Search results for: Aya M. Matloob

Authors: S. Said, Samira M. Abdel-Azim, Aya M. Matloob

Abstract:

Nowadays, one of the most important industries is how to prepare a starting material like (styrene) which is used for the preparation of many petrochemical products in simple and inexpensive ways. Oxidative dehydrogenation of ethylbenzene (using CO2 as a soft oxidant) can solve this issue when using highly effective catalysts like SnO₂ and its nanocomposites (V₂Ox/SnO₂.) This study shows the effect of different synthesis methods of SnO₂ either by ethylene glycol or MOF then, uses the impregnation method for the preparation of its nanocomposite catalysts (V₂Ox/SnO₂.). The prepared catalysts were characterized by using different analytical techniques like XRD, BET, FTIR, TGA, XPS, and H₂-TPR. Oxidative dehydrogenation experimental results demonstrated that the composite V loading of 1 and 5 wt.% V₂Ox/SnO₂ (MOF &EG) catalyst exhibited extraordinarily high catalytic performance with selectivity toward styrene formation > 90% at 500oC, which can be attributed to the superior surface, textural, and structural properties of nanocomposites catalysts.

Keywords: SnO₂, vanadium oxide, ethylbenzene dehydrogenation, styrene, CO₂

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Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif

Abstract:

As Indo-Pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.

Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix

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Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif

Abstract:

As Indo-pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring the prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.

Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix

Procedia PDF Downloads 351

Authors: Ling Qi, Matloob Khushi, Josiah Poon

Abstract:

This paper introduces a pre-trained Masked Candlestick Model (MCM) for trading time-series data. The pre-trained model is based on three core designs. First, we convert trading price data at each data point as a set of normalized elements and produce embeddings of each element. Second, we generate a masked sequence of such embedded elements as inputs for self-supervised learning. Third, we use the encoder mechanism from the transformer to train the inputs. The masked model learns the contextual relations among the sequence of embedded elements, which can aid downstream classification tasks. To evaluate the performance of the pre-trained model, we fine-tune MCM for three different downstream classification tasks to predict future price trends. The fine-tuned models achieved better accuracy rates for all three tasks than the baseline models. To better analyze the effectiveness of MCM, we test the same architecture for three currency pairs, namely EUR/GBP, AUD/USD, and EUR/JPY. The experimentation results demonstrate MCM’s effectiveness on all three currency pairs and indicate the MCM’s capability for signal extraction from trading data.

Keywords: masked language model, transformer, time series prediction, trading prediction, embedding, transfer learning, self-supervised learning

Procedia PDF Downloads 123

Authors: Tayyaba Zahra, Shehla Gul Bokhari, Asim Khalid Mahmood, Raheela Akhtar, Khizar Matloob

Abstract:

In Pakistan, dogs are commonly infested with ticks, especially in summers, causing not only dermatological issues but also systemic problems. Persistence of tick infestation often leads to heavy losses. Different acaricides are locally available with variable efficacy; however, recurrence of infestation is commonly reported. The present study was thus designed to compare the efficacy of a novel drug Fluralaner and conventionally used Ivermectin against tick infestation. Dogs positive for tick infestation were randomly divided into 2 groups viz, Groups A and B having 8 dogs each. Ticks were enumerated manually from the whole body of dogs at day 0 before the administration of drugs Dogs in Group A were treated with Fluralaner at day 0, and dogs in Group B were treated with Ivermectin. Post-treatment, ticks were counted again at days 7, 14, 21, 28, and 35. At day 07 of the study, no tick was found on the dogs treated with Fluralaner, while many ticks were present on the dogs treated with Ivermectin showing an efficacy up to 50%. On the consecutive follow-up evaluations, similar results were found for Fluralaner while the efficacy of Ivermectin was further reduced to less than 50%. Furthermore, Fluralaner treated dogs had better RBC counts, PCV, Hgb concentration, LFTs, RFTs post-treatment than the dogs treated with Ivermectin. Statistically, oral Fluralaner proved a more effective drug (P≤0.05)than oral Ivermectin against tick infestation in dogs.

Keywords: fluralaner, ivermectin, dogs, tick infestations

Procedia PDF Downloads 196

Authors: M.A. Ali, M. Matloob, A. Sahar, M. Yamin, M. Imran, Y.A. Yusof

Abstract:

Quinoa (Chenopodium quinoa Willd.) is known as pseudocereal was originated in South America's Andes. Quinoa is a good source of protein, amino acids, micronutrients and bioactive components. The lack of gluten makes it suitable for celiac patients. Saponins, the leading ant-nutrient, are found in the pericarp, which adheres to the seed and transmits the bitter flavor to the quinoa grain. It is found in varying amounts in quinoa from 0.1% to 5%. This study was planned to design an indigenous machine to remove saponin from quinoa grains at the farm level to promote entrepreneurship. The machine consisted of a feeding hopper, rotating shaft, grooved stone, perforated steel cylinder, V-belts, pulleys, electric motor and mild steel angle iron and sheets. The motor transmitted power to the shaft with a belt drive. The shaft on which the grooved stone was attached rotated inside the perforated cylinder having a clearance of 2 mm and was removed saponin by an abrasion mechanism. The saponin-removed quinoa was then dipped in water to determine the presence of saponin as it produced foam in water and data were statistically analyzed. The results showed that the raw seed feeding rate of 25 g/s and milling time of 135 s completely removed saponin from seeds with minimum grain losses of 2.85% as compared to the economic analysis of the machine showed that its break-even point was achieved after one and half months with 18,000 s and a production capacity of 33 g/s.

Keywords: quinoa seeds, saponin, abrasion mechanism, stone polishing, indigenous machine

Procedia PDF Downloads 71