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1 |
A survey on adversarial attacks in computer vision: Taxonomy, visualization and future directions
بررسی حملات خصمانه در بینایی کامپیوتر: طبقه بندی، تجسم و جهت گیری های آینده-2022 Deep learning has been widely applied in various fields such as computer vision, natural language pro-
cessing, and data mining. Although deep learning has achieved significant success in solving complex
problems, it has been shown that deep neural networks are vulnerable to adversarial attacks, result-
ing in models that fail to perform their tasks properly, which limits the application of deep learning
in security-critical areas. In this paper, we first review some of the classical and latest representative
adversarial attacks based on a reasonable taxonomy of adversarial attacks. Then, we construct a knowl-
edge graph based on the citation relationship relying on the software VOSviewer, visualize and analyze
the subject development in this field based on the information of 5923 articles from Scopus. In the
end, possible research directions for the development about adversarial attacks are proposed based on
the trends deduced by keywords detection analysis. All the data used for visualization are available at:
https://github.com/NanyunLengmu/Adversarial- Attack- Visualization . keywords: یادگیری عمیق | حمله خصمانه | حمله جعبه سیاه | حمله به جعبه سفید | نیرومندی | تجزیه و تحلیل تجسم | Deep learning | Adversarial attack | Black-box attack | White-box attack | Robustness | Visualization analysis |
مقاله انگلیسی |
2 |
Monitoring crop phenology with street-level imagery using computer vision
پایش فنولوژی محصول با تصاویر سطح خیابان با استفاده از بینایی ماشین-2022 Street-level imagery holds a significant potential to scale-up in-situ data collection. This is enabled by combining
the use of cheap high-quality cameras with recent advances in deep learning compute solutions to derive relevant
thematic information. We present a framework to collect and extract crop type and phenological information
from street level imagery using computer vision. Monitoring crop phenology is critical to assess gross primary
productivity and crop yield. During the 2018 growing season, high-definition pictures were captured with side-
looking action cameras in the Flevoland province of the Netherlands. Each month from March to October, a fixed
200-km route was surveyed collecting one picture per second resulting in a total of 400,000 geo-tagged pictures.
At 220 specific parcel locations, detailed on the spot crop phenology observations were recorded for 17 crop
types (including bare soil, green manure, and tulips): bare soil, carrots, green manure, grassland, grass seeds,
maize, onion, potato, summer barley, sugar beet, spring cereals, spring wheat, tulips, vegetables, winter barley,
winter cereals and winter wheat. Furthermore, the time span included specific pre-emergence parcel stages, such
as differently cultivated bare soil for spring and summer crops as well as post-harvest cultivation practices, e.g.
green manuring and catch crops. Classification was done using TensorFlow with a well-known image recognition
model, based on transfer learning with convolutional neural network (MobileNet). A hypertuning methodology
was developed to obtain the best performing model among 160 models. This best model was applied on an
independent inference set discriminating crop type with a Macro F1 score of 88.1% and main phenological stage
at 86.9% at the parcel level. Potential and caveats of the approach along with practical considerations for
implementation and improvement are discussed. The proposed framework speeds up high quality in-situ data
collection and suggests avenues for massive data collection via automated classification using computer vision. keywords: Phenology | Plant recognition | Agriculture | Computer vision | Deep learning | Remote sensing | CNN | BBCH | Crop type | Street view imagery | Survey | In-situ | Earth observation | Parcel | In situ |
مقاله انگلیسی |
3 |
Computer vision model for estimating the mass and volume of freshly harvested Thai apple ber ( Ziziphus mauritiana L:) and its variation with storage days
مدل بینایی کامپیوتری برای تخمین جرم و حجم سیب تازه برداشت شده تایلندی (Ziziphus mauritiana L:) و تغییرات آن با روزهای نگهداری-2022 The physical properties of fruits are proportional to their mass and volume; this connection is used to determine
the fruit qualities and in designing the novel postharvest machinery. The present study aimed to forecast the
mass and volume of Thai apple ber (Ziziphus mauritiana L.) as a function of its physical properties measured using
image processing techniques at different stages of ripening (1st day, 4th day, 7th day, and 10th day). The mass
and volume models developed and analyzed the single variable regression, multilinear regressions, and mass
regression based on volume. Among these models, linear support vector machine (SVM) was found appropriate.
The experimental data analysis showed that the R2 of the linear SVM model for mass and volume of the projected
area were 0.955 and 0.965, respectively. In contrast, for the multilinear regression model, R2 values were 0.967
and 0.972, respectively. For the mass prediction model, the R2 was 0.970 based on calculated volume showing a
linear relationship. Thus, it was concluded that real-time measurement of physical properties of Thai apple ber
using an image-processing technique to estimate the mass and volume is a precise and accurate approach. keywords: بینایی کامپیوتر | پردازش تصویر | فراگیری ماشین | پسرفت | ماشین بردار پشتیبانی | Computer vision | Image processing | Machine learning | Regression | Support vector machine |
مقاله انگلیسی |
4 |
آموزش آسیب شناسی از راه دور تحت همه گیری COVID-19: برداشت های دانشجویان پزشکی
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 4 - تعداد صفحات فایل doc فارسی: 12 زمینه: همهگیری COVID-19 آموزش سنتی را مجبور کرده است که دوباره ساختار یافته و به صورت آنلاین ارائه شود. هدف: تجزیه و تحلیل ادراک دانشجویان پزشکی در مورد مزایا و مشکلات آموزش از راه دور پاتولوژی در طول همه گیری COVID-19.
طراحی: یک مطالعه مقطعی با یک نظرسنجی آنلاین برای دانشجویان سال سوم و چهارم فارغالتحصیلی پزشکی، که در آموزش از راه دور پاتولوژی در طول همهگیری COVID-19 شرکت کردند، انجام شد. روشهای تدریس آنلاین شامل فعالیتهای همزمان با سخنرانیهای تعاملی زنده، بحثهای مبتنی بر مورد و فعالیتهای ناهمزمان با سخنرانیهای ضبطشده، آموزشها و متون موجود در پلت فرم آموزش آنلاین است. ادراک دانشجویان در مورد آموزش از راه دور آسیب شناسی از طریق نظرسنجی آنلاین مورد ارزیابی قرار گرفت. یافتهها: 90 دانشجو (47%) از 190 شرکتکننده پرسشنامه را تکمیل کردند که 45 نفر مرد و 52 نفر در سال سوم فارغالتحصیلی پزشکی بودند. شرایط درک شده ای که یادگیری آسیب شناسی را تسهیل می کرد شامل استفاده از پلت فرم آموزش آنلاین و انعطاف پذیری زمانی برای مطالعه بود. دانشجویان سخنرانی های زنده تعاملی را برتر از سخنرانی های سنتی سنتی می دانستند. شرایط درک شده ای که مانع اجرای آموزش آنلاین شد، شامل دشواری جداسازی مطالعه از فعالیت های خانگی، بی انگیزگی و بدتر شدن کیفیت زندگی به دلیل دوری فیزیکی از همکاران و اساتید بود. به طور کلی، آموزش از راه دور آسیب شناسی توسط 80٪ از دانشجویان ارزش مثبت داشت. نتیجهگیری: ابزارهای آنلاین اجازه میدهند تا محتوای پاتولوژی با موفقیت در طول همهگیری COVID-19 به دانشآموزان ارائه شود. این تجربه می تواند الگویی برای فعالیت های آموزشی آتی آسیب شناسی در آموزش علوم بهداشت باشد. کلید واژه ها: پاتولوژی | آموزش از راه دور | کووید -19 | آموزش پزشکی |
مقاله ترجمه شده |
5 |
TUI Model for data privacy assessment in IoT networks
مدل TUI برای ارزیابی حریم خصوصی داده ها در شبکه های اینترنت اشیا-2022 The development of the Internet of Things (IoT) has been at the forefront of progressing societal
functionality. However, the addition of IoT devices in conventional information technology (IT)
infrastructure has raised and prioritized the concern of information security and data privacy. The
Common Vulnerability Scoring System (CVSS) is a framework for providing information to the
public about the impact of vulnerabilities and exploits executed on a multitude of devices. While
the CVSS addresses a plethora of conditions for vulnerabilities, it does not adequately make end-
users aware of the impact data privacy can have on their devices. The primary objective of this
research work is to extend the existing CVSS and propose a new model that acknowledges
Transparency, Unlinkability, and Intervenability (TUI) to address the data privacy issues of IoT
devices when scoring impacts of vulnerabilities. Our research has developed this model to provide
a new sufficient score for analyzing the true impact of compromised data privacy. After the
development of the new scoring for TUI, our research highlights case studies to emphasize the
impact our TUI model will have on the CVSS. We strongly believe that our proposed model benefit
both the individual users (consumers of IoT devices) and the industry to portray the possible
vulnerabilities from a user standpoint as well as a manufacturer standpoint. keywords: حریم خصوصی داده ها | امنیت اینترنت اشیا | مدل سیا | امتیازدهی آسیب پذیری | امنیت دستگاه | ارزیابی امنیتی | Data privacy | IoT security | CIA model | Vulnerability scoring | Device security | Security assessment |
مقاله انگلیسی |
6 |
A framework for intelligent IoT firmware compliance testing
چارچوبی برای تست سازگاری سیستم عامل اینترنت اشیاء هوشمند-2022 The recent mass production and usage of the Internet of Things (IoT) have posed serious concerns due to the
unavoidable security complications. The firmware of IoT systems is a critical component of IoT security. Although
multiple organizations have released security guidelines, few IoT vendors are following these guidelines properly,
either due to a lack of accountability or the availability of appropriate resources. Some tools for this purpose can
use static, dynamic, or fuzzing techniques to test the security of IoT firmware, which may result in false positives
or failure to discover vulnerabilities. Furthermore, the vast majority of resources are devoted to a single subject,
such as networking protocols, web interfaces, or Internet of Things computer applications. This paper aims to
present a novel method for conducting compliance testing and vulnerability evaluation on IoT system firmware,
communication interfaces, and networking services using static and dynamic analysis. The proposed system detects a broad range of security bugs across a wide range of platforms and hardware architectures. To test and
validate our prototype, we ran tests on 4300 firmware images and discovered 13,000þ compliance issues. This
work, we believe, will be the first step toward developing a reliable automated compliance testing framework for
the IoT manufacturing industry and other stakeholders.
keywords: اینترنت اشیا | امنیت اینترنت اشیا | تست انطباق | آسیب پذیری های میان افزار | IoT | IoT security | Compliance testing | Firmware vulnerabilities |
مقاله انگلیسی |
7 |
A survey on security in internet of things with a focus on the impact of emerging technologies
بررسی امنیت در اینترنت اشیا با تمرکز بر تاثیر فناوری های نوظهور-2022 Internet of Things (IoT) have opened the door to a world of unlimited possibilities for imple-
mentations in varied sectors in society, but it also has many challenges. One of those challenges is
security and privacy. IoT devices are more susceptible to security threats and attacks. Due to
constraints of the IoT devices such as area, power, memory, etc., there is a lack of security so-
lutions that are compatible with IoT devices and applications, which is leading this world of
securely connected things to the “internet of insecure things.” A promising solution to this
problem is going beyond the standard or classical techniques to implementing the security so-
lutions in the hardware of the IoT device. The integration of emerging technologies in IoT net-
works, such as machine learning, blockchain, fog/edge/cloud computing, and quantum
computing have added more vulnerable points in the network. This paper introduces a
comprehensive study on IoT security threats and solutions. Additionally, this survey outlines how
emerging technologies such as machine learning and blockchain are integrated in IoT, challenges
resulted from this integration, and potential solutions to these challenges. The paper utilizes the
4-layer IoT architecture as a reference to identify security issues with corresponding solutions. keywords: اینترنت اشیا | امنیت | فراگیری ماشین | بلاک چین | تهدیدها | راه حل های امنیتی | IoT | Security | Machine learning | Blockchain | Threats | Security solutions |
مقاله انگلیسی |
8 |
Accounting to the end of life: Scarcity, performance and death
حسابداری تا پایان زندگی، عملکرد و مرگ-2021 This paper follows accounting to the end of life. We question how accounting can influence the
way life ends to understand the conceptions of life, health and normality that inform accounting
valuations of life itself. Specifically, we conducted an ethnographic study of a hospital’s geriatrics
and palliative care unit to analyse how accounting influences, and is informed by, conceptions of
what makes a life worth living. The end of life problematises accounting and makes visible as-
sumptions on what constitutes a good life. We draw on Agamben and Canguilhem to show that
accounting builds on, and reproduces, several discursive positions – scarcity and the need for
efficient resource allocation; separability and the possibility to isolate segments; commensuration
and the possibility to relate each situation to standardised categories; valuation and the reduction
of life to exchange values; normativity and the definition of normality through statistical regu-
larities. We then discuss the kind of life that is included in accounting valuations of life itself and
the dehumanising consequences accounting practices can have on the end of life. We conclude
with opening questions on how to imagine forms of accounting that would acknowledge our
vulnerability and allow for an art of living while dying. keywords: قوم شناسی | مرگ | جرات | زیست شناسی | زندگی | Ethnography | Death | Geriatrics | Biopolitics | Life |
مقاله انگلیسی |
9 |
Cultural consensus knowledge of rice farmers for climate risk management in the Philippines
دانش اجماع فرهنگی کشاورزان برنج برای مدیریت ریسک آب و هوایی در فیلیپین-2021 Despite efforts and investments to integrate weather and climate knowledges, often dichotomized
into the scientific and the local, a top-down practice of science communication that tends to
ignore cultural consensus knowledge still prevails. This paper presents an empirical application of
cultural consensus analysis for climate risk management. It uses mixed methods such as focus
groups, freelisting, pilesorting, and rapid ethnographic assessment to understand farmers’
knowledge of weather and climate conditions in Barangay Biga, Oriental Mindoro, Philippines.
Multi-dimensional scaling and aggregate proximity matrix of items are generated to assess the
similarity among the different locally perceived weather and climate conditions. Farmers’
knowledge is then qualitatively compared with the technical classification from the government’s
weather bureau. There is cultural agreement among farmers that the weather and climate con-
ditions can be generally grouped into wet, dry, and unpredictable weather (Maria Loka).
Damaging hazards belong into two subgroups on the opposite ends of the wet and dry scale, that
is, tropical cyclone is grouped together with La Ni˜na, rainy season, and flooding season, while
farmers perceive no significant difference between El Ni˜no, drought, and dry spells. Ethnographic
information reveals that compared to the technocrats’ reductive knowledge, farmers imagine
weather and climate conditions (panahon) as an event or a phenomenon they are actively
experiencing by observing bioindicators, making sense of the interactions between the sky and
the landscape, and the agroecology of pest and diseases, while being subjected to agricultural
regulations on irrigation, price volatility, and control of power on subsidies and technologies. This
situated local knowledge is also being informed by forecasts and advisories from the weather
bureau illustrating a hybrid of technical science, both from the technocrats and the farmers, and
personal experiences amidst agricultural precarities. Speaking about the hybridity of knowledge
rather than localizing the scientific obliges technocrats and scientists to productively engage with
different ways of knowing and the tensions that mediate farmers’ knowledge as a societal
experience. keywords: دانش اجماع | پیش بینی آب و هوا | کشاورزی | خطر ابتلا به آب و هوا | Consensus knowledge | Weather forecasting | Agriculture | Climate risk |
مقاله انگلیسی |
10 |
Disaster management training in the euregio-meuse-rhine: What can we learn from each other to improve cross-border practices?
آموزش مدیریت بلایا در euregio-meuse-rhine: برای بهبود شیوه های فرامرزی چه چیزی می توانیم از یکدیگر بیاموزیم؟-2021 Increasing numbers of disasters require comprehensive preparedness. Border regions are vulnerable as disasters
might not halt at administrative borders. Cross-border coordination is therefore required. As integral part of
cross-border collaborations initiative in the Meuse–Rhine Euregio (EMR), we reviewed published evidence
informing on existing initiatives dedicated to disaster education in the EMR. A search based on the PRISMA
guidelines for scoping reviews was conducted to retrieve articles in the following databases: Medline, PsychInfo
and Scopus. The searches were limited to English, French, Dutch and German language articles and the period
between January 2010 and June 2019. No restrictions were set for the study design or the type of methodology
used. A total of 18 articles met the inclusion criteria out of a total of 1771 publications. Training development
was found in two studies while nine studies focused on the state of knowledge in disaster management. Seven
articles referred only to technical skills, three only to non-technical skills and eight combined both types of skills.
For the technical nature, Knowledge was found seven times, Skills five times and Attitudes twice. On the non-
technical side, Knowledge was found three and both Skills twice and Attitudes three times. Five studies
trained and assessed all the Knowledge, skills and attitudes. Most of the studies constitute inventories with
descriptive reporting and very few experimental studies of quality have been carried. Non-technical skills for
disaster preparedness have been well considered among the articles. Cross-border collaboration needs to be
further investigated. keywords: پزشکی فاجعه | حوادث تلفات جمعی | آموزش فاجعه | برنامه ریزی فاجعه | Disaster medicine | Mass casualty incidents | Disaster education | Disaster planning |
مقاله انگلیسی |