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Добірка наукової літератури з теми "SPAM FILTER SOFTWARE"

Автор: Grafiati

Опубліковано: 11 вересня 2023

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Статті в журналах з теми "SPAM FILTER SOFTWARE"

1

Caha, Tomáš, and Martin Kovařík. "Spam filter based on geographical location of the sender." Journal of Electrical Engineering 73, no. 4 (August 1, 2022): 292–98. http://dx.doi.org/10.2478/jee-2022-0038.

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Abstract Spam annoys users and poses a security threat. This article proposes a spam filter based on geographical location of the sender determined by IP geolocation. This filter was implemented as a plugin to the SpamAssassin anti-spam software. The plugin allows to define a penalty score for specific countries sending spam. The proposed filter was tested on a dataset of 1500 e-mails consisting of 1200 spam and 300 legitimate e-mails. The Matthews correlation coefficient of the filter has a value of 0.222. This indicates that the proposed spam filter contributes to the correct spam filtering.

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2

Xiong, Yanzhi, and Tianlan Wei. "Probalistic model of spam filter system." Applied and Computational Engineering 6, no. 1 (June 14, 2023): 382–87. http://dx.doi.org/10.54254/2755-2721/6/20230812.

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Numerous tasks have been carried out using probabilistic reasoning, including picture recognition, computer diagnosis, stock price prediction, movie recommendation, and cyber intrusion detection. But until recently, the breadth of probabilistic programming was constrained (partly because of the low processing power), and the majority of inference methods had to be created manually for every job. Nevertheless, in 2015, 3D representations of human faces were created from 2D photographs of such faces using a 50-line probabilistic computer vision software. The inference approach of the software, which was developed in Julia using the Picture package, was based on inverted graphics. "What used to require thousands of lines of code" might now be accomplished in just 50. Probabilistic computing is a method to create systems that help us make decisions in the face of uncertainty. In this paper we propose a spam-filtering system. The novelty of our spam-filtering system is that we utilize probabilistic programming to improve spam-filtering reasoning systems. We implement several factors from email to establish a model to get the output. Our preliminary results show that we successfully accomplish a spam-filtering system. More problem of classification of spam filter can be described in a probabilistic modelling language in our future work.

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3

Roy, Pradeep Kumar, Jyoti Prakash Singh, and Snehasish Banerjee. "Deep learning to filter SMS Spam." Future Generation Computer Systems 102 (January 2020): 524–33. http://dx.doi.org/10.1016/j.future.2019.09.001.

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4

Li, Kang, and Zhenyu Zhong. "Fast statistical spam filter by approximate classifications." ACM SIGMETRICS Performance Evaluation Review 34, no. 1 (June 26, 2006): 347–58. http://dx.doi.org/10.1145/1140103.1140317.

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5

Zhong, Zhenyu, and Kang Li. "Speed Up Statistical Spam Filter by Approximation." IEEE Transactions on Computers 60, no. 1 (January 2011): 120–34. http://dx.doi.org/10.1109/tc.2010.92.

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6

Yue, Xun, Ajith Abraham, Zhong-Xian Chi, Yan-You Hao, and Hongwei Mo. "Artificial immune system inspired behavior-based anti-spam filter." Soft Computing 11, no. 8 (September 2, 2006): 729–40. http://dx.doi.org/10.1007/s00500-006-0116-0.

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7

Mizuno, Osamu, and Michi Nakai. "Can Faulty Modules Be Predicted by Warning Messages of Static Code Analyzer?" Advances in Software Engineering 2012 (May 10, 2012): 1–8. http://dx.doi.org/10.1155/2012/924923.

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We have proposed a detection method of fault-prone modules based on the spam filtering technique, “Fault-prone filtering.” Fault-prone filtering is a method which uses the text classifier (spam filter) to classify source code modules in software. In this study, we propose an extension to use warning messages of a static code analyzer instead of raw source code. Since such warnings include useful information to detect faults, it is expected to improve the accuracy of fault-prone module prediction. From the result of experiment, it is found that warning messages of a static code analyzer are a good source of fault-prone filtering as the original source code. Moreover, it is discovered that it is more effective than the conventional method (that is, without static code analyzer) to raise the coverage rate of actual faulty modules.

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8

Akinyemi, Bodunde O., Oluwatoyin H. Odukoya, Mistura L. Sanni, Gilbert Sewagnon, and Ganiyu A. Aderounmu. "Performance Evaluation of Machine Learning based Robocalls Detection Models in Telephony Networks." International Journal of Computer Network and Information Security 14, no. 6 (December 8, 2022): 37–53. http://dx.doi.org/10.5815/ijcnis.2022.06.04.

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Many techniques have been proposed to detect and prevent spam over Internet telephony. Human spam calls can be detected more accurately with these techniques. However, robocalls, a type of voice spammer whose calling patterns are similar to those of legitimate users, cannot be detected as effectively. This paper proposes a model for robocall detection using a machine learning approach. Voice data recordings were collected and the relevant features for study were selected. The selected features were then used to formulate six (6) detection models. The formulated models were simulated and evaluated using some performance metrics to ascertain the model with the best performance. The C4.5 decision tree algorithm gave the best evaluation result with an accuracy of 99.15%, a sensitivity of 0.991%, a false alarm rate of 0.009%, and a precision of 0.992%. As a result, it was concluded that this approach can be used to detect and filter both machine-initiated and human-initiated spam calls.

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9

Tian, Juan, and Yingxiang Li. "Convolutional Neural Networks for Steganalysis via Transfer Learning." International Journal of Pattern Recognition and Artificial Intelligence 33, no. 02 (October 24, 2018): 1959006. http://dx.doi.org/10.1142/s0218001419590067.

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Recently, a large number of studies have shown that Convolutional Neural Networks are effective for learning features automatically for steganalysis. This paper uses the transfer learning method to help the training of CNNs for steganalysis. First, a Gaussian high-pass filter is designed for pretreatment of the images, that can enhance the weak stego noise in the stegos. Then, the classical Inception-V3 model is improved, and the improved network is used for steganalysis through the method of transfer learning. In order to test the effectiveness of the developed model, two spatial domain content-adaptive steganographic algorithms WOW and S-UNIWARD are used. The results imply that the proposed CNN achieves a better performance at low embedding rates compared with the SRM with ensemble classifiers and the SPAM implemented with a Gaussian SVM on BOSSbase. Finally, a steganalysis system based on the trained model was designed. Through experiments, the generalization ability of the system was tested and discussed.

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10

Sivakumar, Arunachalam, Muthamizhan Thiyagarajan, and Karthick Kanagarathinam. "Mitigation of supply current harmonics in fuzzy-logic based 3-phase induction motor." International Journal of Power Electronics and Drive Systems (IJPEDS) 14, no. 1 (March 1, 2023): 266. http://dx.doi.org/10.11591/ijpeds.v14.i1.pp266-274.

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<span lang="EN-US">A parallel active power filter is employed to enrich the quality of power in the power grid with non-linear loads. The induction motor drive requires better performance in many applications. The overall performance enhancement is performed by mitigating the delivery of current harmonics and related warmness losses in an induction motor. In this paper, comprehensive performance evaluation of a 3-phase induction motor is mentioned with fuzzy logic controller-based shunt active filter (SAF), and the outcomes are compared with proportional integral (PI) and proportional derivative controller (PID) controller. In this work, a new scheme of shunt active filters is connected at the supply side of the vertical speed indicator VSI fed induction motor. The simulation was performed by a fuzzy logic controller (FLC) based 3-</span><span lang="EN-US">f</span><span lang="EN-US"> induction motor drive (IMD) using parallel SAF. Simulation result from MATLAB/Simulink software has been presented to understand the reduction in harmonics by introducing an active filter near the supply side. A fuzzy suitable judgment controller is brought on this work to develop the induction motor dynamic response. Analysis of the simulation outcomes, the usage of MATLAB/Simulink software program for the proposed FLC managed induction motor had been demonstrated and overall performance enhancement of induction motor was discussed.</span>

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Більше джерел

Дисертації з теми "SPAM FILTER SOFTWARE"

1

Anders, Jörg. "WORKSHOP "MOBILITÄT"." Universitätsbibliothek Chemnitz, 2001. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200100538.

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2

POONIA, SANDEEP. "EMAIL SPAM DETECTION." Thesis, 2018. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16193.

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Анотація:

Internet has opened new channels of communication; enabling an e-mail to be sent to a relative thousands of kilometers away. This medium of communication opens doors for virtually free mass e-mailing, reaching out to hundred of thousands users within seconds. However, this freedom of communication can be misused. In the last couple of years spam has become a phenomenon that threatens the viability of communication via e-mail. It is difficult to develop an accurate and useful definition of spam, although every e-mail user will quickly recognize spam messages. Merriam-Webster Online Dictionary1 defines spam as “unsolicited usually commercial e-mail sent to a large number of addresses”. Some other than commercial purposes of spam are to express political or religious opinions, deceive the target audience with promises of fortune, spread meaningless chain letters and infect the receivers’ computer with viruses. Even though one can argue that what is spam for one person can be an interesting mail message for another, most people agree that spam is a public frustration.

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Книги з теми "SPAM FILTER SOFTWARE"

1

Downing, Robert. Spam Filter: Little Known Tips You Need to Know about Anti Spam, Email Spam and Spam Software. Lulu Press, Inc., 2015.

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2

Hilgurt, S. Ya, and O. A. Chemerys. Reconfigurable signature-based information security tools of computer systems. PH “Akademperiodyka”, 2022. http://dx.doi.org/10.15407/akademperiodyka.458.297.

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Анотація:

The book is devoted to the research and development of methods for combining computational structures for reconfigurable signature-based information protection tools for computer systems and networks in order to increase their efficiency. Network security tools based, among others, on such AI-based approaches as deep neural networking, despite the great progress shown in recent years, still suffer from nonzero recognition error probability. Even a low probability of such an error in a critical infrastructure can be disastrous. Therefore, signature-based recognition methods with their theoretically exact matching feature are still relevant when creating information security systems such as network intrusion detection systems, antivirus, anti-spam, and wormcontainment systems. The real time multi-pattern string matching task has been a major performance bottleneck in such systems. To speed up the recognition process, developers use a reconfigurable hardware platform based on FPGA devices. Such platform provides almost software flexibility and near-ASIC performance. The most important component of a signature-based information security system in terms of efficiency is the recognition module, in which the multipattern matching task is directly solved. It must not only check each byte of input data at speeds of tens and hundreds of gigabits/sec against hundreds of thousand or even millions patterns of signature database, but also change its structure every time a new signature appears or the operating conditions of the protected system change. As a result of the analysis of numerous examples of the development of reconfigurable information security systems, three most promising approaches to the construction of hardware circuits of recognition modules were identified, namely, content-addressable memory based on digital comparators, Bloom filter and Aho–Corasick finite automata. A method for fast quantification of components of recognition module and the entire system was proposed. The method makes it possible to exclude resource-intensive procedures for synthesizing digital circuits on FPGAs when building complex reconfigurable information security systems and their components. To improve the efficiency of the systems under study, structural-level combinational methods are proposed, which allow combining into single recognition device several matching schemes built on different approaches and their modifications, in such a way that their advantages are enhanced and disadvantages are eliminated. In order to achieve the maximum efficiency of combining methods, optimization methods are used. The methods of: parallel combining, sequential cascading and vertical junction have been formulated and investigated. The principle of multi-level combining of combining methods is also considered and researched. Algorithms for the implementation of the proposed combining methods have been developed. Software has been created that allows to conduct experiments with the developed methods and tools. Quantitative estimates are obtained for increasing the efficiency of constructing recognition modules as a result of using combination methods. The issue of optimization of reconfigurable devices presented in hardware description languages is considered. A modification of the method of affine transformations, which allows parallelizing such cycles that cannot be optimized by other methods, was presented. In order to facilitate the practical application of the developed methods and tools, a web service using high-performance computer technologies of grid and cloud computing was considered. The proposed methods to increase efficiency of matching procedure can also be used to solve important problems in other fields of science as data mining, analysis of DNA molecules, etc. Keywords: information security, signature, multi-pattern matching, FPGA, structural combining, efficiency, optimization, hardware description language.

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Частини книг з теми "SPAM FILTER SOFTWARE"

1

Whitworth, Brian. "Spam as a Symptom of Electronic Communication Technologies that Ignore Social Requirements." In E-Collaboration, 1464–73. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-652-5.ch107.

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Spam, undesired and usually unsolicited e-mail, has been a growing problem for some time. A 2003 Sunbelt Software poll found spam (or junk mail) has surpassed viruses as the number-one unwanted network intrusion (Townsend & Taphouse, 2003). Time magazine reports that for major e-mail providers, 40 to 70% of all incoming mail is deleted at the server (Taylor, 2003), and AOL reports that 80% of its inbound e-mail, 1.5 to 1.9 billion messages a day, is spam the company blocks. Spam is the e-mail consumer’s number-one complaint (Davidson, 2003). Despite Internet service provider (ISP) filtering, up to 30% of in-box messages are spam. While each of us may only take seconds (or minutes) to deal with such mail, over billions of cases the losses are significant. A Ferris Research report estimates spam 2003 costs for U.S. companies at $10 billion (Bekker, 2003). While improved filters send more spam to trash cans, ever more spam is sent, consuming an increasing proportion of network resources. Users shielded behind spam filters may notice little change, but the Internet transmitted-spam percentage has been steadily growing. It was 8% in 2001, grew from 20% to 40% in 6 months over 2002 to 2003, and continues to grow (Weiss, 2003). In May 2003, the amount of spam e-mail exceeded nonspam for the first time, that is, over 50% of transmitted e-mail is now spam (Vaughan-Nichols, 2003). Informal estimates for 2004 are over 60%, with some as high as 80%. In practical terms, an ISP needing one server for customers must buy another just for spam almost no one reads. This cost passes on to users in increased connection fees. Pretransmission filtering could reduce this waste, but creates another problem: spam false positives, that is, valid e-mail filtered as spam. If you accidentally use spam words, like enlarge, your e-mail may be filtered. Currently, receivers can recover false rejects from their spam filter’s quarantine area, but filtering before transmission means the message never arrives at all, so neither sender nor receiver knows there is an error. Imagine if the postal mail system shredded unwanted mail and lost mail in the process. People could lose confidence that the mail will get through. If a communication environment cannot be trusted, confidence in it can collapse. Electronic communication systems sit on the horns of a dilemma. Reducing spam increases delivery failure rate, while guaranteeing delivery increases spam rates. Either way, by social failure of confidence or technical failure of capability, spam threatens the transmission system itself (Weinstein, 2003). As the percentage of transmitted spam increases, both problems increase. If spam were 99% of sent mail, a small false-positive percentage becomes a much higher percentage of valid e-mail that failed. The growing spam problem is recognized ambivalently by IT writers who espouse new Bayesian spam filters but note, “The problem with spam is that it is almost impossible to define” (Vaughan-Nichols, 2003, p. 142), or who advocate legal solutions but say none have worked so far. The technical community seems to be in a state of denial regarding spam. Despite some successes, transmitted spam is increasing. Moral outrage, spam blockers, spamming the spammers, black and white lists, and legal responses have slowed but not stopped it. Spam blockers, by hiding the problem from users, may be making it worse, as a Band-Aid covers but does not cure a systemic sore. Asking for a technical tool to stop spam may be asking the wrong question. If spam is a social problem, it may require a social solution, which in cyberspace means technical support for social requirements (Whitworth & Whitworth, 2004).

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2

Whitworth, Brian. "Spam as a Symptom of Electronic Communication Technologies that Ignore Social Requirements." In Encyclopedia of Human Computer Interaction, 559–66. IGI Global, 2006. http://dx.doi.org/10.4018/978-1-59140-562-7.ch083.

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Анотація:

Spam, undesired and usually unsolicited e-mail, has been a growing problem for some time. A 2003 Sunbelt Software poll found spam (or junk mail) has surpassed viruses as the number-one unwanted network intrusion (Townsend & Taphouse, 2003). Time magazine reports that for major e-mail providers, 40 to 70% of all incoming mail is deleted at the server (Taylor, 2003), and AOL reports that 80% of its inbound e-mail, 1.5 to 1.9 billion messages a day, is spam the company blocks. Spam is the e-mail consumer’s number-one complaint (Davidson, 2003). Despite Internet service provider (ISP) filtering, up to 30% of in-box messages are spam. While each of us may only take seconds (or minutes) to deal with such mail, over billions of cases the losses are significant. A Ferris Research report estimates spam 2003 costs for U.S. companies at $10 billion (Bekker, 2003). While improved filters send more spam to trash cans, ever more spam is sent, consuming an increasing proportion of network resources. Users shielded behind spam filters may notice little change, but the Internet transmitted-spam percentage has been steadily growing. It was 8% in 2001, grew from 20% to 40% in 6 months over 2002 to 2003, and continues to grow (Weiss, 2003). In May 2003, the amount of spam e-mail exceeded nonspam for the first time, that is, over 50% of transmitted e-mail is now spam (Vaughan-Nichols, 2003). Informal estimates for 2004 are over 60%, with some as high as 80%. In practical terms, an ISP needing one server for customers must buy another just for spam almost no one reads. This cost passes on to users in increased connection fees. Pretransmission filtering could reduce this waste, but creates another problem: spam false positives, that is, valid e-mail filtered as spam. If you accidentally use spam words, like enlarge, your e-mail may be filtered. Currently, receivers can recover false rejects from their spam filter’s quarantine area, but filtering before transmission means the message never arrives at all, so neither sender nor receiver knows there is an error. Imagine if the postal mail system shredded unwanted mail and lost mail in the process. People could lose confidence that the mail will get through. If a communication environment cannot be trusted, confidence in it can collapse. Electronic communication systems sit on the horns of a dilemma. Reducing spam increases delivery failure rate, while guaranteeing delivery increases spam rates. Either way, by social failure of confidence or technical failure of capability, spam threatens the transmission system itself (Weinstein, 2003). As the percentage of transmitted spam increases, both problems increase. If spam were 99% of sent mail, a small false-positive percentage becomes a much higher percentage of valid e-mail that failed. The growing spam problem is recognized ambivalently by IT writers who espouse new Bayesian spam filters but note, “The problem with spam is that it is almost impossible to define” (Vaughan-Nichols, 2003, p. 142), or who advocate legal solutions but say none have worked so far. The technical community seems to be in a state of denial regarding spam. Despite some successes, transmitted spam is increasing. Moral outrage, spam blockers, spamming the spammers, black and white lists, and legal responses have slowed but not stopped it. Spam blockers, by hiding the problem from users, may be making it worse, as a Band-Aid covers but does not cure a systemic sore. Asking for a technical tool to stop spam may be asking the wrong question. If spam is a social problem, it may require a social solution, which in cyberspace means technical support for social requirements (Whitworth & Whitworth, 2004).

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3

Dubey, Rachnana, Jay Prakash Maurya, and R. S. Thakur. "Detection Approaches for Categorization of Spam and Legitimate E-Mail." In Advances in Systems Analysis, Software Engineering, and High Performance Computing, 274–96. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3870-7.ch016.

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Анотація:

The internet has become very popular, and the concept of electronic mail has made it easy and cheap to communicate with many people. But, many undesired mails are also received by users and the higher percentage of these e-mails is termed spam. The goal of spam classification is to distinguish between spam and legitimate e-mail messages. But, with the popularization of the internet, it is challenging to develop spam filters that can effectively eliminate the increasing volumes of unwanted e-mails automatically before they enter a user's mailbox. The main objective of this chapter is to examine and identify the best detection approach for spam categorization. Different types of algorithms and data mining models are proposed, implemented, and evaluated on data sets. For improvement of spam filtering technique, the authors analyze the methods of feature selection and give recommendations of their use. The chapter concludes that the data mining models using a combination of supervised learning algorithms provide better results than single data models.

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4

Vishwanath, Sankar, Sadasiva Kadandale, Anupama Ramachandran, Srividhya Srinivasan, Revathy Parthasarathy, Yashini Thanikachalam, and Srividhya Srinivasan. "ARTIFICIAL INTELLIGENCE IN CONSERVATIVE DENTISTRY AND ENDODONTICS." In Emerging Trends in Oral Health Sciences and Dentistry. Technoarete Publishers, 2022. http://dx.doi.org/10.36647/etohsd/2022.01.b1.ch034.

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Анотація:

The Fourth Industrial Revolution is predicted to improve the quality of life by widespread, sophisticated developments in comparison to earlier industrial revolutions. In particular, the medical and life sciences are anticipated to play a pivotal role in this revolution. Artificial intelligence forms the key driver of this development. This exponential development in science and technology has established different applications, which are utilized in day-to-day life. This includes navigation maps, smart assistants such as Siri and Alexa, rideshare apps like Uber, spam filters, media recommendations and online banking. These applications forms the state of art in artificial intelligence technology. Artificial intelligence illustrate how technology is utilized to expand a software which can easily simulate human intelligence and successfully perform any sort of intellectual activity that could be taken by the human brain. This AI machines can even perform better at a task that is typically performed by humans. In the present day world, AI systems can imitate human cognitive skills like problem solving that makes it very useful in medical and dental field.

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5

"Modeling Search Systems by Composite Inverted Index." In Architectural Framework for Web Development and Micro Distributed Applications, 248–61. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-4849-6.ch013.

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There tends to be a propensity to utilize search systems that contain a custom software component for the specific purpose of meeting this need of inquiry. What falls through the gap with these systems however is the need of the customer to simultaneously query across datastore types such as web documents, database structures, and flat files. The tenants of indexing as they have been addressed in this body of work help to structure the discussion to one whereby this need to query across data type structures can be facilitated. The essence of search has been identified at the systems level and as such for the construct to carry forward to distinct data types requires the identification of the attributes of these other data structures. This chapter builds a generic construct for search to span repository type through an inverted composite index, which addresses the gap identified.

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Тези доповідей конференцій з теми "SPAM FILTER SOFTWARE"

1

Rejeb, Jalel, Thuy Le, and Narinder Anand. "High Speed and Reliable Anti-Spam Filter." In 2006 International Conference on Software Engineering Advances (ICSEA'06). IEEE, 2006. http://dx.doi.org/10.1109/icsea.2006.261322.

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2

Wang, Lei, Song Ma, and Xin-hong Hei. "Research on an Immune Mechanism Based Intelligent Spam Filter." In 2008 International Conference on Computer Science and Software Engineering. IEEE, 2008. http://dx.doi.org/10.1109/csse.2008.1622.

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3

Mizuno, Osamu, Shiro Ikami, Shuya Nakaichi, and Tohru Kikuno. "Spam Filter Based Approach for Finding Fault-Prone Software Modules." In Fourth International Workshop on Mining Software Repositories. IEEE, 2007. http://dx.doi.org/10.1109/msr.2007.29.

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4

Alkabani, Yousra, M. El-kharashi, and Hassan Bedor. "Hardware/Software Partitioning of a Bayesian Spam Filter via Hardware Profiling." In 2006 IEEE International Symposium on Industrial Electronics. IEEE, 2006. http://dx.doi.org/10.1109/isie.2006.296140.

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5

Mizuno, Osamu, and Tohru Kikuno. "Training on errors experiment to detect fault-prone software modules by spam filter." In the the 6th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1287624.1287683.

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6

Madhavan, Yugesh, João W. Cangussu, and Ram Dantu. "Penetration Testing for Spam Filters." In 2009 33rd Annual IEEE International Computer Software and Applications Conference. IEEE, 2009. http://dx.doi.org/10.1109/compsac.2009.168.

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7

Wan, Peng, and Minoru Uehara. "Multiple Filters of Spam Using Sobel Operators and OCR." In 2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS). IEEE, 2012. http://dx.doi.org/10.1109/cisis.2012.104.

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8

Lu, Kai-Shin, and Carl K. Chang. "Using Web Search Results and Genetic Algorithm to Improve the Accuracy of Chinese Spam Email Filters." In 2011 IEEE 35th IEEE Annual Computer Software and Applications Conference Workshops (COMPSACW). IEEE, 2011. http://dx.doi.org/10.1109/compsacw.2011.56.

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9

Briseghella, Bruno, Ruihuan Fu, Junqing Xue, Angelo Aloisio та Camillo Nuti. "Numerical Study on Inﬂuence of Mass on Dynamic Performance of Piles with Pre-hole Seismic Isolation System in IABs". У IABSE Symposium, Istanbul 2023: Long Span Bridges. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2023. http://dx.doi.org/10.2749/istanbul.2023.0101.

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<p>Integral abutment bridges (IABs) could fundamentally resolve the durability problems of expansion joints. The concrete piles beneath the abutments are the most vulnerable components in IABs. To improve the seismicperformanceof IABs, the pile with pre-hole filled by damping materials (called pre-hole seismic isolation system) has been proposed. In this paper, the shaking table test of the pre-hole seismic isolation system under sine wave load is simulated by using the finite element software ABAQUS/Explicit. The influence of the mass on the pile top and the pre-hole dimension on the dynamic performance of the pre-hole seismic isolation system was analysed. It can be concluded that with an increase in the mass or pre-hole dimension, the fundamental frequency of the pile-soil system decreased. With an increase in the input wave’s frequency, the pile with a pre-hole seismic isolation system could have a better seismic performance by reducing the mass or pre-hole dimension.</p>

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Stoll, Tobias, Andre Casal Kulzer, and Hans-Juergen Berner. "Simulative Estimation of a Super-High-Efficiency Stoichiometric Gasoline Engine with GT-Power." In 16th International Conference on Engines & Vehicles. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2023. http://dx.doi.org/10.4271/2023-24-0129.

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<div class="section abstract"><div class="htmlview paragraph">This paper presents a concept of a high efficiency stoichiometric gasoline engine first published in [<span class="xref">1</span>]. The engine is modelled in GT-Power and uses the FKFS UserCylinder. All effects and components that cannot be modelled with these two software modules are estimated by tuning the model parameters to achieve the desired effects. The basic concept of the engine for the model was first published in [<span class="xref">2</span>] and [<span class="xref">3</span>] by Negüs et al. and includes engine friction reduction, improved turbocharger efficiency, variable compression ratio and variable valve train to allow Miller-Cycle and zero-cam profile cylinder deactivation capability. To further increase efficiency of the engine, measures are introduced to increase knock resistance. The first measure includes a pre-chamber spark plug, which proved to significantly reduce combustion duration [<span class="xref">4</span>] and thus the likelihood of knock due to rapid combustion of the fuel mass. The second measure is a high-turbulence tumble concept with a switchable tumble flap to further shorten the burn time. The third measure is high-pressure injection [<span class="xref">5</span>], feeding fuel close to TDC of the compression stroke. This slows down the pre-knock reactions and further reduces the engine's knock probability. The engine uses an electrically heated three-way catalytic converter and a gasoline particle filter. To make the simulation for the engine comparable, it is integrated into a P0-hybrid-electric powertrain and simulated in a comparative analysis with a low-cost engine for four representative drive cycles.</div></div>

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