A Survey of Advances in Hierarchical Clustering Algorithms and Applications

Munshi, Amr International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.5

Hierarchical clustering methods have been proposed for more than sixty years and yet are used in various disciplines for relation observation and clustering purposes. In 1965, divisive hierarchical methods were proposed in biological sciences and have been used in various disciplines such as, and anthropology, ecology. Furthermore, recently hierarchical methods are being deployed in economy and energy studies. Unlike most clustering algorithms that require the number of clusters to be specified by the user, hierarchical clustering is well suited for situations where the number of clusters is unknown. This paper presents an overview of the hierarchical clustering algorithm. The dissimilarity measurements that can be utilized in hierarchical clustering algorithms are discussed. Further, the paper highlights the various and recent disciplines where the hierarchical clustering algorithms are employed.

An Empirical Investigation of Triple Helix and National Innovation System Dynamics in ASEAN-5 Economies

Munshi Naser Ibne Afzal,Kasim Bin HJ. MD. Mansur,Rini Suryati Sulong 아시아기술혁신학회 2017 Asian Journal of Innovation and Policy Vol.6 No.3

This paper exhibits the concept of Triple Helix model to explain and link university-industry-government (Triple Helix) connections to national innovation systems theory. The driver of this paper is to test the dynamics of Triple Helix concept under national innovation system in the Association of South East Asian Countries (ASEAN)-5 economies. Panel econometric analysis with cross-sectional dependence (CD) test is applied to investigate the relationship amongst Triple Helix variables. The empirical analysis employs innovation indicators of five founding ASEAN countries namely Malaysia, Indonesia, Singapore, the Philippines and Thailand for the period of 2000-2015 from an existing WDI and WCY database. Econometric results support the two research questions of this study; firstly, there is a significant relationship between innovation outcome and its key drivers under Triple Helix context of National Innovation System in ASEAN-5 economies; secondly, the extent of the relationship among government R&D expenditure with high-tech productions are positive and significant while new ideas coming from universities as scientific publications and high-tech production have positive relationship but not significant yet in ASEAN-5 countries. Overall labor productivity is positive and significant with innovation outcomes in ASEAN-5.

Clustering of PV Load Patterns Based on Any Colony Centroid Model

Munshi, Amr International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.5

There has been a significant growth in global population and industrialization, as a consequence demand for electricity is increasing rapidly and the power systems need to increase the electricity generation. Currently, most of generated electricity is generated from fossil fuels. However, there are many financial and environmental concerns associated with the generation of electricity from such resource. Photovoltaic )PV) solar as a renewable resource is promising. The power output of PV systems is mainly affected by the solar irradiation and ambient temperature. This paper attempts at reducing the burden and improving the accuracy of the extensive simulations related to integrating PV systems into the electrical grid.

Fuzzy Partitioning of Photovoltaic Solar Power Patterns

Munshi, Amr International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.5

Photovoltaic systems provide a reliable green energy solution. The sustainability and low-maintenance of Photovoltaic systems motivate the integration of Photovoltaic systems into the electrical grid and further contribute to a greener environment, as the system does not cause any pollution or emissions. Developing methodologies based on machine learning techniques to assist in reducing the burden of studies related to integrating Photovoltaic systems into the electric grid are of interest. This research aims to develop a methodology based on a unsupervised machine learning algorithm that can reduce the burden of extensive studies and simulations related to the integration of Photovoltaic systems into the electrical grid.

Neural Network Self-Organizing Maps Model for Partitioning PV Solar Power

Munshi, Amr International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.5

The growth in global population and industrialization has led to an increasing demand for electricity. Accordingly, the electricity providers need to increase the electricity generation. Due to the economical and environmental concerns associated with the generation of electricity from fossil fuels. Alternative power recourses that can potentially mitigate the economical and environmental are of interest. Renewable energy resources are promising recourses that can participate in producing power. Among renewable power resources, solar energy is an abundant resource and is currently a field of research interest. Photovoltaic solar power is a promising renewable energy resource. The power output of PV systems is mainly affected by the solar irradiation and ambient temperature. this paper investigates the utilization of machine learning unsupervised neural network techniques that potentially improves the reliability of PV solar power systems during integration into the electrical grid.

Experimental investigations on the crashworthiness of flexible polyurethane foam under constant impact energy

Munshi Mahbubul Basit,Amkee Kim,Seong Sik Cheon 대한기계학회 2006 대한기계학회 춘추학술대회 Vol.2006 No.11

Based on experimental impact testing data, due to changing of velocity and mass of the impactor simultaneously under constant impact energy, crashworthiness of polyurethane foam has been observed. Dynamic tests were carried out in an instrumented impact-testing machine. Observation made mean that, densification strain appears later and the net amount of useful absorbed energy increases with the velocity of the impactor, though impact energy is constant. Some general, quantitative conclusions and decisions of the crashworthiness of polyurethane foam at constant impact energy have been formulated.

Image compression using K-mean clustering algorithm

Munshi, Amani,Alshehri, Asma,Alharbi, Bayan,AlGhamdi, Eman,Banajjar, Esraa,Albogami, Meznah,Alshanbari, Hanan S. International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.9

With the development of communication networks, the processes of exchanging and transmitting information rapidly developed. As millions of images are sent via social media every day, also wireless sensor networks are now used in all applications to capture images such as those used in traffic lights, roads and malls. Therefore, there is a need to reduce the size of these images while maintaining an acceptable degree of quality. In this paper, we use Python software to apply K-mean Clustering algorithm to compress RGB images. The PSNR, MSE, and SSIM are utilized to measure the image quality after image compression. The results of compression reduced the image size to nearly half the size of the original images using k = 64. In the SSIM measure, the higher the K, the greater the similarity between the two images which is a good indicator to a significant reduction in image size. Our proposed compression technique powered by the K-Mean clustering algorithm is useful for compressing images and reducing the size of images.

‘ARRANGED’ MARRIAGE, EDUCATION, AND DOWRY: A CONTRACT-THEORETIC PERSPECTIVE

SOUMYANETRA MUNSHI 중앙대학교 경제연구소 2017 Journal of Economic Development Vol.42 No.1

This paper propounds a contract-theoretic model that addresses the empirically observed conundrum of increased education of the groom being associated with increased dowry transactions. Unlike the human capital approach, we impart a signaling role to education whereby education signals unobservable qualities of the groom that are valuable to the bride. In ‘arranged’ marriage settings that are characterized by incomplete information in the sense that the true quality of the groom remains unobservable to the bride, and in the presence of observable traits like education that are easier for the better quality groom to achieve, education-dowry contracts can potentially serve as a screening instrument to differentiate grooms of varying qualities. In equilibrium, different types of grooms select different education-dowry contracts, with better types being associated with both higher education and higher dowry. Hence the model has interesting and important policy implications since it means that increased public expenditure on education may actually be forcing dowry levels to rise. The paper also discusses historical and narrative evidences in support of its main hypotheses.

Performance Analysis of a Compressive Sensing–based Channel Estimation Algorithm in a Noisy Channel

Ami Munshi,Srija Unnikrishnan 대한전자공학회 2019 IEIE Transactions on Smart Processing & Computing Vol.8 No.3

Taking forward Compressive Sensing (CS)-based channel estimation, the emphasis of this paper is to analyze the performance of CS-based channel estimation by varying the Fast Fourier Transform (FFT) size (number of subcarriers) employed in Orthogonal Frequency Division Multiplexing (OFDM). By selecting an optimal FFT size, it is possible to bring the Bit Error Rate (BER) down to zero at a particular Signal-to-Noise Ratio (SNR) for both the Least Square (LS) channel estimation technique and the least square with compressive sensing (LS-CS) channel estimation technique. The main benefit is that in the LS-CS technique, we need to sense only a very small percentage of the total channel coefficients, whereas in LS we must sense all channel coefficients, making the LS-CS technique much more efficient without any significant effect on the result. We also observe that by increasing the FFT size, performance of the system in terms of BER can be significantly improved, even when the channel is very noisy.

An Empirical Investigation of Triple Helix and National Innovation System Dynamics in ASEAN-5 Economies

Afza, Munshi Naser Ibne,Mansur, Kasim Bin HJ. MD.,Sulong, Rini Suryati Asian Society for Innovation and Policy 2017 Asian Journal of Innovation and Policy Vol.6 No.3

This paper exhibits the concept of Triple Helix model to explain and link university-industry-government (Triple Helix) connections to national innovation systems theory. The driver of this paper is to test the dynamics of Triple Helix concept under national innovation system in the Association of South East Asian Countries (ASEAN)-5 economies. Panel econometric analysis with cross-sectional dependence (CD) test is applied to investigate the relationship amongst Triple Helix variables. The empirical analysis employs innovation indicators of five founding ASEAN countries namely Malaysia, Indonesia, Singapore, the Philippines and Thailand for the period of 2000-2015 from an existing WDI and WCY database. Econometric results support the two research questions of this study; firstly, there is a significant relationship between innovation outcome and its key drivers under Triple Helix context of National Innovation System in ASEAN-5 economies; secondly, the extent of the relationship among government R&D expenditure with high-tech productions are positive and significant while new ideas coming from universities as scientific publications and high-tech production have positive relationship but not significant yet in ASEAN-5 countries. Overall labor productivity is positive and significant with innovation outcomes in ASEAN-5.