A Structured Inverse Spectrum Problem for Infinite Graphs and Unbounded Operators

Given an infinite graph $G$ on countably many vertices, and a closed, infinite set $\Lambda$ of real numbers, we prove the existence of an unbounded self-adjoint operator whose graph is $G$ and whose spectrum is $\Lambda$

On the treatment of uncertainty in innovation projects

Innovations encounter a relatively high level of uncertainty in their lifecycle path. As innovations are about implementing a new idea, they suffer from a shortage or lack of knowledge dependent on and directly proportional to the radical quality of novelty. They lack information to predict the future and face (high) uncertainty in the background knowledge used for the risk assessment. Incomplete information causes innovation risk analysts to assign subjective assumptions to simplify system models developed for innovation risk assessment. Subjective and non-subjective assumptions as uncertain assumptions are part of the background knowledge and source of uncertainty. This thesis tries to assess and treat innovation assumptions uncertainties by proposing a hybrid model which comprises the semi-quantitative risk assessment (SQRA) approach, extended semi-quantitative risk assessment (EQRA) approach, and knowledge dimension method. SQRA and EQRA highlight the criticality of assumptions and present a systematic approach to assess and treat assumption uncertainties. SQRA applies probabilistic analysis to conduct an assumptions risk assessment, and EQRA provides innovation managers with guidance on developing strategies to follow up uncertain assumptions over the process implementation. The knowledge dimension technique evaluates and communicates the strength of background knowledge applied in assumptions risk assessment to innovation decision-makers expressing whole uncertainty aspects in the background knowledge (assumptions, data, models, and expert judgment). The model can effectively contribute to innovation risks and uncertainties management during the project execution.2021-09-29T16:30:09

GENERALIZABLE MODELING OF CHARGE TRANSPORT IN SINGLE ELECTRON TRANSISTOR DEVICES: APPLICATION TO THERMAL SENSITIVITY IN SEMICONDUCTING ISLAND SYSTEMS

Electronic devices, especially MOSFETs, have been dimensionally scaled down to enhance operation of integrated circuits, addressing challenges such as current leakage, fluctuation of intrinsic semiconductor properties, and power dissipation. Reaching dimensions below 20 nm, there are fundamental limitations that are difficult to overcome, driving alternative device paradigms to be sought utilizing the quantum mechanical behavior of electrons. Single electron transistor (SET) devices are examples of a new generation of low-power transistors designed to transport information via single electron tunneling through one or more islands separated by tunnel junctions. Experimentally explored SET devices have shown that there are advantages to using semiconductors for the islands as compared to using metallic islands. Although semiconducting SET devices have been experimentally explored, the simulation of the transport characteristics of such devices remains an area requiring further development for gaining deeper insights into the device behavior. Progress has been limited due to the complexity of the underlying physics of electron tunneling to and from a semiconducting nanometer-scale island. Ab initio calculations are capable of accurate modeling of the physics, but are computationally prohibitive given the nanometer scales represented in the system. This work is dedicated to understanding the behavior of electron transport involving semiconducting islands and has led to development of a kinetic Monte Carlo (KMC)-based algorithm to simulate the current-voltage characteristics of single electron transistor (SET) devices comprised of one or two semiconducting nanometer-scale islands and three electrodes (source, drain and gate) with regard to the terminal potentials, temperature. The impact of the band gap, the more complex density of states, charging energy, and island-size-dependent discreteness of energy levels in a semiconducting island on the tunneling rate are also examined. Semiconducting islands provide parameters that can be utilized to control the SET characteristics. The alignment of the semiconducting island’s band gap with the Fermi energy of the electrodes can be tuned to control the degree of temperature’s impact on the currant-voltage characteristics of the device. It is confirmed in this work that our model is generalizable to predict electron tunneling in materials with different band structure

Half-Day Vulnerabilities: A study of the First Days of CVE Entries

The National Vulnerability Disclosure Database is an invaluable source of information for security professionals and researchers. However, in some cases, a vulnerability report is initially published with incomplete information, a situation that complicates incident response and mitigation. In this paper, we perform an empirical study of vulnerabilities that are initially submitted with an incomplete report, and present key findings related to their frequency, nature, and the time needed to update them. We further present a novel ticketing process that is tailored to addressing the problems related to such vulnerabilities and demonstrate the use of this system with a real-life use case.Comment: Please cite as: Kobra Khanmohammadi & Raphael Khoury, Half-Day Vulnerabilities: A study of the First Days of CVE Entries, The Conference on Applied Machine Learning in Information Security (CAMLIS), Arlington, VI, USA, oct. 2

ELECTROPHORETIC DEPOSITION OF HYDROXYAPATITE NANOPARTICLES FROM DIFFERENT ALCOHOLIC SUSPENSIONS: EFFECT OF TRIETHANOLAMINE

The suspensions of HA nanoparticles in different alcohols (methanol, ethanol, isopropanol and butanol) were prepared and triethanolamine (TEA) was used as a dispersant. The results obtained for the conductivity of suspensions, zeta potential of particles, sedimentation of suspensions and FTIR analysis showed that protonated TEA (H+TEA) is adsorbed on the surface of HA nanoparticles. The adsorption of TEA on the HA nanoparticles is strong enough so that the degree of its protonation in the alcoholic suspensions determines its optimum concentration. TEA captures proton more easily from lower molecular weight alcohols; so at same TEA concentration there will be more H+TEA in lower molecular weight alcohols leading to its smaller optimum concentration in them: methanol: 0.67mL/L, ethanol: 0.67mL/L, isopropanol: 4mL/L and butanol: 8mL/L. Electrophoretic deposition (EPD) was performed at 60V. The current density and in-situ kinetics of EPD were recorded. The f factor was calculated against TEA concentration. f factor decreased with TEA concentration in all alcoholic suspensions due to the increase in the electrochemical potential difference at the interface between deposit and suspension. At same TEA concentration, the f factor was smaller in low molecular size alcohols due to their lower viscosity leading to the faster detachment of particles in the interface. In contrast to isopropanolic and butanolic suspensions, the current density from methanolic and ethanolic suspensions containing TEA increased during EPD. If the resistivity of deposit is higher than the corresponding suspension (as usually is) the current density decreases and vice versa. It is concluded that the increase in current density during EPD from methanolic and ethanolic suspensions is due to the detachment of H+TEA from the surface of HA nanoparticles as a result of applied electric field leading to the high concentration of free ions and so less resistivity of deposit relative to the corresponding suspension