A Learning-Community Recommendation Approach for Web-Based Cooperative Learning

Cooperative learning has been defined as learners working together as a team to solve a problem to complete a task or to accomplish a common goal, which emphasizes the importance of interactions among members to promote the whole learning performance. With the popularity of society networks, cooperative learning is no longer limited to traditional classroom teaching activities. Since society networks facilitate to organize online learners, to establish common shared visions, and to advance learning interaction, the online community and online learning community have triggered the establishment of web-based societies. Numerous research literatures have indicated that the collaborative learning community is a critical issue to enhance learning performance. Hence, this paper proposes a learning community recommendation approach to facilitate that a learner joins the appropriate learning communities, which is based on k-nearest neighbor (kNN) classification. To demonstrate the viability of the proposed approach, the proposed approach is implemented for 117 students to recommend learning communities. The experimental results indicate that the proposed approach can effectively recommend appropriate learning communities for learners.

Preparation and Characterization of M. × Piperita L. Oil Based Gel Formulation

The essential oil of M. × piperita L. was formulated into a topical gel. The prepared gel was characterized for its pH, viscosity, spreadiblity, consistency and extrudiblity, while its stability was evaluated under different temperature conditions. The prepared M. × piperita oil gel was clear and transparent. The pH value of developed gel was 6.6, while its viscosity was 1200 cP. Spreadability and consistency of the M. × piperita oil gel was 10.7 g.cm/sec and 7 mm, respectively. The prepared gel showed good extrudiblity. During the stability studies, no significant change in pH and viscosity as a function of time for gel was observed, indicating stability of prepared formulation. The gel developed in this study is expected to forward the usage of M. × piperita essential towards commercial application.

Comparing Autoregressive Moving Average (ARMA) Coefficients Determination using Artificial Neural Networks with Other Techniques

Autoregressive Moving average (ARMA) is a parametric based method of signal representation. It is suitable for problems in which the signal can be modeled by explicit known source functions with a few adjustable parameters. Various methods have been suggested for the coefficients determination among which are Prony, Pade, Autocorrelation, Covariance and most recently, the use of Artificial Neural Network technique. In this paper, the method of using Artificial Neural network (ANN) technique is compared with some known and widely acceptable techniques. The comparisons is entirely based on the value of the coefficients obtained. Result obtained shows that the use of ANN also gives accurate in computing the coefficients of an ARMA system.

A WIP Control Based On an Intelligent Controller

In this study, a robust intelligent backstepping tracking control (RIBTC) system combined with adaptive output recurrent cerebellar model articulation control (AORCMAC) and H∞ control technique is proposed for wheeled inverted pendulums (WIPs) real-time control with exact system dynamics unknown. Moreover, a robust H∞ controller is designed to attenuate the effect of the residual approximation errors and external disturbances with desired attenuation level. The experimental results indicate that the WIPs can stand upright stably when using the proposed RIBTC.

Globally Convergent Edge-preserving Reconstruction with Contour-line Smoothing

The standard approach to image reconstruction is to stabilize the problem by including an edge-preserving roughness penalty in addition to faithfulness to the data. However, this methodology produces noisy object boundaries and creates a staircase effect. The existing attempts to favor the formation of smooth contour lines take the edge field explicitly into account; they either are computationally expensive or produce disappointing results. In this paper, we propose to incorporate the smoothness of the edge field in an implicit way by means of an additional penalty term defined in the wavelet domain. We also derive an efficient half-quadratic algorithm to solve the resulting optimization problem, including the case when the data fidelity term is non-quadratic and the cost function is nonconvex. Numerical experiments show that our technique preserves edge sharpness while smoothing contour lines; it produces visually pleasing reconstructions which are quantitatively better than those obtained without wavelet-domain constraints.

The Influence of Gravity on The Temporal Instability of Viscoelastic Liquid Curved Jets

A liquid curved jet has many applications in different industrial and engineering processes, such as the prilling process for generating small spherical pellets (fertilizer or magnesium). The liquids used are usually molten and contain small quantities of polymers and therefore can be modelled as non-Newtonian liquids. In this paper, we model the viscoelastic liquid jet by using the Oldroyd- B model. An asymptotic analysis has been used to simplify the governing equations. Furthermore, the trajectory and a linear temporal stability in the presence of gravity and rotation have been determined.

Mechanical Buckling of Engesser-Timoshenko Beams with a Pair of Piezoelectric Layers

This paper presents the elastic buckling of homogeneous beams with a pair of piezoelectric layers surface bonded on both sides of the beams. The displacement field of beam is assumed based on the Engesser-Timoshenko beam theory. Applying the Hamilton's principle, the equilibrium equation is established. The influences of applied voltage, dimensionless geometrical parameter and piezoelectric thickness on the critical buckling load of beam are presented. To investigate the accuracy of the present analysis, a compression study is carried out with a known data.

Global Existence of Periodic Solutions in a Delayed Tri–neuron Network

In this paper, a tri–neuron network model with time delay is investigated. By using the Bendixson-s criterion for high– dimensional ordinary differential equations and global Hopf bifurcation theory for functional differential equations, sufficient conditions for existence of periodic solutions when the time delay is sufficiently large are established.

Screening and Identification of Microorganisms – Potential Producers of Arachidonic Acid

Microorganisms isolated from water and soil of Kazakhstan to identify potential high-effective producers of the arachidonic acid, exhibiting a wide range of physiological activity and having practical applications were screened. Based on the results of two independent tests (the test on the sensitivity of the growth processes of microorganisms to acetylsalicylic acid - an irreversible inhibitor of PGH-synthase involved in the metabolism of arachidonic acid and its derivatives, the test for inhibition of peroxidase activity of membrane-bounding fraction of PGH - synthase by acetylsalicylic acid) were selected microbial cultures which are potential highproducer of arachidonic acid. They are characterized by a stable strong growth in the laboratory conditions. Identification of microorganism cultures based on morphological, physiological, biochemical and molecular genetic characteristics was performed.

Nonlinear Optimal Line-Of-Sight Stabilization with Fuzzy Gain-Scheduling

A nonlinear optimal controller with a fuzzy gain scheduler has been designed and applied to a Line-Of-Sight (LOS) stabilization system. Use of Linear Quadratic Regulator (LQR) theory is an optimal and simple manner of solving many control engineering problems. However, this method cannot be utilized directly for multigimbal LOS systems since they are nonlinear in nature. To adapt LQ controllers to nonlinear systems at least a linearization of the model plant is required. When the linearized model is only valid within the vicinity of an operating point a gain scheduler is required. Therefore, a Takagi-Sugeno Fuzzy Inference System gain scheduler has been implemented, which keeps the asymptotic stability performance provided by the optimal feedback gain approach. The simulation results illustrate that the proposed controller is capable of overcoming disturbances and maintaining a satisfactory tracking performance.

Experimental and Analytical Study of Scrap Tire Rubber Pad for Seismic Isolation

A seismic isolation pad produced by utilizing the scrap tire rubber which contains interleaved steel reinforcing cords has been proposed. The steel cords are expected to function similar to the steel plates used in conventional laminated rubber bearings. The scrap tire rubber pad (STRP) isolator is intended to be used in low rise residential buildings of highly seismic areas of the developing countries. Experimental investigation was conducted on unbonded STRP isolators, and test results provided useful information including stiffness, damping values and an eventual instability of the isolation unit. Finite element analysis (FE analysis) of STRP isolator was carried out on properly bonded samples. These types of isolators provide positive incremental force resisting capacity up to shear strain level of 155%. This paper briefly discusses the force deformation behavior of bonded STRP isolators including stability of the isolation unit.

Reduce of Fermentation Time in Composting Process by Using a Special Microbial Consortium

Composting is the process in which municipal solid waste (MSW) and other organic waste materials such as biosolids and manures are decomposed through the action of bacteria and other microorganisms into a stable granular material which, applied to land, as soil conditioner. Microorganisms, especially those that are able to degrade polymeric organic material have a key role in speed up this process. The aim of this study has been established to isolation of microorganisms with high ability to production extracellular enzymes for degradation of natural polymers that are exists in MSW for decreasing time of degradation phase. Our experimental study for isolation designed in two phases: in first phase we isolated degrading microorganism with selected media that consist a special natural polymer such as cellulose, starch, lipids and etc as sole source of carbon. In second phase we selected microorganism that had high degrading enzyme production with enzymatic assay for seed production. However, our findings in pilot scale have indicated that usage of this microbial consortium had high efficiency for decreasing degradation phase.

The Necessity of Biomass Application for Developing Combined Heat and Power(CHP) with Biogas Fuel: Case Study

The daily increase of organic waste materials resulting from different activities in the country is one of the main factors for the pollution of environment. Today, with regard to the low level of the output of using traditional methods, the high cost of disposal waste materials and environmental pollutions, the use of modern methods such as anaerobic digestion for the production of biogas has been prevailing. The collected biogas from the process of anaerobic digestion, as a renewable energy source similar to natural gas but with a less methane and heating value is usable. Today, with the help of technologies of filtration and proper preparation, access to biogas with features fully similar to natural gas has become possible. At present biogas is one of the main sources of supplying electrical and thermal energy and also an appropriate option to be used in four stroke engine, diesel engine, sterling engine, gas turbine, gas micro turbine and fuel cell to produce electricity. The use of biogas for different reasons which returns to socio-economic and environmental advantages has been noticed in CHP for the production of energy in the world. The production of biogas from the technology of anaerobic digestion and its application in CHP power plants in Iran can not only supply part of the energy demands in the country, but it can materialize moving in line with the sustainable development. In this article, the necessity of the development of CHP plants with biogas fuels in the country will be dealt based on studies performed from the economic, environmental and social aspects. Also to prove the importance of the establishment of these kinds of power plants from the economic point of view, necessary calculations has been done as a case study for a CHP power plant with a biogas fuel.

Texture Feature-Based Language Identification Using Wavelet-Domain BDIP and BVLC Features and FFT Feature

In this paper, we propose a texture feature-based language identification using wavelet-domain BDIP (block difference of inverse probabilities) and BVLC (block variance of local correlation coefficients) features and FFT (fast Fourier transform) feature. In the proposed method, wavelet subbands are first obtained by wavelet transform from a test image and denoised by Donoho-s soft-thresholding. BDIP and BVLC operators are next applied to the wavelet subbands. FFT blocks are also obtained by 2D (twodimensional) FFT from the blocks into which the test image is partitioned. Some significant FFT coefficients in each block are selected and magnitude operator is applied to them. Moments for each subband of BDIP and BVLC and for each magnitude of significant FFT coefficients are then computed and fused into a feature vector. In classification, a stabilized Bayesian classifier, which adopts variance thresholding, searches the training feature vector most similar to the test feature vector. Experimental results show that the proposed method with the three operations yields excellent language identification even with rather low feature dimension.

Model-free Prediction based on Tracking Theory and Newton Form of Polynomial

The majority of existing predictors for time series are model-dependent and therefore require some prior knowledge for the identification of complex systems, usually involving system identification, extensive training, or online adaptation in the case of time-varying systems. Additionally, since a time series is usually generated by complex processes such as the stock market or other chaotic systems, identification, modeling or the online updating of parameters can be problematic. In this paper a model-free predictor (MFP) for a time series produced by an unknown nonlinear system or process is derived using tracking theory. An identical derivation of the MFP using the property of the Newton form of the interpolating polynomial is also presented. The MFP is able to accurately predict future values of a time series, is stable, has few tuning parameters and is desirable for engineering applications due to its simplicity, fast prediction speed and extremely low computational load. The performance of the proposed MFP is demonstrated using the prediction of the Dow Jones Industrial Average stock index.

Multiple Positive Periodic Solutions to a Periodic Predator-Prey-Chain Model with Harvesting Terms

In this paper, a class of predator-prey-chain model with harvesting terms are studied. By using Mawhin-s continuation theorem of coincidence degree theory and some skills of inequalities, some sufficient conditions are established for the existence of eight positive periodic solutions. Finally, an example is presented to illustrate the feasibility and effectiveness of the results.

A Preliminary Study of Drug Perfusion Enhancement by Microstreaming Induced by an Oscillating Microbubble

Microbubbbles incorporating ultrasound have been used to increase the efficacy of targeted drug delivery, because microstreaming induced by cavitating bubbles affects the drug perfusion into the target cells and tissues. In order to clarify the physical effects of microstreaming on drug perfusion into tissues, a preliminary experimental study of perfusion enhancement by a stably oscillating microbubble was performed. Microstreaming was induced by an oscillating bubble at 15 kHz, and perfusion of dye into an agar phantom was optically measured by histology on agar phantom. Surface color intensity and the penetration length of dye in the agar phantom were increased more than 70% and 30%, respectively, due to the microstreaming induced by an oscillating bubble. The mass of dye perfused into a tissue phantom for 30 s was increased about 80% in the phantom with an oscillating bubble. This preliminary experiment shows the physical effects of steady streaming by an oscillating bubble can enhance the drug perfusion into the tissues while minimizing the biological effects.

Adjusting the Furnace and Converter Temperature of the Sulfur Recovery Units

The modified Claus process is commonly used in oil refining and gas processing to recover sulfur and destroy contaminants formed in upstream processing. A Claus furnace feed containing a relatively low concentration of H2S may be incapable of producing a stable flame. Also, incomplete combustion of hydrocarbons in the feed can lead to deterioration of the catalyst in the reactors due to soot or carbon deposition. Therefore, special consideration is necessary to achieve the appropriate overall sulfur recovery. In this paper, some configurations available to treat lean acid gas streams are described and the most appropriate ones are studied to overcome low H2S concentration problems. As a result, overall sulfur recovery is investigated for feed preheating and hot gas configurations.

Resistive RAM Based on Hfox and its Temperature Instability Study

High performance Resistive Random Access Memory (RRAM) based on HfOx has been prepared and its temperature instability has been investigated in this work. With increasing temperature, it is found that: leakage current at high resistance state increases, which can be explained by the higher density of traps inside dielectrics (related to trap-assistant tunneling), leading to a smaller On/Off ratio; set and reset voltages decrease, which may be attributed to the higher oxygen ion mobility, in addition to the reduced potential barrier to create / recover oxygen ions (or oxygen vacancies); temperature impact on the RRAM retention degradation is more serious than electrical bias.

A Study on the Condition Monitoring of Transmission Line by On-line Circuit Parameter Measurement

An on-line condition monitoring method for transmission line is proposed using electrical circuit theory and IT technology in this paper. It is reasonable that the circuit parameters such as resistance (R), inductance (L), conductance (g) and capacitance (C) of a transmission line expose the electrical conditions and physical state of the line. Those parameters can be calculated from the linear equation composed of voltages and currents measured by synchro-phasor measurement technique at both end of the line. A set of linear voltage drop equations containing four terminal constants (A, B ,C ,D ) are mathematical models of the transmission line circuits. At least two sets of those linear equations are established from different operation condition of the line, they may mathematically yield those circuit parameters of the line. The conditions of line connectivity including state of connecting parts or contacting parts of the switching device may be monitored by resistance variations during operation. The insulation conditions of the line can be monitored by conductance (g) and capacitance(C) measurements. Together with other condition monitoring devices such as partial discharge, sensors and visual sensing device etc.,they may give useful information to monitor out any incipient symptoms of faults. The prototype of hardware system has been developed and tested through laboratory level simulated transmission lines. The test has shown enough evident to put the proposed method to practical uses.