مطالب مرتبط با کلیدواژه

Artificial Intelligence


۱.

MSAS: An M-mental health care System for Automatic Stress detection(مقاله علمی وزارت علوم)

نویسنده:
منبع: مطالعات روان شناسی بالینی سال هفتم پاییز ۱۳۹۶ شماره ۲۸ 72 - 80

کلیدواژه‌ها: stress Mental Disorder M-health Sensory System Artificial Intelligence

حوزه های تخصصی:
تعداد بازدید : ۳۱۱ تعداد دانلود : ۱۸۶
The negative signs of stress can be reduced or even eliminated if they are recognized early. Hence, the level of stress needs to be continuously measured and reported especially if the stressors are frequent or continuous. M-health is a new technology to provide mobile healthcare services including mental and behavioral. It allows the healthcare specialists and patients are linked beyond their mobility and physical location while the system is connected. This paper presents the system model for an M-mental healthcare system which automatically detects stress. This system, which is called MSAS, continuously measures the stress level using wearable sensors connected to a mobile phone. The consumer gets alarm and/or the mental healthcare team receives a call if the stress level is recognized above a particular threshold. MathLab is used to simulate and evaluate MSAS. The results show that MSAS offers benefits to detect stress with an acceptable level of accuracy.
۲.

Review of “The People Vs Tech: How the Internet is Killing Democracy (and How We Save It)” by Jamie Bartlett

نویسنده:
منبع: Cyberspace Studies, Winter and Spring ۲۰۱۹, Volume ۳, Issue ۱ 105 - 107

کلیدواژه‌ها: social media Artificial Intelligence Democracy bots trolls

حوزه های تخصصی:
تعداد بازدید : ۵۰۴ تعداد دانلود : ۳۸۳
The People Vs Tech: How the Internet is Killing Democracy (and How We Save It) by Jamie Bartlett. New York: Dutton, 2018. 256 pp., £8.99 (p/b), ISBN 978-1785039065.
۳.

Genetic Engineering, Artificial Intelligence, and Natural Man: An Existential Inquiry into Being and Rights(مقاله علمی وزارت علوم)

نویسنده:
منبع: پژوهش های فلسفی پاییز ۱۳۹۸ شماره ۲۸ 181-193

کلیدواژه‌ها: Genetic Engineering Artificial Intelligence Existentialism ontology/being Rights

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تعداد بازدید : ۳۷۱ تعداد دانلود : ۱۸۲
.It is apt and usual to cogitate and ratiocinate man and human rights; it is less so about or with (other) animal rights; and much more less and lesser so with/about “plant rights” and (possibly) the rights of cloned/the artificially intelligent agents’. This condition is unfair and not ideal because man, other animals, plants, and other human manipulations (AI) from nature constitute varying levels of being; therefore, they possess varying levels of rights. Hence there is need to espouse the nature/levels of being, on the one hand, and to adumbrate the nature/types of rights and as related to being as such—which is the imperative of this article. Dwelling on the cornucopia of literature/and common biological (and other) features in nature as basis for analysis, this article, first, seeks to establish that man, other animals, plants, and other human manipulations from nature constitute varying levels of being; and second, argues that each level of being as such possesses some rights associated with it. It argues further that either all beings have rights, or they don’t. The work concludes that if one accepts that all the levels of being possess rights (accordingly including plant, cloned and AI agents), then one has certain obligation to all levels of being; but accepting either poses the most existential and ontological threat to humanity and all of nature.
۴.

Comparing Prediction Methods of Artificial Neural Networks in Extracting Financial Cycles of Tehran Stock Exchange based on Markov Switching and Ant Colony Algorithm(مقاله علمی وزارت علوم)

نویسنده:
منبع: Iranian Journal of Finance, Volume ۳, Issue ۲, Spring ۲۰۱۹ 1 - 24

کلیدواژه‌ها: Market Financial Cycles Bear Market Bull Market Artificial Intelligence Markov Switching Model

حوزه های تخصصی:
تعداد بازدید : ۳۴۴ تعداد دانلود : ۳۳۶
The stock exchange is considered to be an important establishment to finance long term projects, on one hand, and to collect savings and finance of private section. The stock exchange can be a safe and secure place to invest surplus funds to purchase corporate stocks. As recession and prosperity in this market can have a great role in stockholders` decision-making, it becomes vital to predict these cycles. In this paper, using model MSMH(4)AR(2), we extract the financial cycles of the market. Then, using the ant colony algorithm, we determine the most significant predictors and predict the market financial cycles using neural networks. The results show that the PNN model performs better in predicting the future market with respect to the criteria of mean squared error, the root mean squared error, the model accuracy and kappa coefficient.
۵.

Debt Collection Industry: Machine Learning Approach(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Money and Economy, Vol. ۱۴, No. ۴, Fall ۲۰۱۹ 453-473

کلیدواژه‌ها: Debt Collection Artificial Intelligence Machine Learning Approximate Dynamic Programming Prescriptive Analytics

حوزه های تخصصی:
تعداد بازدید : ۲۴۴ تعداد دانلود : ۱۸۹
Businesses are increasingly interested in how big data, artificial intelligence, machine learning, and predictive analytics can be used to increase revenue, lower costs, and improve their business processes. In this paper, we describe how we have developed a data-driven machine learning method to optimize the collection process for a debt collection agency. Precisely speaking, we create a framework for the data-driven scheduling of outbound calls made by debt collectors. These phone calls are used to persuade debtors to settle their debt, or to negotiate payment arrangements in case debtors are willing, but unable to repay. We determine daily which debtors should be called to maximize the amount of delinquent debt recovered in the long term, under the constraint that only a limited number of phone calls can be made each day. Our approach is to formulate a Markov decision process and, given its intractability, approximate the value function based on historical data through the use of state-of-the-art machine learning techniques. Precisely, we predict the likelihood with which a debtor in a particular state is going to settle its debt and use this as a proxy for the value function. Based on this value function approximation, we compute for each debtor the marginal value of making a call. This leads to a particularly straightforward optimization procedure, namely, we prioritize the debtors that have the highest marginal value per phone call. We believe that our optimized policy substantially outperforms the current scheduling policy that has been used in business practice for many years. Most importantly, our policy collects more debt in less time, whilst using substantially fewer resources leading to a large increase in the amount of debt collected per phone call.
۶.

Revolution of Artificial Intelligence and the Internet of Objects in the Customer Journey and the Air Sector(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۲, Issue ۲, ۲۰۲۰ (Proceedings of The ۶'th International Conference on Communication Management and Information Technology (ICCMIT'۲۰)) 59 - 69

کلیدواژه‌ها: Artificial Intelligence RFID Browses customer Airline industry IoT

حوزه های تخصصی:
تعداد بازدید : ۲۵۸ تعداد دانلود : ۱۰۹
Artificial intelligence (AI) is a discipline interested in the processes and methods that allow a machine to perform tasks related to human intelligence. It offers many opportunities related to problem solving, quick decision-making, increasing efficiency and reducing costs. Because of its so various fields of application, artificial intelligence is at the heart of the new industrial revolution. Algeria aims to present its AI strategy by 2020. In this paper, we are interested in defining AI, its potential fields of application, and in particular, its influence in the customer journey and position of RFID ( Radio-Frequency Identification ) in the chain; application in the aviation sector and its relationship to the Internet of Things are also described through examples.
۷.

Development of Robot Journalism Application: Tweets of News Content in the Turkish Language Shared by a Bot(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۲, Special Issue: The Importance of Human Computer Interaction: Challenges, Methods and Applications., ۲۰۲۰ 68 - 88

کلیدواژه‌ها: Natural language generation Artificial Intelligence Robot journalism Data journalism Newspapers

حوزه های تخصصی:
تعداد بازدید : ۳۲۵ تعداد دانلود : ۹۴
Today, news texts can be created automatically and presented to readers without human participation through technologies and methods such as big data, deep learning, and natural language generation. With this research, we have developed an application that can contribute to the literature regarding The Studies on Robot Journalism Applications with a technology-reductionist perspective. Robot journalism application named Robottan Al Haberi (the English equivalent of the application name is “get the news from the robot”) produces news text by placing weather, exchange rates, and earthquake data in certain templates. The news texts, which are produced by placing the data in appropriate spaces on the template and with a maximum length of 280 characters, are automatically shared via the Twitter account @robottanalhaber. The weather information is shared once a day, the exchange rate information is shared three times a day, and the earthquake information is shared instantly. Here, we aim to produce automatic and short news by using the available structured data by placing them in specific news templates suggesting different options or a combination of them for different situations.
۸.

Deep-Learning-CNN for Detecting Covered Faces with Niqab(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۴, ۵th International Conference of Reliable Information and Communication Technology (IRICT ۲۰۲۰), ۲۰۲۲ 114 - 123

کلیدواژه‌ها: Face-detection Object-detection Computer Vison deep learning Artificial Intelligence Convolutional Neural Network

حوزه های تخصصی:
تعداد بازدید : ۲۴۰ تعداد دانلود : ۱۲۴
Detecting occluded faces is a non-trivial problem for face detection in computer vision. This challenge becomes more difficult when the occlusion covers majority of the face. Despite the high performance of current state-of-the-art face detection algorithms, the detection of occluded and covered faces is an unsolved problem and is still worthy of study. In this paper, a deep-learning-face-detection model Niqab-Face-Detector is proposed along with context-based labeling technique for detecting unconstrained veiled faces such as faces covered with niqab. An experimental test was conducted to evaluate the performances of the proposed model using the Niqab-Face dataset. The experiment showed encouraging results and improved accuracy compared with state-of-the-art face detection algorithms
۹.

A Hybrid Artificial Intelligence Approach to Portfolio Management(مقاله علمی وزارت علوم)

نویسنده:
منبع: Iranian Journal of Finance, Volume ۶, Issue ۱, Winter ۲۰۲۲ 1 - 27

کلیدواژه‌ها: Portfolio optimization Artificial Intelligence Algorithmic Trading trading systems Genetic Algorithm Technical Analysis Neural Network

حوزه های تخصصی:
تعداد بازدید : ۳۳۸ تعداد دانلود : ۱۷۵
The tremendous advances in artificial intelligence over the past decade have led to their increasing use in financial markets. In recent years a large number of investment companies and hedge funds have been implementing algorithmic and automated trading on their trading. The speed of decision-making and execution is the most important factor in the success of institutional and individual investors in capital markets. Algorithmic trading using machine learning methods has been able to improve the performance of investors by finding investment opportunities as well as time entry and exit of trading. The purpose of this study is to achieve a better portfolio performance by designing an intelligent and fully automated trading system that investors with the support of this system, in addition to finding the best opportunities in the market, can allocate resources optimally. The present study consists of four separate steps. Respectively, tuning the parameters of technical indicators, detecting the current market regime (trending or non-trending), issuing a definite signal (buy, sell or hold) from the indicators’ signals and finally portfolio rebalancing. These 4 steps respectively are performed using genetic algorithm, fuzzy logic, artificial neural network and conventional portfolio optimization model. The results show the complete superiority of the proposed model in achieving higher returns and less risk compared to the performance of the TEDPIX and other mutual funds in the same period.
۱۰.

A Combined Model for Prediction of Financial Software Learning Rate based on the Accounting Students’ Characteristics(مقاله علمی وزارت علوم)

نویسنده:
منبع: Advances in Mathematical Finance and Application, Volume ۷, Issue ۴, Autumn ۲۰۲۲ 961 - 980

کلیدواژه‌ها: accounting software Accounting information system Artificial Intelligence Data mining

حوزه های تخصصی:
تعداد بازدید : ۲۵۴ تعداد دانلود : ۱۵۸
The accounting software is considered to be of the most critical components of accounting information system, with particular significance as of accounting and financial systems. the most important problems with accounting education systems is that students do not adequately learn the financial software required by the accounting profession, which, in turn, reduces the credibility and position of the accounting profession. That the main objective of accounting software education is to educate skilled and expert accountants to enter the accounting profession, which is considered as of the success factors of country’s economy. In this study, employ data mining techniques to investigate the accuracy, precision, and recall performance measures and to predict the rate of financial software learning based on accounting students’ emotional intelligence (EI), gender and education level. Accordingly, a machine-learning-based multivariate statistical analysis is performed on 100 Iranian accounting students. The results show that emotional intelligence has the most impact on the rate of financial software learning among the variables. Gender and education level were influential. Also, among the five algorithms, the highest precision and recall are achieved by both Decision Tree and XGBoost and are presented as the most appropriate models for the prediction rate of financial software learning.
۱۱.

Artificial Intelligence in Solving Educational Problems(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۴, Special Issue: Digitalization of Socio-Economic Processes, September ۲۰۲۲ 132 - 146

کلیدواژه‌ها: Educational Software Artificial Intelligence Empirical study

حوزه های تخصصی:
تعداد بازدید : ۲۴۰ تعداد دانلود : ۱۱۸
External factorsexert an enormous influence on the exigencies of changing the technological course of individualsectors. Digitalizationrepresents not a new milestone in the evolution of education, but its technological and methodological development. Due to a period of constraints, caused by COVID-19 pandemic, educational institutions at all levels in most countries have been forced to resort to digitalization of the learning process. Intelligent learning software provide their users with a variety of options to design and individualize the learning process, as well as independence from time and space. Teachers benefit from flexible content generation and just-in-time assessment of learners' progress, evaluation of large task sets, knowledge sharing with other teachers and knowledge institutions. Learners benefit from anytime availability of learning tools and just-in-time feedback. In our investigation, we consider the current state-of-the-art of educational software. Considering the results of quantitative empirical study and analysis of educational issues solvable by artificial intelligence, we present a developed and tested framework for selected educational problem.
۱۲.

Changes in the Balance of International Power in the Light of China's Artificial Intelligence(مقاله علمی وزارت علوم)

نویسنده:
منبع: World Sociopolitical Studies, Volume ۵, Issue ۴, Autumn ۲۰۲۱ 833 - 863

کلیدواژه‌ها: Artificial Intelligence Balance of power China Liberal Order Mearsheimer

حوزه های تخصصی:
تعداد بازدید : ۲۸۵ تعداد دانلود : ۱۰۸
Artificial Intelligence (AI), as a strategic technology, has provided a platform for international competition; ever since the development of the first AI strategy in 2017, to the final days of 2021, more than fifty countries drafted or declared their national strategy aiming at becoming one of the pioneering countries in this field. Although the United States is known as the current pioneering country in the field of AI, China has been able to lead in various areas related to AI, such as occupational opportunities, Internet of Things (IoT), Big Data, Blockchain, and G5, which, due to the historical significance of emerging technologies in changing the balance of power, present a clear image of what is to come at the international stage. Given the novelty of artificial intelligence in the balance of power, the author asks about the effect of China’s artificial intelligence on the international balance of power. The answer is the hypothesis that China tries to effectively interact with its leading private artificial intelligence companies and implement this technology in internal, economic, and military governance. Thus, China aims to raise its national power and challenge the American hegemony through hard internal balance, paving the way for a multipolar world order alongside other regional powers leading in artificial intelligence. This could lead to further instability in the international system. The research hypothesis was analyzed using the explanatory method and Mearsheimer's Balance of Power Theory, and the data collection method consisted of library research.
۱۳.

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

کلیدواژه‌ها: Natural Language Processing Artificial Intelligence Syntax Parser CYK Parsing Algorithm Probabilistic Context Free Grammar

حوزه های تخصصی:
تعداد بازدید : ۲۰۵ تعداد دانلود : ۱۲۷
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.
۱۴.

A Video Game-based Paragraph Writing Instruction vs. Teacher-based Writing Instruction: Examining L2 Learners’ Perceptions through Dynamic Assessment(مقاله علمی وزارت علوم)

نویسنده:
منبع: Teaching Language Skills (JTLS), Volume ۴۲, Issue ۱, Winter ۲۰۲۳ 121 - 146

کلیدواژه‌ها: writing Process-based Approach dynamic assessment Video game Artificial Intelligence

حوزه های تخصصی:
تعداد بازدید : ۲۵۰ تعداد دانلود : ۱۴۹
Game-based learning and the use of Artificial Intelligence in education is a powerful way to enhance learning and provide content that has been underrated in the Iranian context. This study designed an educational video game under the name of Lost p to improve learners’ writing ability based on a process based-approach within Dynamic Assessment context. Thus, the researcher employed experimental design and used the designed video game as a medium of instruction for the experimental group. The control group received a teacher-oriented method and both groups received feedback and corrections based on the Aljaafreh & Lantolf (1994) self-regulatory scale. The result of the study shows that the experimental group outperformed learners in the control class. We found that teaching paragraph writing rules, such as drafting, getting idea techniques, topic sentence development, and integrating them with the elements of the game were entertaining for the gamified group. To explore players’ attitudes toward the game, a semi-structured interview was conducted that showed differences between gamified and non-gamified writing tasks in the post-test phase of the research since the experimental group’s writing scores were enhanced in the second phase of the study. Moreover, this study suggests L2 learners and teachers can adapt game thinking and elements of games to their educational practice.
۱۵.

Optimizing the human resource management process with artificial intelligence algorithmic approach(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of System Management, Volume ۹, Issue ۳, Summer ۲۰۲۳ 285 - 298

کلیدواژه‌ها: Human Resource Management Process Throughput model Perception judgment Artificial Intelligence

حوزه های تخصصی:
تعداد بازدید : ۱۴۸ تعداد دانلود : ۸۴
The human resource management works closely with all the employees in the organization. An HRM must allow the employees to make constructive criticism when there is a need for it. The duty of organizing the company towards achieving their set goals lies in the hands of the HRM. A Human Resource management process can best be distinct as a tool which is utilized to collect, organize, present, keep and share applied information about the human resource of an organization. To this end, this research present a Throughput model framework that describes individuals' decision-making processes in an algorithmic HRM context. The model depicts how perceptions, judgments, and the use of information affect strategy selection, identifying how diverse strategies may be supported by the employment of certain decision-making algorithmic pathways. In focusing on concerns relating to the impact and acceptance of artificial intelligence (AI) integration in HRM, this research draws insights from multidisciplinary theoretical lenses, such as Al-augmented and HRM assimilation processes, AI-mediated social exchange, and the judgment and choice literature. Results highlight the use of algorithmic ethical positions in the adoption of AI for better HRM outcomes in terms of intelligibility and accountability of AI-generated HRM decision-making, which is often underexplored in existing research.
۱۶.

Image processing on images of ancient artifacts with the help of methods based on artificial intelligence

نویسنده:
منبع: Journal of Archaeology and Archaeometry, Volume ۲, Issue ۱ - Serial Number ۵, June ۲۰۲۳ 27 - 39

کلیدواژه‌ها: image processing Artificial Intelligence Algorithms Historical image information MATLAB

حوزه های تخصصی:
تعداد بازدید : ۱۱۸ تعداد دانلود : ۱۳۱
Artificial intelligence (AI) has the potential to revolutionize the field of archaeology by enabling researchers to analyze large amounts of data quickly and accurately. In this article, we have tried to implement some methods and algorithms in image processing on the image of ancient artifacts. We implemented the algorithms on two historical models as examples, one of which is the image of a coin decorated with the image of Farkhan the Great and the other is the coin with the image of Khursheed Daboui to obtain the details of these works from the images on the computer. We used Edge Detection, Hough Transform, imcontour, and Filter Images Using Predefined Filters algorithms in MATLAB software, each of these algorithms is used for specific purposes in image processing. By using digital image analysis techniques, researchers can gain a deeper understanding of the objects and sites they are studying and can make new and important discoveries about the history and culture of ancient civilizations.
۱۷.

Artificial Intelligence Driven Human Identification(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۳, ۲۰۲۳ 113 - 133

کلیدواژه‌ها: Gait Analysis Identification Background subtraction Vectorization Projec-tions Quarter-cycles Artificial Intelligence

حوزه های تخصصی:
تعداد بازدید : ۹۲ تعداد دانلود : ۷۱
Human Identification has been widely implemented to enhance the efficiency of surveillance systems, however, systems based on common CCTV (closed-circuit television) cameras are mostly incompatible with the advanced identification algorithms which aim to extract the facial features or speech of an individual for identification. Gait (i.e., an individual’s unique walking pattern/style) is a leading exponent when compared to first-generation biometric modalities as it is unobtrusive (i.e., it requires no contact with the individual), hence proving gait to be an optimal solution to human identification at a distance. This paper proposes an automatic identification system that analyzes gait to identify humans at a distance and predicts the strength of the match (i.e., probability of the match being positive) between two gait profiles. This is achieved by incorporating computer vision, digital image processing, vectorization, artificial intelligence, and multi-threading. The proposed model extracts gait profiles (from low-resolution camera feeds) by breaking down the complete gait cycle into four quarter-cycles using the variations in the width of the region-of-interest and then saves the gait profile in the form of four distinct projections (i.e., vectors) of length 20 units each, thus, summing up to 80 features for each individual’s gait profile. The focus of this study revolved around the speed-accuracy tradeoff of the proposed model where, with a limited dataset and training, the model runs at a speed of 30Hz and yields 85% accurate results on average. A Receiver Operating Characteristic Curve (ROC) is obtained for comparison of the proposed model with other machine learning models to better understand the efficiency of the system
۱۸.

In-Depth Analysis of Various Artificial Intelligence Techniques in Software Engineering: Experimental Study(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۵, Issue ۳, ۲۰۲۳ 162 - 181

کلیدواژه‌ها: Software Engineering Defects Prediction Artificial Intelligence ML ANN DNN CNN

حوزه های تخصصی:
تعداد بازدید : ۹۶ تعداد دانلود : ۷۱
In this paper, we have extended our literature survey with experimental implementation. Analyzing numerous Artificial Intelligence (AI) techniques in software engineering (SE) can help understand the field better; the outcomes will be more effective when used with it. Our manuscript shows various AI-based algorithms that include Machine learning techniques (ML), Artificial Neural Networks (ANN), Deep Neural Networks (DNN) and Convolutional Neural Networks (CNN), Natural Language Processing (NLP), Genetic Algorithms (GA) applications. Software testing using Ant Colony Optimization (ACO) approach, predicting software maintainability with Group Method of Data Handling (GMDH), Probabilistic Neural Network (PNN), and Software production with time series analysis technique. Furthermore, data is the fuel for AI-based model testing and validation techniques. We have also used NASA dataset promise repository in our script. There are various applications of AI in SE, and we have experimentally demonstrated one among them, i.e., software defect prediction using AI-based techniques. Moreover, the expected future trends have also been mentioned; these are some significant contributions to the research
۱۹.

Evaluation of COVID-19 Spread Effect on the Commercial Instagram Posts using ANN: A Case Study on The Holy Shrine in Mashhad, Iran(مقاله علمی وزارت علوم)

نویسنده:
منبع: International Journal of Digital Content Management, Vol. ۲, No. ۳, Summer & Autumn ۲۰۲۱ 63 - 97

کلیدواژه‌ها: social media Classification Coronavirus word embedding Artificial Intelligence

حوزه های تخصصی:
تعداد بازدید : ۱۰۹ تعداد دانلود : ۷۶
The widespread deployment of social media has helped researchers access an enormous amount of data in various domains, including the the COVID-19 pandemic. This study draws on a heuristic approach to classify Commercial Instagram Posts (CIPs) and explores how the businesses around the Holy Shrine were impacted by the pandemic. Two datasets of Instagram posts (one gathered data from March 14th to April 10th, 2020, when Holy Shrine and nearby shops were closed, and one extracted data from the same period in 2019), two word embedding models – aimed at vectorizing associated caption of each post, and two neural networks – multi-layer perceptron and convolutional neural network – were employed to classify CIPs in 2019. Among the scenarios defined for the 2019 CIPs classification, the results revealed that the combination of MLP and CBoW achieved the best performance, which was then used for the 2020 CIPs classification. It was found out that the fraction of CIPs to total Instagram posts has increased from 5.58% in 2019 to 8.08% in 2020, meaning that business owners were using Instagram to increase their sales and continue their commercial activities to compensate for the closure of their stores during the pandemic. Moreover, the portion of non-commercial Instagram posts (NCIPs) in total posts has decreased from 94.42% in 2019 to 91.92% in 2020, implying the fact that since the Holy Shrine was closed, Mashhad residents and tourists could not visit it and take photos to post on their Instagram accounts.
۲۰.

Racist Artificial Intelligence: Where does it come from?(مقاله علمی وزارت علوم)

نویسنده:
منبع: مطالعات بین المللی سال ۲۰ پاییز ۱۴۰۲ شماره ۲ (پیاپی ۷۸) 139 - 159

کلیدواژه‌ها: Artificial Intelligence racism Algorithms philosophy ethics Bad AI

حوزه های تخصصی:
تعداد بازدید : ۱۳۴ تعداد دانلود : ۸۳
How did racism creep into the algorithms that govern our daily lives, from banking and shopping, to job applications? Connecting the legacy of enlightenment racism to forms of discrimination in modern day algorithms and Artificial Intelligence, this article examines what data feeds into AI technology - and how this data will shape our future, in terms of both social relations and politics.