A comparative study of linear control strategies on the aerodynamics twin rotor system

Adnan Qayyum Shah,Muhammad Awais,Muhammad Zafar,Ashfaq Ahmed,Muhammad Mudassar,Muhammad Muneer,Memoona Saif,Abdul Razzaq,Seong Ho Jang,김선형,박영권 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.8

This work presents the comparative study among pole-placement (PP), optimalcontrol using output-feedback (OCOF), linear-quadratic regulator (LQR), and PID controllers for the twin rotor multi-input multi-output system (TRMS). The pitch and yaw are key attributes for stabilizing the TRMS MIMO system and control of flight. The main objective of this study is to use these classical controller techniques to monitor the pitch and yaw angles of TRMS and show the result of these techniques. Simulation results depicts the actual performance and reveals how PP outperforms the other techniques.

Object Tracking With A Robotic Manipulator Mounted On Ground Vehicle Using Image Based Visual Servoing

Muhammad Ahsan Sami,Muhammad Umar Masood,Muhammad Waqar,Muhammad Mujtaba,Abrahim Ali Shah,Nasir Rashid,Mohsin I. Tiwana,Javaid Iqbal,Adnan Shujah 제어로봇시스템학회 2017 제어로봇시스템학회 국제학술대회 논문집 Vol.2017 No.10

This paper presents an application of a novel approach for detecting and tracking an object with a 2 DOF robotic manipulator which can be equipped with an array of electrically controlled actuators. The said approach utilizes the Image Based Visual Servoing (IBVS) technique. The developed system is able to determine the object pose in real time from features in the image. Object is detected using shaped based approach algorithms of image processing. The position and orientation of the world coordinates of the object being tracked are calculated from the coordinates of the object in image plane using camera’s intrinsic and extrinsic parameters. Experimental results demonstrate the effectiveness of this proposed approach.

The Effects of Fermented and Non-Fermented Soymilk (Glycine max) Beverage on Superoxide Dismutase Activity in Liver Tissue of Hyperlipidemic Rats (Rattus Norvegicus)

( Muhammad Luthfi Adnan ),( Dini Islamiana ),( Hilmi Ardian Sudarto ),( Miranti Dewi Pramaningtyas ) 대한간학회 2020 춘·추계 학술대회 (KASL) Vol.2020 No.1

Aims: Hyperlipidemia and oxidative stress are risk factors for various diseases such as cancer and increase the risk of liver stenosis. Reactive oxygen species arising from oxidative stress in hyperlipidemic conditions can cause liver cell damage. Superoxide Dismutase is a natural antioxidant in the body to fight oxidative stress. Soybeans have long been known to have good effects on health. Soybeans contain oligosaccharides which are good for the growth of probiotic bacteria. Probiotics can reduce lipid levels and have antioxidant activity. The aim of this study was to determine the effect between ferments and non-fermented soy drinks on superoxide dismutase activity in hyperlipidemic rat liver tissue. Methods: The subjects are male Wistar (Rattus norvegicus) strain rats 2-3 months with body weight 200-300 grams divided into 4 groups (K+, K-, P1, and P2). Group of K+, P1, and P2 were given quail egg yolk for 2 weeks with a dose of 5 ml while group of K- were only given fed ad libitum. For the next 2 weeks, P1 group was given non-fermented soymilk (5 ml), and fermented soymilk (5 ml) for P2 group. All rats terminated to taken the liver tissue to measure the level of superoxide dismutase activity. All data were statistically analyzed with one way ANOVA. Values were considered significant at P<0,05. Results: Mean of superoxide dismutase activity (expressed in percent (%)) in rats was 68,75 ± 1,68 in K- group, 16,08 ± 1,33 in K+ group, 41,79 ± 1,33 in P1 group and 57,81 ± 2,38. The One-Way ANOVA test showed significant differences in superoxide dismutase activity between group with P<0,001 and Bonferroni Post Hoc test P<0,001. Conclusions: Fermented and non-fermented soymilk has a significant effect of increasing superoxide dismutase activity in hyperlipidemic rat liver tissue. Fermented soymilk has a higher superoxide dismutase activity compared to non-fermented soymilk.

Institutional Ownership Heterogeneity and Earnings Management Practices

Muhammad Adnan PARWAR,Shahzad HUSSAIN,Abdul WAHEED,Qaisar Ali MALIK,Muddasir MEHBOOBMuhammad Adnan PARWAR,Shahzad HUSSAIN,Abdul WAHEED,Qaisar Ali MALIK,Muddasir MEHBOOB 한국유통과학회 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.6

The manipulation of the firms’ earnings reported in the financial statements, also known as earnings management, is common among companies. The current study examined the relationship of institutional ownership heterogeneity and earnings management practices through the Arellano-Bond Dynamic Data-Estimation regression approach. The study adopted the Kothari et al. (2005) model for the measurement of earnings management practices. The research classified the institutional investors into different categories such as mutual funds, pension funds, investment companies, foreign companies, and group ownership. The study analyzed the selected variables by tanking a sample of 206 listed companies on Pakistan Stock Exchange (PSX) for 2013 to 2018. Consistent with agency theory, the results reveal that mutual funds and financial firms’ ownership curtail earnings management practices. Our results reveal the negligible effect of group ownership, investment companies’ ownership, and pension funds ownership in curtailing the earnings management practices in Pakistan. As a result, the findings support monitoring the role of hedge funds and international ownership in earnings management, which restricts managers’ opportunistic behavior. Thus, the proclivity of earnings management practices by managers is mitigated by mutual funds and foreign ownership as compared to the other institutional ownership structure in Pakistani firms.

Variability and Predictability of Summer Monsoon Rainfall over Pakistan

Adnan Muhammad,Khan Firdos,Rehman Nadia,Ali Shaukat,Hassan Sher Shah,Dogar Muhammad Mubashar,Mehmood Shahbaz,Hasson Shabehul 한국기상학회 2021 Asia-Pacific Journal of Atmospheric Sciences Vol.57 No.1

Rainfall variability associated with the South Asian Summer Monsoon has increased in recent decades, particularly at the northwestern monsoon margins over Pakistan, leading to more frequent and intense hydro-meteorological extremes that have adversely affected the agrarian economy, water and food security in the country. Devising effective strategies to ensure sustainable development in Pakistan thus requires that the monsoonal rainfall be predicted on an inter-annual scale. Here, we predicted the inter- and intra-annual variability of the monsoonal rainfall over Pakistan and its possible drivers using a linear statistical forecast model of the principal component (PC) regression analysis. For this purpose, highly correlated PCs of the National Centre for Environmental Prediction (NCEP) based sea level pressure, horizontal and meridional winds to the observed rainfall for the period 2001–2013 were ingested in a stepwise multiple regression model, which was further validated for the duration of 2014–2015. Our results suggest that featuring correlation coefficient, mean absolute error, mean bias, and root mean square error of 0.75, 42.23, −14.92 and 60.65, respectively, the model exhibits robust skill in predicting the inter-annual monsoonal rainfall variability at its extreme northwestern margins over Pakistan.

Enhancement in the Photovoltaic Properties of Hole Transport Materials by End-Capped Donor Modifications for Solar Cell Applications

Muhammad Yasir Mehboob,Riaz Hussain,Zobia Irshad,Muhammad Adnan 대한화학회 2021 Bulletin of the Korean Chemical Society Vol.42 No.4

Efficient hole transport materials for solar cell applications are gained huge intension of every scientist. Hole transport materials play a dominant role in solar cells as they provide high power conversion efficiency along with low cost, less toxic, and easy synthesis routs. Motivates from valuable literature, here efforts are being made to designed new novel hole transport materials for solar cell applications. Five new and highly efficient hole transport molecules (BT1–BT5) are designed after end-capped donor modifications of recently synthesized B3 (R) molecule. The photovoltaic, optoelectronic, and structural-property relationship of all designed molecules are extensively studied while using density functional theory and time-dependent density functional theory at MPW1PW91/6-31G(d,p) basis set. Low reorganizational energy of hole is observed in all designed molecules as compared to reference molecule which suggested that designed molecules have high hole mobility as compared to R molecule. Red-shifting in absorption spectrum of designed molecules (as compared to reference molecule) is also seen which offer high power conversion efficiency and high excited highest occupied molecular orbital to lowest unoccupied molecular orbital charge shifting. Low binding and excitation energies are observed in designed molecules. Molecular electrostatic potential, transition density matrix, hole–electron overlap as heat map, open circuit voltage, density of states, and complex study of BT5:PC61BM is also performed for all studied molecule. After all analysis, we believed that our theoretical designed molecules are superior to R molecule, thus we recommend these molecules to experimentalist for future development of highly-efficient solar cells.

Challenges and Issues of Resource Allocation Techniques in Cloud Computing

( Adnan Abid ),( Muhammad Faraz Manzoor ),( Muhammad Shoaib Farooq ),( Uzma Farooq ),( Muzammil Hussain ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.7

In a cloud computing paradigm, allocation of various virtualized ICT resources is a complex problem due to the presence of heterogeneous application (MapReduce, content delivery and networks web applications) workloads having contentious allocation requirements in terms of ICT resource capacities (resource utilization, execution time, response time, etc.). This task of resource allocation becomes more challenging due to finite available resources and increasing consumer demands. Therefore, many unique models and techniques have been proposed to allocate resources efficiently. However, there is no published research available in this domain that clearly address this research problem and provides research taxonomy for classification of resource allocation techniques including strategic, target resources, optimization, scheduling and power. Hence, the main aim of this paper is to identify open challenges faced by the cloud service provider related to allocation of resource such as servers, storage and networks in cloud computing. More than 70 articles, between year 2007 and 2020, related to resource allocation in cloud computing have been shortlisted through a structured mechanism and are reviewed under clearly defined objectives. Lastly, the evolution of research in resource allocation techniques has also been discussed along with salient future directions in this area.

An efficient hydration of nitriles with ruthenium-supported heterogeneous catalyst in water under moderate conditions

Muhammad Asif Hussain,최은주,Adnan Maqbool,Muhammad Atif,Hassan Zeb,여재구,유정아,조영훈,Moses Noh,김정원 한국공업화학회 2021 Journal of Industrial and Engineering Chemistry Vol.99 No.-

A facile eco-friendly heterogeneous catalytic system has been developed for amide synthesis that furtherutilized in pharmaceutical and organic chemistry. The Ru/MnO2 catalyst has shown outstanding andunprecedented activity for a wide range of aliphatic and benzylic nitriles in green solvent water at 60 C. The system has also exhibited a remarkable tolerance for selective hydration of heteroatom (e.g. nitrogen,oxygen and sulphur atoms) containing nitriles. Pharmaceutically important nicotinamides andpyrazinamide has been synthesized by hydration of the heteroatomic nitriles with appreciable yieldsand selectivities. Moreover, the Ru/MnO2 catalyst has employed water as a benign solvent, with morethan 30,000 TONs and reusabilityfive times after isolation from the reaction mixture by centrifugationand easy workup that established a path for green environmental and technologically acceptableprotocol.

The Role of Virtual Community Participation and Engagement in Building Brand Trust: Evidence from Pakistan Business Schools

Muhammad TABISH,Muhammad Adnan BASHIR,Muhammad Mansoor ALAM,Zalizah Awang LONG,Mohd. Khairil RAHMAT 한국유통과학회 2022 The Journal of Asian Finance, Economics and Busine Vol.9 No.3

The purpose of this study is to examine the role of virtual community participation and engagement in the brand decision by building community and brand trust. In this study, two theories (Social Capital Theory and Theory of Collective Action) were tested. Both theories were linked based on existing literature, and empirical evidence was obtained through testing hypotheses. Students from five prestigious Pakistani business schools provided a total of 849 replies. The measurement model and structural model were both analyzed using the partial least square (PLS) method. The findings show that virtual community engagement and participation have a positive and significant impact on virtual community trust. Although virtual community engagement has a positive effect on brand trust, we found no evidence of a link between virtual community participation and brand trust. Later, these trusts positively influence brand choice. This study has several managerial implications. The suggested model of this study helps managers to get customers’ insight, choose the right target market, and set integrated marketing communication strategies besides social media marketing strategies. The study represents a new perspective of consumer behavior that helps to understand how a customer behaves in virtual communities to trust and take the final decision to purchase.

An Application of Machine Learning in Retail for Demand Forecasting

Muhammad Umer Farooq,Mustafa Latif,Waseem,Mirza Adnan Baig,Muhammad Ali Akhtar,Nuzhat Sana International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.8

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.