Splice-induced impairments on very-high-speed digital data communications over copper telephone networks

The effects of splice-induced crosstalk, insertion loss and echo on very-high-speed digital data communications over copper telephone networks are analysed and evaluated. Sealing current is used to mitigate the adverse effects of the splices. The specifications of sealing current (i.e. magnitude, shape, frequency of application) have significant ramifications on the operations of the digital communication systems. For proper operation of echo-cancellers (i.e. fast adaptation and tracking) on full-duplex transceivers operating at 800 kbit/s, and to achieve a bit error ratio of 10^?7, the magnitude and the rate of the change of splice fluctuations must be controlled. It is shown that the effects of crosstalk and insertion loss are not as severe as the occurrence of echo due to rapid fluctuations of splice impedance. The admissible ranges of splice fluctuations for a series of worst-case scenarios are computed, and their effects on the performance of the echo-canceller are discussed. If the splice fluctuation is restricted to 0·1 Ω on a 20 Ω splice, with the splice in the vicinity of the transceiver, the echo is —36 dB with respect to the far-end received signal, which is an acceptable level on a 9 kft subscriber loop with an American Wire Gauge of 26. However, quantification of the dynamics (i.e. the rate of change) of splice fluctuations requires laboratory experiments and field measurements.     

Harmonic phase-dispersion microscope with a Mach-Zehnder interferometer

Harmonic phase-dispersion microscopy (PDM) is a new imaging technique in which contrast is provided by differences in refractive index at two harmonically related wavelengths. We report a new configuration of the harmonic phase-dispersion microscope in a Mach-Zehnder geometry as an instrument for imaging biological samples. Several improvements on the earlier design are demonstrated, including a single-pass configuration and acousto-optic modulators for generating the heterodyne signals without mechanical arm scanning. We demonstrate quantitative phase-dispersion images of test structures and biological samples.     

Low power multipliers based on new hybrid full adders

Five hybrid full adder designs are proposed for low power parallel multipliers. The new adders allow NAND gates to generate most of the multiplier partial product bits instead of AND gates, thereby lowering the power consumption and the total number of needed transistors. For an 8×8 implementation, the ALL-NAND array multiplier achieves 15.7% and 7.8% reduction in power consumption and transistor count at the cost of a 6.9% increase in time delay compared to standard array multiplier. The ALL-NAND tree multiplier exhibits lower power consumption and transistor count by 12.5% and 7.3%, respectively, with a 4.4% longer time delay, compared to conventional tree multiplier.     

The effects of ginger intake on weight loss and metabolic profiles among overweight and obese subjects: A systematic review and meta-analysis of randomized controlled trials

This systematic review and meta-analysis of randomized controlled trials (RCTs) was performed to summarize the effect of ginger intake on weight loss, glycemic control and lipid profiles among overweight and obese subjects. We searched the following databases through November 2017: MEDLINE, EMBASE, Web of Science, and Cochrane Central Register of Controlled Trials. The relevant data were extracted and assessed for quality of the studies according to the Cochrane risk of bias tool. Data were pooled using the inverse variance method and expressed as Standardized Mean Difference (SMD) with 95% Confidence Intervals (95% CI). Heterogeneity between studies was assessed by the Cochran Q statistic and I-squared tests (I²). Overall, 14 studies were included in the meta-analyses. Fourteen RCTs with 473 subjects were included in our meta-analysis. The results indicated that the supplementation with ginger significantly decreased body weight (BW) (SMD ?0.66; 95% CI, ?1.31, ?0.01; P = 0.04), waist-to-hip ratio (WHR) (SMD ?0.49; 95% CI, ?0.82, ?0.17; P = 0.003), hip ratio (HR) (SMD ?0.42; 95% CI, ?0.77, ?0.08; P = 0.01), fasting glucose (SMD ?0.68; 95% CI, ?1.23, ?0.05; P = 0.03) and insulin resistance index (HOMA-IR) (SMD ?1.67; 95% CI, ?2.86, ?0.48; P = 0.006), and significantly increased HDL-cholesterol levels (SMD 0.40; 95% CI, 0.10, 0.70; P = 0.009). We found no detrimental effect of ginger on body mass index (BMI) (SMD ?0.65; 95% CI, ?1.36, 0.06; P = 0.074), insulin (SMD ?0.54; 95% CI, ?1.43, 0.35; P = 0.23), triglycerides (SMD ?0.27; 95% CI, ?0.71, 0.18; P = 0.24), total- (SMD ?0.20; 95% CI, ?0.58, 0.18; P = 0.30) and LDL-cholesterol (SMD ?0.13; 95% CI, ?0.51, 0.24; P = 0.48). Overall, the current meta-analysis demonstrated that ginger intake reduced BW, WHR, HR, fasting glucose and HOMA-IR, and increased HDL-cholesterol, but did not affect insulin, BMI, triglycerides, total- and LDL-cholesterol levels.     

Energy and economic aspects of synthesis gas production from oil sludge and plastic waste

A series of experiments have been performed to investigate the influence of reaction temperature, the equivalence ratio (ER), and blending ratio on the gas composition, tar content and higher heating value (HHV) of synthesis gas. H₂ content decreased from 10.7 to 8.2% in the range of BR while CO and CH₄ increased from 17.4 to 23.1% and 3.4 to 6.3%, respectively. HHV increased with BR and H₂/CO showed an opposite trend. The highest HHV and H₂/CO were obtained at 100%PW and 100%OS, respectively. Tar content increased from 4.8 to 9.5?g/Nm³ with BR increasing in the range because of a reduction in the endothermic nature of volatile combustion.     

Prolong network lifetime and improve efficiency in WSN‐UAV systems using new clustering parameters and CSMA modification

Since unmanned aerial vehicles (UAVs) have been introduced as mobile nodes for data gathering, wireless sensor networks (WSNs) have progressed considerably. The resulting WSN‐UAV systems are employed for emergency applications and also for remote monitoring purposes. WSN‐UAV systems yield an optimum data gathering method using the WSN. In the proposed method, the nodes' data are transferred using a remotely operated vehicle (drone) rather than the conventional data transferring methods like the direct and hop‐to‐hop data transmission approaches. Then, the gathered data are delivered in the pre‐determined destination point. WSN‐UAV systems, in fact, are a special case of the systems with the mobile sink in which the sink path is previously specified and controlled. In this paper, the effects of clustering parameters on the WSNs are studied; then, the network's lifetime is prolonged by applying some parameters. In addition, the network's performance is enhanced to some extent by assigning some changes in the media access control (MAC) layer. Also, the effect of drone's path pattern on the lifetime of the network is studied.     

Optimizing Irrigation Deficit of Multipurpose Cascade Reservoirs

Reservoirs play a strategic role in the rapid monetary growth of the world by providing numerous benefits. However, the reduction in appropriate sites along with environmental and social apprehensions has resulted in curtailment of new reservoirs around the world in twenty-first century. There is a potential of benefits available from existing reservoirs which can be best capitalized through their optimized operation. Reservoirs Operation Optimization considering Sediment Evacuation (RESOOSE), recently developed model which combines multiple reservoirs operation and sediment evacuation with Genetic Algorithm based optimization module, has been used in the study. The objective of the study was to optimize the irrigation deficit through cascade reservoirs with consideration to hydropower, sediment evacuation and flood damages reduction benefits. The RESOOSE model was applied to optimize the irrigation deficits of Tarbela and Diamer Basha Reservoirs in Pakistan using developed objective function. The article computed and compared the benefits of optimized and existing rule curves. The hydropower benefits of 36.92 Billion Kw, sediment evacuation benefits of 21.534 Million m³ and flood damages of 616.19 Million US$ due to existing rule curves were considered as minimum benefits for achieving the optimized rule curves to minimize irrigation deficits. The developed optimized rule curves reduced the irrigation shortages of case study reservoirs from 6.9 to 5.8 Billion m³ (16% enhancement) annually as compared to existing rule curves. The optimized rule curves minimized the irrigation deficits by maintaining the existing benefits and without lowering the minimum operating levels of case study reservoirs. The study suggests change in existing rule curves of Tarbela and Diamer Basha Reservoirs due to less irrigation shortages. The RESOOSE model can be applied to other cascade reservoirs for optimizing the rule curves.     

Information extraction from scientific articles: a survey

In last few decades, with the advent of World Wide Web (WWW), world is being overloaded with huge data. This huge data carries potential information that once extracted, can be used for betterment of humanity. Information from this data can be extracted using manual and automatic analysis. Manual analysis is not scalable and efficient, whereas, the automatic analysis involves computing mechanisms that aid in automatic information extraction over huge amount of data. WWW has also affected overall growth in scientific literature that makes the process of literature review quite laborious, time consuming and cumbersome job for researchers. Hence a dire need is felt to automatically extract potential information out of immense set of scientific articles to automate the process of literature review. Therefore, in this study, aim is to present the overall progress concerning automatic information extraction from scientific articles. The information insights extracted from scientific articles are classified in two broad categories i.e. metadata and key-insights. As available benchmark datasets carry a significant role in overall development in this research domain, existing datasets against both categories are extensively reviewed. Later, research studies in literature that have applied various computational approaches applied on these datasets are consolidated. Major computational approaches in this regard include Rule-based approaches, Hidden Markov Models, Conditional Random Fields, Support Vector Machines, Naïve-Bayes classification and Deep Learning approaches. Currently, there are multiple projects going on that are focused towards the dataset construction tailored to specific information needs from scientific articles. Hence, in this study, state-of-the-art regarding information extraction from scientific articles is covered. This study also consolidates evolving datasets as well as various toolkits and code-bases that can be used for information extraction from scientific articles.

     

Thresholded Multivariate Principal Component Analysis for Phase I Multichannel Profile Monitoring

Monitoring multichannel profiles has important applications in manufacturing systems improvement, but it is nontrivial to develop efficient statistical methods because profiles are high-dimensional functional data with intrinsic inner- and interchannel correlations, and that the change might only affect a few unknown features of multichannel profiles. To tackle these challenges, we propose a novel thresholded multivariate principal component analysis (PCA) method for multichannel profile monitoring. Our proposed method consists of two steps of dimension reduction: It first applies the functional PCA to extract a reasonably large number of features under the in-control state, and then uses the soft-thresholding techniques to further select significant features capturing profile information under the out-of-control state. The choice of tuning parameter for soft-thresholding is provided based on asymptotic analysis, and extensive numerical studies are conducted to illustrate the efficacy of our proposed thresholded PCA methodology.