Novel tiO2 nanocatalysts for wastewater purification: tapping energy from the sun.

Water treatment using TiO2 semiconductor as a durable heterogeneous photocatalyst has been the focus of environmentalists in recent years. Currently, we developed an inexpensive and highly efficient approach for synthesizing nitrogen-doped TiO2 with lower band-gap energy that can respond to visible light. Doping on the molecular scale led to an enhanced nitrogen concentration of up to 21.8%. Reflectance measurements showed the synthesized N-doped TiO2 nanoparticles are catalytically active with the absorbance that extends into the visible region up to 600 nm. The water purification potential of this new class of compound was evaluated by studying the photodegradation of Acid Orange 7 (AO7) and E. coli. Experiments were conducted to compare the photocatalytic activities of N-doped TiO2 nanocatalysts and commercially available Degussa P25 power under identical solar light exposure. N-doped TiO2 demonstrated superior photocatalytic activities in both chemical compound degradation and bactericidal reactions. The result of this study shows the potential of applying new generations of catalyst for wastewater purification and disinfection.     

Sampling and the discretization theorem

An algorithm was obtained for restoration of a continuous process from a finite number of its equispaced discrete samples. The necessary and sufficient sampling conditions were formulated.     

Learning with belief levels

We study learning of predicate logics formulas from “elementary facts,” i.e. from the values of the predicates in the given model. Several models of learning are considered, but most of our attention is paid to learning with belief levels. We propose an axiom system which describes what we consider to be a human scientist's natural behavior when trying to explore these elementary facts. It is proved that no such system can be complete. However we believe that our axiom system is “practically” complete. Theorems presented in the paper in some sense confirm our hypothesis.     

On the SEP of Cooperative Diversity with Opportunistic Relaying

We analyze the exact symbol error probability (SEP) of cooperative diversity with opportunistic amplify-and-forward (AF) relaying. The benefit of this opportunism to the SEP is assessed by comparing with maximal ratio combining of orthogonal multiple AF relay transmissions.     

Softwarekartographie

Zusammenfassung  Anwendungslandschaften in Unternehmen sind langlebige hoch-komplexe Strukturen bestehend aus hunderten bis tausenden von miteinander vernetzten betrieblichen Informationssystemen, die von Personen mit sehr unterschiedlichen Interessen und Erfahrungshintergrund konzipiert, erstellt, modifiziert, betrieben, genutzt und finanziert werden. Die Softwarekartographie zielt darauf ab, die Kommunikation zwischen diesen Personen durch zielgruppenspezifische verst?ndliche graphische Visualisierungen zu unterstützen, die Gesch?fts- und Informatik-Aspekte gleicherma?en berücksichtigen, und die speziell für langfristige und strategische Management-Betrachtungen geeignet sind. In diesem Beitrag fassen wir zun?chst die in der betrieblichen Praxis wohlbekannten Probleme beim Management von Anwendungslandschaften zusammen und diagnostizieren erhebliche Kommunikationsdefizite. Da Anwendungslandschaften als Systeme von Systemen mit Menschen als integrale Systembestandteile zu verstehen sind, werden Karten als attraktiver L?sungsansatz identifiziert und die wesentlichen Konzepte der Softwarekartographie anhand von Beispielen vorgestellt. Dabei werden Querbezüge zu anderen Fachgebieten der Informatik und Wirtschaftsinformatik hergestellt, und die bisherige Nutzung der Forschungsergebnisse in der Praxis gezeigt.     

Modeling wireless fading channels via stochastic differential equations: identification and estimation based on noisy measurements

This paper is concerned with modeling and identification of wireless channels using noisy measurements. The models employed are governed by stochastic differential equations (SDEs) in state space form, while the identification method is based on the expectation-maximization (EM) algorithm and Kalman filtering. The algorithm is tested against real channel measurements. The results presented include state space models for the channels, estimates of inphase and quadrature components, and estimates of the corresponding Doppler power spectral densities (DPSDs), from sample noisy measurements. Based on the available measurements, it is concluded that state space models of order two are sufficient for wireless flat fading channel characterization.     

One-to-Many and Many-to-One Optical Chaos Communications Using Semiconductor Lasers

A theoretical construction of one-to-many (OTM) and many-to-one (MTO) chaos synchronization communications using semiconductor lasers is presented. One center laser provides strong injections (strong link) to other side lasers, and the side lasers also provide weak injections (weak link) to the center one. Simulation results show that the side lasers synchronize with the center laser through injection-locking. In addition, messages transmitted via the strong links or the weak links experience strong chaos pass filtering, enabling us to realize OTM and MTO communications.     

基于MoCA标准的家庭网络研究

本文描述了一种基于MOCA标准的家庭网络,并对该网络及设备进行了基本性能的测试.本文首先介绍了家庭网络的发展现状,对目前的各种家庭网络标准进行了比较.在此基础上详细描述了基于MOCA标准的家庭网络,并对该网络的设计,实现、网络性能进行了详述.然后对该网络进行了测试并得出了相关的测试结论.最后指出该网络的不足及改进之处.     

Self-adjusting the intensity of assortative mating in genetic algorithms

Mate selection plays a crucial role in both natural and artificial systems. While traditional Evolutionary Algorithms (EA) usually engage in random mating strategies, that is, mating chance is independent of genotypic or phenotypic distance between individuals, in natural systems non-random mating is common, which means that somehow this mechanism has been favored during the evolutionary process. In non-random mating, the individuals mate according to their parenthood or likeness. Previous studies indicate that negative assortative mating (AM)—also known as dissortative mating—, which is a specific type of non-random mating, may improve EAs performance by maintaining the genetic diversity of the population at a higher level during the search process. In this paper we present the Variable Dissortative Mating Genetic Algorithm (VDMGA). The algorithm holds a mechanism that varies the GA’s mating restrictions during the run by means of simple rule based on the number of chromosomes created in each generation and indirectly influenced by the genetic diversity of the population. We compare VDMGA not only with traditional Genetic Algorithms (GA) but also with two preceding non-random mating EAs: the CHC algorithm and the negative Assortative Mating Genetic Algorithm (nAMGA). We intend to study the effects of the different methods in the performance of GAs and verify the reliability of the proposed algorithm when facing an heterogeneous set of landscapes. In addition, we include the positive Assortative Mating Genetic Algorithm (pAMGA) in the experiments in order test both negative and positive AM mechanisms, and try to understand if and when negative AM (or DM) speeds up the search process or enables the GAs to escape local optima traps. For these purposes, an extensive set of optimization test problems was chosen to cover a variety of search landscapes with different characteristics. Our results confirm that negative AM is effective in leading EAs out of local optima traps, and show that the proposed VDMGA is at least as efficient as nAMGA when applied to the range of our problems, being more efficient in very hard functions were traditional GAs usually fail to escape local optima. Also, scalability tests have been made that show VDMGA ability to decrease optimal population size, thus reducing the amount of evaluations needed to attain global optima. We like to stress that only two parameters need to be hand-tuned in VDMGA, thus reducing the tuning effort present in traditional GAs and nAMGA.