Relevant bibliographies by topics / False-self system

Academic literature on the topic 'False-self system'

Author: Grafiati

Published: 10 December 2022

Last updated: 29 January 2023

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Journal articles on the topic "False-self system"

Klímová, Helena. "The False We – the False Collective Self – and the Social Unconscious in a Totalitarian System." Group Analysis 48, no. 2_suppl (May 26, 2015): 50–54. http://dx.doi.org/10.1177/0533316415583262j.

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Sokolovsky, S. P., and A. P. Telenga. "METHODOLOGY FOR THE FORMATION OF INFORMATION SYSTEMS FALSE NETWORK TRAFFIC FOR PROTECTION AGAINST NETWORK RECONNAISSANCE." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 212 (February 2022): 40–47. http://dx.doi.org/10.14489/vkit.2022.02.pp.040-047.

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Simulation of false network traffic in order to protect the structural and functional characteristics of information systems is a difficult task in view of the self-similarity of its statistical properties in IP networks, not only in the current moment, but also retrospectively. A Hurst index based algorithm for assessing the degree of self-similarity of network traffic of information systems has been proposed. The connection between the fractal dimension of the attractor of the model of information system functioning and the Hurst index is shown. A technique has been developed to substantiate the characteristics of false network traffic to simulate the functioning of information systems in the process of reconfiguration of their structural and functional characteristics caused by an intruder conducting network reconnaissance. The methodology allows to solve the problem of improving the protection of information systems from network reconnaissance by providing the maximum likelihood of false network traffic by pseudophase reconstruction of the dynamic system attractor, approximating the time series of information traffic of the protected object. The approaches to the description of the network traffic of the information system are considered, the parameters determining the network interaction between the two nodes of the data transmission network are selected as follows: source IP-address, source port, destination IP-address, destination port, protocol, packet size, duration of connection. The process of functioning of information system in different situations is formalized and the dependences allowing to synthesize parameters of false network traffic, statistically similar to the reference ones are received.

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Fatourechi, M., R. K. Ward, and G. E. Birch. "A self-paced brain–computer interface system with a low false positive rate." Journal of Neural Engineering 5, no. 1 (December 11, 2007): 9–23. http://dx.doi.org/10.1088/1741-2560/5/1/002.

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Ambawade, Dayanand, and Dr Jagdish W. Bakal. "Alert Clustering using Self-Organizing Maps and K-Means Algorithm." International Journal of Engineering and Advanced Technology 12, no. 1 (October 30, 2022): 82–87. http://dx.doi.org/10.35940/ijeat.a3852.1012122.

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Alert correlation is a system that receives alerts from heterogeneous Intrusion Detection Systems and reduces false alerts, detects high-level patterns of attacks, increases the meaning of occurred incidents, predicts the future states of attacks, and detects root cause of attacks. This paper presents self-organizing maps and the k-means machine learning algorithms to reduce the number of alerts by clustering them.

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Valentino, Kristin, Dante Cicchetti, Fred A. Rogosch, and Sheree L. Toth. "True and false recall and dissociation among maltreated children: The role of self-schema." Development and Psychopathology 20, no. 1 (2008): 213–32. http://dx.doi.org/10.1017/s0954579408000102.

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AbstractThe current investigation addresses the manner through which trauma affects basic memory and self-system processes. True and false recall for self-referent stimuli were assessed in conjunction with dissociative symptomatology among abused (N= 76), neglected (N= 92), and nonmaltreated (N= 116) school-aged children. Abused, neglected, and nonmaltreated children did not differ in the level of processing self-schema effect or in the occurrence and frequency of false recall. Rather, differences in the affective valence of false recall emerged as a function of maltreatment subtype and age. Regarding dissociation, the abused children displayed higher levels of dissociative symptomatology than did the nonmaltreated children. Although abused, neglected, and nonmaltreated children did not exhibit differences in the valence of their self-schemas, positive and negative self-schemas were related to self-integration differently among the subgroups of maltreatment. Negative self-schemas were associated with increased dissociation among the abused children, whereas positive self-schemas were related to increased dissociation for the neglected children. Thus, positive self-schemas displayed by the younger neglected children were related to higher dissociation, suggestive of defensive self-processing. Implications for clinical intervention are underscored.

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Hofmeyr, Steven A., and Stephanie Forrest. "Architecture for an Artificial Immune System." Evolutionary Computation 8, no. 4 (December 2000): 443–73. http://dx.doi.org/10.1162/106365600568257.

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An artificial immune system (ARTIS) is described which incorporates many properties of natural immune systems, including diversity, distributed computation, error tolerance, dynamic learning and adaptation, and self-monitoring. ARTIS is a general framework for a distributed adaptive system and could, in principle, be applied to many domains. In this paper, ARTIS is applied to computer security in the form of a network intrusion detection system called LISYS. LISYS is described and shown to be effective at detecting intrusions, while maintaining low false positive rates. Finally, similarities and differences between ARTIS and Holland's classifier systems are discussed.

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Asante, Emmanuel, and Raphael Avornyo. "Enhancing Healthcare System in Ghana through Integration of Traditional Medicine." Journal of Sociological Research 4, no. 2 (October 9, 2013): 256. http://dx.doi.org/10.5296/jsr.v4i2.4224.

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Abstract Traditional Medicine (TM) has been practised in Ghana from time immemorial and many Ghanaians still patronise the services of traditional medical practitioners (TMPs). However, TM has not been integrated into the formal healthcare delivery system of the country. This might be partly due to attitudes and perceptions towards it. The aim of the study was to find out the attitudes and perceptions of Scientific Medical Practitioners (SMPs) towards TM in Ghana and then propose measures for the full integration of TM into Ghana’s healthcare delivery system. A descriptive survey methodology was used to solicit responses from all 33 SMPs practising in the Central Region of Ghana. An in-depth interview and self administered questionnaire were the main instruments used for data collection. The main result of the study is that, although SMPs would want the full integration of TM into the formal healthcare delivery system, when confronted with possible ways of working with TMPs they showed reluctance to accepting them as equal partners since they perceived their practice as inferior to theirs. In order to reduce the mistrust and lack of understanding of the philosophy that underlie Scientific Medicine and Traditional Medicine, there must be regular consultations and dialogue between and among practitioners of the two medical systems. This may engender the needed trust and respect that the practitioners need to accord each other in order to develop and integrate TM into the national healthcare system.Keywords: attitudes, integration, perception, scientific medical practitioners, traditional medicine.

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Bashashati, Ali, Rabab K. Ward, and Gary E. Birch. "Towards Development of a 3-State Self-Paced Brain-Computer Interface." Computational Intelligence and Neuroscience 2007 (2007): 1–8. http://dx.doi.org/10.1155/2007/84386.

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Most existing brain-computer interfaces (BCIs) detect specific mental activity in a so-called synchronous paradigm. Unlike synchronous systems which are operational at specific system-defined periods, self-paced (asynchronous) interfaces have the advantage of being operational at all times. The low-frequency asynchronous switch design (LF-ASD) is a 2-state self-paced BCI that detects the presence of a specific finger movement in the ongoing EEG. Recent evaluations of the 2-state LF-ASD show an average true positive rate of 41% at the fixed false positive rate of 1%. This paper proposes two designs for a 3-state self-paced BCI that is capable of handling idle brain state. The two proposed designs aim at detecting right- and left-hand extensions from the ongoing EEG. They are formed of two consecutive detectors. The first detects the presence of a right- or a left-hand movement and the second classifies the detected movement as a right or a left one. In an offline analysis of the EEG data collected from four able-bodied individuals, the 3-state brain-computer interface shows a comparable performance with a 2-state system and significant performance improvement if used as a 2-state BCI, that is, in detecting the presence of a right- or a left-hand movement (regardless of the type of movement). It has an average true positive rate of 37.5% and 42.8% (at false positives rate of 1%) in detecting right- and left-hand extensions, respectively, in the context of a 3-state self-paced BCI and average detection rate of 58.1% (at false positive rate of 1%) in the context of a 2-state self-paced BCI.

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Mina Qaisar, Saeed, Dija Sidiya, Mohammad Akbar, and Abdulhamit Subasi. "An Event-Driven Multiple Objects Surveillance System." International journal of electrical and computer engineering systems 9, no. 1 (2018): 35–44. http://dx.doi.org/10.32985/ijeces.9.1.2.

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Traditional surveillance systems are constrained because of a fixed and preset pattern of monitoring. It can reduce the reliability of the system and cause an increased generation of false alarms. It results in an increased processing activity of the system, which causes an augmented consumption of system resources and power. Within this framework, a human surveillance system is proposed based on the event-driven awakening and self-organization principle. The proposed system overcomes these downsides up to a certain level. It is achieved by intelligently merging an assembly of sensors with two cameras, actuators, a lighting module and cost-effective embedded processors. With the exception of low-power event detectors, all other system modules remain in the sleep mode. These modules are activated only upon detection of an event and as a function of the sensing environment condition. It reduces power consumption and processing activity of the proposed system. An effective combination of a sensor assembly and a robust classifier suppresses generation of false alarms and improves system reliability. An experimental setup is realized in order to verify the functionality of the proposed system. Results confirm proper functionality of the implemented system. A 62.3-fold system memory utilization and bandwidth consumption reduction compared to traditional counterparts is achieved, i.e. a result of the proposed system self-organization and event-driven awakening features. It confirms that the proposed system outperforms its classical counterparts in terms of processing activity, power consumption and usage of resources

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Zhao, Xuemin. "Application of Data Mining Technology in Software Intrusion Detection and Information Processing." Wireless Communications and Mobile Computing 2022 (June 9, 2022): 1–8. http://dx.doi.org/10.1155/2022/3829160.

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In order to improve the efficiency of the software intrusion detection system, the author proposes an application based on data mining technology in software intrusion detection and information processing. Apply data mining technology to software intrusion detection; first, analyze and research software intrusion detection technology and data mining technology, including the basic concepts of software intrusion detection, the realization technology of software intrusion detection, the classification of software intrusion detection systems, and the typical software intrusion detection system situation. By detecting and analyzing known intrusion data and using association rules, constructing the inspection system rule base enables the system to learn independently and improve itself and has good scalability, while improving the degree of automation and complete intrusion detection. Experimental results show that under the same test sample, the accuracy of the detection system model designed in this paper is 95.67%, higher than the other three detection systems, and the false alarm rate is lower than other systems, which has certain advantages. It is proved that the system in this paper can help improve the accuracy of software intrusion detection, significantly reduce the false alarm rate and false alarm rate of software intrusion detection, and provide reference for the optimization and improvement of software intrusion detection system and information processing. The system has a certain degree of self-adaptation, which can effectively detect external intrusions.

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Books on the topic "False-self system"

Plotch, Philip Mark. Last Subway. Cornell University Press, 2020. http://dx.doi.org/10.7591/cornell/9780801453663.001.0001.

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This book is the fascinating and dramatic story behind New York City's struggle to build a new subway line under Second Avenue and improve transit services all across the city. The book reveals why the city's subway system, once the best in the world, is now too often unreliable, overcrowded, and uncomfortable. It explains how a series of uninformed and self-serving elected officials have fostered false expectations about the city's ability to adequately maintain and significantly expand its transit system. Since the 1920s, New Yorkers have been promised a Second Avenue subway. When the first of four planned phases opened on Manhattan's Upper East Side in 2017, subway service improved for tens of thousands of people. Riders have been delighted with the clean, quiet, and spacious new stations. Yet these types of accomplishments will not be repeated unless New Yorkers learn from their century-long struggle. The book offers valuable lessons in how governments can overcome political gridlock and enormous obstacles to build grand projects. However, it is also a cautionary tale for cities. It reveals how false promises, redirected funds, and political ambitions have derailed subway improvements. Given the ridiculously high cost of building new subways in New York and their lengthy construction period, the Second Avenue subway (if it is ever completed) will be the last subway built in New York for generations to come.

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Book chapters on the topic "False-self system"

Singh, Greg. "Social media as a false-self system." In The Death of Web 2.0, 139–58. Abingdon, Oxon ; New York, NY : Routledge, 2019.: Routledge, 2018. http://dx.doi.org/10.4324/9780429020032-8.

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Smullyan, Raymond M. "Self-Referential Systems." In Gödel's Incompleteness Theorems. Oxford University Press, 1992. http://dx.doi.org/10.1093/oso/9780195046724.003.0014.

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Self-Referential Systems This chapter is largely a review of the essential ideas behind the proofs of Gödel, Rosser and Löb—only presented in a more abstract setting. We believe that it will tie up these ideas in a helpful and instructive manner. We shall first present these ideas in the form of logic puzzles (much in the manner of Smtdlyan [1987]). Then we shall state the results more generally in terms of abstract systems that we call provability systems. These are closely related to certain axiom systems of modal logic, which we briefly discuss at the end of the chapter. In the puzzles to which we now turn, belief will play the rôle of provability. Instead of considering a mathematical system and the sentences provable in it, we consider a logician (sometimes call a reasoner) and the propositions believed by the reasoner. Apart from the heuristic value, these “epistemic” incompleteness theorems appear to be of some interest to those working in artificial intelligence. We shall pay a visit to the Island of Knights and Knaves, in which knights make only true statements and knaves make only false ones. Each inhabitant is either a knight or a knave. No inhabitant can claim that he is not a knight (since a knight would never make such a false claim and a knave would never make such a true claim). A logician visits this island one day and meets a native. All we are told about the logician is that he is completely accurate in his beliefs—he never believes anything false. The native then makes a certain statement X. It then follows that the logician can never believe that the native is a knight nor can he ever believe that the native is a knave.

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Sigamani, Rama Mercy Sam. "Adoption of Machine Learning With Adaptive Approach for Securing CPS." In Handbook of Research on Machine and Deep Learning Applications for Cyber Security, 388–415. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-5225-9611-0.ch018.

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The cyber physical system safety and security is the major concern on the incorporated components with interface standards, communication protocols, physical operational characteristics, and real-time sensing. The seamless integration of computational and distributed physical components with intelligent mechanisms increases the adaptability, autonomy, efficiency, functionality, reliability, safety, and usability of cyber-physical systems. In IoT-enabled cyber physical systems, cyber security is an essential challenge due to IoT devices in industrial control systems. Computational intelligence algorithms have been proposed to detect and mitigate the cyber-attacks in cyber physical systems, smart grids, power systems. The various machine learning approaches towards securing CPS is observed based on the performance metrics like detection accuracy, average classification rate, false negative rate, false positive rate, processing time per packet. A unique feature of CPS is considered through structural adaptation which facilitates a self-healing CPS.

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Koleva, Maria K. "Semantic Intelligence." In Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction, 158–67. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7368-5.ch013.

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Semantic intelligence is exclusive for the intelligent complex systems way of response to an ever-changing environment. Its major distinctive property is autonomous comprehension and creation of information. Another exclusive property of semantic intelligence is autonomous discrimination between true and false statements. The semantic intelligence naturally arises in the setting of concept of boundedness where it commences from highly non-trivial interplay between structural and functional properties of a complex system. The major generic property of that interplay is that it renders the relation between structural and functional properties to be non-recursive. In result, this renders the efficiency of semantic intelligence to be provided by efficiency of hierarchical self-organization of a complex system prior to the efficiency of software and to the speed of hardware.

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López González, Luis F. "“Mais braadou come cabron”." In The Aesthetics of Melancholia, 23–49. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780192859228.003.0002.

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Abstract Chapter 1 studies an odd type of madness believed to result from the burning of the melancholic humors, or black bile, a common disease characterized by false identity beliefs and a misperception of the external world. King Alfonso, King Sancho IV, and Juan Manuel knew this illness from the New Galenic system of thought dominating in cultured circles across Europe. This type of aberration quickly became a literary motif and was exploited by Iberian authors to showcase the frailty of humankind and the transience of life. This first chapter benefits from these literary tropes to analyze cantigas 65 and 283 from King Alfonso’s influential Cantigas de Santa Maria. Both cantigas exhibit traits of what medieval physicians believed to be adust melancholia, including the false belief of having become an animal and the withdrawal from society and into the self.

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Koleva, Maria K. "Semantic Intelligence." In Encyclopedia of Information Science and Technology, Fourth Edition, 220–28. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2255-3.ch020.

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Semantic intelligence is an exclusive for the intelligent complex systems way of response to an ever-changing environment. Its major distinctive property is autonomous comprehension and creation of information. Another exclusive property of semantic intelligence is autonomous discrimination between true and false statements. The semantic intelligence naturally arises in the setting of concept of boundedness where it commences from highly non-trivial interplay between structural and functional properties of a complex system. The major generic property of that interplay is that it renders the relation between structural and functional properties to be non-recursive. In result this renders the efficiency of semantic intelligence to be provided by efficiency of hierarchical self-organization of a complex system prior to the efficiency of software and to the speed of hardware.

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Dailey, Anne C. "Guilty Minds." In Law and the Unconscious. Yale University Press, 2017. http://dx.doi.org/10.12987/yale/9780300188837.003.0005.

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This chapter examines the puzzling question of why an otherwise rational person would voluntarily confess to a crime, knowing full well that the state will punish in return. Even more puzzling is the phenomenon of false confessions, where an individual inexplicably confesses to a crime she did not commit, in some cases believing in her own guilt. Psychoanalysis gives us important insights into these irrational phenomena. The focus in this chapter is on the ways in which certain deceptive and degrading police interrogation tactics may override a suspect’s conscious rational decision-making powers by enlisting unconscious needs, aggressions, and guilt. Three interrogation tactics are of greatest concern: false sympathy, degradation, and trickery. As this chapter shows, false sympathy and degradation exploit deep-seated, unconscious desires for absolution and punishment that undermine the voluntariness of a suspect’s self-incriminating statements. Similarly, police trickery can take unfair advantage of a suspect’s need to rationalize unconscious guilt for a crime he did not commit. By drawing attention to the risks associated with these methods, psychoanalysis ensures that the most egregious practices can be eliminated from our criminal justice system. Psychoanalytic insights into unconscious processes advances the law’s own best ideals of fundamental fairness in the criminal law.

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Irwin, Terence. "Beyond Kantian and Utilitarian Morality: An Idealist Alternative." In Ethics Through History, 256–63. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780199603701.003.0021.

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Green and Bradley believe that a Hegelian conception of self-realization allows us to recognize what is true and false in utilitarian and Kantian views, and to see the connexion between these modern views and Aristotelian eudaemonism. A free and rational will aims at self-realization, the fulfilment of one’s capacities as a rational agent. This is different from, and more plausible, than, the utilitarian conception of one’s good as maximum pleasure. Moreover, attention to self-realization helps to explain why we should not recognize any basic conflict—either for utilitarian or for Kantian reasons—between the requirements of self-realization and the demands of morality. Since the realization of one’s own capacities includes the realization of those that essentially involve relations to other people, it requires us to belong to a social and moral system in which we occupy roles that achieve one’s good as a member of a well-ordered society.

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Gupta, Gopal K. "Māyā’s Relation to the Temporal Realm." In Māyā in the Bhāgavata Purāṇa, 37–64. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198856993.003.0003.

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This chapter shows how māyā, on behalf of Kṛṣṇa, makes manifest all the ingredients of creation, and, through a sequential series of developments, forms those ingredients into a plurality of universes, bodies, and minds, known as the temporal (phenomenal) realm. It specifically explores māyā’s relation to material creation, concentrating on the Bhāgavata’s Sāṁkhya account of the manner in which māyā transforms into the various elements of the temporal realm. In the course of this examination, we will attempt to compare the Bhāgavata’s Sāṁkhya system to that of classical Sāṁkhya, specifically with regard to such standard Sāṁkhya categories as puruṣa (the individual self), prakṛti (the physical world), ahaṁkāra (false identification), the guṇas (qualitative energies), the twenty-three elements, and so on.

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Swanson, G. A. "An Analysis of the Imbursement of Currency in a Debt-Based Money-Information System." In Emerging Systems Approaches in Information Technologies, 119–36. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-976-2.ch008.

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The imbursement of currency into modern debtbased money-information systems is a concrete phenomenon. Economic jargon traffics in abstract concepts. This analysis attempts to bridge the gap between the abstract and the concrete and to provide practical insights into certain social consequences of different modes of currency imbursement. Information science, like economics, has developed as an analytic science. Many reasons might explain that development. Not least among them is the daunting complexity of the matter-energy systems they concern. Button and Dourish (1996) provide an interesting view of the role of systems design to provide an opaque barrier for decisionmakers against that complexity while enabling engagement. That conceptual distance can give a false sense that the design of information systems should be limited only by imagination. Many definitions of information have been proposed and some have gained acceptance in certain circles. In some highly abstracted systems, Bateson’s (1972, xxv-xxvi) “difference that makes a difference” has appeal. Nevertheless, when we consider that technology emerges in self-organizing, evolving living systems that exist in physical space-time, that definition has little explanatory power. Alternatively, Shannon’s H restatement of the measure of entropy (Shannon, 1948) that became known as a measure of information is significantly explicatory of an essential connection between information and matter-energy processes. Shannon’s treatment of information as a reduction of uncertainty has found wide application.

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Conference papers on the topic "False-self system"

Moguel, Israel, Hever Moncayo, Andres Perez, Mario Perhinschi, Dia Al Azzawi, and Adil Togayev. "Bio-Inspired Approach for Aircraft Health Assessment and Flight Envelope Estimation." In ASME 2014 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/dscc2014-5885.

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Based on the artificial immune system paradigm and a hierarchical multi-self strategy, a set of algorithms for aircraft sub-systems failure detection, identification, evaluation and flight envelope estimation have been developed and implemented. Data from a six degrees-of-freedom flight simulator were used to define a large set of 2-dimensional self/non-self projections as well as for the generation of antibodies and identifiers designated for health assessment of an aircraft under upset conditions. The methodology presented in this paper classifies and quantifies the type and severity of a broad number of aircraft actuators, sensors, engine and structural component failures. In addition, the impact of these upset conditions on the flight envelope is estimated using nominal test data. Based on immune negative and positive selection mechanisms, a heuristic selection of sub-selves and the formulation of a mapping-based algorithm capable of selectively capturing the dynamic fingerprint of upset conditions is implemented. The performance of the approach is assessed in terms of detection and identification rates, false alarms, and correct prediction of flight envelope reduction with respect to specific states.

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Matsushita, Haruna, and Yoshifumi Nishio. "Self-Organizing Map Considering False Neighboring Neuron." In 2007 IEEE International Symposium on Circuits and Systems. IEEE, 2007. http://dx.doi.org/10.1109/iscas.2007.378703.

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Penney, Randy, and Hugh Flesher. "Electronic Equipment Provides Pipeline Monitoring and Protection: Applications and Limitations." In 2000 3rd International Pipeline Conference. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/ipc2000-242.

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Background: Line break controls developed to date have provided the Pipeline Industry with the best protection available with proven and available technologies. There have been shortcomings in line break control due to various factors including; lack of accurate pressure history at the valve sites creating uncertainty for proper set points and limitations in the flexibility of mechanical systems. Safety: Providing pipeline safety through a line break detection system is critically important for the protection of people, property, and the environment. Safer procedures are available through continuous pipeline monitoring. Application of new technology: Increased availability of “smart” pressure sensors offers a greater degree of accuracy and control. Real time communication for data collection and system configuration (operating data, alarm status and settings, valve status) or remote operation (valve closures or line break override) provides increased control over pipeline operations. Real time information allows continuous monitoring and control. This can be provided through commercially available networks, hence providing economical and reliable methods of communication. Data acquisition through Windows based software allows the user to accumulate, sort, and analyze the data. Overview: Industry requires the ability to monitor pipeline pressures and pipeline rate of pressure change. Industry requires accuracy, reliability, and real time access for controlling valves, while minimizing the occurrences of false valve closures. The pipeline and gas transmission industry is growing, with increasing demands for safe, reliable, and efficient operating systems. New technologies are capable of providing solutions for the Pipeline Industry’s needs. Solutions: A self-contained electronic system, purpose built for the gas pipeline industry is available. The equipment continuously monitors the pipeline, measures pipeline pressures, and calculates pressure changes so that, in the case of a pipeline failure, a command is sent to the actuator to stroke the valve to the fail safe position. The equipment is accessible locally or remotely via SCADA or telemetry to acquire and analyze pipeline conditions on a real time basis, and control the actuator. The equipment is low power consumption suitable for external line power, or is available with solar panels and rechargeable batteries. The equipment continuously gathers information and provides history for pipeline operators. This allows the optimization of set points, with time delays and averaging, to minimize false trips. Windows based software enables ease of use. Owner can set alarm parameters that are protected through password authorization. Summary: Electronic Linebreak Detection Systems are able to provide the flexibility, reliability and responsiveness necessary to meet the growing safety and efficiency demands of the Pipeline Industry. Current technology provides this capability.

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von Staudt, Hans Martin, and Frank Schwiderski. "Trading Off Test Coverage and False Reject Risk of Self-Calibrating Self-Test Systems." In 2012 18th International Mixed-Signals, Sensors and Systems Test Workshop (IMS3TW 2012). IEEE, 2012. http://dx.doi.org/10.1109/ims3tw.2012.32.

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Matsushita, Haruna, and Yoshifumi Nishio. "Self-Organizing Map with Weighted Connections avoiding false-neighbor effects." In 2010 IEEE International Symposium on Circuits and Systems - ISCAS 2010. IEEE, 2010. http://dx.doi.org/10.1109/iscas.2010.5537113.

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Hodkhasa, Sandip, and Huiping Guo. "Forward Chaining and Self-Embedding Watermarking for Tamper Detection in a Continuous Stream of Data." In 8th International Conference on Artificial Intelligence and Fuzzy Logic System (AIFZ 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.121612.

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Watermarking is extensively used in various media for data transfer, content authentication and integrity. The continuous flow of data is always vulnerable to tamper. This research proposes a new watermarking scheme that detects tampering in a stream of data. The stream of data is dynamically divided into different sized groups using synchronization points. A computed watermark is embedded in each group by hashing the concatenating the current group and the next group. A secondary watermark is generated based on the current group that prevents tampering from any attacks in the current group. Watermark verification table is used to determine all possible scenarios for false results. Experiments are performed to show its efficiency. False results decrease as the group size becomes larger. Random burst attacked requires larger group size. The scheme also shows with the increase in grouping parameter ‘m’ which defines the synchronization point, the false positive rate decreases.

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Liu, Yi-Hung, Chun-Wei Huang, and Yu-Tsung Hsiao. "Controlling the False Positive Rate of a Two-State Self-Paced Brain-Computer Interface." In 2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013). IEEE, 2013. http://dx.doi.org/10.1109/smc.2013.255.

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Araujo, Maria S., Heath A. Spidle, Shane P. Siebenaler, Samantha G. Blaisdell, and David W. Vickers. "Application of Machine Learning to Distributed Temperature Sensing (DTS) Systems." In 2018 12th International Pipeline Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/ipc2018-78640.

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The timely detection of small leaks from liquid pipelines poses a significant challenge for pipeline operations. One technology considered for continual monitoring is distributed temperature sensing (DTS), which utilizes a fiber-optic cable to provide distributed temperature measurements along a pipeline segment. This measurement technique allows for a high accuracy of temperature determination over long distances. Unexpected deviations in temperature at any given location can indicate various physical changes in the environment, including contact with a heated hydrocarbon due to a pipeline leak. The signals stemming from pipeline leaks may not be significantly greater than the noise in the DTS measurements, so care must be taken to configure the system in a manner that can detect small leaks while rejecting non-leak temperature anomalies. There are many factors that influence the frequency and intensity of the backscattered optical signal. This can result in noise in the fine-grained temperature sensing data. Thus, the DTS system must be tuned to the nominal temperature profile along the pipe segment. This customization allows for significant sensitivity and can utilize different leak detection thresholds at various locations based on normal temperature patterns. However, this segment-specific tuning can require a significant amount of resources and time. Additionally, this configuration exercise may have to be repeated as pipeline operating conditions change over time. Thus, there is a significant need and interest in advancing existing DTS processing techniques to enable the detection of leaks that today go undetected by DTS due to their signal response being too close to the noise floor and/or requiring significant resources to achieve positive results. This paper discusses the recent work focused on using machine learning (ML) techniques to detect leak signatures. Initial proof-of-concept results provide a more robust methodology for detecting leaks and allow for the detection of smaller leaks than are currently detectable by typical DTS systems, with low false alarm rates. A key use of ML approaches is that the system can “learn” about a given pipeline on its own without the need to utilize resources for pipeline segment-specific tuning. The potential to have a self-taught system is a powerful concept, and this paper discusses some key initial findings from applying ML-based techniques to optimize leak detection capabilities of an existing DTS system.

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BULJUBAŠIĆ, Ema. "HAPPINESS, FREEDOM AND VALUES IN MODERN SOCIETY." In Happiness And Contemporary Society : Conference Proceedings Volume. SPOLOM, 2021. http://dx.doi.org/10.31108/7.2021.8.

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Pursuit of happiness is a highly valued human ambition that seems impossible to achieve in modern society. Ancient Greek philosophers, especially Aristotle’s concept of eudaimonia, present a theoretical starting point for defining happiness and bringing it firmly into relation with values. Philosopher Herbert Marcuse provides a valuable analysis of modern industrialized society explaining man’s loss of freedom in exchange for comfort and the self-perpetuating mechanism of consumerism that keeps people under willingly oppressed by imposing false needs. Consumerism also causes a distortion of people’s values and alienates them from their true values causing them psychological damage. Using Dr. Melanie Joy’s analysis of the psychological importance of living in accordance with one’s values and the distortion of values as a manipulation tactic common to different systems of oppression (racism, sexism, speciesism) we will identify two prerequisite conditions for achieving happiness: freedom and the alignment of values and behavior. Key words: happiness, freedom, values, false needs, consumerism

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Al Sawafi, Mohammed, Antonio Andrade, Nitish Kumar, Rahul Gala, Eduardo Marin, Sandeep Soni, and Conny Velazco. "Intelligent Operating Envelope Integrated with Automated Well Models Improves Asset Wide PCP Surveillance and Optimization." In Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/207290-ms.

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Abstract Petroleum Development Oman (PDO) has been a pioneer in improving Well management processes utilizing its valuable human resources, continuous improvement and digitalization. Managing several PCP wells through Exception Based Surveillance (EBS) methodology had already improved PCP surveillance and optimization across assets. The key to trigger EBS was to keep Operating Envelope (OE), Design Limits updated in Well Management Visualization System (WMVS) after every change in operating speed (RPM), workover and new completion. The sustainable solution was required for automatic update of OEs, having well inflow potential and oil gain opportunities available for quicker optimization decisions for further improvements. PDO has completed a project automating PCP well modeling process where models are built and sustained automatically in Well Management System (WMS) for all active PCP wells, with huge impact on day-to-day operational activities. The paper discusses utilization of physics based well models from WMS to automatically update OE, identify oil gain potential daily and enable real time PCP performance visualization in WMVS. The integration of WMS and WMVS was completed to share data between two systems and automatically update well's OE daily. A tuned well model from WMS was utilized to provide well performance data and sensitivity analysis results for various RPMs. Among the various data obtained from WMS, live OE of torque and fluid above pump (FAP) for various speeds, operating limits, design limits, locked in potential (LIP) for optimization and pump upsize were utilized to process PCP well EBS and create live OE visualization. The visualization is created on a torque-speed chart where a live OE and FAP can be observed in provided picture with current RPM and torque with optimum operating condition. The project is completed after conducting successful change management across PDO assets and after thorough analysis of implementation following benefits were observed: 5% net gain of total PCP production is being executed with zero CAPEX using LIP reports. 50% of engineer's time was saved by updating OEs in WMVS automatically, reduction of false EBS and EBS rationalization. 200% improvement in PCP well performance diagnostics capabilities of Engineers. 15% CAPEX free optimization and pump upsize cases were identified based on well inflow potential. 100% visibility to PCP well's performance was achieved using well model. The visualization has supported engineers monitoring well performance in real time and easily identifying ongoing changes in well and pump performance. PCP well models have supported engineers in new PCP well design and pump upsize. The current efforts in utilizing real time well models, inferred production, automating processes to update OE is one more step toward Digitalization of PCP Surveillance and optimization and to achieve self well optimization for further improving operational efficiency.

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