Enhanced gravimetric CO2 capacity and viscosity for ionic liquids with cyanopyrrolide anion

Ionic Liquids (ILs) are considered as alternative solvents for the separation of CO₂ from flue gas due mainly to their CO₂ affinity and thermal stability. The cation architecture in a matrix of ammonium and mostly phosphonium‐based ILs with 2‐cyanopyrrolide as the anion to evaluate its impact on gravimetric CO₂ absorption capacity, viscosity, and thermal stability and the three fundamental properties vital for application realization are systematically investigated. Among the investigated ILs, [P2,2,2,8][2‐CNpyr] demonstrated the lowest viscosity, 95 cP at 40°C, and highest CO₂ uptake, 114 mg CO₂ per g IL at 40°C. Combined effects of asymmetry and the optimized chain lengths also resulted in improved thermal stability for [P2,2,2,8][2‐CNpyr], with a mass loss rate of 1.35 × 10^?6 g h^?1 (0.0067 mass % h^?1) at 80°C. © 2015 American Institute of Chemical Engineers AIChE J, 61: 2280–2285, 2015     

Empirical Correlations for Estimating Filtrate Volume of Water Based Drilling Fluids

Standard American Petroleum Institute (API) filter press is generally used for identifying the filtrate volume of drilling fluids and works only at very low pressures. In fact, during a drilling operation, at downhole conditions, the pressures encountered are significantly higher than what is used during standard API filter press tests. A relationship between the well-known fluid properties and the filtrate volume test is developed. In this study, experiments have been conducted for different water-clay mixtures with varying concentrations at different pressure values by using standard API filter press and HP&HT (high-pressure high-temperature) filter press. The relationship between physical and chemical properties of water-clay mixtures and filtrate volume is analyzed. An empirical correlation has been developed for estimating filtrate volume using basic information of the mud (i.e., rotational viscometer readings, density, pressure, cation exchange capacity, and chemical composition). The developed correlation can estimate filtrate volume with an error less than 20% for a wide range of pressure values.     

Wettability of tundish periclase lining by steel

Results of a study of the wettability of the tundish periclase lining by molten steel using a sessile drop method are presented. The wetting angle θ tends to decrease with increase in temperature and contact time on adding glass fiber and Fe₂O₃ powder in excess of 2% to the magnesite powder; a similar effect is observed in steels high in manganese. An increase in angle θ is observed on adding carbon fiber or glass fiber (not in excess of 1%) to the magnesite powder; the angle θ tends to increase with increase in MgO powder grain size and with carbon contained in steel in excess of 0.04%. __________ Translated from Novye Ogneupory, No. 1, pp. 63–68, January, 2006.     

A Novel Approach to Steganography: Enhanced Least Significant Bit Substitution Algorithm Integrated with Self-Determining Encryption Feature

One of the most well-known and used algorithms for Steganography is Least Significant Bit (LSB) substitution. Although LSB has several advantages such as simplicity, efficiency, and easy-to-do implementation, it has some distinct disadvantages such as it openness to miscellaneous attacks. In this study, we aim to improve the traditional LSB algorithm by eliminating its main disadvantage, being easy to detect, and this way propose an enhanced LSB algorithm called E-LSB. We mainly aim to minimize differences which are due to encryption and image hiding steps in LSB algorithm and make it more difficult to notice that some text has been hidden in the original cover image.
As most of the researchers and practitioners in security field argue, stenographic techniques alone are not sufficient for protecting sensitive information and thus must be used together with encryption algorithms. Therefore, the proposed approach integrates E-LSB with an encryption algorithm. E-LSB does not modify the file size and allows the flexibility of choosing one of well-known encryption algorithms including RSA, AES and CAESAR, but others can be implemented in it. With a set of experiments, the proposed approach is compared with the traditional LSB based embedding approach, and its efficiency and usability is analyzed. A set of performance evaluations realized with the developed software tool based on E-LSB algorithm show that E-LSB is better than the traditional LSB algorithm from security point of view.     

A New Mobile Robot Toolbox for Matlab

In this study, a wheeled mobile robot navigation toolbox for Matlab is presented. The toolbox includes algorithms for 3D map design, static and dynamic path planning, point stabilization, localization, gap detection and collision avoidance. One can use the toolbox as a test platform for developing custom mobile robot navigation algorithms. The toolbox allows users to insert/remove obstacles to/from the robot’s workspace, upload/save a customized map and configure simulation parameters such as robot size, virtual sensor position, Kalman filter parameters for localization, speed controller and collision avoidance settings. It is possible to simulate data from a virtual laser imaging detection and ranging (LIDAR) sensor providing a map of the mobile robot’s immediate surroundings. Differential drive forward kinematic equations and extended Kalman filter (EKF) based localization scheme is used to determine where the robot will be located at each simulation step. The LIDAR data and the navigation process are visualized on the developed virtual reality interface. During the navigation of the robot, gap detection, dynamic path planning, collision avoidance and point stabilization procedures are implemented. Simulation results prove the efficacy of the algorithms implemented in the toolbox.     

Change detection in desktop virtual environments: An eye-tracking study

It is common knowledge that attention is important for learning. We need to utilize attention in order to learn something efficiently and effectively. Similarly, we may also need to acquire familiarity with (i.e., learn) our surroundings in order to utilize our attention. In this study, learning is defined as a product of one’s exposure to natural visual stimuli. Using a virtual model of a natural scene, we investigate both attention and its relationship to learning, according to this definition. Specifically, our focus is the effect of environment familiarity on gaze direction. Our findings reveal that the factor of familiarity with one’s surroundings in virtual reality environments exerts a significant influence on peoples’ ability to detect a variety of specific changes that occur within scenes under their observation.