DF 2.0: An Automated, Privacy Preserving, and Efficient Digital Forensic Framework That Leverages Machine Learning for Evidence Prediction and Privacy Evaluation

The current state of digital forensic investigation is continuously challenged by the rapid technological changes, the increase in the use of digital devices (both the heterogeneity and the count), and the sheer volume of data that these devices could contain. Although data privacy protection is not a performance measure, however, preventing privacy violations during the digital forensic investigation, is also a big challenge. With a perception that the completeness of investigation and the data privacy preservation are incompatible with each other, the researchers have provided solutions to address the above-stated challenges that either focus on the effectiveness of the investigation process or the data privacy preservation. However, a comprehensive approach that preserves data privacy without affecting the capabilities of the investigator or the overall efficiency of the investigation process is still an open problem. In the current work, the authors have proposed a digital forensic framework that uses case information, case profile data and expert knowledge for automation of the digital forensic analysis process; utilizes machine learning for finding most relevant pieces of evidence; and maintains data privacy of non-evidential private files. All these operations are coordinated in a way that the overall efficiency of the digital forensic investigation process increases while the integrity and admissibility of the evidence remain intact. The framework improves validation which boosts transparency in the investigation process. The framework also achieves a higher level of accountability by securely logging the investigation steps. As the proposed solution introduces notable enhancements to the current investigative practices more like the next version of Digital Forensics, the authors have named the framework `Digital Forensics 2.0\u27, or `DF 2.0\u27 in short

Scapinin, the Protein Phosphatase 1 Binding Protein, Enhances Cell Spreading and Motility by Interacting with the Actin Cytoskeleton

Copyright (c) 2009 Sagara et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Scapinin, also named phactr3, is an actin and protein phosphatase 1 (PP1) binding protein, which is expressed in the adult brain and some tumor cells. At present, the role(s) of scapinin in the brain and tumors are poorly understood. We show that the RPEL-repeat domain of scapinin, which is responsible for its direct interaction with actin, inhibits actin polymerization in vitro. Next, we established a Hela cell line, where scapinin expression was induced by tetracycline. In these cells, expression of scapinin stimulated cell spreading and motility. Scapinin was colocalized with actin at the edge of spreading cells. To explore the roles of the RPEL-repeat and PP1-binding domains, we expressed wild-type and mutant scapinins as fusion proteins with green fluorescence protein (GFP) in Cos7 cells. Expression of GFP-scapinin (wild type) also stimulated cell spreading, but mutation in the RPEL-repeat domain abolished both the actin binding and the cell spreading activity. PP1-binding deficient mutants strongly induced cell retraction. Long and branched cytoplasmic processes were developed during the cell retraction. These results suggest that scapinin enhances cell spreading and motility through direct interaction with actin and that PP1 plays a regulatory role in scapinin-induced morphological changes.ArticlePLOS ONE. 4(1):e4247 (2009)journal articl

A molecular roadmap of the AGM region reveals BMP ER as a novel regulator of HSC maturation

In the developing embryo, hematopoietic stem cells (HSCs) emerge from the aorta-gonad-mesonephros (AGM) region, but the molecular regulation of this process is poorly understood. Recently, the progression from E9.5 to E10.5 and polarity along the dorso-ventral axis have been identified as clear demarcations of the supportive HSC niche. To identify novel secreted regulators of HSC maturation, we performed RNA sequencing over these spatiotemporal transitions in the AGM region and supportive OP9 cell line. Screening several proteins through an ex vivo reaggregate culture system, we identify BMP ER as a novel positive regulator of HSC development. We demonstrate that BMP ER is associated with BMP signaling inhibition, but is transcriptionally induced by BMP4, suggesting that BMP ER contributes to the precise control of BMP activity within the AGM region, enabling the maturation of HSCs within a BMP-negative environment. These findings and the availability of our transcriptional data through an accessible interface should provide insight into the maintenance and potential derivation of HSCs in culture.Peer reviewe

A Unified Geometric Framework for Kinematics, Dynamics and Concurrent Control of Free-base, Open-chain Multi-body Systems with Holonomic and Nonholonomic Constraints

This thesis presents a geometric approach to studying kinematics, dynamics and controls of open-chain multi-body systems with non-zero momentum and multi-degree-of-freedom joints subject to holonomic and nonholonomic constraints. Some examples of such systems appear in space robotics, where mobile and free-base manipulators are developed. The proposed approach introduces a unified framework for considering holonomic and nonholonomic, multi-degree-of-freedom joints through: (i) generalization of the product of exponentials formula for kinematics, and (ii) aggregation of the dynamical reduction theories, using differential geometry. Further, this framework paves the ground for the input-output linearization and controller design for concurrent trajectory tracking of base-manipulator(s). In terms of kinematics, displacement subgroups are introduced, whose relative configuration manifolds are Lie groups and they are parametrized using the exponential map. Consequently, the product of exponentials formula for forward and differential kinematics is generalized to include multi-degree-of-freedom joints and nonholonomic constraints in open-chain multi-body systems. As for dynamics, it is observed that the action of the relative configuration manifold corresponding to the first joint of an open-chain multi-body system leaves Hamilton's equation invariant. Using the symplectic reduction theorem, the dynamical equations of such systems with constant momentum (not necessarily zero) are formulated in the reduced phase space, which present the system dynamics based on the internal parameters of the system. In the nonholonomic case, a three-step reduction process is presented for nonholonomic Hamiltonian mechanical systems. The Chaplygin reduction theorem eliminates the nonholonomic constraints in the first step, and an almost symplectic reduction procedure in the unconstrained phase space further reduces the dynamical equations. Consequently, the proposed approach is used to reduce the dynamical equations of nonholonomic open-chain multi-body systems. Regarding the controls, it is shown that a generic free-base, holonomic or nonholonomic open-chain multi-body system is input-output linearizable in the reduced phase space. As a result, a feed-forward servo control law is proposed to concurrently control the base and the extremities of such systems. It is shown that the closed-loop system is exponentially stable, using a proper Lyapunov function. In each chapter of the thesis, the developed concepts are illustrated through various case studies.Ph

Concurrent Design of Reconfigurable Robots using a Robotic Hardware-in-the-loop Simulation

This thesis discusses a practical approach to the concurrent analysis and synthesis of reconfigurable robot manipulators based on the alternative design methodology of Linguistic Mechatronics (LM) as well as the utilization of a modular Robotic Hardware-In-the-Loop Simulation (RHILS) platform. Linguistic Mechatronics is a systematic design methodology for mechatronic systems, which formalizes subjective notions and simplifies the optimization process, in the hope that numerous naturally different design variables can be considered concurrently. The methodology redefines the ultimate goal of design based on the qualitative notions of wish and must satisfactions. The underlying concepts of LM are investigated through a simulation case study. In addition, the RHILS platform involving physical joint modules and a control unit, which takes into account various physical phenomena and reduces the simulation complexities, is employed to the design architecture. Ultimately, the new approach is applied to redesigning kinematic, dynamic and control parameters of an industrial manipulator.MAS