On the performance of improved quadrature spatial modulation

Quadrature spatial modulation (QSM) utilizes the in‐phase and quadrature spatial dimensions to transmit the real and imaginary parts of a single signal symbol, respectively. The improved QSM (IQSM) transmits two signal symbols per channel use through a combination of two antennas for each of the real and imaginary parts. The main contributions of this study can be summarized as follows. First, we derive an upper bound for the error performance of the IQSM. We then design constellation sets that minimize the error performance of the IQSM for several system configurations. Second, we propose a double QSM (DQSM) that transmits the real and imaginary parts of two signal symbols through any available transmit antennas. Finally, we propose a parallel IQSM (PIQSM) that splits the antenna set into equal subsets and performs IQSM within each subset using the same two signal symbols. Simulation results demonstrate that the proposed constellations significantly outperform conventional constellations. Additionally, DQSM and PIQSM provide a performance similar to that of IQSM while requiring a smaller number of transmit antennas and outperform IQSM with the same number of transmit antennas.     

Improving security of the Internet of Things via RF fingerprinting based device identification system

Neural Computing and Applications - Security is one of the primary concerns when designing wireless networks. Along detecting user identity, it is also important to detect the devices at the...     

Mechanical characterization and chemical resistances of cured unsaturated polyester resins modified with vinyl ester resins based on recycled poly(ethylene terephthalate)

Unsaturated polyester resin (UP) was prepared from glycolyzed oligomer of poly(ethylene terephthalate) (PET) waste based on diethylene glycol (DEG). New diacrylate and dimethacrylate vinyl ester resins prepared from glycolysis of PET with tetraethylene glycol were blended with UP to study the mechanical characteristics of the cured UP. The vinyl ester resins were used as crosslinking agents for unsaturated polyester resin diluted with styrene, using free‐radical initiator and accelerator. The mechanical properties of the cured UP resins were evaluated. The compressive properties of the cured UP/styrene resins in the presence of different vinyl ester concentrations were evaluated. Increasing the vinyl ester content led to a pronounced improvement in the compression strength. The chemical resistances of the cured resins were evaluated through hot water, solvents, acid, and alkali resistance measurements. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 3175–3182, 2007     

Goal-driven automation of a deep space communications station: a case study in knowledge engineering for plan generation and execution

Abstract: This paper describes the application of Artificial Intelligence techniques for plan generation, plan execution, and plan monitoring to automate a Deep Space Communication Station. This automation allows a communication station to respond to a set of tracking goals by appropriately reconfiguring the communications hardware and software to provide the requested communications services. In particular this paper describes: (1) the overall automation architecture, (2) the plan generation and execution monitoring AI technologies used and implemented software components, and (3) the knowledge engineering process and effort required for automation. This automation was demonstrated in February 1995, at the DSS13 Antenna Station in Goldstone, CA on a series of Voyager tracks and the technologies demonstrated are being transferred to the operational Deep Space Network stations.     

Fate of Triton X-100 Applications on Water and Soil Environments: A Review

Triton X-100 applications as surfactant raises concern on water and soil environment due to its non-biodegradability and inhibition effect. This paper aims at reviewing Triton X-100 biodegradability and inhibition literature. It shows Triton X-100 is biodegradable by aerobic and anaerobic municipal wastewater sludge and Vibrio cyclitrophicus-sp-Nov organism. Adsorption and biodegradation are mechanisms of Triton removal. Triton inhibits anaerobic sludge organisms and some single aerobic organisms. Inhibition mechanisms are substrate shortage, physiological membrane-damaging and/or alteration in organism cell membrane. Thus Triton X-100 fate in the environment and its sustainable application can be controlled via proper selection of organism type, Triton concentration, and substrate.     

Antitumor activity and antioxidant role of a novel water-soluble carboxymethyl chitosan-based copolymer

In this study, a natural polymer, chitosan (CS) has been converted through modified procedures to produce a water-soluble nontoxic form that has been evaluated as a novel potential antitumor drug. CS was carboxymethylated and then further modified in mild aqueous medium via graft copolymerization using a new simple and reproducible method. The synthesized new derivative of carboxymethylated CS (DCMC) was fully characterized by numerous techniques including Fourier transform infrared spectroscopy (FT-IR), elemental analyzer (EA), scanning electron microscopy (SEM), two-dimensional wide-angle X-ray scattering (2D-WAXS), and differential scanning calorimetry (DSC). The anticancer activity of the DCMC was investigated using mice bearing Ehrlich ascites tumor cells (EAC) at different doses dissolved in isotonic saline. It has been found that treatment with DCMC significantly inhibited tumor growth in a dose-dependent manner. To better understand the molecular mechanism explaining the DCMC effect on cancer cells, we tested the response of EAC cells in vivo to DCMC using flow cytometry cell cycle analysis. The cell cycle analysis revealed a G?/M phase accumulation as well as a significant increase in sub-G? phase cells after treatment with DCMC. This indicates an induction of apoptosis in EAC cells associated with a highly significant decrease in tumor volume. In general, our results indicated that the DCMC is a regulator of tumor cell growth and differentiation not only by causing G?/M cell cycle arrest but also inducing their apoptotic death. Moreover, the estimated hematological profile such as hemoglobin, RBCs, as well as WBCs counts revealed normal levels in mice treated with DCMC, indicating the possibility of using the DCMC in cancer chemotherapy without causing anemia like other drugs. Biochemical assays also revealed that treatment with DCMC has led to an augmentation of the antioxidant defense system without affecting lipid peroxidation in EAC-bearing mice.     

Automated analysis and exploration of image databases: Results,progress, and challenges

In areas as diverse as earth remote sensing, astronomy, and medical imaging, image acquisition technology has undergone tremendous improvements in recent years. The vast amounts of scientific data are potential treasure-troves for scientific investigation and analysis. Unfortunately, advances in our ability to deal with this volume of data in an effective manner have not paralleled the hardware gains. While special-purpose tools for particular applications exist, there is a dearth of useful general-purpose software tools and algorithms which can assist a scientist in exploring large scientific image databases. This paper presents our recent progress in developing interactive semi-automated image database exploration tools based on pattern recognition and machine learning technology. We first present a completed and successful application that illustrates the basic approach: the SKICAT system used for the reduction and analysis of a 3 terabyte astronomical data set. SKICAT integrates techniques from image processing, data classification, and database management. It represents a system in which machine learning played a powerful and enabling role, and solved a difficult, scientifically significant problem. We then proceed to discuss the general problem of automated image database exploration, the particular aspects of image databases which distinguish them from other databases, and how this impacts the application of off-the-shelf learning algorithms to problems of this nature. A second large image database is used to ground this discussion: Magellan's images of the surface of the planet Venus. The paper concludes with a discussion of current and future challenges.     

Hierarchical Clustering Algorithms for Document Datasets

Fast and high-quality document clustering algorithms play an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of meaningful clusters. In particular, clustering algorithms that build meaningful hierarchies out of large document collections are ideal tools for their interactive visualization and exploration as they provide data-views that are consistent, predictable, and at different levels of granularity. This paper focuses on document clustering algorithms that build such hierarchical solutions and (i) presents a comprehensive study of partitional and agglomerative algorithms that use different criterion functions and merging schemes, and (ii) presents a new class of clustering algorithms called constrained agglomerative algorithms, which combine features from both partitional and agglomerative approaches that allows them to reduce the early-stage errors made by agglomerative methods and hence improve the quality of clustering solutions. The experimental evaluation shows that, contrary to the common belief, partitional algorithms always lead to better solutions than agglomerative algorithms; making them ideal for clustering large document collections due to not only their relatively low computational requirements, but also higher clustering quality. Furthermore, the constrained agglomerative methods consistently lead to better solutions than agglomerative methods alone and for many cases they outperform partitional methods, as well.