Multimodal neural machine translation for low-resource language pairs using synthetic data

In this paper, we investigate the effectiveness of training a multimodal neural machine translation (MNMT) system with image features for a lowresource language pair, Hindi and English, using synthetic data. A threeway parallel corpus which contains bilingual texts and corresponding images is required to train a MNMT system with image features. However, such a corpus is not available for low resource language pairs. To address this, we developed both a synthetic training dataset and a manually curated development/test dataset for Hindi based on an existing English-image parallel corpus. We used these datasets to build our image description translation system by adopting state-of-theart MNMT models. Our results show that it is possible to train a MNMT system for low-resource language pairs through the use of synthetic data and that such a system can benefit from image features

Boosting Image Forgery Detection using Resampling Features and Copy-move analysis

Realistic image forgeries involve a combination of splicing, resampling, cloning, region removal and other methods. While resampling detection algorithms are effective in detecting splicing and resampling, copy-move detection algorithms excel in detecting cloning and region removal. In this paper, we combine these complementary approaches in a way that boosts the overall accuracy of image manipulation detection. We use the copy-move detection method as a pre-filtering step and pass those images that are classified as untampered to a deep learning based resampling detection framework. Experimental results on various datasets including the 2017 NIST Nimble Challenge Evaluation dataset comprising nearly 10,000 pristine and tampered images shows that there is a consistent increase of 8%-10% in detection rates, when copy-move algorithm is combined with different resampling detection algorithms

Pyrolysis of municipal green waste: a modelling, simulation and experimental analysis

Pyrolysis is the thermo-chemical conversion of carbonaceous feedstock in the absence of oxygen to produce bio-fuel (bio-oil, bio-char and syn-gas). Bio-fuel production from municipal green waste (MGW) through the pyrolysis process has attracted considerable attention recently in the renewable energy sector because it can reduce greenhouse gas emissions and contribute to energy security. This study analyses properties of MGW feedstock available in Rockhampton city of Central Queensland, Australia, and presents an experimental investigation of producing bio-fuel from that MGW through the pyrolysis process using a short sealed rotary furnace. It was found from the experiment that about 19.97% bio-oil, 40.83% bio-char and 29.77% syn-gas can be produced from the MGW. Then, a four-stage steady state simulation model is developed for pyrolysis process performance simulation using Aspen Plus software. In the first stage, the moisture content of the MGW feed is reduced. In the second stage, the MGW is decomposed according to its elemental constituents. In the third stage, condensate material is separated and, finally, the pyrolysis reactions are modelled using the Gibbs free energy minimisation approach. The MGW\u27s ultimate and proximate analysis data were used in the Aspen Plus simulation as input parameters. The model is validated with experimentally measured data. A good agreement between simulation and experimental results was found. More specifically, the variation of modelling and experimental elemental compositions of the MGW was found to be 7.3% for carbon, 15.82% for hydrogen, 7.04% for nitrogen and 5.56% for sulphur. The validated model is used to optimise the biofuel production from the MGW as a function of operating variables such as temperature, moisture content, particle size and process heat air-fuel ratio. The modelling and optimisation results are presented, analysed and discussed

Ultra-fast sampling of terahertz pulses from a quantum cascade laser using superconducting antenna-coupled NbN and YBCO detectors

We demonstrate the ultra-fast detection of terahertz pulses from a quantum cascade laser (QCL) using superconducting NbN and YBCO detectors. This has enabled both the intrapulse and interpulse dynamics of a THz QCL to be measured directly, including interpulse heating effects on sub-μs timescales

Sub-clinical mastitis prevalent in dairy cows in Chittagong district of Bangladesh: detection by different screening tests

Aim: Mastitis is recognized as one of the most costly health disorder affecting dairy cows. An epidemiological study was carried out at some selected farms in Chittagong district of Bangladesh to determine the prevalence and risk factors of sub-clinical mastitis (SCM) in dairy cows. Materials and Methods: For conducting the study, some dairy farms of Chittagong were selected from urban and periurban areas by stratified random sampling. A total of 444 quarter samples of 111 (56 from commercial dairy farms and 55 from backyards) lactating dairy cows were considered. Sub-clinical mastitis (SCM) was determined using three different indirect screening tests: California Mastitis Test (CMT), White Slide Test (WST) and Surf Field Mastitis Test (SFMT). Sensitivity and specificity were also determined to measure the accuracy of those tests. Results: The prevalence of SCM by CMT, WST and SFMT were 32.43% (n=144), 33.56% (n=149) and 31.53% (n=140), respectively. Distribution of SCM in relation to different variables at quarter level and animal level was also recorded. The prevalence of SCM was significantly (P<0.05) higher in aged, high yielding cows in addition with history of periparturient diseases, without dry cow therapy both at quarter and animal level. A significantly (p<0.01) higher prevalence (48.98%) of SCM was observed in higher parity number (>4) than others at quarter level. No significant difference (P>0.05) was found in relation to breed. Using CMT as a gold standard, sensitivity and specificity of WST and SFMT were also calculated at 95% confidence interval. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, positive predictive value, negative predictive value and disease prevalence by WST and SFMT were comparable. Conclusion: This study recommends that regular screening of sub-clinical mastitis will reduce the prevalence of sub-clinical mastitis. The most effective way to control sub-clinical mastitis is to take preventive measures such as regular cleaning of the floor, keeping the udder clean, milkman's cleanliness, dry cow therapy specially in high yielding dairy cows

Determination of Mineral, Trace Element, and Pesticide Levels in Honey Samples Originating from Different Regions of Malaysia Compared to Manuka Honey

Thepresent study was undertaken to determine the content of six minerals, five trace elements, and ten pesticide residues in honeys originating from different regions of Malaysia. Calcium (Ca), magnesium (Mg), iron (Fe), and zinc (Zn) were analyzed by flame atomic absorption spectrometry (FAAS), while sodium (Na) and potassium (K) were analyzed by flame emission spectrometry (FAES). Trace elements such as arsenic (As), lead (Pb), cadmium (Cd), copper (Cu), and cobalt (Co) were analyzed by graphite furnace atomic absorption spectrometry (GFAAS) following the microwave digestion of honey. High mineral contents were observed in the investigated honeys with K, Na, Ca, and Fe being the most abundant elements (mean concentrations of 1349.34, 236.80, 183.67, and 162.31mg/kg, resp.).The concentrations of the trace elements were within the recommended limits, indicating that the honeys were of good quality. Principal component analysis reveals good discrimination between the different honey samples. The pesticide analysis for the presence of organophosphorus and carbamates was performed by high performance liquid chromatography (HPLC). No pesticide residues were detected in any of the investigated honey samples, indicating that the honeys were pure. Our study reveals that Malaysian honeys are rich sources of minerals with trace elements present within permissible limits and that they are free from pesticide contamination

Oxidizability assay of unfractionated plasma of patients’ with different plasma profile: a methodological study

BACKGROUND: Present study describe the in vitro model of plasma oxidation of patients with different lipid profile, that can be correlated to their invivo plasma oxidizability in order to find the arterial diseases prone patient groups. METHOD: The method applied here to measure the invitro plasma oxidizability, accounts a convenient way that can be well suited in any clinical laboratory settings. Un-fractionated plasma was exposed to CuSO4 (5.0 mmol/L), a pro-oxidant, and low frequency ultrasonic wave to induce oxidation, and finally oxidizability was calculated by TBARS and Conjugated Diene methods. RESULT: In our study, plasma LDL greater than 150 mg/dL possess 1.75 times more risk to undergo oxidation (CI, 0.7774 to 3.94; p = 0.071) than the low LDL plasma, percent of oxidation increased from 38.3% to 67.1% for the LDL level upto 150 mg/dL and high. Lag phase, which is considered as the plasma antioxidative protection, was also influenced by the higher LDL concentration. The mean lag time was 65.27 ± 20.02 (p = 0.02 compared to healthy), where as for 94.71 ± 35.11 min for the normolipidemic subject. The plasma oxidizability was also changed drastically for total cholesterol level, oxidative susceptibility shown 35% and 55.02% for 200 mg/dL and high respectively, however it didn’t appear as risk factor. Patient samples were also stratified according to their age, gender, and blood glucose level. Older persons (≥40 years) were 1.096 times (95% CL, 0.5607 to 2.141, p = 0.396) than younger (≤39 years age), males are 1.071 (95% CI, 0.5072- 2.264) times than the females, and diabetic patients are 1.091 (CI, 0.6153 to 1.934, p = 0.391) times in more risk than the non-diabetic counterpart. CONCLUSION: This method addressing its easy applicability in biomedical research. And by this we were able to show that patients with high LDL (≥150 mg/dL) are in alarming condition besides diabetic and elderly (≥40 years age) males are considered to be susceptible and more prone to develop vascular diseases

Enhancing Motivation and Work Performance of the Salespeople: The Impact of Supervisors’ Behavior

This study examines the importance of authoritarian and positive achievement motivation behavior of the supervisors in enhancing salespeople’s motivation and work performance. Survey data were collected from all 105 sales employees in two retail organizations. Supervisors’ ratings were collected on all 105 of the salespersons. All hypotheses were tested using regression analysis and Pearson correlations controlling for background variables of gender, marital status, and ethnicity. The findings indicated that to the extent that supervisors engaged in positive motivational behaviors, salespersons’ intrinsic motivations were increased, which, in turn, increased their performance. Implications and a number of recommendations are discussed

Determination of Carbamate and Organophosphorus Pesticides in Vegetable Samples and the Efficiency of Gamma-Radiation in Their Removal

In the present study, the residual pesticide levels were determined in eggplants (Solanummelongena)