Groundwater Level Simulation Using Soft Computing Methods with Emphasis on Major Meteorological Components

Water Resources Management - Precise estimation of groundwater level (GWL) might be of great importance for attaining sustainable development goals and integrated water resources management....     

Electro-copolymerisation of indene and styrene

Electroinitiated cationic copolymerisation of indene and styrene was investigated by constant potential electrolysis. Effects of copolymerisation potential and temperature on the copolymer composition and the reactivity ratios are discussed. The reactivity ratios of the monomers were calculated according to the integrated Lewis-Mayo equation.     

Fast Decodable Turbo Codes

Decoding delay is an important consideration for the use of turbo codes in practical applications. We propose a new structure for turbo codes which is very suitable for parallel decoding. It is shown by union bound analysis and simulation results that the proposed system performance is comparable to that of the classical turbo codes     

Reducing Average and Peak Test Power Through Scan Chain Modification

Parallel test application helps reduce the otherwise considerable test times in SOCs; yet its applicability is limited by average and peak power considerations. The typical test vector loading techniques result in frequent transitions in the scan chain, which in turn reflect into significant levels of circuit switching unnecessarily. Judicious utilization of logic in the scan chain can help reduce transitions while loading the test vector needed. The transitions embedded in both test stimuli and the responses are handled through scan chain modifications consisting of logic gate insertion between scan cells as well as inversion of capture paths. No performance degradation ensues as these modifications have no impact on functional execution. To reduce average and peak power, we herein propose computationally efficient schemes that identify the location and the type of logic to be inserted. The experimental results confirm the significant reductions in test power possible under the proposed scheme.     

Fuzzy rule interpolation for multidimensional input spaces in determining d50c of hydrocyclones

Fuzzy rule-based systems have been very popular in many engineering applications. In mineral engineering, fuzzy rules are normally constructed using some fuzzy rule extraction techniques to establish the determination model in predicting the d50c of hydrocyclones. However, when generating fuzzy rules from the available information, it may result in a sparse fuzzy rule base. The use of more than one input variable is also common in hydrocyclone data analysis. This paper examines the application of fuzzy interpolation to resolve the problems using sparse fuzzy rule bases, and to perform analysis of fuzzy interpolation in multidimensional input spaces.     

Scaling Laws for One- and Two-Dimensional Random Wireless Networks in the Low-Attenuation Regime

The capacity scaling of extended two-dimensional wireless networks is known in the high-attenuation regime, i.e., when the power path loss exponent alpha is greater than 4. This has been accomplished by deriving information-theoretic upper bounds for this regime that match the corresponding lower bounds. On the contrary, not much is known in the so-called low-attenuation regime when 2lesalphales4. (For one-dimensional networks, the uncharacterized regime is 1lesalphales2.5.) The dichotomy is due to the fact that while communication is highly power-limited in the first case and power-based arguments suffice to get tight upper bounds, the study of the low-attenuation regime requires a more precise analysis of the degrees of freedom involved. In this paper, we study the capacity scaling of extended wireless networks with an emphasis on the low-attenuation regime and show that in the absence of small scale fading, the low attenuation regime does not behave significantly different from the high attenuation regime.     

A new deep intuitionistic fuzzy time series forecasting method based on long short-term memory

The Journal of Supercomputing - In recent years, deep artificial neural networks can have better forecasting performance than many other artificial neural networks. The long short-term memory...     

Simultaneous afterclearing and decolorisation by ozonation after disperse dyeing of polyester

A set of trials have been conducted to examine the efficiency of ozonation on afterclearing of disperse dyed poly(ethylene terephthalate) fibres. Ozonation was performed in the cooled dyebath after the completion of the dyeing cycle. The ozone concentration used was 12.8 ± 0.3 mg/min at a gas flow rate of 400 ml/min. The results indicate that 3 min ozonation time is appropriate to achieve wash fastness results comparable to conventional reduction clearing. These results were obtained with simultaneous dyebath decolorisation ratios up to 67% and without significant colour yield ( K/S value) losses of the dyed fabric. Ozonation periods exceeding 3 min caused significant colour yield ( K/S value) losses, although dyebath decolorisation ratios increased up to 82% and wash fastness properties further improved. The chemical oxygen demand of the dyeing process decreased up to 62% by the ozonation afterclearing. The advantages of the ozonation afterclearing process are savings in terms of water, energy and time and reduction in environmental load.     

A modified genetic algorithm for forecasting fuzzy time series

Fuzzy time series approaches are used when observations of time series contain uncertainty. Moreover, these approaches do not require the assumptions needed for traditional time series approaches. Generally, fuzzy time series methods consist of three stages, namely, fuzzification, determination of fuzzy relations, and defuzzification. Artificial intelligence algorithms are frequently used in these stages with genetic algorithms being the most popular of these algorithms owing to their rich operators and good performance. However, the mutation operator of a GA may cause some negative results in the solution set. Thus, we propose a modified genetic algorithm to find optimal interval lengths and control the effects of the mutation operator. The results of applying our new approach to real datasets show superior forecasting performance when compared with those obtained by other techniques.     

Scan Cell Positioning for Boosting the Compression of Fan-Out Networks

Ensuring a high manufacturing test quality of an integrated electronic circuit mandates the application of a large volume test set. Even if the test data can be fit into the memory of an external tester, the consequent increase in test application time reflects into elevated production costs. Test data compression solutions have been proposed to address the test time and data volume problem by storing and delivering the test data in a compressed format, and subsequently by expanding the data on-chip. In this paper, we propose a scan cell positioning methodology that accompanies a compression technique in order to boost the compression ratio, and squash the test data even further. While we present the application of the proposed approach in conjunction with the fan-out based decompression architecture, this approach can be extended for application along with other compression solutions as well. The experimental results also confirm the compression enhancement of the proposed methodology.