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Nanoplastics: Methods, Exposure and Effects on Domestic, Farm and Wild Animals
Journal of Applied Toxicology, EarlyView.ABSTRACT Nanoplastics (NPs) are synthetic polymer particles ranging in size from 1 nm to 1 μm that have been identified as a major concern for ecosystems and organisms due to their plethora of negative effects. The aim of this review is to provide a comprehensive overview of the knowledge relating to exposure and effects of NPs in domestic (i.e., farm ...
B. De Felice +8 more
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Journal of Chemical Technology &Biotechnology, EarlyView.Abstract BACKGROUND Curcumin is a naturally derived polyphenol known for its potent biological properties. Its therapeutic potential, however, is hindered by low bioavailability. Nanostructured lipid carriers (NLCs) have emerged as advanced delivery systems to overcome such limitations. Natural deep eutectic solvents (NADESs) have garnered attention as
Kyriaki Safari +5 more
wiley +1 more source
Complement Bloom Filter for Identifying True Positiveness of a Bloom Filter
IEEE Communications Letters, 2015 The use of Bloom filters in network applications has increased rapidly. Since Bloom filters can produce false positives, the trueness of each positive needs to be identified by referring to an off-chip hash table. This letter proposes a new method for identifying the trueness of Bloom filter positives.
Hyesook Lim, Changhoon Yim
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Ternary Bloom filter replacing counting Bloom filter
2016 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia), 2016 A counting Bloom filter (CBF) generalizes a standard 1-bit vector Bloom filter and allows not only membership queries but also insertion and deletion operations for dynamic sets. However, the CBF can cause false negatives because of counter overflows. A 4-bit vector CBF, which provides the probability of false negatives sufficiently small, is generally
Hayoung Byun, Jungwon Lee, Hyesook Lim
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Effect of Hadamard multiplication on bloom filter and double bloom filter transformations
Security and Privacy, 2023AbstractIris biometric is the most common and widely accepted biometric authentication method due to its high accuracy. The iris biometric template should be protected to overcome security and privacy attacks. The two standard iris biometric template protection methods are bloom filter and double bloom filter‐based feature transformations.
Ajish Sreedharan
exaly +3 more sources
A new Bloom filter structure for identifying true positiveness of a Bloom filter
2017 IEEE 18th International Conference on High Performance Switching and Routing (HPSR), 2017 Bloom filters have been employed in various fields because of its simple and effective structure in identifying the membership of an input. Since a Bloom filter can produce false positives, the positive results of a Bloom filter should be identified whether the positives are true or not by accessing the original database.
Ju Hyoung Mun, Jungwon Lee, Hyesook Lim
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Does not Bloom Filter bloom in membership filtering?
2023Naresh Babu Muppalaneni, Ripon Patgiri
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2008 Proceedings IEEE INFOCOM - The 27th Conference on Computer Communications, 2008
A bloom filter is a randomized data structure for performing approximate membership queries. It is being increasingly used in networking applications ranging from security to routing in peer to peer networks. In order to meet a given false positive rate, the amount of memory required by a bloom filter is a function of the number of elements in the set.
Fang Hao +2 more
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A bloom filter is a randomized data structure for performing approximate membership queries. It is being increasingly used in networking applications ranging from security to routing in peer to peer networks. In order to meet a given false positive rate, the amount of memory required by a bloom filter is a function of the number of elements in the set.
Fang Hao +2 more
openaire +2 more sources
IEEE Transactions on Knowledge and Data Engineering, 2010
A Bloom filter is an effective, space-efficient data structure for concisely representing a set, and supporting approximate membership queries. Traditionally, the Bloom filter and its variants just focus on how to represent a static set and decrease the false positive probability to a sufficiently low level.
Deke Guo +4 more
openaire +1 more source
A Bloom filter is an effective, space-efficient data structure for concisely representing a set, and supporting approximate membership queries. Traditionally, the Bloom filter and its variants just focus on how to represent a static set and decrease the false positive probability to a sufficiently low level.
Deke Guo +4 more
openaire +1 more source
2019 International Conference on Electronics, Information, and Communication (ICEIC), 2019
A membership identification is a key functionality in many network applications. Various data structures have been introduced in order to support the efficient membership identification. Since a Bloom filter can provide simple but efficient membership checking, it is widely used in many network applications.
Ju Hyoung Mun, Hyesook Lim
openaire +2 more sources
A membership identification is a key functionality in many network applications. Various data structures have been introduced in order to support the efficient membership identification. Since a Bloom filter can provide simple but efficient membership checking, it is widely used in many network applications.
Ju Hyoung Mun, Hyesook Lim
openaire +2 more sources