The Experts below are selected from a list of 216 Experts worldwide ranked by ideXlab platform

Michael L Perlin - One of the best experts on this subject based on the ideXlab platform.

  • deceived me into thinking i had something to protect a therapeutic jurisprudence analysis of when multiple experts are necessary in cases in which fact finders rely on Heuristic Reasoning and ordinary common sense
    Social Science Research Network, 2019
    Co-Authors: Michael L Perlin
    Abstract:

    There is a stunning disconnect between the false “ordinary common sense” of fact-finders (both jurors and judges) and the valid and reliable scientific evidence that should inform decisions on the full range of questions that are raised in cases involving the forensic mental health systems – predictions of future dangerousness, competency and insanity determinations, sentencing mitigation in death penalty cases, and sexually violent predator commitments. Abetted by the misuse of Heuristic Reasoning (the vividness effect, confirmatory bias, and more), decisionmakers in such case frequently “get it wrong” in ways that poison the criminal justice system. If we were to adopt this proposal – to provide two experts in cases in which such inaccuracy is likely, one to explain to the fact-finders why their “common sense” is fatally flawed, and one to provide an evaluation of the defendant in the context of the specific question before the court – then, and only then, would therapeutic jurisprudence principles be vindicated.

  • morality and pretextuality psychiatry and law of ordinary common sense Heuristic Reasoning and cognitive dissonance
    Journal of the American Academy of Psychiatry and the Law, 1991
    Co-Authors: Michael L Perlin
    Abstract:

    The thesis of this paper is that we will not make significant progress in understanding the tensions between the legal and mental health systems until we look carefully at a series of dissonances that affect both systems. We must consider the way that the law frequently condones pretextuality as a way of dealing with troubling or cognitively dissonant information, and the way that mental health professionals encourage a self-referential concept of morality as a way of subverting legal doctrines with which they disagree. These dissonances must be considered contextually in connection with the ways that courts generally read social science data and the ways that jurors and legislators employ such cognitive devices as "ordinary common sense" and Heuristic Reasoning in their judgments of cases involving mental disability questions. To ameliorate the current dilemma, we must redefine institutional and professional roles, reconsider the way we privilege expertise, recalibrate our allocation of "moral jurisdiction" over these matters, and consciously confront the way our simplifying thinking mechanisms distort the underlying social and political issues.

Marco Moretti - One of the best experts on this subject based on the ideXlab platform.

  • A Robust Maximum Likelihood Scheme for PSS Detection and Integer Frequency Offset Recovery in LTE Systems
    IEEE Transactions on Wireless Communications, 2016
    Co-Authors: Michele Morelli, Marco Moretti
    Abstract:

    Before establishing a communication link in a cellular network, the user terminal must activate a synchronization procedure called initial cell search in order to acquire specific information about the serving base station. To accomplish this task, the primary synchronization signal (PSS) and secondary synchronization signal (SSS) are periodically transmitted in the downlink of a long term evolution (LTE) network. Since SSS detection can be performed only after successful identification of the primary signal, in this work, we present a novel algorithm for joint PSS detection, sector index identification, and integer frequency offset (IFO) recovery in an LTE system. The proposed scheme relies on the maximum likelihood (ML) estimation criterion and exploits a suitable reduced-rank representation of the channel frequency response, which proves robust against multipath distortions and residual timing errors. We show that a number of PSS detection methods that were originally introduced through Heuristic Reasoning can be derived from our ML framework by simply selecting an appropriate model for the channel gains over the PSS subcarriers. Numerical simulations indicate that the proposed scheme can be effectively applied in the presence of severe multipath propagation, where existing alternatives provide unsatisfactory performance.

  • a robust scheme for pss detection and integer frequency offset recovery in lte systems
    arXiv: Information Theory, 2015
    Co-Authors: M Morelli, Marco Moretti
    Abstract:

    Before establishing a communication link in a cellular network, the user terminal must activate a synchronization procedure called initial cell search in order to acquire specific information about the serving base station. To accomplish this task, the primary synchronization signal (PSS) and secondary synchronization signal (SSS) are periodically transmitted in the downlink of a Long Term Evolution (LTE) network. Since SSS detection can be performed only after successful identification of the primary signal, in this work we present a robust scheme for joint PSS detection, sector index identification and integer frequency offset (IFO) recovery in an LTE system. The proposed algorithm relies on the maximum likelihood (ML) estimation criterion and exploits a suitable reduced-rank representation of the channel frequency response to take multipath distortions into account. We show that some PSS detection methods that were originally introduced through Heuristic Reasoning can be derived from our ML framework by selecting an appropriate model for the channel gains over the PSS subcarriers. Numerical simulations indicate that the proposed scheme can be effectively applied in the presence of severe multipath propagation, where existing alternatives provide unsatisfactory performance.

Mohd Rizal Arshad - One of the best experts on this subject based on the ideXlab platform.

  • robotics vision based Heuristic Reasoning for underwater target tracking and navigation
    arXiv: Robotics, 2006
    Co-Authors: Chua Kia, Mohd Rizal Arshad
    Abstract:

    This paper presents a robotics vision-based Heuristic Reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs) operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. ...

  • robotics vision based Heuristic Reasoning for underwater target tracking and navigation
    International Journal of Advanced Robotic Systems, 2005
    Co-Authors: Chua Kia, Mohd Rizal Arshad
    Abstract:

    This paper presents a robotics vision-based Heuristic Reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs) operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. This study focuses on developing image processing algorithms and fuzzy inference system for the analysis of the terrain. The vision system developed is capable of interpreting underwater scene by extracting subjective uncertainties of the object of interest. Subjective uncertainties are further processed as multiple inputs of a fuzzy inference system that is capable of making crisp decisions concerning where to navigate. The important part of the image analysis is morphological filtering. The applications focus on binary images with the extension of gray-level concepts. An open-loop fuzzy control system is developed for classifying the traverse of terrain. The great achievement is the system's capability to recognize and perform target tracking of the object of interest (pipeline) in perspective view based on perceived condition. The effectiveness of this approach is demonstrated by computer and prototype simulations. This work is originated from the desire to develop robotics vision system with the ability to mimic the human expert's judgement and Reasoning when maneuvering ROV in the traverse of the underwater terrain.

Chua Kia - One of the best experts on this subject based on the ideXlab platform.

  • robotics vision based Heuristic Reasoning for underwater target tracking and navigation
    arXiv: Robotics, 2006
    Co-Authors: Chua Kia, Mohd Rizal Arshad
    Abstract:

    This paper presents a robotics vision-based Heuristic Reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs) operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. ...

  • robotics vision based Heuristic Reasoning for underwater target tracking and navigation
    International Journal of Advanced Robotic Systems, 2005
    Co-Authors: Chua Kia, Mohd Rizal Arshad
    Abstract:

    This paper presents a robotics vision-based Heuristic Reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs) operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. This study focuses on developing image processing algorithms and fuzzy inference system for the analysis of the terrain. The vision system developed is capable of interpreting underwater scene by extracting subjective uncertainties of the object of interest. Subjective uncertainties are further processed as multiple inputs of a fuzzy inference system that is capable of making crisp decisions concerning where to navigate. The important part of the image analysis is morphological filtering. The applications focus on binary images with the extension of gray-level concepts. An open-loop fuzzy control system is developed for classifying the traverse of terrain. The great achievement is the system's capability to recognize and perform target tracking of the object of interest (pipeline) in perspective view based on perceived condition. The effectiveness of this approach is demonstrated by computer and prototype simulations. This work is originated from the desire to develop robotics vision system with the ability to mimic the human expert's judgement and Reasoning when maneuvering ROV in the traverse of the underwater terrain.

Michele Morelli - One of the best experts on this subject based on the ideXlab platform.

  • A Robust Maximum Likelihood Scheme for PSS Detection and Integer Frequency Offset Recovery in LTE Systems
    IEEE Transactions on Wireless Communications, 2016
    Co-Authors: Michele Morelli, Marco Moretti
    Abstract:

    Before establishing a communication link in a cellular network, the user terminal must activate a synchronization procedure called initial cell search in order to acquire specific information about the serving base station. To accomplish this task, the primary synchronization signal (PSS) and secondary synchronization signal (SSS) are periodically transmitted in the downlink of a long term evolution (LTE) network. Since SSS detection can be performed only after successful identification of the primary signal, in this work, we present a novel algorithm for joint PSS detection, sector index identification, and integer frequency offset (IFO) recovery in an LTE system. The proposed scheme relies on the maximum likelihood (ML) estimation criterion and exploits a suitable reduced-rank representation of the channel frequency response, which proves robust against multipath distortions and residual timing errors. We show that a number of PSS detection methods that were originally introduced through Heuristic Reasoning can be derived from our ML framework by simply selecting an appropriate model for the channel gains over the PSS subcarriers. Numerical simulations indicate that the proposed scheme can be effectively applied in the presence of severe multipath propagation, where existing alternatives provide unsatisfactory performance.