Evaluation of an adaptive and intelligent educational hypermedia for enhanced individual learning of mathematics: A qualitative study

The purpose of this study is to design a personalized adaptive and intelligent web based tutoring system based on learning style and expert system named UZWEBMAT and to evaluate its effects on 10th grade students’ learning of the unit of probability. In the study, initially, learning objects were prepared in three different ways in relation to three sub-learning areas of Visual–Auditory–Kinesthetic (VAK) learning style for each subject of the probability unit. These were appropriate for secondary school mathematics curricula. Then, they were transferred into the digital environment. Each student’s dominant learning style determines the content to which s/he will be directed since s/he is directed to the content that is appropriate for his/her learning style. The course to be followed by the students within UZWEBMAT and their browsing around the pages are decided by expert system integrated into the system. This expert system sets the situations in which s/he will get solution supports and the course s/he will follow in accordance with the performance of the student. Hereby, each student may follow a different course, and the solution supports s/he will get may also differ highlighting the individual learning. The sample of the study consists of 81 10th grade students and 3 mathematics teachers from two high schools in Trabzon, Turkey. Qualitative data were obtained both from the teachers and students participating in the study in order to answer the research questions about the implementation and evaluation of UZWEBMAT for mathematics teaching in a high school classroom. Obtained data were analyzed using qualitative data analysis methods. According to the results of the present study, positive opinions of students and teachers such as taking into account the individual learning differences and deriving mathematical relations and formulas through exploration became prominent. In addition, there were also other positive opinions of students and teachers such as providing permanent learning and introducing learning responsibility to the students. In this sense, it was concluded that UZWEBMAT is a beneficial instrument for both students and teachers.     

Natural frequencies of a flat viaduct road part simply supported on two ends

Viaduct roads have wide application in big cities with high traffic loads, in order to decrease traffic density and to connect subways to highways. Viaduct roads are constructed using steel structures instead of concrete ones in areas of earthquake risks. The low weight of steel structures however causes problems such as vibration and noise. There is increasing demand especially in populated areas to suppress vibration and noise on highway roads for reducing noise-related environmental pollution. In this study, bending vibrations of rectangular plate viaduct roads, which are supported by six fixed elements of rectangular cross-sectional elements are considered. Natural frequencies are obtained using the Rayleigh-Ritz technique, finite elements analysis, experimentally and neural networks (NN).     

Calculations of the Elastic Scattering Properties of Ultra-cold Francium Isotopes

The calculations of the elastic scattering properties of ultra-cold francium isotopes are reported in detail. A parametric model potential for the triplet molecular states of the Fr₂ is represented, and the scattering lengths a_t and the effective range r_e are calculated using WKB and Numerov methods for Fr--Fr in the triplet state. The convergence of these scattering properties depending on a K⁰ parameter and core radius is also investigated using two methods: Quantum Defect Theory and analytical formula of Symskoviski.     

Application of InP Neural Network to ECG BeatClassification

This paper presents an application of a hybrid neural network structure to the classification of the electrocardiogram (ECG) beats. Three different feature extraction methods are comparatively examined: discrete cosine transform, wavelet transform and a direct method. Classification performances, training times and the numbers of nodes of Kohonen network, Restricted Coulomb Energy (RCE) network and the hybrid neural network are presented. To increase the classification performance and to decrease the number of nodes, the hybrid neural network is trained by Genetic Algorithms (GAs). Ten types of ECG beats obtained from the MIT-BIH database and from a real-time ECG measurement system are classified with a success of 98% by using the hybrid neural network structure and discrete cosine transform together.     

On periodic resource scheduling for continuous-media databases

The Enhanced Pay-Per-View (EPPV) model for providing continuous-media services associates with each continuous-media clip a display frequency that depends on the clip's popularity. The aim is to increase the number of clients that can be serviced concurrently beyond the capacity limitations of available resources, while guaranteeing a constraint on the response time. This is achieved by sharing periodic continuous-media streams among multiple clients. The EPPV model offers a number of advantages over other data-sharing schemes (e.g., batching), which make it more attractive to large-scale service providers. In this paper, we provide a comprehensive study of the resource-scheduling problems associated with supporting EPPV for continuous-media clips with (possibly) different display rates, frequencies, and lengths. Our main objective is to maximize the amount of disk bandwidth that is effectively scheduled under the given data layout and storage constraints. Our formulation gives rise to -hard combinatorial optimization problems that fall within the realm of hard real-time scheduling theory. Given the intractability of the problems, we propose novel heuristic solutions with polynomial-time complexity. We also present preliminary experimental results for the average case behavior of the proposed scheduling schemes and examine how they compare to each other under different workloads. A major contribution of our work is the introduction of a robust scheduling framework that, we believe, can provide solutions for a variety of realistic EPPV resource-scheduling scenarios, as well as any scheduling problem involving regular, periodic use of a shared resource. Based on this framework, we propose various interesting research directions for extending the results presented in this paper. Received June 9, 1998 / Accepted October 13, 1998     

Real-time monitoring of flank wear behavior of ceramic cutting tool in turning hardened steels

Flank wear of an alumina-based ceramic cutting tool was determined in hard turning two workpieces (AISI 4340 and 52100 hardened steels) at three cutting speeds (142, 181, and 264?m/min) to devise a real-time monitoring system. Results of the six turning tests were assessed using Kruskal?CWallis test, regression models, and linear trend analysis. Multiple non-linear regression models that explained variation in flank wear as a function of time (second) had a range of $ R_{\rm{adj}}^2 $ values of 27.7% for the test 4340-142 to 95% for the test 52100-181. Linear trend models revealed that the highest flank wear rate of the ceramic cutting tool belonged to the test 52100-181. Interaction effect of the three cutting speeds and the two workpiece types was determined to account for 82.2% of variation in flank wear (P?<?0.001). The real-time monitoring system designed in this study appeared to be promising in terms of determining and quantifying flank wear behavior of the ceramic cutting tool and optimal hard turning conditions.     

The Popov criterion and the inverse Nyquist method†

Kosonbrock's inverse Nyquist array (I.N.A.) theory for linear multivariable control Bystema with constant feedback elements is extended, to include systems lip to m nonlinear feedback elements, where the system has m inputs and m outputs. This extension is achieved by considering the Popov criterion for the most general case and through two further theorems. It shows that, as in the ease of Rosenbrock's I.N.A. theory, when certain auxiliary conditions are met with the help of suitable controllers, the design of multivariable controllers containing many non-linear feedbacks, can be based on the m frequency response loci corresponding to the diagonal entries of the open-loop inverse transfer function matrix. This leads to a simple design technique identical to the I.N.A. design method, suitable for use with a computer-aided design facility which permits a designer to use his intuitive understanding of transfer functions based on classical theory. The I.N.A. theory has been extended by Rosenbrock to cover systems having non-linear, time-varying feedback elements very recently.     

Particle-based simulation of the interaction between fluid and knitwear

We present a particle-based method to simulate and visualize the interaction of knitwear with fluids. The knitwear is modeled using spring-mass systems and the fluid is modeled using the smoothed particle hydrodynamics method. Two-way coupling is achieved by considering surface tension, capillary, and interparticle forces between the fluid and knitwear. The simulation of fluid and knitwear particles is performed on the graphics processing unit. Photorealistic rendering of knitwear and fluid is achieved by using a hardware-accelerated rasterization-based rendering technique. Our method is able to simulate and visualize the macro- and microstructure of free-form knitwear and reflective and refractive characteristics of the fluid surface.     

Propagation dynamics of ultra-short high-power laser pulses in air: supercontinuum generation and transverse ring formation

Numerical and semi-analytical results of the propagation of high-power ultra-short near IR laser pulses propagating in ionizing air are presented.