Risk assessment in investment project by A. L. Tkachenko, O. G. Sheveleva

“…As a result of the study, existing risk assessment and uncertainty methods are analyzed when deciding on investment, a Monte-Carlo simulation is performed using Microsoft Excel, and the results are analyzed using the Descriptive Statistics tool…”
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On Risk Assessment for Out-of-Distribution Detection by Anton Vasiliuk

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Desertification risk assessment and management program by M. Akbari, M. Ownegh, H.R. Asgari, A. Sadoddin, H. Khosravi

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Integrated risk analyses as part of national climate risk assessments: lessons learnt from the climate risk assessment of Germany by Walter Kahlenborn, Maike Voss, Luise Porst, Marc Zebisch, Kathrin Renner, Inke Schauser

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Risk assessment of complex organoarsenic species in food by EFSA Panel on Contaminants in the Food Chain (CONTAM), Helle Katrine Knutsen, Agneta Åkesson, Vasileios Bampidis, Margherita Bignami, Laurent Bodin, James Kevin Chipman, Gisela Degen, Antonio Hernández‐Jerez, Tim Hofer, Christer Hogstrand, Stefano Landi, Jean‐Charles Leblanc, Kyriaki Machera, Evangelia Ntzani, Guido Rychen, Salomon Sand, Katharina Vejdovszky, Barbara Viviani, Lars Barregård, Diane Benford, Eugenia Dogliotti, Kevin Francesconi, Jose Ángel Gómez Ruiz, Hans Steinkellner, Tanja Schwerdtle

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Ecological Risk Assessment for Invasive Wildlife in Florida by Venetia Briggs-Gonzalez, Kyle Allen, Rebecca G. Harvey, Frank J. Mazzotti

“…WEC374/UW419: Ecological Risk Assessment for Invasive Wildlife in Florida (ufl.edu) …”
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Uncertainties in Earthquake Risk Assessment for Disaster Planning by Yasin Fahjan, Ferhat Pakdamar, Yaşasın Eryılmaz, Fatma Kara

“…Uncertainties of the seismic risk assessment parameters can be generated from ground motion computations, structural inventories and risk methodologies. …”
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Traffic Risk Assessment Based on Warning Data by Tao Wang, Binbin Chen, Yuzhi Chen, Shejun Deng, Jun Chen

“…To address the issues of insufficient danger excavation and long data collection period in traditional traffic risk assessment methods, this paper proposes a risk assessment method based on driver’s improper driving behavior and abnormal vehicle state warning data. …”
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Ecological Risk Assessment for Invasive Wildlife in Florida by Venetia Briggs-Gonzalez, Kyle Allen, Rebecca G. Harvey, Frank J. Mazzotti

“…WEC374/UW419: Ecological Risk Assessment for Invasive Wildlife in Florida (ufl.edu) …”
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The importance and challenges of data collection in risk assessment by Xekalakis Georgios, Fokaides Paris, Christou Petros

“…This study underscores the significance of diverse data collection methods, including field surveys, artificial intelligence (AI) analysis, and satellite imagery, each essential for developing robust risk assessment frameworks. Field surveys offer detailed insights into structural and non-structural building components, critical for localized risk assessments. …”
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Estimation of soil erosion and risk assessment in Somalia by Abdiaziz Hassan Nur, Abdullahi Ali Ibrahim, Abas Abdi Warsame, Abdikarim Hurre Farah

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Scenario-Based Risk Assessment for Düzce Province by Zeynep Mıhçı, Hüseyin Bayraktar

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Satellite In-Orbit Secondary Collision Risk Assessment by Haicheng Tao, Xueke Che, Qinyu Zhu, XinHong Li

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The Residues and Risk Assessment of Sulfonamides in Animal Products by Xiao-lei Zuo, Han Ai-yun

“…Combined with the data of Chinese residents’ dietary survey in 2015, a nonparametric probability assessment model was constructed to assess the risk of sulfonamides in the livestock and poultry products of Shijiazhuang residents by using the professional risk assessment software @Risk. Risk assessment of the consumption of sulfonamide veterinary drugs in livestock and poultry products of Shijiazhuang residents was conducted. …”
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Model of fuzzy risk assessment of the information system by ZHAO Dong-mei1, MA Jian-feng1, WANG Yue-sheng2

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RETRACTED: Risk assessment methodology for environmental monitoring in construction by Mukhamedzhanova Olga, Kokhreidze Murman, Marchenko Nikita

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Privacy leakage risk assessment for reversible neural network by Yifan HE, Jie ZHANG, Weiming ZHANG, Nenghai YU

“…In recent years, deep learning has emerged as a crucial technology in various fields.However, the training process of deep learning models often requires a substantial amount of data, which may contain private and sensitive information such as personal identities and financial or medical details.Consequently, research on the privacy risk associated with artificial intelligence models has garnered significant attention in academia.However, privacy research in deep learning models has mainly focused on traditional neural networks, with limited exploration of emerging networks like reversible networks.Reversible neural networks have a distinct structure where the upper information input can be directly obtained from the lower output.Intuitively, this structure retains more information about the training data, potentially resulting in a higher risk of privacy leakage compared to traditional networks.Therefore, the privacy of reversible networks was discussed from two aspects: data privacy leakage and model function privacy leakage.The risk assessment strategy was applied to reversible networks.Two classical reversible networks were selected, namely RevNet and i-RevNet.And four attack methods were used accordingly, namely membership inference attack, model inversion attack, attribute inference attack, and model extraction attack, to analyze privacy leakage.The experimental results demonstrate that reversible networks exhibit more serious privacy risks than traditional neural networks when subjected to membership inference attacks, model inversion attacks, and attribute inference attacks.And reversible networks have similar privacy risks to traditional neural networks when subjected to model extraction attack.Considering the increasing popularity of reversible neural networks in various tasks, including those involving sensitive data, it becomes imperative to address these privacy risks.Based on the analysis of the experimental results, potential solutions were proposed which can be applied to the development of reversible networks in the future.…”
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Advanced Tree Risk Assessment: Resistance Recording Drills by Drew McLean, Andrew Koeser, Gitta Hasing

“… Resistance recording drills are specialized pieces of decay detection equipment that may be used as part of an advanced risk assessment. While not required for tree risk assessment work, resistance recording drills have been shown to be effective in helping arborists detect and document internal tree decay in trees. …”
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Health Risk Assessment of Chemicals: From Bulk to Nano by Soqrat Omari Shekaftik, Jamal Biganeh, Maedeh Hosseinzadeh, Hamidreza Jafari Nodoushan, Neda Mehrparvar

Subjects: “…health risk assessment…”
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