CLIMATE CHANGE ACTION AND STATE SOVEREIGNTY

Climate change is a reality recognized globally. Although global efforts are accelerating, there are fears in the underdeveloped world regarding the erosion of their sovereignty through climate change action and response mechanisms. Remedial actions taken at various levels are not a compensating reflection of this reality. There is a need to establish a well-thought-out mechanism and support fast-track climate change action and responses. This study, therefore, highlights the impact of climate change action on state sovereignty through in-depth analysis by interviewing climate experts and officials. It reckons that the issue revolves around interference in internal policies through the prism of climate change action incorporating world organisations. It concludes that developing states may have fears regarding the overreach of developed states in their remedial actions, as seen in the Global South and Global North divide.   Bibliography Entry Shafi, Khalid Mahmood, Arif Ullah Khan, and Rafaqat Islam. 2021. "Climate Change Action and State Sovereignty." Margalla Papers 25 (2): 98-108

Unsupervised Ranking of Numerical Observations based on Magnetic Properties and Correlation Coefficient

This paper addresses a novel unsupervised algorithm to rank numerical observations which is important in many applications in computer science, especially in information retrieval (IR). The proposed algorithm shows how correlation coefficients between attribute values and the concept of magnetic properties can be explored to rank multi-attribute numerical objects. One of the main reasons of using correlation coefficients between attribute values and the concept of magnetic properties is that they are easy to compute and interpret. Our proposed Unsupervised Ranking using Magnetic properties and Correlation coefficient (URMC) algorithm can use some or all the numerical attributes of objects and can also handle objects with missing attribute values. The proposed algorithm overcomes a major limitation of the state-of-the-art technique while achieving excellent results

Examining the Mediating Role of Strategic Integration of Purchasing, And Advance Purchasing Practices in the Relationship between Purchasing Operational Performance and IT Investment in Purchasing

The main purpose of the current study is to investigate the mediating role of strategic integration of purchasing, and advance purchasing practices in the relationship between purchasing operational performance and IT investment in purchasing. In this research, some other practices have been considered including involvement of suppliers, evaluation and assessment of suppliers and integration of logistics. Strategic integration of purchasing is referred as the degree to which the strategic relevance of purchasing function is recognized by a company. This has been regarded as an important antecedent of supply management practices and advanced purchasing. In the relation of performance, supply and purchasing practices and IT investments, one of the important factors is strategic integration of purchasing. The study has used survey-based method and data is collected by the aid of questionnaire. The collected data is analyzed with the SEM-PLS. The findings of the study have shown agreement with the proposed results. In author knowledge it is among the pioneering studies on the issues related to strategic integration of purchasing, advance purchasing practices, purchasing operational performance and IT investment in purchasing. This study will provide guidelines to policymakers, researchers and corporate personnel in understanding the relationship between strategic integration of purchasing, advance purchasing practices, purchasing operational performance and IT investment in purchasing

Maternal and Neonatal Factors Influencing Preterm Birth and Low Birth Weight in Oman: A Hospital Based Study

Background: Preterm births (PTB) and low birth weight (LBW) - the two distinct adverse pregnancy outcomes - are the major determinants of perinatal survival and development. The purpose of this study was to determine the incidence of LBW and PTB and identify the maternal and neonatal risk factors influencing them. Methods: Data for the study come from a cross-sectional retrospective study conducted at the maternity ward of Sultan Qaboos University Hospital (SQUH) in Oman during the period between November 2011 and February 2012. Data on 534 singleton live births that occurred during the study period were extracted from hospital record. Descriptive statistics, bivariate analysis and multivariate logistic regression model were used for data analysis. Results: The incidence of PTB and LBW were observed to be 9.7% and 13.7% respectively. Half (51.8%) of the LBW babies were PTB and 48.2% of the LBW babies were of term births. Differences and similarities were noted for the risk profile for PTB and LBW. Risk factors specific to PTB were maternal age, previous pregnancy loss, and infant’s length, while birth interval, maternal weight and BMI during pregnancy, and gestational age were the risk factors unique to LBW. ANC visit, infant’s gender, Apgar score, and head circumference of infants were the common significant risk factors influencing both LBW and PTB. Conclusions: The incidence of PTB and LBW are moderately high in Oman. They are associated with different risk factors. A greater understanding and modification of identified risk factors would help reduce the incidence of PTB and LBW in Oman

Scintillation measurement on ku-band satellite path in tropical climate

Scintillation data was collected in Kuala Lumpur, Malaysia for one year measurement. The data were obtained from MEASAT3 satellite operating at Ku-band with elevation angle of 77.4˚. In this paper, scintillation statistics are analysed in dry (non-rain) condition. The scintillation distributions are represented scintillation intensity and amplitude by monthly, seasonal, worst-month and annual distributions. Probability density function (PDF) of scintillation intensity correspondingly agrees to Generalize Extreme Value (GEV) fit. In addition, model validation to the measured data is also provided

Improvement of voltage stability and loadability of power system employing the placement of unified power flow controller using artificial neural network

This paper proposes a voltage stability and loadability improvement model of power systems by incorporating the optimal placement of flexible alternating current transmission systems (FACTS) using an artificial neural network (ANN) called OPFANN. The key aspect of this model is to identify the weakest lines which having the most probability of voltage collapse utilized for placing FACTS devices. As installing a new power system network with rapidly increasing power demand cannot be possible, the operator usually operates the power system close to the stability limit. In this regard, continuous monitoring and improvement of system voltage stability and loadability of the existing system are vital issues for energy management systems nowadays. However, the proposed OPFANN introduces a more straightforward and faster scheme for voltage stability monitoring systems using ANN. Intelligent and reliable data samples have been designed to train the ANN based on two-line voltage stability indices (LVSI) techniques. Compared with other works, OPFANN effectively improves voltage stability and loadability at the load point by installing the unified power flow controller (UPFC) FACTS devices to the weakest lines. OPFANN can provide information on voltage collapse points using ANN and reduce the further computational cost of LVSI. Finally, OPFANN ensures faster and more secure operation of the power system