Exploring Factors That Influence Students’ Behaviors in Information Security

Due to the ever-increasing use of the Internet, information security has become a critical issue in society. This is especially the case for young adults who have different attitudes towards information security practices. In this research, we examine factors that motivate college students’ information security behaviors. Based on the concept of fear arousal in the presence of a threatened event, a well-founded theory known as Protection Motivation Theory (PMT) is adopted in the research model. Social norms and habit factors are integrated to the model as a means to assess students’ behaviors of information security. A survey of 202 responses is used to test the designed model using structural equation modeling to analyze relationships among variables. Results indicated that students are very motivated to practice information security if they perceive high levels of severity, response efficacy, response costs and self-efficacy. Their intentions, however, are not affected by perceived vulnerability or by social influence. Our findings suggest that PMT is a valuable model for predicting students’ attitudes towards information security and that their motivation is influenced by education in security awareness and understanding severity of such issues

Relaxation of superfluid turbulence in highly oblate Bose-Einstein condensates

We investigate thermal relaxation of superfluid turbulence in a highly oblate Bose-Einstein condensate. We generate turbulent flow in the condensate by sweeping the center region of the condensate with a repulsive optical potential. The turbulent condensate shows a spatially disordered distribution of quantized vortices and the vortex number of the condensate exhibits nonexponential decay behavior which we attribute to the vortex pair annihilation. The vortex-antivortex collisions in the condensate are identified with crescent-shaped, coalesced vortex cores. We observe that the nonexponential decay of the vortex number is quantitatively well described by a rate equation consisting of one-body and two-body decay terms. In our measurement, we find that the local two-body decay rate is closely proportional to $T^2/\mu$, where $T$ is the temperature and $\mu$ is the chemical potential.Comment: 7 pages, 9 figure

Observation of a Geometric Hall Effect in a Spinor Bose-Einstein Condensate with a Skyrmion Spin Texture

For a spin-carrying particle moving in a spatially varying magnetic field, effective electromagnetic forces can arise due to the geometric phase associated with adiabatic spin rotation of the particle. We report the observation of a geometric Hall effect in a spinor Bose-Einstein condensate with a skyrmion spin texture. Under translational oscillations of the spin texture, the condensate resonantly develops a circular motion in a harmonic trap, demonstrating the existence of an effective Lorentz force. When the condensate circulates, quantized vortices are nucleated in the boundary region of the condensate and the vortex number increases over 100 without significant heating. We attribute the vortex nucleation to the shearing effect of the effective Lorentz force from the inhomogeneous effective magnetic field.Comment: 9 pages, 11 figure

Multi-jet electrospinning of polystyrene/polyamide 6 blend: thermal and mechanical properties

Citation: Yoon, J. W., Park, Y., Kim, J., & Park, C. H. (2017). Multi-jet electrospinning of polystyrene/polyamide 6 blend: thermal and mechanical properties. Fashion and Textiles, 4, 12. doi:10.1186/s40691-017-0090-4Polystyrene (PS) has high thermal resistance thus can be applied as thermally comfortable textile. However, the application is limited due its low mechanical strength. In this study, polyamide 6 (PA6) was blended with PS to improve the mechanical strength of PS, by means of a multi-jet electrospinning. Content ratio of the blend web was measured by chemical immersion test and confocal microscopy analysis. Fiber content was in accordance with the number of syringes used for PS and PA6 respectively. The effects of content ratio on the web morphology, thermal resistance, tensile behavior, air and water vapor permeability, and surface hydrophilicity were investigated. The influence of environmental humidity during electrospinning process on three dimensional (3D) web structure was also reported. PS web produced from higher humidity had more pores and corrugations at the surface. The increased surface roughness and porosity led to the increased hydrophobicity and thermal resistance. Though the blending of PA6 with PS enhanced the mechanical strength, the added PA6 decreased air/water vapor permeability and thermal resistance. The lowered thermal resistance by the addition of PA6 was mainly attributed to higher thermal conductivity of PA6 material and lowered air content with PA6 fibers

Efficient and Privacy Preserving Group Signature for Federated Learning

Federated Learning (FL) is a Machine Learning (ML) technique that aims to reduce the threats to user data privacy. Training is done using the raw data on the users' device, called clients, and only the training results, called gradients, are sent to the server to be aggregated and generate an updated model. However, we cannot assume that the server can be trusted with private information, such as metadata related to the owner or source of the data. So, hiding the client information from the server helps reduce privacy-related attacks. Therefore, the privacy of the client's identity, along with the privacy of the client's data, is necessary to make such attacks more difficult. This paper proposes an efficient and privacy-preserving protocol for FL based on group signature. A new group signature for federated learning, called GSFL, is designed to not only protect the privacy of the client's data and identity but also significantly reduce the computation and communication costs considering the iterative process of federated learning. We show that GSFL outperforms existing approaches in terms of computation, communication, and signaling costs. Also, we show that the proposed protocol can handle various security attacks in the federated learning environment

Development of the MICROMEGAS Detector for Measuring the Energy Spectrum of Alpha Particles by using a 241-Am Source

We have developed MICROMEGAS (MICRO MEsh GASeous) detectors for detecting {\alpha} particles emitted from an 241-Am standard source. The voltage applied to the ionization region of the detector is optimized for stable operation at room temperature and atmospheric pressure. The energy of {\alpha} particles from the 241-Am source can be varied by changing the flight path of the {\alpha} particle from the 241 Am source. The channel numbers of the experimentally-measured pulse peak positions for different energies of the {\alpha} particles are associated with the energies deposited by the alpha particles in the ionization region of the detector as calculated by using GEANT4 simulations; thus, the energy calibration of the MICROMEGAS detector for {\alpha} particles is done. For the energy calibration, the thickness of the ionization region is adjusted so that {\alpha} particles may completely stop in the ionization region and their kinetic energies are fully deposited in the region. The efficiency of our MICROMEGAS detector for {\alpha} particles under the present conditions is found to be ~ 97.3 %