Optimal throughput performance in full-duplex relay assisted cognitive networks

Wireless Networks - In this paper, we study a full-duplex cooperative cognitive radio network with multiple full-duplex secondary users acting as potential relays for transmitting the packets of a...     

Multistage bayesian autonomy for high‐precision operation in a large field

This paper presents a generalized multistage bayesian framework to enable an autonomous robot to complete high‐precision operations on a static target in a large field. The proposed framework consists of two multistage approaches, capable of dealing with the complexity of high‐precision operation in a large field to detect and localize the target. In the multistage localization, locations of the robot and the target are estimated sequentially when the target is far away from the robot, whereas these locations are estimated simultaneously when the target is close. A level of confidence (LOC) for each detection criterion of a sensor and the associated probability of detection (POD) of the sensor are defined to make the target detectable with different LOCs at varying distances. Differential entropies of the robot and target are used as a precision metric for evaluating the performance of the proposed approach. The proposed multistage observation and localization approaches were applied to scenarios using an unmanned ground vehicle (UGV) and an unmanned aerial vehicle (UAV). Results with the UGV in simulated environments and then real environments show the effectiveness of the proposed approaches to real‐world problems. A successful demonstration using the UAV is also presented.     

Experimental and theoretical study for the determination of thermal conductivity of porous building material made with pumice and tragacanth

In this study, porous solid materials were produced with mixture combinations of materials such as tragacanth, cement, and pumice aggregate. Thermal conductivities of the produced materials were determined using hot wire methodology. The thermal conductivities of the produced samples ranged from 0.433 to 0.177 W/mK, depending on pumice diameter, pumice, tragacanth, and cement rates. A new model was developed to determine the effective thermal conductivities of the produced samples. The thermal conductivities obtained by the measurements were compared to the ones predicted by the model. The predicted values deviated as 1–31% from the measured values. It was finally shown that the experimental results were in good agreement to the predicted results.     

Formulation studies for mirtazapine orally disintegrating tablets

Abstract

Objective: Orally disintegrating tablets (ODTs) recently have gained much attention to fulfill the needs for pediatric, geriatric, and psychiatric patients with dysphagia. Aim of this study was to develop new ODT formulations containing mirtazapine, an antidepressant drug molecule having bitter taste, by using simple and inexpensive preparation methods such as coacervation, direct compression and to compare their characteristics with those of reference product (Remereon SolTab).

Materials and methods: Coacervation method was chosen for taste masking of mirtazapine. In vitro characterization studies such as diameter and thickness, weight variation, tablet hardness, tablet friability and disintegration time were performed on tablet formulations. Wetting time and in vitro dissolution tests of developed ODTs also studied using 900?mL 0.1?N HCl medium, 900?mL pH 6.8 phosphate buffer or 900?mL pH 4.5 acetate buffer at 37?±?0.2?°C as dissolution medium.

Results: Ratio of Eudragit® E-100 was chosen as 6% (w/w) since the dissolution profile of A1 (6% Eudragit® E-100) was found closer to the reference product than A2 (4% Eudragit® E-100) and A3 (8% Eudragit® E-100). Group D, E and F formulations were presented better results in terms of disintegration time. Dissolution results indicated that Group E and F formulations showed optimum properties in all three dissolution media.

Discussion: Formulations D1, D4, D5, E3, E4, F1 and F5 found suitable as ODT formulations due to their favorable disintegration times and dissolution profiles.

Conclusion: Developed mirtazapine ODTs were found promising in terms of showing the similar characteristics to the original formulation.     

Reusable water oxidation catalyst with dual active center for enhanced water oxidation: Iridium oxide nanoparticles immobilized on monodisperse-porous Mn5O8 microspheres

A reusable catalyst with dual active center for chemical water oxidation is synthesized for the first time by immobilization of iridium oxide nanoparticles (IrO₂ NPs) on monodisperse-porous manganese oxide microspheres acting both catalytic active center and support. Individual catalytic activity of manganese oxide microspheres is explained by multiple oxidation states of manganese which are capable of forming oxidative oxygen species. Monodisperse-porous microspheres in the form of Mn₅O₈, MnO₂ and Mn₂O₃ are used for synthesis of different catalysts and the highest activity in water oxidation is observed with the catalyst synthesized using Mn₅O₈ microspheres. The catalytic activity is correlated with the total Mn(II) and Mn(III) percentage of manganese oxide type selected for composite catalyst. The oxygen evolution up to 244 μmol is achieved in 30 min with the catalyst synthesized using Mn₅O₈ microspheres. Maximum TON and TOF numbers are obtained as 298 and 557 h^?1 with excellent reusability.     

Malware clustering using suffix trees

Clustering is an important problem in malware research, as the number of malicious samples that appear every day makes manual analysis impractical. Although these samples belong to a limited number of malware families, it is difficult to categorize them automatically as obfuscation is involved. By extracting relevant features we can apply clustering algorithms, then only analyze a couple of representatives from each cluster. However, classic clustering algorithms that compute the similarity between each pair of samples are slow when a large collection is involved. In this paper, the features will be strings of operation codes extracted from the binary code of each sample. With a modified suffix tree data structure we can find long enough substrings that correspond to portions of a program’s code. These substrings must be filtered against a database of known substrings so that common library code will be ignored. The items that have common substrings above a certain threshold will be grouped into the same cluster. Our algorithm was tested with data extracted from real-world malware and constructed quality clusters.