Corroborating social media echelon in cancer research

Mehmood, A.,On, B. W.,Lee, I.,Park, H. W.,Choi, G. S. Springer Science + Business Media 2018 Quality & quantity Vol.52 No.2

<P>Worldwide medical facilities differ, and for this reason, the causes of death can vary. Cancer is considered the second leading cause of death after heart disease worldwide, and the same causes of death are observed in the United States (US). Therefore, the purposes of this study are to explore worldwide research levels in the field of cancer and the social collaboration of researchers and institutions in this field. This article examines the structural patterns of international co-authors and co-institutions in science citation index papers in cancer research. The study uses measures from the social network analysis method, including degree centrality, betweenness centrality, eigenvector centrality, and effectiveness, to investigate the effects of social networks in the area of cancer research. Empirical analysis results identify the US is the most central country, followed by Germany, Italy, France, and China, in terms of co-authored networks in this research field. Institutional analysis results indicate that the University of Milan is at the top in terms of degree centrality. The Gustave Roussy Cancer Campus in France and German University of Dusseldorf occupy the second and fourth positions, respectively. The University of California in Los Angeles and Harvard University, both in the US, are at third and fifth positions, respectively.</P>

Unified Planning of Wind Generators and Switched Capacitor Banks: A Multiagent Clustering-Based Distributed Approach

Mehmood, Khawaja Khalid,Kim, Chul-Hwan,Khan, Saad Ullah,Haider, Zunaib Maqsood IEEE 2018 IEEE transactions on power systems Vol.33 No.6

<P>In this paper, a multiagent clustering-based distributed approach for the optimal planning of wind-distributed generators (DGs) and switched capacitor banks (SCBs) is proposed. First, electrical distance matrices for the power systems are constructed. Additionally, a constrained optimization problem, which includes several indices and a few constraints, for the optimal clustering of distribution networks is formulated and solved. After obtaining optimal clusters, agents are assigned to the clusters, and a second multiobjective optimization problem (MOOP) for the distributed planning of wind DGs and SCBs is formulated and assigned to a head agent. The number of objective functions in the MOOP is equal to the number of agents. The objective function of an agent consists of three indices: annual energy losses, investment costs, and voltage enhancement. Moreover, a deep neural network architecture is designed, and four independent networks are trained with six years of wind speed data for the seasonal wind speed forecasting. Two IEEE unbalanced test feeders, one with 37 nodes and the other with 123 nodes, and eight test cases are considered for simulations. The results show that losses and costs are optimized, and the voltage unbalance of the system is reduced.</P>

DYNAMICS OF PAKISTAN’S POST 9/11 CRISIS FOREIGN POLICY DECISION-MAKING PROCESS

Mehmood Hussain 한국정치사회연구소 2018 한국과 국제사회 Vol.2 No.2

이 연구는 파키스탄에서 9/11 테러 이후 외교정책 결정 과정을 추적하기 위해 4단계 위기에서의 국가 행동 모델 을 적용했다. 그것은 알카에다의 미국에 대한 불길한 공격과 테러에 맞서 싸우기 위한 부시대통령의 후속 선언이 t1 단계의 세계와 지역의 정치 안보 차원을 변화시켰다고 주장한다. 이웃 국가인 파키스탄의 지원은 테러와의 전쟁에서 불가피했고, 미국은 이슬람 바드의 협력을 얻기 위해 강압적인 외교를 취했다. 결과적으로, 미국의 요구를 수용하지 않을 경우 파키스탄은 국가의 기본 가치/목표에 대한 위협을 인식하고 동시에 시간 압박은 t2 단계에서 의사결정자들의 심리적 스트레스를 증폭시켰다. 따라서 의사결정 포럼은 t3 단계에서 시작되었고 파키스탄은 외교 정책 위기를 완화시킨 t4 단계로 미국에 합류하기로 결정했다. The study has applied the four stage Model of State Behavior in Crisis to trace the post 9/11 crisis foreign policy decision making process in Pakistan. It argues that ominous attacks on the United States by al-Qaeda and subsequent declaration of President Bush to fight against terrorism transformed the global and regional politico-security dimensions at t1 stage. Being a neighboring country, Pakistan’s support was inevitable in the war on terror and Washington applied coercive diplomacy to win the cooperation from Islamabad. Consequently, in case of decline to accept American demands, Pakistan perceived threat to basic values/objectives of the country and simultaneous time pressure amplified the psychological stress in decision makers at t2 stage. Therefore, the decisional forum was setup at t3 stage and Pakistan decided to join the United States at t4 stage, which defused the foreign policy crisis.

A novel feature extraction method based on late positive potential for emotion recognition in human brain signal patterns

Mehmood, R.M.,Lee, H.J. Pergamon Press ; Elsevier Science Ltd 2016 Computers & electrical engineering Vol.53 No.-

<P>Several methods for collecting psychophysiological data from humans have been developed, including galvanic skin response (GSR), electromyography (EMG), electroencephalography (EEG), and the electrocardiogram (ECG). This paper proposes a feature extraction method for emotion recognition in EEG-based human brain signals. In this research, emotions were elicited from subjects using emotion-related stimuli from the International Affective Picture System (IAPS) database. We selected four kinds of emotional stimuli in the arousal-valence domain. Raw brain signals were preprocessed using independent component analysis (ICA) to remove artifacts. We introduced a feature extraction method using LPP, and implemented a benchmark based on statistical and frequency domain features. The LPP-based results show the highest accuracy when using SVM in the all-selected feature set. The results also provide evidence and suggest a way for further developing a more specialized emotion recognition system using brain signals. (C) 2016 Elsevier Ltd. All rights reserved.</P>

Multivariate Procedure for Variable Selection and Classification of High Dimensional Heterogeneous Data

Mehmood, Tahir,Rasheed, Zahid The Korean Statistical Society 2015 Communications for statistical applications and me Vol.22 No.6

The development in data collection techniques results in high dimensional data sets, where discrimination is an important and commonly encountered problem that are crucial to resolve when high dimensional data is heterogeneous (non-common variance covariance structure for classes). An example of this is to classify microbial habitat preferences based on codon/bi-codon usage. Habitat preference is important to study for evolutionary genetic relationships and may help industry produce specific enzymes. Most classification procedures assume homogeneity (common variance covariance structure for all classes), which is not guaranteed in most high dimensional data sets. We have introduced regularized elimination in partial least square coupled with QDA (rePLS-QDA) for the parsimonious variable selection and classification of high dimensional heterogeneous data sets based on recently introduced regularized elimination for variable selection in partial least square (rePLS) and heterogeneous classification procedure quadratic discriminant analysis (QDA). A comparison of proposed and existing methods is conducted over the simulated data set; in addition, the proposed procedure is implemented to classify microbial habitat preferences by their codon/bi-codon usage. Five bacterial habitats (Aquatic, Host Associated, Multiple, Specialized and Terrestrial) are modeled. The classification accuracy of each habitat is satisfactory and ranges from 89.1% to 100% on test data. Interesting codon/bi-codons usage, their mutual interactions influential for respective habitat preference are identified. The proposed method also produced results that concurred with known biological characteristics that will help researchers better understand divergence of species.

The Reaction of the Malaysian Stock Market to the COVID-19 Pandemic

Mehmood, Waqas,Mohd-Rashid, Rasidah,Aman-Ullah, Attia,Shafique, Owais,Tajuddin, Ahmad Hakimi World Association for Triple Helix and Future Stra 2021 Journal of Contemporary Eastern Asia Vol.20 No.2

The present study was conducted to understand the turmoil effects of COVID-19 pandemic on the Malaysian stock market during the different periods of the Movement Control Order (MCO). The present study was based on the secondary data extracted from the DataStream and Bloomberg from 2nd January 2020 to 29th May 2020 to evaluate the effects of COVID-19 pandemic on the Malaysian stock market. The findings suggested that during the different periods of the Movement Control Order (MCO) from the 1st January to 29th May 2020, the COVID-19 pandemic adversely affected the performance of KLCI index and all sectoral indices. The weakest performance indices were energy, property, and finance while the least affected indices were healthcare, technology, telecommunications, and media. This paper provides a review of the impacts of COVID-19 pandemic on the Malaysian stock market throughout the different periods of MCO.

Dynamic Fractional Frequency Reuse Diversity Design for Intercell Interference Mitigation in Nonorthogonal Multiple Access Multicellular Networks

Mehmood, Kashif,Niaz, Muhammad Tabish,Kim, Hyung Seok Hindawi Limited 2018 WIRELESS COMMUNICATIONS AND MOBILE COMPUTING Vol.2018 No.-

<P>Nonorthogonal multiple access (NOMA) is one of the few promising techniques that can ensure the achievement of benefits foreseen in next-generation 5G wireless networks and beyond. By using superposition coding, NOMA allows multiple users to share the same time and frequency resources, thereby enhancing user connectivity, spectral efficiency, and a considerable increase in user throughput. Interference mitigation is an important consideration in NOMA and is considerably more influencing in multicellular environments. First, a brief description of the impairments that can arise in a NOMA cellular network along with responsible factors is provided. Second, different approaches adopted to minimize these impairments are discussed. Finally, a possible solution is proposed that consists of a coordinated approach between the individual cells in the NOMA domain to minimize interferences and improve user throughput. Adaptive fractional frequency reuse (FFR) is used to allocate distinct frequency resources to edge users of different cells to minimize intercell interference in NOMA. Simulation results prove that the proposed NOMA scheme plays an important role in minimizing impairment effects and enhancing the SINR and the throughput performance of edge users while ensuring fairness in its design.</P>

Variable selection of spectroscopic data through monitoring both location and dispersion of PLS loading weights

Mehmood Tahir,Turk Arslan Munir 한국통계학회 2021 Journal of the Korean Statistical Society Vol.50 No.4

High dimensional data sets against the small sample size is essential for most of the sciences. The variable selection contributes to a better prediction of real-life phenomena. A multivariate approach called partial least squares (PLS) has the potential to model the high dimensional data, where the sample size is usually smaller than the number of variables. Truncation for variables selection in PLS T−PLS is considered a reference method. T−PLS and many others only monitors the location of PLS loading weights for variable selection. In the current article, we propose to monitor both location and dispersion of PLS loading weights for variable selection over the high dimensional spectral data. The proposed PLS variants are based on location, dispersion, both location and dispersion and at least location or dispersion monitoring of PLS loading weights, and are denoted by X−PLS, S−PLS, X&S−PLS and X|S−PLS respectively. Proposed PLS variants are compared with standard PLS and T−PLS through the Monte Carlo simulation of 100 runs on simulated and real data sets which includes corn, milk, and oil contents prediction based on spectroscopic data. X&S−PLS shows the best capability in selecting the real variables over the simulated data. The validated RMSE comparison indicates X|S−PLS and X&S−PLS outperforms compared to other methods in predicting corn, milk, and oil contents. X&S−PLS selects the smallest number of variables. Interestingly, selected variables by X&S−PLS are more consistent compared to all other methods. Hence X&S−PLS appears a potential candidate for variable selection in high dimensional data.

Integrated Power Optimization with Battery Friendly Algorithm in Wireless Capsule Endoscopy

Mehmood, Tariq,Naeem, Nadeem,Parveen, Sajida International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.11

The recently continuous enhancement and development in the biomedical side for the betterment of human life. The Wireless Body Area Networks is a significant tool for the current researcher to design and transfer data with greater data rates among the sensors and sensor nodes for biomedical applications. The core area for research in WBANs is power efficiency, battery-driven devices for health and medical, the Charging limitation is a major and serious problem for the WBANs.this research work is proposed to find out the optimal solution for battery-friendly technology. In this research we have addressed the solution to increasing the battery lifetime with variable data transmission rates from medical equipment as Wireless Endoscopy Capsules, this device will analyze a patient's inner body gastrointestinal tract by capturing images and visualization at the workstation. The second major issue is that the Wireless Endoscopy Capsule based systems are currently not used for clinical applications due to their low data rate as well as low resolution and limited battery lifetime, in case of these devices are more enhanced in these cases it will be the best solution for the medical applications. The main objective of this research is to power optimization by reducing the power consumption of the battery in the Wireless Endoscopy Capsule to make it battery-friendly. To overcome the problem we have proposed the algorithm for "Battery Friendly Algorithm" and we have compared the different frame rates of buffer sizes for Transmissions. The proposed Battery Friendly Algorithm is to send the images on average frame rate instead of transmitting the images on maximum or minimum frame rates. The proposed algorithm extends the battery lifetime in comparison with the previous baseline proposed algorithm as well as increased the battery lifetime of the capsule.

Effect of Human Related Factors on Requirements Change Management in Offshore Software Development Outsourcing: A theoretical framework

Mehmood, Faisal,Zulfqar, Sukana Institute of Information Science and Technology 2021 Soft computing and machine intelligence Vol.1 No.1

Software development organizations are globalizing their development activities increasingly due to strategic and economic gains. Global software development (GSD) is an intricate concept, and various challenges are associated with it, specifically related to the software requirement change management Process (RCM). This research aims to identify humans' related success factors (HSFs) and human-related challenges (HCHs) that could influence the RCM process in GSD organizations and propose a theoretical framework of the identified factors concerning RCM process implementation. The Systematic Literature Review (SLR) method was adopted to investigate the HSFs and HCHs. Using the SLR approach, a total of 10 SFs and 10 CHs were identified. The study also reported the critical success factors (HCSFs) and critical challenges (HCCHs) for RCM process implementation following the factors having a frequency 50% as critical. Our results reveal that five out of ten HSFs and 4 out of ten HCHs are critical for RCM process implementation in GSD. Finally, we have developed a theoretical framework based on the identified factors that indicated a relationship among the identified factors and the implementation of the RCM process in the context of GSD. We believe that the results of this research can help tackle the complications associated with the RCM in GSD environment, which is vigorous to the success and progression of GSD organizations.