram (EEG) etc., are peeling off new paradigms for pattern recognition in human brain-machine interaction applications. In the present paper, an effective novel scheme based upon a synergetic approach employing the Genetic Algorithm (GA), Support Vector Machine and Wavelet packet transform for motor imagery classification and optimal Channel selection is proposed. GA with SVM acting as the objective function is employed for simultaneous selection of features and channels optimally. The binary population of GA is uniquely represented in three-dimensional structure and a new cross-over operator for GA are introduced. The new modified cross-over operator is proposed for the modified three-dimensional population. The ‘data set I’ of ‘BCI Competition IV’ is taken for evaluation of the efficacy of the proposed scheme. For subject ‘a’ accuracy is 88.9 6.9 with 10 channels, for subject ‘b’ accuracy is 79.20±5.36with 11 channels, for subject ‘f’ accuracy is 90.50±3.56 with 13 channels, and for subject ‘g’ accuracy is 92.23±3.21with 12 channels. The proposed scheme outperforms in terms of classification accuracy for subjects ‘a, b, f, g’ and in terms of number of channels for subject ‘a’ and that for subject ‘b’ is same as reported earlier in literature. Therefore, proposed scheme contributes a significant development in terms of new three-dimensional representation of binary population for GA as well as significant new modification to the GA operators. The efficacy of the scheme is evident from the results presented in the paper for dataset under consideration.
۱۱۶.

The Pandemic Benefits Reaped by Online Teaching Platforms: A Case study of Whitehat Junior(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۳, ۲۰۲۳ 69 - 84

کلید واژه ها: pandemic Online Education teaching Platforms parents Perspectiv COVID -19

حوزه های تخصصی:
تعداد بازدید : ۶۹ تعداد دانلود : ۶۰
Pandemic has brought all together a new environment of working and compelled all the off line educational institutions to become online educational platforms and strengthen their online resources. We need to understand online platforms as universities, institutes, schools, colleges or any educational institute which are working online and providing degrees, certificates, diplomas for several courses and programs. In different researches related to online education and Covid -19, investigations addressed student’s perspective or teachers perspective. Literature review has showed the gap in exploring the turnaround strategies inspired by the parent’s perspective for online education especially with respect to young children (Age group 8 to 12 years). Apart from literature review and analysis of secondary data from websites and search engines, qualitative research was undertaken to know about parent’s views in general about the online platforms and particularly about WHJ (White Hat Junior). The focused group discussion and the indepth interviews revealed very useful information with regard to Online educational platforms and especially WHJ in relation to Covid -19 times. Findings relate to awareness, acceptability, perception change, costs, safety issues, etc. It has brought out elaborately in this case based research, how parents expectation may impact the turnaround strategies of their wards’ online educational platforms. In different researches related to online education and Covid -19, investigations addressed student’s perspective or teacher’s perspective.
۱۱۷.

Three Machine Learning Techniques for Melanoma Cancer Detection(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۲, ۲۰۲۳ 59 - 72

کلید واژه ها: Artificial Neural Network Multi-Layer Perceptron Support vector machine K-Nearest skin cancer image processing

حوزه های تخصصی:
تعداد بازدید : ۸۲ تعداد دانلود : ۶۱
The application of machine learning technologies for cancer detection purposes are rising due to their ever-increasing accuracy. Melanoma is one of the most common types of skin cancer. Detection of melanoma in the early stages can significantly prevent illness and fetal death. The application of innovative machine learning technology is highly relevant and valuable due to medical practitioners' difficulty in early-stage diagnoses. This paper provides an open-source tutorial on the performance of an algorithm that helps to diagnose melanoma by extracting features from dermatoscopic images and their classification. First, we used a Dull-Razor preprocessing method to remove extra details such as hair. Next, histogram adjustments and lighting thresholds were used to increase the contrast and select lesion boundaries. After using a threshold, a binary-classified version of image was obtained, and the boundary of the lesion was determined. As a result, the features from skin tissue were extracted. Finally, a comparative study was conducted between three methods which are Artificial Neural Network (ANN), Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). The results show that ANN could achieve better accuracy (83.5%). In order to mitigate the biases in existing studies, the source code of this research is available at hadi-naghavipour.com/ml to serve aspiring researchers for improvement, correction and learning and provide a guideline for technology manager practitioners.
۱۱۸.

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

کلید واژه ها: Shadow Economy Financial Security of the State De-Criminalization of the Economy Legalization of the Shadow Economy Income Amnesty Informatization of society

حوزه های تخصصی:
تعداد بازدید : ۶۶ تعداد دانلود : ۴۳
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.
۱۱۹.

Analysis of Diabetes disease using Machine Learning Techniques: A Review(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۴, ۲۰۲۳ 139 - 159

کلید واژه ها: Machine Learning diabetes Classifiers Prediction Classification

حوزه های تخصصی:
تعداد بازدید : ۷۰ تعداد دانلود : ۵۸
Diabetes is a type of metabolic disorder with a high level of blood glucose. Due to the high blood sugar, the risk of heart-related diseases like heart attack and stroke got increased. The number of diabetic patients worldwide has increased significantly, and it is considered to be a major life-threatening disease worldwide. The diabetic disease cannot be cured but it can be controlled and managed by timely detection. Artificial Intelligence (AI) with Machine Learning (ML) empowers automatic early diabetes detection which is found to be much better than a manual method of diagnosis. At present, there are many research papers available on diabetes detection using ML techniques. This article aims to outline most of the literature related to ML techniques applied for diabetes prediction and summarize the related challenges. It also talks about the conclusions of the existing model and the benefits of the AI model. After a thorough screening method, 74 articles from the Scopus and Web of Science databases are selected for this study. This review article presents a clear outlook of diabetes detection which helps the researchers work in the area of automated diabetes prediction.
۱۲۰.

Economic and mathematical modeling of innovative development of the agglomeration on the basis of information technologies(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۱, ۲۰۲۳ 1 - 13

کلید واژه ها: Urban agglomeration Innovation Innovative development Region Information and Communication Technologies

حوزه های تخصصی:
تعداد بازدید : ۱۹۰ تعداد دانلود : ۱۱۴
Management of innovation processes is one of the functions of local governments and, therefore, they should be the initiators and moderators of communication between research organizations and enterprises. The program formation of agglomeration innovative development involves the creation of promoting innovation body, which allows to achieve the maximum involvement degree of all the participants in the innovation process. The article is devoted to the research of urban agglomeration innovative development, the need to create a special body or center for innovation, which will form a set and interconnected, and will be integrated into the urban agglomeration and carry out innovation and technological activities as part of research and production infrastructure. The article develops a method for predicting the effectiveness of the advancement of this body through the digital space using trend models. It is expected to receive three forecasts: optimistic, realistic and pessimistic. This will accelerate the establishment of links between the players of the regional innovation market and contribute to a qualitative change in the spatial and functional structure of urban agglomerations. The development of information and communication technologies allows to create effective systems that will stimulate the agglomerations innovative development . Therefore, the communicative activities of regional governments should be carried out through the use of information and communication technologies. Thus, the urgency of developing a methodology for assessing the increase of the innovative component of agglomeration economic development is due to the low percentage of implementation research results, low science-intensive gross value added in the Ukrainian regions, the possibility of using information and communication technologies. Increasing the number of targeted visits will simplify and speed up the process of establishing links between innovation market players at the agglomeration spatial level in both the short and long term

پالایش نتایج جستجو

تعداد نتایج در یک صفحه:

درجه علمی

مجله

سال

زبان