Classification and assessment of rock mass parameters in Choghart iron mine using P-wave velocity

Engineering rock mass classification,based on empirical relations between rock mass parameters and engineering applications,is commonly used in rock engineering and forms the basis for designing rock structures.The basic data required may be obtained from visual observation and laboratory or field tests.However,owing to the discontinuous and variable nature of rock masses,it is difficult for rock engineers to directly obtain the specific design parameters needed.As an alternative,the use of geophysical methods in geomechanics such as seismography may largely address this problem.In this study,25 seismic profiles with the total length of 543 m have been scanned to determine the geomechanical properties of the rock mass in blocks Ⅰ,Ⅲ and Ⅳ-2 of the Choghart iron mine.Moreover,rock joint measurements and sampling for laboratory tests were conducted.The results show that the rock mass rating(RMR) and Q values have a close relation with P-wave velocity parameters,including P-wave velocity in field(V_(PF)).P-wave velocity in the laboratory(V_(PL)) and the ratio of V_(PF) V_(PL)(i.e.K_p = V_(PF)/V_(PL).However,Q value,totally,has greater correlation coefficient and less error than the RMR,In addition,rock mass parameters including rock quality designation(RQD),uniaxial compressive strength(UCS),joint roughness coefficient(JRC) and Schmidt number(RN) show close relationship with P-wave velocity.An equation based on these parameters was obtained to estimate the P-wave velocity in the rock mass with a correlation coefficient of 91%.The velocities in two orthogonal directions and the results of joint study show that the wave velocity anisotropy in rock mass may be used as an efficient tool to assess the strong and weak directions in rock mass.     

A multiple clocking scheme for low-power RTL design

This paper presents a resource allocation technique to design low-power register-transfer-level datapaths. The basis of this technique is to use a multiple clocking scheme of n nonoverlapping clocks, by dividing the frequency f of a single clock into n cycles, to partition the circuit into n disjoint modules and assign each module to a distinct clock, and to operate each module only during its corresponding duty cycle, thus clocking each module by a frequency f/n to reduce power. However, the overall effective frequency of the circuit remains f, i.e., the single clock frequency. Further power reduction is also obtained by tradeoffs between voltage, power, and delay across multiple clock partitions. Power savings up to 50% of the proposed multiple clocking scheme in comparison to single gated clock designs are also reported     

Development of Nonlinear Model Based on Wavelet-ANFIS for Rainfall Forecasting at Klang Gates Dam

Rainfall is one of the most complicated effective hydrologic processes in runoff prediction and water management. Artificial neural networks (ANN) have been found efficient, particularly in problems where characteristics of the processes are stochastic and difficult to describe using explicit mathematical models. However, time series prediction based on ANN algorithms is fundamentally difficult and faces some other problems. For this purpose, one method that has been identified as a possible alternative for ANN in hydrology and water resources problems is the adaptive neuro-fuzzy inference system (ANFIS). Nevertheless, the data arising from the monitoring stations and experiment might be corrupted by noise signals owing to systematic and non-systematic errors. This noisy data often made the prediction task relatively difficult. Thus, in order to compensate for this augmented noise, the primary objective of this paper is to develop a technique that could enhance the accuracy of rainfall prediction. Therefore, the wavelet decomposition method is proposed to link to ANFIS and ANN models. In this paper, two scenarios are employed; in the first scenario, monthly rainfall value is imposed solely as an input in different time delays from the time (t) to the time (t-4) into ANN and ANFIS, second scenario uses the wavelet transform to eliminate the error and prepares sub-series as inputs in different time delays to the ANN and ANFIS. The four criteria as Root Mean Square Error (RMSE), Correlation Coefficient (R ²), Gamma coefficient (G), and Spearman Correlation Coefficient (ρ) are used to evaluate the proposed models. The results showed that the model based on wavelet decomposition conjoined with ANFIS could perform better than the ANN and ANFIS models individually.     

Prefix segregation scheme for a TCAM-based IP forwarding engine

A novel design for IP packet forwarding based on a new ternary content-addressable-memory configuration offers an efficient hardware solution for the longest-prefix matching problem in Internet routers. The architecture has lower update complexity, lower cost, and shorter search latency compared to the conventional TCAM structure.     

Correction to: Spatiotemporal Analysis of Droughts Over Different Climate Regions Using Hybrid Clustering Method

Water Resources Management -     

Pulmonary venous sphincters in cattle

Formulation difficulties prevented the otherwise promising clinical development of the anti-tumour agent trimelamol (TM; tris-[hydroxymethyl]trimethylmelamine]). A synthetic analogue programme resulted in the identification of CB 7646 (bis N-[hydroxymethyl]trimethylmelamine) as a compound with improved stability and favourable formulation characteristics. The in vitro and in vivo activity of CB 7646 was shown to be very similar to that of TM. In addition, curative activities were shown in the PXN/65 human ovarian cancer xenograft and the MX-1 and T-61 human breast cancer xenograft models. The effectiveness of the N-(hydroxymethyl)melamines against platinum-refractory disease was noted in the phase I clinical trial of TM. In line with this finding, the present study confirmed the effective activity of both TM and CB 7646 against various forms of platinum resistance in in vitro models. Curative activity for TM and CB 7646 was seen in the HX110P human ovarian cancer xenograft with acquired carboplatin resistance. Animal studies indicated less neurotoxicity for CB 7646 than for TM. The pharmacokinetic profile of CB 7646 indicated a decreased plasma elimination, indicative of slower in vivo degradation than for TM. CB 7646, therefore, represents a promising candidate for clinical development, designed to supersede TM.     

Testing On-Die Process Variation in Nanometer VLSI

As device technology progresses toward 45 nm and beyond, the fidelity of process parameter modeling becomes questionable. The authors propose the concept of process variation (PV) testing, which involves applying an innovative fault model and test methodology that uses PV sensing circuitry and frequency domain analysis. Rather than pinpointing the variation of different parameters, the architecture proposed by the authors looks at the effect of PV on a chip indirectly and collectively. The novelty of this architecture is in shifting the strategy of VLSI testing to the frequency domain by using a distributed network of frequency-sensitive sensors such as ring oscillators. This provides an intrinsic advantage by minimizing the effect of noise (signal integrity loss, crosstalk, IR drop, and so on) and by using the powerful concept of digital signal processing for test analysis. The test architecture does not interfere with the rest of the circuit, thus providing freedom to tune the accuracy of PV test by choosing the proper number and type of oscillators.