Forecasting Chinese Yuan/USD Via Combination Techniques During COVID-19

Muhammad ASADULLAH,Imam UDDIN,Arsalan QAYYUM,Sharique AYUBI,Rabia SABRI 한국유통과학회 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.5

This study aims to forecast the exchange rate of the Chinese Yuan against the US Dollar by a combination of different models as proposed by Poon and Granger (2003) during the Covid-19 pandemic. For this purpose, we include three uni-variate time series models, i.e., ARIMA, Naïve, Exponential smoothing, and one multivariate model, i.e., NARDL. This is the first of its kind endeavor to combine univariate models along with NARDL to the best of our knowledge. Utilizing monthly data from January 2011 to December 2020, we predict the Chinese Yuan against the US dollar by two combination criteria i.e. var-cor and equal weightage. After finding out the individual accuracy, the models are then assessed through equal weightage and var-cor methods. Our results suggest that Naïve outperforms all individual & combination of time series models. Similarly, the combination of NARDL and Naïve model again outperformed all of the individual as well as combined models except the Naïve model, with the lowest MAPE value of 0764. The results suggesting that the Chinese Yuan exchange rate against the US Dollar is dependent upon the recent observations of the time series. Further evidence shows that the combination of models plays a vital role in forecasting which commensurate with the literature.

Role of microporosity and surface functionality of activated carbon in methylene blue dye removal from water

Mohammad Asadullah,Mohammad Shajahan Kabir,Mohammad Boshir Ahmed,Nadiah Abdul Razak,Nurul Suhada Abdur Rasid,Airin Aezzira 한국화학공학회 2013 Korean Journal of Chemical Engineering Vol.30 No.12

Activated carbons have been prepared from jute stick by both chemical and physical activation methods using zinc chloride and steam, respectively. They were characterized by evaluating surface area, iodine number, pore size distribution, and concentration of surface functional groups. The chemically activated carbon largely featured micropore structure,while the physically activated carbon mainly featured macropore structure. The specific surface area of chemically and physically activated carbons was 2,325 and 723 m2/g, while the iodine number was 2,105 and 815mg/g, respectively. The concentration of surface functional groups was determined by Boehm titration method, which suggested that different types of surface functional groups are randomly distributed on chemical activated carbons, while it is limited for physical activated carbon. The microporosity along with surface functional groups provided a unique property to chemically activated carbon to adsorb Methylene Blue dye to a large extent. The adsorption of dye was also affected by the adsorption parameters such as adsorption time, temperature and pH. Comparatively, higher temperature and pH significantly facilitated dye adsorption on chemically activated carbon.

Preparation of microporous activated carbon and its modification for arsenic removal from water

Mohammad Asadullah,Israt Jahan,Mohammad Boshir Ahmed,Pasilatun Adawiyah,Nur Hanina Malek,Mohammad Sahedur Rahman 한국공업화학회 2014 Journal of Industrial and Engineering Chemistry Vol.20 No.3

Arsenic removal from water was investigated using activated carbon. The chemical activated carbon(CAC) prepared using H3PO4 from jute stick largely featured micropore structure with surface functionalgroups, while meso- and macropore structures were mainly developed in physical activated carbon(PAC). The CAC and PAC reduced arsenic concentration to 45 and 55 mg L-1, respectively, from100 mg L-1 while iron-loaded CAC reduced to 3 mg L-1, which is lower than the upper permissible limit(10 mg L-1). The micropore structure of CAC along with complexation affinity of iron species towardsarsenic species attributed to enhanced separation of arsenic.

Forecasting Exchange Rates: An Empirical Application to Pakistani Rupee

Muhammad ASADULLAH,Adnan BASHIR,Abdur Rahman ALEEMI 한국유통과학회 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.4

This study aims to forecast the exchange rate by a combination of different models as proposed by Poon and Granger (2003). For this purpose, we include three univariate time series models, i.e., ARIMA, Naïve, Exponential smoothing, and one multivariate model, i.e., NARDL. This is the first of its kind endeavor to combine univariate models along with NARDL to the best of our knowledge. Utilizing monthly data from January 2011 to December 2020, we predict the Pakistani Rupee against the US dollar by a combination of different forecasting techniques. The observations from M1 2020 to M12 2020 are held back for in-sample forecasting. The models are then assessed through equal weightage and var-cor methods. Our results suggest that NARDL outperforms all individual time series models in terms of forecasting the exchange rate. Similarly, the combination of NARDL and Naïve model again outperformed all of the individual as well as combined models with the lowest MAPE value of 0.612 suggesting that the Pakistani Rupee exchange rate against the US Dollar is dependent upon the macro-economic fundamentals and recent observations of the time series. Further evidence shows that the combination of models plays a vital role in forecasting, as stated by Poon and Granger (2003).

Life cycle assessment to evaluate the green house gas emission from oil palm bio-oil based power plant

Mohammad Asadullah,Nurul Suhada Abdur Rasid,Syed Shatir Asghrar Syed-Hassan,Sharifah Aishah Syed Abdul Kadir 한국화학공학회 2013 Korean Journal of Chemical Engineering Vol.30 No.6

The objective of this study is to assess the green house gas (GHG) emission for the production of bio-oil from oil palm biomass and its utilization for 10 MW power generation by evaluating the life cycle carbon footprint analysis. The life cycle GHG emission assessment includes four main stages, which cover the oil-palm cultivation,palm oil mill operation, biomass transportation and pyrolysis process for the production of bio-oil and its utilization for 10MW power generation. The results obtained suggest that the palm bio-oil has potential as a carbon neutral renewable energy source in the future. More importantly, it has no negative impact on the environment as the amount of CO2 emitted to the atmosphere during combustion of this fuel is lower than that of the CO2 absorbed from the atmosphere during cultivation stage.

The Costs and Financing of Education: Trends and Policy Implications

M. Niaz Asadullah 서울대학교 교육연구소 2004 Asia Pacific Education Review Vol.5 No.1

Risk Management Policy of Telecommunication and Engineering Laboratory

Abdul Salam Shah,Muhammad Fayaz,Asadullah Shah,Shahnawaz Shah 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.4

The Telecommunication laboratory plays an important role in carrying out research in the different fields like Telecommunication, Information Technology, Wireless Sensor Networks, Mobile Networks and many other fields. Every Engineering University has a setup of laboratories for students particularly for Ph.D. scholars to work on the performance analysis of different Telecommunication Networks including WLANs, 3G/4G, and Long Term Evolution (LTE). The laboratories help students to have hand on practice on the theoretical concepts they have learned during the teachings at the university. The technical subjects have a practical part also which boosts the knowledge of students and learning of new ideas. The Telecommunication and Engineering laboratories are equipped with different electronic equipment’s like digital trainers, simulators etc. and some additional supportive devices like computers, air conditioners, projectors, and large screens, with power backup facility that creates the perfect environment for experimentation. The setup of Telecommunication and Engineering laboratories cost huge amount, required to purchase equipment, and maintain the equipment. In any working environment risk factor is involved. To handle and avoid risks there must be risk management policy to tackle with accidents and other damages during working in the laboratory, may it be human or equipment at risk. In this paper, we have proposed a risk management policy for the Telecommunication and Engineering laboratories, which can be generalized for similar type of laboratories in engineering fields of studies.

Testing Desktop Application : Police Station Information Management System

Abdul Salam Shah,Muhammad Fayaz,Asadullah Shah,Shahnawaz Shah 보안공학연구지원센터 2016 International Journal of Software Engineering and Vol.10 No.7

The police stations have adequate importance in the society to control the law and order situations of the country. In Pakistan, police stations manage criminal records and information manually. We have previously developed and improved a desktop application for the record keeping of the different registers of the police stations. The data of police stations is sensitive and that need to be handled within secured and fully functional software to avoid any unauthorized access. For the proper utilization of the newly developed software, it is necessary to test and analyze the system before deployment into the real environment. In this paper, we have performed the testing of an application. For this purpose, we have used Ranorex, automated testing tool for the functional and performance testing, and reported the results of test cases as pass or fail.

A Robust Technique of Brain MRI Classification using Color Features and K-Nearest Neighbors Algorithm

Muhammad Fayaz,Abdul Salam Shah,Fazli Wahid,Asadullah Shah 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.10

The analysis of MRI images is a manual process carried by experts which need to be automated to accurately classify the normal and abnormal images. We have proposed a reduced, three staged model having pre-processing, feature extraction and classification steps. In preprocessing the noise has been removed from grayscale images using a median filter, and then grayscale images have been converted to color (RGB) images. In feature extraction, red, green and blue channels from each channel of the RGB has been extracted because they are so much informative and easier to process. The first three color moments mean, variance, and skewness are calculated for each red, green and blue channel of images. The features extracted in the feature extraction stage are classified into normal and abnormal with K-Nearest Neighbors (k-NN). This method is applied to 100 images (70 normal, 30 abnormal). The proposed method gives 98.00% training and 95.00% test accuracy with datasets of normal images and 100% training and 90.00% test accuracy with abnormal images. The average computation time for each image was .06s.

An Offline Signature Verification Technique Using Pixels Intensity Levels

Abdul Salam Shah,M.N.A. Khan,Fazli Subhan,Muhammad Fayaz,Asadullah Shah 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.8

Offline signature recognition has great importance in our day to day activities. Researchers are trying to use them as biometric identification in various areas like banks, security systems and for other identification purposes. Fingerprints, iris, thumb impression and face detection based biometrics are successfully used for identification of individuals because of their static nature. However, people’s signatures show variability that makes it difficult to recognize the original signatures correctly and to use them as biometrics. The handwritten signatures have importance in banks for cheque, credit card processing, legal and financial transactions, and the signatures are the main target of fraudulence. To deal with complex signatures, there should be a robust signature verification method in places such as banks that can correctly classify the signatures into genuine or forgery to avoid financial frauds. This paper, presents a pixels intensity level based offline signature verification model for the correct classification of signatures. To achieve the target, three statistical classifiers; Decision Tree (J48), probability based Naïve Bayes (NB tree) and Euclidean distance based k-Nearest Neighbor (IBk), are used. For comparison of the accuracy rates of offline signatures with online signatures, three classifiers were applied on online signature database and achieved a 99.90% accuracy rate with decision tree (J48), 99.82% with Naïve Bayes Tree and 98.11% with K-Nearest Neighbor (with 10 fold cross validation). The results of offline signatures were 64.97% accuracy rate with decision tree (J48), 76.16% with Naïve Bayes Tree and 91.91% with k-Nearest Neighbor (IBk) (without forgeries). The accuracy rate dropped with the inclusion of forgery signatures as, 55.63% accuracy rate with decision tree (J48), 67.02% with Naïve Bayes Tree and 88.12% (with forgeries).