Abstract:
Multiple kernel learning algorithms are proposed to combine kernels in order to obtain a better similarity measure or to integrate feature representations coming from different data sources. Most of the previous research on such methods is focused on the computational efficiency issue. However, it is still not feasible to combine many kernels using existing Bayesian approaches due to their high time complexity. We propose a fully conjugate Bayesian formulation and derive a deterministic variational approximation, which allows us to combine hundreds or thousands of kernels very efficiently. We briefly explain how the proposed method can be extended for multiclass learning and semi-supervised learning. Experiments with large numbers of kernels on benchmark data sets show that our inference method is quite fast, requiring less than a minute. On one bioinformatics and three image recognition data sets, our method outperforms previously reported results with better generalization performance.

Abstract:
A Matlab implemented computer code for spectral resolution is presented. The code enables the user to resolve the UV-visible absorption spectrum of a mixture of up to 3 previously known components, to the individual components, thus, evaluating their quantities. The resolving procedure is based on searching the combination of the components which yields the spectrum which is the most similar (minimal RMSE) to the measured spectrum of the mixture. Examples of using the software for pKa value estimation and multicomponent analysis are presented and other implementations are suggested.

Abstract:
The purpose of this study was to investigate the effects of a Computer-Assisted Instruction designed according to 7E model of constructivist learning(CAI7E) related to ‘‘electrostatic’’ topic on physics student teachers’ cognitive development, misconceptions, self-efficacy perceptions and attitudes. The study was conducted in 2006–2007 academic year and was carried out in three different classes taught by the same teacher, in which there were 79 2nd, 3rd and 4th grade university students, in central city of Diyarbak r in Turkey. An experimental research design including the electrostatic achievement test (EAT), the electrostatic concept test (ECT), physics attitude scale (PAS) and self-efficacy perception scale (SEPS) was applied at the beginning and at the end of the research as pre-test and post-test. After the treatment, general achievement in EAT increased (P<0.05), but not all of subgroup. Difference between pre-test and post-test both knowledge and application levels of cognitive domain was found significant (P<0.05), but not in comprehension level. This result showed that using CAI7E in teaching electrostatic topic was very effective for physics student teachers already learned this topic in several physics course to reach knowledge and application levels of cognitive domain. Analysis of electrostatic concept test (ECT); CAI7E changed students’ misconceptions related to electrostatic and electric field positively (P<0.05) and additionally change was found in SEPS (P<0.05). It was also found out that there was no change about students’ attitudes towards physics (P>0.05).

Abstract:
Students enter the classrooms with a preexisting knowledge of science concepts. These science concepts sometimes show inconsistency with the accepted ones by the scientists and called as misconceptions. Studies applied science field have to get possession of abilities that not only detect these misconceptions also help to solve these problems. Hence, instructional methods that correct students’ misconceptions become important. In this sense, a material related to the physics course is designed according to 7E model with the help of instructional technology.

Abstract:
ABSTRACT In this article, two basic purposes are presented. First, taking effective feedbacks in the electronic learning environment about the learning level of students at the problem solving which are told in physics lessons and laboratories. Second, providing a possibility for students to repeat the subjects and solved problems by watching and listening, which are told in lessons and laboratories, whenever or wherever they want. For this purpose, in the first step, the problems solved in classroom and laboratories about physics and subject expressions are transferred to digital environment and e-learning materials are developed. In the second step, these materials are converted to standard SCORM (Sharable Content Object Reference Model) package and integrated to Course Management System (CMS).

Abstract:
A Matlab implemented computer code for spectral resolution is presented. The code enables the user to resolve the UV-visible absorption spectrum of a mixture of up to 3 previously known components, to the individual components, thus, evaluating their quantities. The resolving procedure is based on searching the combination of the components which yields the spectrum which is the most similar (minimal RMSE) to the measured spectrum of the mixture. Examples of using the software for pKa value estimation and multicomponent analysis are presented and other implementations are suggested.

Abstract:
We analyze the space of deterministic, dominant-strategy incentive compatible, individually rational and Pareto optimal combinatorial auctions. We examine a model with multidimensional types, nonidentical items, private values and quasilinear preferences for the players with one relaxation; the players are subject to publicly-known budget constraints. We show that the space includes dictatorial mechanisms and that if dictatorial mechanisms are ruled out by a natural anonymity property, then an impossibility of design is revealed. The same impossibility naturally extends to other abstract mechanisms with an arbitrary outcome set if one maintains the original assumptions of players with quasilinear utilities, public budgets and nonnegative prices.

Abstract:
In the present article we calculate the expectation values of of S$_{z}$ and S$^{2}$ operators for spin-1 and spin-3/2 particles by expanding a general wave function which includes all spin values. The results are same as in the stantard quantum mechanics.

Abstract:
We consider the "coded cooperative data exchange problem" for general graphs. In this problem, given a graph G=(V,E) representing clients in a broadcast network, each of which initially hold a (not necessarily disjoint) set of information packets; one wishes to design a communication scheme in which eventually all clients will hold all the packets of the network. Communication is performed in rounds, where in each round a single client broadcasts a single (possibly encoded) information packet to its neighbors in G. The objective is to design a broadcast scheme that satisfies all clients with the minimum number of broadcast rounds. The coded cooperative data exchange problem has seen significant research over the last few years; mostly when the graph G is the complete broadcast graph in which each client is adjacent to all other clients in the network, but also on general topologies, both in the fractional and integral setting. In this work we focus on the integral setting in general undirected topologies G. We tie the data exchange problem on G to certain well studied combinatorial properties of G and in such show that solving the problem exactly or even approximately within a multiplicative factor of \log{|V|} is intractable (i.e., NP-Hard). We then turn to study efficient data exchange schemes yielding a number of communication rounds comparable to our intractability result. Our communication schemes do not involve encoding, and in such yield bounds on the "coding advantage" in the setting at hand.

Abstract:
In highly distributed Internet measurement systems distributed agents periodically measure the Internet using a tool called {\tt traceroute}, which discovers a path in the network graph. Each agent performs many traceroute measurement to a set of destinations in the network, and thus reveals a portion of the Internet graph as it is seen from the agent locations. In every period we need to check whether previously discovered edges still exist in this period, a process termed {\em validation}. For this end we maintain a database of all the different measurements performed by each agent. Our aim is to be able to {\em validate} the existence of all previously discovered edges in the minimum possible time. In this work we formulate the validation problem as a generalization of the well know set cover problem. We reduce the set cover problem to the validation problem, thus proving that the validation problem is ${\cal NP}$-hard. We present a $O(\log n)$-approximation algorithm to the validation problem, where $n$ in the number of edges that need to be validated. We also show that unless ${\cal P = NP}$ the approximation ratio of the validation problem is $\Omega(\log n)$.