Cognitive Congestion Control for Data Portal

Network congestion is one of challenging tasks in communication networks and leads to queuing delay, packet loss or the blocking of new connections. Here, a data portal is considered as an application-based network, and a cognitive method is proposed to deal with congestion in this kind of network. The cognitive method is proposed to improve bandwidth sharing, and deal with congestion in a data portal. When the data portal is about climate change data, congestion control is more emphasized, because the scientific climate data is voluminous and there is a high traffic to/from data portal by the scientific community, research groups, and general readers

Remote sensing based on hyperspectral data analysis

In remote sensing, accurate identification of far objects, especially concealed objects is difficult. In this study, to improve object detection from a distance, the hyperspecral imaging and wideband technology are employed with the emphasis on wideband radar. As the wideband data includes a broad range of frequencies, it can reveal information about both the surface of the object and its content. Two main contributions are made in this study: 1) Developing concept of return loss for target detection: Unlike typical radar detection methods which uses radar cross section to detect an object, it is possible to enhance the process of detection and identification of concealed targets using the wideband radar based on the electromagnetic characteristics conductivity, permeability, permittivity, and return loss of materials. During the identification process, collected wideband data is evaluated with information from wideband signature library which has already been built. In fact, several classes (e.g. metal, wood, etc.) and subclasses (ex. metals with high conductivity) have been defined based on their electromagnetic characteristics. Materials in a scene are then classified based on these classes. As an example, materials with high electrical conductivity can be conveniently detected. In fact, increasing relative conductivity leads to a reduction in the return loss. Therefore, metals with high conductivity (ex. copper) shows stronger radar reflections compared with metals with low conductivity (ex. stainless steel). Thus, it is possible to appropriately discriminate copper from stainless steel. 2) Target recognition techniques: To detect and identify targets, several techniques have been proposed, in particular the Multi-Spectral Wideband Radar Image (MSWRI) which is able to localize and identify concealed targets. The MSWRI is based on the theory of robust capon beamformer. During identification process, information from wideband signature library is utilized. The WB signature library includes such parameters as conductivity, permeability, permittivity, and return loss at different frequencies for possible materials related to a target. In the MSWRI approach, identification procedure is performed by calculating the RLs at different selected frequencies. Based on similarity of the calculated RLs and RL from WB signature library, targets are detected and identified. Based on the simulation and experimental results, it is concluded that the MSWRI technique is a promising approach for standoff target detection

Hybrid POI Recommendation System for Tourism

Due to the increase in amount of available information, finding places and planning of the activities to be done during a tour can be strenuous. Tourists are looking for information about a place in which they have not been before, which worsen the selection of places that fit better with user’s preferences. Recommendation systems have been fundamentally applicable in tourism, suggest suitable places, and effectively prune large information from different locations, so tourists are directed toward those places where are matched with their needs and preferences. Several techniques have been studied for point-of-interest (POI) recommendation, including content-based which builds based on user preferences, collaborative filtering which exploits the behavior of other users, and different places, knowledge-based method, and several other techniques. These methods are vulnerable to some limitations and shortcomings related to recommendation environment such as scalability, sparsity, first-rater or gray sheep problems. This paper tries to identify the drawbacks that prevent wide spread use of these methodologies in recommendation. To improve performance of recommendation systems, these methods are combined to form hybrid recommenders. This paper proposes a novel hybrid recommender system which suggests tourism destinations to a user with minimal user interaction. Furthermore, we use sentiment analysis of user’s comments to enhance the efficiency of the proposed system

Production and structural studies of lung surfactant protein B (SP-B) peptides

Lung surfactant is a mixture of lipids and proteins which is critical for normal breathing by lining the air-water interface to reduce the surface tension. Lung surfactant protein B (SP-B) is the only essential protein component of lung surfactant complex due to the lethality of any SP-B deficiency. It is thought that SP-B functions by enhancing lipid rearrangements at various phases of the breathing cycle. However, the high-resolution structure and mechanism of SP-B are not yet understood. In the first part of this research, SP-B and a 7-residue deletion mutant of SP-B were produced recombinantly and partially characterized. In the second part of this research, circular dichroism, solution and solid-state nuclear magnetic resonance (NMR) methods were used to assess the structure of two SP-B-based peptides, Super-Mini-B and N-terminal insertion sequence (SP-B₁₋₇). Super-Mini-B is composed of the N-terminal 7-residue insertion sequence and the N-and C-terminal helices of SP-B. Interestingly, it was observed that Super-Mini-B produces greater lipid membrane perturbation than the peptide which lacks the N-terminal insertion sequence (i.e. Mini-B). Comparing the results of structural studies on Mini-B, SP-B₁₋₇ and Super-Mini-B helps unveil the contribution of the 7-residue insertion sequence to the function of SP-B

Handbook of Research on Tribology in Coatings and Surface Treatment

Advances are continuously being made in applying the coatings and surface treatments by different techniques to reduce the damages from tribology. Engineers need more detailed information to compare the capability of each coating process in wear resistant and lubrication applications. It is also important to focus on the concepts of tribology in various applications such as the manufacturing process, bio implants, machine elements, and corrosive environments. The need for a comprehensive resource addressing these findings in order to improve wear resistance is unavoidable.The Handbook of Research on Tribology in Coatings and Surface Treatment evaluates the latest advances the fabrication of wear-resistant and lubricant coatings by different techniques and investigates wear-resistant coatings and surface treatments in various applications such as the automobile industry. Covering a wide range of topics such as lubricant coatings and wearable electronic devices, it is ideal for engineers, industry professionalИспользуемые программы Adobe AcrobatПостоянно совершенствуются технологии нанесения покрытий и обработки поверхности различными методами, чтобы уменьшить повреждения, вызванные трибологией. Инженерам нужна более подробная информация, чтобы сравнить возможности каждого процесса нанесения покрытий в области износостойкости и смазки. Также важно сосредоточиться на концепциях трибологии в различных областях применения, таких как производственный процесс, биоимплантаты, элементы машин и агрессивные среды. Необходимость во всеобъемлющем ресурсе, посвященном этим выводам, с целью повышения износостойкости неизбежна. Руководство по исследованиям в области трибологии покрытий и обработки поверхностей оценивает последние достижения в области изготовления износостойких и смазочных покрытий различными методами и исследует износостойкие покрытия и обработку поверхностей в различных областях применения, таких как автомобильная промышленность. Охватывающий широкий спектр тем, таких как смазочные покрытия и носимые электронные устройства, он идеально подходи

Water Environment Risk Prediction Using Bayesian network

To improve better usage of water resources, risk prediction of water environment is crucial. Here, Bayesian network is applied to perform water environment risk prediction. In proposed approach, two steps are taken to choose the effective parameters in prediction. The proposed method is applied to water environment data in Nevada. Results show that the proposed method is effective for water environment risk prediction, and improvement of utilization of water resources