Evaluation on the Viability of Combined Heat and Power with Different Distributed Generation Technologies for Various Bindings in Japan

This paper has examined the energy consumption characteristics in six different buildings including apartments, offices, commercial buildings, hospitals, hotels and educational facilities. Then 5-hectare (50000m2) development site for respective building-s type has been assumed as case study to evaluate the introduction effect of Combined Heat and Power (CHP). All kinds of CHP systems with different distributed generation technologies including Gas Turbine (GT), Gas Engine (GE), Diesel Engine (DE), Solid Oxide Fuel Cell (SOFC) and Polymer Electrolyte Fuel Cell (PEFC), have been simulated by using HEATMAP, CHP system analysis software. And their primary energy utilization efficiency, energy saving ratio and CO2 reduction ratio have evaluated and compared respectively. The results can be summarized as follows: Various buildings have their special heat to power ratio characteristics. Matching the heat to power ratio demanded from an individual building with that supplied from a CHP system is very important. It is necessary to select a reasonable distributed generation technologies according to the load characteristics of various buildings. Distributed generation technologies with high energy generating efficiency and low heat to power ratio, like SOFC and PEFC is more reasonable selection for Building Combined Heat and Power (BCHP). CHP system is an attractive option for hotels, hospitals and apartments in Japan. The users can achieve high energy saving and environmental benefit by introducing a CHP systems. In others buildings, especially like commercial buildings and offices, the introduction of CHP system is unreasonable.

Interfacial Layer Effect on Novel p-Ni1-xO:Li/n-Si Heterojunction Solar Cells

This study fabricates p-type Ni1−xO:Li/n-Si heterojunction solar cells (P+/n HJSCs) by using radio frequency (RF) magnetron sputtering and investigates the effect of substrate temperature on photovoltaic cell properties. Grazing incidence x-ray diffraction, four point probe, and ultraviolet-visible-near infrared discover the optoelectrical properties of p-Ni1-xO thin films. The results show that p-Ni1-xO thin films deposited at 300 oC has the highest grain size (22.4 nm), average visible transmittance (~42%), and electrical resistivity (2.7 Ωcm). However, the conversion efficiency of cell is shown only 2.33% which is lower than the cell (3.39%) fabricated at room temperature. This result can be mainly attributed to interfacial layer thickness (SiOx) reduces from 2.35 nm to 1.70 nm, as verified by high-resolution transmission electron microscopy.

Simulation Study on the Thin-walled Tube Structure of a Vehicle Simulator Crash Testing Equipment

A kind of crash energy absorption structure adopted by vehicle simulator crash testing equipment based on mechanical energy storage was studied. Dynamic explicit finite element simulation was achieved for thin-walled tube structure under different conditions of section shape, thickness and inducement groove style. Crash energy absorption property of the structure was obtained. After optimization, a reasonable structure was given which can meet current vehicle crash regulation. And the optimized structure can be adopted in vehicle simulator, which can increase the practicability of the testing equipment.

Multi-Criteria Decision Analysis in Planning of Asbestos-Containing Waste Management

Environmental decision making, particularly about hazardous waste management, is inherently exposed to a high potential conflict, principally because of the trade-off between sociopolitical, environmental, health and economic factors. The need to plan complex contexts has led to an increasing request for decision analytic techniques as support for the decision process. In this work, alternative systems of asbestos-containing waste management (ACW) in Puglia (Southern Italy) were explored by a multi-criteria decision analysis. In particular, through Analytic Hierarchy Process five alternatives management have been compared and ranked according to their performance and efficiency, taking into account environmental, health and socio-economic aspects. A separated valuation has been performed for different temporal scale. For short period results showed a narrow deviation between the disposal alternatives “mono-material landfill in public quarry" and “dedicate cells in existing landfill", with the best performance of the first one. While for long period “treatment plant to eliminate hazard from asbestos-containing waste" was prevalent, although high energy demand required to achieve the change of crystalline structure. A comparison with results from a participative approach in valuation process might be considered as future development of method application to ACW management.

Computation of the Filtering Properties of Photonic Crystal Waveguide Discontinuities Using the Mode Matching Method

In this paper, the application of the Mode Matching (MM) method in the case of photonic crystal waveguide discontinuities is presented. The structure under consideration is divided into a number of cells, which supports a number of guided and evanescent modes. These modes can be calculated numerically by an alternative formulation of the plane wave expansion method for each frequency. A matrix equation is then formed relating the modal amplitudes at the beginning and at the end of the structure. The theory is highly efficient and accurate and can be applied to study the transmission sensitivity of photonic crystal devices due to fabrication tolerances. The accuracy of the MM method is compared to the Finite Difference Frequency Domain (FDFD) and the Adjoint Variable Method (AVM) and good agreement is observed.

Evaluation of Geosynthetic Forces in GRSRW under Dynamic Condition

Geosynthetics have proved to be suitable for reinforced soil retaining walls. Based on the increasing uses of geosynthetic reinforced soil systems in the regions, which bear frequent earthquakes, the study of dynamic behavior of structures seems necessary. Determining the reinforcement forces is; therefore, one of the most important and main points of discussions in designing retaining walls, by which we prevent from conservative planning. Thus, this paper intended to investigate the effects of such parameters as wall height, acceleration type, vertical spacing of reinforcement, type of reinforcement and soil type on forces and deformation through numerical modeling of the geosynthetic reinforced soil retaining walls (GRSRW) under dynamic loading with finite difference method by using FLAC. The findings indicate rather positive results with each parameter.

A Study on Cancer-Cell Invasion Based On the Diffuse Interface Model

In this study, a three-dimensional haptotaxis model to simulate the migration of a population of cancer cells has been proposed. The invasion of cancer cells is related with the hapto-attractant and the effect of the interface energies between the cells and the ECM. The diffuse interface model, which incorporates the haptotaxis mechanism and interface energies, is employed. The semi-implicit Fourier spectral scheme is adopted for efficient evaluation of the simulation. The simulation results thoroughly reveal the dynamics of cancer-cell migration.

Evolving Neural Networks using Moment Method for Handwritten Digit Recognition

This paper proposes a neural network weights and topology optimization using genetic evolution and the backpropagation training algorithm. The proposed crossover and mutation operators aims to adapt the networks architectures and weights during the evolution process. Through a specific inheritance procedure, the weights are transmitted from the parents to their offsprings, which allows re-exploitation of the already trained networks and hence the acceleration of the global convergence of the algorithm. In the preprocessing phase, a new feature extraction method is proposed based on Legendre moments with the Maximum entropy principle MEP as a selection criterion. This allows a global search space reduction in the design of the networks. The proposed method has been applied and tested on the well known MNIST database of handwritten digits.

Study of Sugarcane Bagasse Pretreatment with Sulfuric Acid as a Step of Cellulose Obtaining

To produce sugar and ethanol, sugarcane processing generates several agricultural residues, being straw and bagasse is considered as the main among them. And what to do with this residues has been subject of many studies and experiences in an industry that, in recent years, highlighted by the ability to transform waste into valuable products such as electric power. Cellulose is the main component of these materials. It is the most common organic polymer and represents about 1.5 x 1012 tons of total production of biomass per year and is considered an almost inexhaustible source of raw material. Pretreatment with mineral acids is one of the most widely used as stage of cellulose extraction from lignocellulosic materials for solubilizing most of the hemicellulose content. This study had as goal to find the best reaction time of sugarcane bagasse pretreatment with sulfuric acid in order to minimize the losses of cellulose concomitantly with the highest possible removal of hemicellulose and lignin. It was found that the best time for this reaction was 40 minutes, in which it was reached a loss of hemicelluloses around 70% and lignin and cellulose, around 15%. Over this time, it was verified that the cellulose loss increased and there was no loss of lignin and hemicellulose.

Dimension Reduction of Microarray Data Based on Local Principal Component

Analysis and visualization of microarraydata is veryassistantfor biologists and clinicians in the field of diagnosis and treatment of patients. It allows Clinicians to better understand the structure of microarray and facilitates understanding gene expression in cells. However, microarray dataset is a complex data set and has thousands of features and a very small number of observations. This very high dimensional data set often contains some noise, non-useful information and a small number of relevant features for disease or genotype. This paper proposes a non-linear dimensionality reduction algorithm Local Principal Component (LPC) which aims to maps high dimensional data to a lower dimensional space. The reduced data represents the most important variables underlying the original data. Experimental results and comparisons are presented to show the quality of the proposed algorithm. Moreover, experiments also show how this algorithm reduces high dimensional data whilst preserving the neighbourhoods of the points in the low dimensional space as in the high dimensional space.

Optimization of Two-Stage Pretreatment Combined with Microwave Radiation Using Response Surface Methodology

Pretreatment is an essential step in the conversion of lignocellulosic biomass to fermentable sugar that used for biobutanol production. Among pretreatment processes, microwave is considered to improve pretreatment efficiency due to its high heating efficiency, easy operation, and easily to combine with chemical reaction. The main objectives of this work are to investigate the feasibility of microwave pretreatment to enhance enzymatic hydrolysis of corncobs and to determine the optimal conditions using response surface methodology. Corncobs were pretreated via two-stage pretreatment in dilute sodium hydroxide (2 %) followed by dilute sulfuric acid 1 %. Pretreated corncobs were subjected to enzymatic hydrolysis to produce reducing sugar. Statistical experimental design was used to optimize pretreatment parameters including temperature, residence time and solid-to-liquid ratio to achieve the highest amount of glucose. The results revealed that solid-to-liquid ratio and temperature had a significant effect on the amount of glucose.

Developing Efficient Testing and Unloading Procedures for a Local Sewage Holding Pit

A local municipality has decided to build a sewage pit to receive residential sewage waste arriving by tank trucks. Daily accumulated waste are to be pumped to a nearby waste water treatment facility to be re-consumed for agricultural and construction projects. A discrete-event simulation model using Arena Software was constructed to assist in defining the capacity of the system in cubic meters, number of tank trucks to use the system, number of unload docks required, number of standby areas needed and manpower required for data collection at entrance checkpoint and truck tank load toxicity testing. The results of the model are statistically validated. Simulation turned out to be an excellent tool in the facility planning effort for the pit project, as it insured smooth flow lines of tank trucks load discharge and best utilization of facilities on site.

Performance Analysis of an Adaptive Threshold Hybrid Double-Dwell System with Antenna Diversity for Acquisition in DS-CDMA Systems

In this paper, we consider the analysis of the acquisition process for a hybrid double-dwell system with antenna diversity for DS-CDMA (direct sequence-code division multiple access) using an adaptive threshold. Acquisition systems with a fixed threshold value are unable to adapt to fast varying mobile communications environments and may result in a high false alarm rate, and/or low detection probability. Therefore, we propose an adaptively varying threshold scheme through the use of a cellaveraging constant false alarm rate (CA-CFAR) algorithm, which is well known in the field of radar detection. We derive exact expressions for the probabilities of detection and false alarm in Rayleigh fading channels. The mean acquisition time of the system under consideration is also derived. The performance of the system is analyzed and compared to that of a hybrid single dwell system.

Design a Biodegradable Hydrogel for Drug Delivery System

In this article, we synthesize a novel chitosan -based superabsorbent hydrogel via graft copolymerization of mixtures acrylic acid (AA) and N-vinyl pyrollidon onto chitosan backbones. The polymerization reaction was carried out in an aqueous medium and in the presence of ammonium persulfate (APS) as an initiator and N,N'-methylene bisacrylamide (MBA) as a crosslinker.The hydrogel structures were confirmed by FTIR spectroscopy. The swelling behavior of these absorbent polymers was also investigated in various salt solutions. Results indicated that the swelling capacity decreased with an increase in the ionic strength of the swelling medium. Furthermore, the swelling of superabsorbing hydrogels was examined in solutions with pH values ranging between 1.0 and 13.0. It showed a reversible pH-responsive behavior at pHs 2.0 and 8.0. This on-off switching behavior makes the synthesized hydrogels as an excellent candidate for controlled delivery of bioactive agents.

A Novel Hopfield Neural Network for Perfect Calculation of Magnetic Resonance Spectroscopy

In this paper, an automatic determination algorithm for nuclear magnetic resonance (NMR) spectra of the metabolites in the living body by magnetic resonance spectroscopy (MRS) without human intervention or complicated calculations is presented. In such method, the problem of NMR spectrum determination is transformed into the determination of the parameters of a mathematical model of the NMR signal. To calculate these parameters efficiently, a new model called modified Hopfield neural network is designed. The main achievement of this paper over the work in literature [30] is that the speed of the modified Hopfield neural network is accelerated. This is done by applying cross correlation in the frequency domain between the input values and the input weights. The modified Hopfield neural network can accomplish complex dignals perfectly with out any additinal computation steps. This is a valuable advantage as NMR signals are complex-valued. In addition, a technique called “modified sequential extension of section (MSES)" that takes into account the damping rate of the NMR signal is developed to be faster than that presented in [30]. Simulation results show that the calculation precision of the spectrum improves when MSES is used along with the neural network. Furthermore, MSES is found to reduce the local minimum problem in Hopfield neural networks. Moreover, the performance of the proposed method is evaluated and there is no effect on the performance of calculations when using the modified Hopfield neural networks.

Computational Identification of Bacterial Communities

Stable bacterial polymorphism on a single limiting resource may appear if between the evolved strains metabolic interactions take place that allow the exchange of essential nutrients [8]. Towards an attempt to predict the possible outcome of longrunning evolution experiments, a network based on the metabolic capabilities of homogeneous populations of every single gene knockout strain (nodes) of the bacterium E. coli is reconstructed. Potential metabolic interactions (edges) are allowed only between strains of different metabolic capabilities. Bacterial communities are determined by finding cliques in this network. Growth of the emerged hypothetical bacterial communities is simulated by extending the metabolic flux balance analysis model of Varma et al [2] to embody heterogeneous cell population growth in a mutual environment. Results from aerobic growth on 10 different carbon sources are presented. The upper bounds of the diversity that can emerge from single-cloned populations of E. coli such as the number of strains that appears to metabolically differ from most strains (highly connected nodes), the maximum clique size as well as the number of all the possible communities are determined. Certain single gene deletions are identified to consistently participate in our hypothetical bacterial communities under most environmental conditions implying a pattern of growth-condition- invariant strains with similar metabolic effects. Moreover, evaluation of all the hypothetical bacterial communities under growth on pyruvate reveals heterogeneous populations that can exhibit superior growth performance when compared to the performance of the homogeneous wild-type population.

The Impact of Fish Cages on Water Quality in One Fish Farm in Croatia

In Croatia, the majority of cultured marine fish species are reared in net cages. The intensive production of the fish in net cages may generate the considerable amount of bio waste and change water quality especially in enclosed and semi-enclosed coastal areas. The aim of this paper is to assess the potential impact of sea bass (Dicentrarchus labrax L.) cage farm on water quality. The weak relationship between food supply and water quality parameters (nutrient content and phytoplankton biomass) was found, but significant changes in oxygen saturation was observed in the cages during the warmer period of a year especially in the morning (occasionally it dropped below 70 %). Despite of, satisfactory results of water quality parameters, it is necessary to establish comprehensive monitoring process, especially to include quality assessment of fouling communities.

Evaluation of New Product Development Projects using Artificial Intelligence and Fuzzy Logic

As a vital activity for companies, new product development (NPD) is also a very risky process due to the high uncertainty degree encountered at every development stage and the inevitable dependence on how previous steps are successfully accomplished. Hence, there is an apparent need to evaluate new product initiatives systematically and make accurate decisions under uncertainty. Another major concern is the time pressure to launch a significant number of new products to preserve and increase the competitive power of the company. In this work, we propose an integrated decision-making framework based on neural networks and fuzzy logic to make appropriate decisions and accelerate the evaluation process. We are especially interested in the two initial stages where new product ideas are selected (go/no go decision) and the implementation order of the corresponding projects are determined. We show that this two-staged intelligent approach allows practitioners to roughly and quickly separate good and bad product ideas by making use of previous experiences, and then, analyze a more shortened list rigorously.

Integration of Resistive Switching Memory Cell with Vertical Nanowire Transistor

We integrate TiN/Ni/HfO2/Si RRAM cell with a vertical gate-all-around (GAA) nanowire transistor to achieve compact 4F2 footprint in a 1T1R configuration. The tip of the Si nanowire (source of the transistor) serves as bottom electrode of the memory cell. Fabricated devices with nanowire diameter ~ 50nm demonstrate ultra-low current/power switching; unipolar switching with 10μA/30μW SET and 20μA/30μW RESET and bipolar switching with 20nA/85nW SET and 0.2nA/0.7nW RESET. Further, the switching current is found to scale with nanowire diameter making the architecture promising for future scaling.

A new Cellular Automata Model of Cardiac Action Potential Propagation based on Summation of Excited Neighbors

The heart tissue is an excitable media. A Cellular Automata is a type of model that can be used to model cardiac action potential propagation. One of the advantages of this approach against the methods based on differential equations is its high speed in large scale simulations. Recent cellular automata models are not able to avoid flat edges in the result patterns or have large neighborhoods. In this paper, we present a new model to eliminate flat edges by minimum number of neighbors.