The Approach of Data Mining

The concept of data mining is to classify and analyze the given data and to examine it clearly understandable and discoverable for the learners and researchers. The different types of classifiers are there exist to classify a data accordingly for the best and accurate results. Taking a primary data, and then classifying it into different portions of parts, then to analyze and remove any ambiguities from it and finally make it possible for understanding. With this process, that data will become secondary from primary and will called information. So, the classifiers are doing the same strategy for the solution and accuracy of the data. In this paper, different data mining approaches have been used by applying different classifiers on the taken data set. The data-set consists of 500 candidates' segregated data for the analysis and evaluation to perfectly classify and to show the accurate results by using the proposed Algorithms. The data mining approaches have been used in which HUGO (Highly Undetectable steGO) Algorithm, Naïve Bayes Classification, k-nearest neighbors and Logistic Regression are used with the extension of the other classification methods that are Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) as classifiers. These classifiers are given names for further analysis that are Classifier-1 and Classifier-2 respectively. Along with these, a tool is used named WEKA (Waikato Environment for Knowledge Analysis) for the analysis of the classifier-1 and 2. For performance evaluation and analysis the parameters are used for best classification that which classifier has given best performance and why. These parameters are RRSE (Root Relative Square Error), RAE (Relative Absolute Error), MAE (Mean Absolute Error), and RMSE (Root Mean Square Error). For the best and outstanding accuracy of the proposed work, these parameters have been tested under the simulation environment along with the incorrect, correct classifying and the %age has been witnessed and calculated. From simulation results based on RRSE, RAE, MAE and RMSE, it has been shown that classifier-1 has given outstanding performance among the others and has been placed in highest priority

Resident’s Perceptions towards the Economic, Socio-Cultural, and Environmental Impacts of Tourism: A Case Study of Nathiagali, District Abbottabad, Pakistan

The tourism industry poses both favorable and unfavorable consequences to the local communities of tourist destinations. This study aims to analyze the economic, social, and environmental impacts of tourism on the host community in Nathiagali. In this study, the data were collected through structured questionnaires from 200 residents of the selected tourist destinations. The study applied factor analysis approach for empirical results. It is found that the local community perceives positive and significant economic and social impacts from tourism in the form of job or business opportunities, raising the standard of living and infrastructural development in the area. On the other hand, tourism brings environmental threats including health hazards from air and noise pollution, environmental degradation, and traffic congestion issues for the local community. Based on the results, it is recommended that appropriate policies are needed at the government and local levels to get maximum benefits from tourism in Nathiagali, Pakistan

New Inflation in Waterfall Region

We introduce a class of new inflation models within the waterfall region of a generalized hybrid inflation framework. The initial conditions are generated in the valley of hybrid preinflation. Both single-field and multi-field inflationary scenarios have been identified within this context. A supersymmetric realization of this scenario can successfully be achieved within the tribrid inflation framework. To assess the model's viability, we calculate the predictions of inflationary observables using the $\delta N$ formalism, demonstrating excellent agreement with the most recent Planck data. Furthermore, this model facilitates successful reheating and nonthermal leptogenesis, with the matter-field component of the inflaton identified as a sneutrino.Comment: 15 pages, 9 figure

Abiotic Stress Tolerance in Cotton

Cotton (Gossypium hirsutum L.) is a vital fiber crop that is being cultivated under diverse climatic conditions across the globe. The demand for cotton and its by-products is increasing day by day due to more consumption of this fiber in the textile industry and the utilization of cotton seed as a source of edible oil. However, the average seed cotton yield in the world is below that of the potential yield of cultivars. The factors responsible for low yield includes shortage of approved seed, pest and disease attack, weed infestation, unwise use of nutrients, and the incidence of abiotic stresses (including drought, heat, and salinity). Among these, the abiotic stresses are a single major factor, which is responsible for reducing the yield now and will affect the productivity of cotton in future. In this scenario, it is necessary to adopt ways to improve the tolerance of cotton against abiotic stresses. The strategies for improving tolerance against abiotic stresses may include the wise use of macro- and micronutrients, the use of osmoprotectants, the use of arbuscular mycorrhizal fungi, and the plant-growth promoting rhizobacteria

Exploring the Nexus; Stock Market, T. Bills, Inflation, Interest Rate and Exchange Rate

The main objective of this study is to examine the relationship between Karachi stock exchange and macroeconomic variables i.e. inflation rate, exchange rate, treasury bills and interest rate. Monthly time series data from January 2005 to December 2010 have been used to investigate the causal association among macroeconomic indicators and Karachi stock market. The co-integration test and Granger Casualty have been applied to drive the short and long-term investigation. The results found bi directional Granger causality among KSE and exchange rate and One way Granger causality exists among KSE and interest rate, no Granger causality found among KSE and inflation rate and KSE and treasury bills. Which means performance of macro-economic variable somehow affects the stock index; moreover, stock prices in Pakistan do not reflect the macro-economic condition of the country. This study emphasizes on the crash of macro-economic indicators on the capital market performance of developing countries. The performance of capital markets of developing countries calculated by these macro-economic indicators

Hybridization of Cognitive Radar and Phased Array Radar Having Low Probability of Intercept Transmit Beamforming

A novel design of a cognitive radar (CR) hybridized with a phased array radar (PAR) having a low probability of intercept (LPI) transmit beam forming is proposed. PAR directed high gain property reveals its position to interceptors. Hence, the PAR high gain scanned beam patterns, over the entire surveillance region, are spoiled to get the series of low gain basis patterns. For unaffected array detection performance, these basis patterns are linearly combined to synthesize the high gain beam pattern in the desired direction using the set of weight. Genetic algorithm (GA) based evolutionary computing technique finds these weights offline and stores to memory. The emerging CR technology, having distinct properties (i.e., information feedback, memory, and processing at receiver and transmitter), is hybridized with PAR having LPI property. The proposed radar receiver estimates the interceptor range and the direction of arrival (DOA), using the extended Kalman filter (EKF) and the GA, respectively, and sends as feedback to transmitter. Selector block in transmitter gets appropriate weights from memory to synthesize the high gain beam pattern in accordance with the interceptor range and the direction. Simulations and the results validate the ability of the proposed radar

Shrinking Employees Turnover Intention by applying Tools of Job Embeddedness (Used as a Mediator)

The current research study examined the association among the HRM practices through job embeddedness (as a mediator) and employee turnover intentions. In this study, the researchers used new construct i.e. job embeddedness to explore its mediating impact on the relationship between employee turnover intentions and HRM practices such as training, compensation, career planning, performance appraisal and supervisor support. Job embeddedness was studied in terms of fit, links, and sacrifice organization. Job embeddedness plays a crucial role to reduce turnover. If organization applies these HRM practices in true letter and spirit, then their employees will be more satisfied, committed, and loyal to that organization. If employees are more embedded to the organization in a positive manner, so that employees are more committed, satisfied and impacts their performance

Comparison of Low – Versus Medium-Pressure Shunts in Pediatric Hydrocephalus – A Study of the Children Hospitals, Lahore

Objective:  This prospective cross-sectional study was aimed to assess the effectiveness of low-pressure vs. medium-pressure shunts in children with hydrocephalus. Material and Methods: 52 children with different types of hydrocephalus were admitted through OPD and Surgical emergency at The Children Hospital, Lahore. All Children were gone through Ultrasonography and CT Brain plain after admission. The pediatric hydrocephalus was resolved into two groups. All patients treated with Chhabra differential pressure VP (ventriculoperitoneal) shunt in either low pressure or medium pressure. CT scans were used to assess the postoperative clinical and radiological outcomes to monitor the ventricle hemispheric ratio (VHR). Results:  A low-pressure shunt was implanted in 26 individuals, whereas a medium-pressure shunt was implanted in 26 individuals. Patients varied in age from one day to thirteen years old. In group A, the average VHR was 57.58% preoperatively, but it dropped to 42.88% after surgery. Similarly, in group B, the pre-and postoperative VHR was 59.35% and 42.81%, respectively, which was statistically significant. In both groups, the incidence of shunt complications and redo shunt operation were not statistically significant. Conclusion:  In this study, individuals with pediatric hydrocephalus who had a low-pressure shunt or a medium-pressure shunt had similar outcomes

Approaches to multi-attribute group decision-making based on picture fuzzy prioritized Aczel–Alsina aggregation information

The Aczel-Alsina t-norm and t-conorm were derived by Aczel and Alsina in 1982. They are modified forms of the algebraic t-norm and t-conorm. Furthermore, the theory of picture fuzzy values is a very valuable and appropriate technique for describing awkward and unreliable information in a real-life scenario. In this research, we analyze the theory of averaging and geometric aggregation operators (AOs) in the presence of the Aczel-Alsina operational laws and prioritization degree based on picture fuzzy (PF) information, such as the prioritized PF Aczel-Alsina average operator and prioritized PF Aczel-Alsina geometric operator. Moreover, we examine properties such as idempotency, monotonicity and boundedness for the derived operators and also evaluated some important results. Furthermore, we use the derived operators to create a system for controlling the multi-attribute decision-making problem using PF information. To show the approach's effectiveness and the developed operators' validity, a numerical example is given. Also, a comparative analysis is presented