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Zulfiqar Ahmad,Nauman Khalid,Masood Sadiq Butt,Anwaar Ahmed 한국응용생명화학회 2013 Applied Biological Chemistry (Appl Biol Chem) Vol.56 No.6
Effects of various xylanase treatments applied at different stages of bread making process on dough rheological characteristics and bread quality attributes were investigated. Different doses (200, 400, 600, 800, and 1000 IU) of purified enzyme were applied at two stages (tempering and mixing). In milling and dough making processes, both types of flour (subjected to enzyme treatment during tempering and flour mixing) exhibited decreasing trend in water absorption, dough development time, dough stability, softening of dough, dough mixing time, viscosity peak, set back, and increasing tendency in peak height and pasting temperature. Treatments during tempering resulted in more significant effects as compared to applications during flour mixing. The dough rising during proofing resulted in enhancement from 137±3.21% (control) to maximum value (192.33±2.90%), when 600 IU of xylanases were applied to 1 kg of wheat grains during tempering. The bread sensory attributes also exhibited significant improvement in response to various doses of purified enzymes.
Preliminary pharmacognostical and phytochemical evaluation of Stachys tibetica Vatke
Zulfiqar Ali Bhat,Dinesh Kumar,Vijender Kumar,Ishtaq Ahmad Chashoo,Nisar Ahmad Khan,Irfat Ara,Mohammad Yassin Shah 셀메드 세포교정의약학회 2012 TANG Vol.2 No.1
Stachys tibetica Vatke (Lamiaceae) is an important medicinal plant in the folk medicine of Ladakh, India and Tibet for the treatment of various mental disorders. Infusion and decoction of the whole plant is used as a cup of tea for a severe fever, headaches and to relieve tension. The recent study is aimed to evaluate the preliminary pharmacognostical and phytochemical nature of Stachys tibetica Vatke. The whole plant material was subjected to successive soxhlet extraction with petroleum ether (40 - 60C), chloroform, ethyl acetate, methanol and finally decocted with water to get the respective extracts. The fluorescence characteristics of the powdered materials were analysed under ultraviolet light and ordinary light. Different physicochemical parameters such as ash value, extractive value, foaming index, pH values, loss on drying and determination of foreign matter were carried out as per WHO guidelines. The total fat, flavonoid, saponin and volatile contents were also determined. Macroscopical studies revealed the authentication of the plant drug. Physicochemical parameters helped to standardize the plant material while preliminary qualitative chemical tests of different extracts showed the presence of Glycosides, Carbohydrates, Phytosterols/triterpenoids, Saponins, Fixed oils, Fats and phenols/tannins. Quantification of the total flavonoids and saponins and contents were determined as 54.66 ± 0.58 mg/g and 75.42 ± 0.48 mg/kg respectively, while the volatile and fat contents were 6.5% and 0.7% respectively. Results may lay the foundation for the standardization of the drug and discovery of new molecules from S. tibetica for the treatment of various diseases.
듀얼 스트림 CNN-LSTM 아키텍처를 사용한 태양광 발전 예측
Zulfiqar Ahmad Khan,Noman Khan,Su Min Lee,Sang Il Yoon,Mi Young Lee,Sung Wook Baik 한국차세대컴퓨팅학회 2022 한국차세대컴퓨팅학회 학술대회 Vol.2022 No.05
The integration of solar energy with a power system brings great economic and environmental benefits. However, the high penetration of solar power challenges the operation and planning of the existing power system owing to the intermittence and randomicity of solar power generation. Achieving accurate prediction for power generation is important to provide balanced electric energy for end-users. Therefore, in this paper, we introduce a deep learning-based dual stream Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network to learn spatial patterns using CNN and temporal features via the LSTM network. These features are then fused via a concatenation layer and then feed forward to Dense layers for optimal features selection and future solar power prediction. The performance of the proposed model is evaluated on benchmark datasets and achieved a new state-of-the-art on these datasets.
Ahmad, Zulfiqar,Butt, Masood Sadiq,Ahmed, Anwaar,Khalid, Nauman The Korean Society for Applied Biological Chemistr 2013 Applied Biological Chemistry (Appl Biol Chem) Vol.56 No.6
Effects of various xylanase treatments applied at different stages of bread making process on dough rheological characteristics and bread quality attributes were investigated. Different doses (200, 400, 600, 800, and 1000 IU) of purified enzyme were applied at two stages (tempering and mixing). In milling and dough making processes, both types of flour (subjected to enzyme treatment during tempering and flour mixing) exhibited decreasing trend in water absorption, dough development time, dough stability, softening of dough, dough mixing time, viscosity peak, set back, and increasing tendency in peak height and pasting temperature. Treatments during tempering resulted in more significant effects as compared to applications during flour mixing. The dough rising during proofing resulted in enhancement from $137{\pm}3.21$% (control) to maximum value ($192.33{\pm}2.90$%), when 600 IU of xylanases were applied to 1 kg of wheat grains during tempering. The bread sensory attributes also exhibited significant improvement in response to various doses of purified enzymes.
Salvatrione : A Diterpene-monoterpene Conjugate from Salvia bucharica
Viqar Uddin Ahmad,Muhammad Zahid,Muhammad Shaiq Ali,Amir Reza Jassbi,Shakeel Ahmad,Zulfiqar Ali,Muhammad Zafar Iqbal 한국생약학회 2000 Natural Product Sciences Vol.6 No.2
Salvia bucharica belonging to the family Lamiaceae (Labiatae), afforded a novel terpenoid (1) named as salvatrione. The structure of 1 was elucidated through extensive 2-D NMR experiments and the biogenetic pathway of 1 has also been proposed. On biogenetic grounds, 1 may be considered to be a pseudo-triterpenoid as it is derived from the coupling of mono/diterpenic units and not from squalene.
Ahmad, Fayyaz,Jang, T.S.,Carrasco, Juan A.,Rehman, Shafiq Ur,Ali, Zulfiqar,Ali, Nukhaze Elsevier 2018 Applied mathematics and computation Vol.334 No.-
<P><B>Abstract</B></P> <P>An efficient iterative method is developed for the static analysis of large deflections of an infinite beam with variable cross-section resting on a nonlinear foundation. A pseudo spring constant is added and explicit matrix operators are introduced to perform differentiation through Green’s function. The nonlinearity of the problem is handled with quasilinearization. To compute the solution of the quasilinear differential equation with prescribed accuracy, a new discretization method for solving quasilinear differential equations involving up to the 4th order derivative is used. The discretization method is based on relating discretizations of up to the fourth order derivative of the solution with a discretization of the solution by using a suitable Green function. Numerical experiments show that the error incurred by the discretization can be made small for the two first derivatives and that the method proposed in the paper converges fast and has good accuracy.</P>
Naseer Ahmad,Shahid Kamal,Zulfiqar Ali Raza,Sharjeel Abid,Muhammad Zeshan 한국섬유공학회 2020 Fibers and polymers Vol.21 No.5
Present work investigates multi-response optimization in development of super-oleohydrophobic cotton fabricunder pad-dry-cure method. A bleached cotton fabric was treated with ZnO nanoparticles (NPs) incorporated oil and waterrepellent finish (Oleophobol CP-C®) to impart in it antibacterial activity, UV protection and super oleo/hydrophobicity. Taguchi based fuzzy logics and grey relational analytical techniques were employed to obtain simultaneous optimum settingsof input parameters including concentrations of ZnO NPs, O-CPC® finish and Knittex FEL®, and curing temperature formultiple responses. The fuzzy logics and grey relational analysis were employed on the experimental data to determinesignificant process parameters for optimization of multiple responses. The present set of techniques was effectively used todevelop super-hydrophobic (WCA: 162 o) and oleophobic (OCA: 140 o) cotton fabric along with appropriate textileproperties as reported in the text. The developed fabric has potential uses in various domestic and house-hold applicationsdue to its antibacterial, self-cleaning, non-staining and UV-protection properties.
Habib Khan,Zulfiqar Ahmad Khan,Waseem Ullah,Min Jee Kim,Mi Young Lee,Sung Wook Baik 한국차세대컴퓨팅학회 2023 한국차세대컴퓨팅학회 학술대회 Vol.2023 No.06
Accurate detection of small targets in aerial images is crucial but challenging due to the limited computational resources of UAVs. This paper presents an efficient approach based on YOLO-V5S for detecting and classifying distant vehicles in aerial scenes. Extensive ablation study is conducted to find the optimal YOLO architecture. The proposed method is efficient and effective, making it applicable for real-time deployment. A dataset of 1000 annotated images are developed to validate the proposed method's effectiveness. The proposed network outperforms existing state-of-the-art methods in accuracy, speed, and resource efficiency, making it a promising solution for aerial vision-based applications.
Two New Sesquiterpenes from Pluchea arguta
Viqar Uddin Ahmad,Muhammad Zahid,Rasheeda Khatoon,Zulfiqar Ali,Muhammad Abbas,Muhammad Zafar Iqbal 한국생약학회 1999 Natural Product Sciences Vol.5 No.2
Two new sesquiterpenes, 3`-chloro-2`-hydroxy-3-epi-arguticinin (1) and argutenol (2) belonging to eudesmane and gorgonane classes respectively, have been isolated from Pluchea arguta. Their structures were elucidated with the help of sophisticated spectroscopic techniques including nOe difference and NOESY experiments.
A Fault Tolerant Data Management Scheme for Healthcare Internet of Things in Fog Computing
( Waqar Saeed ),( Zulfiqar Ahmad ),( Ali I. Jehangiri ),( Nader Mohamed ),( Arif I. Umar ),( Jamil Ahmad ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.1
Fog computing aims to provide the solution of bandwidth, network latency and energy consumption problems of cloud computing. Likewise, management of data generated by healthcare IoT devices is one of the significant applications of fog computing. Huge amount of data is being generated by healthcare IoT devices and such types of data is required to be managed efficiently, with low latency, without failure, and with minimum energy consumption and low cost. Failures of task or node can cause more latency, maximum energy consumption and high cost. Thus, a failure free, cost efficient, and energy aware management and scheduling scheme for data generated by healthcare IoT devices not only improves the performance of the system but also saves the precious lives of patients because of due to minimum latency and provision of fault tolerance. Therefore, to address all such challenges with regard to data management and fault tolerance, we have presented a Fault Tolerant Data management (FTDM) scheme for healthcare IoT in fog computing. In FTDM, the data generated by healthcare IoT devices is efficiently organized and managed through well-defined components and steps. A two way fault-tolerant mechanism i.e., task-based fault-tolerance and node-based fault-tolerance, is provided in FTDM through which failure of tasks and nodes are managed. The paper considers energy consumption, execution cost, network usage, latency, and execution time as performance evaluation parameters. The simulation results show significantly improvements which are performed using iFogSim. Further, the simulation results show that the proposed FTDM strategy reduces energy consumption 3.97%, execution cost 5.09%, network usage 25.88%, latency 44.15% and execution time 48.89% as compared with existing Greedy Knapsack Scheduling (GKS) strategy. Moreover, it is worthwhile to mention that sometimes the patients are required to be treated remotely due to non-availability of facilities or due to some infectious diseases such as COVID-19. Thus, in such circumstances, the proposed strategy is significantly efficient.