Improvement of Soil Health through Residue Management and Conservation Tillage in Rice-Wheat Cropping System of Punjab, Pakistan

In South Asia, soil health degradation is affecting the sustainability of the rice-wheat cropping system (RWCS). Indeed, for the sustainability of the soil quality, new adaptive technologies, i.e., conservation tillage and straw management resource conservation, are promising options. This investigation was focused on the interaction of tillage and straw management practices and their effects on Aridisols, Yermosols soil quality, and nutrients dynamics with different soil profiles within RWCS. The long-term field experiment was started in 2014 with the scenarios (i) conventional tillage (SC1), (ii) residue incorporation (SC2), (iii) straw management practices (SC3 and SC4) and conservation tillage (SC5). Conservation tillage practice (SC5) showed significant impact on properties of soil and availability of nutrients in comparison with that of conventional farmers practice (SC1) at the studied soil depths. The SC5 showed significant results of gravitational water contents (25.34%), moderate pH (7.4), soil organic-matter (7.6 g kg(-1)), total nitrogen (0.38 g kg(-1)), available phosphate (7.4 mg kg(-1)), available potassium (208 mg kg(-1)) compared to SC1 treatment at 0 to 15 cm soil depth. Whereas, DTPA-extractable-Cu, Mn, and Zn concentration were significantly higher, i.e., 1.12 mg kg(-1), 2.14 mg kg(-1), and 4.35 mg kg(-1), respectively under SC5 than conventional farmer's practices, while DTPA (diethylene triamine pentaacetic acid) extractable Fe (6.15 mg kg(-1)) was more in straw management practices (SC4) than conventional and conservation tillage. Therefore, conservation tillage (SC5) can surge the sustainability of the region by improving soil assets and nutrients accessibility and has the potential to minimize inorganic fertilizers input in the long run

Study of Multi-Classification of Advanced Daily Life Activities on SHIMMER Sensor Dataset

Today the field of wireless sensors have the dominance in almost every person’s daily life. Therefore researchers are exasperating to make these sensors more dynamic, accurate and high performance computational devices as well as small in size, and also in the application area of these small sensors. The wearable sensors are the one type which are used to acquire a person’s behavioral characteristics. The applications of wearable sensors are healthcare, entertainment, fitness, security and military etc. Human activity recognition (HAR) is the one example, where data received from wearable sensors are further processed to identify the activities executed by the individuals. The HAR system can be used in fall detection, fall prevention and also in posture recognition. The recognition of activities is further divided into two categories, the un-supervised learning and the supervised learning. In this paper we first discussed some existing wearable sensors based HAR systems, then briefly described some classifiers (supervised learning) and then the methodology of how we applied the multiple classification techniques using a benchmark data set of the shimmer sensors placed on human body, to recognize the human activity. Our results shows that the methods are exceptionally accurate and efficient in comparison with other classification methods. We also compare the results and analyzed the accuracy of different classifiers

A Spatial 3 X 3 Average Filter for De-Noising in Digital Images with the Help of Median Filter

Digital image processing includes many factors like Image enhancement, segmentation, object recognition, removal of noise and many more. Noise removal is the one of the hot area of image processing. Noise can be minimized but cannot removed completely. Scientist and researchers has established many filters, which can minimize the noise in the image and enhance its quality. There are many types of noise and many types of filter for the removal of noise. Many types of noise are used. To remove these types of noise, 3 x 3 average filter is used in this paper and its efficiency is measured. The simulations are performed on the MATLAB

Method of Choice for Disphyseal Fracture of Humerus; Closed Intramedullary Interlocking Nail or Functional Brace

Objective: To compare the intramedullary nailing versus functional brace in the cases of disphyseal humeral fractures.Methodology: This was a descriptive comparative analysis study done Shaikh Zayed Hospital from Jan 2016 to March 2018, Pakistan. 60 cases who were presented with the disphyseal fracture of humerus were enrolled. After random allocation in the two different groups viz functional brace and intramedullary nailing. All the patients irrespective of gender and presented with humerus fracture were added. While all other type of fracture cases was excluded.Each patient was treated standardized by a specialist having somewhere around 5 years of experience after post-graduation. All patients were pursued at third week, sixth week and at 3 months to survey the radiological result according to the radiological sign of union i-e formation of callus on the fracture point.Results: Both treatment group in this study were same with non-significant difference with respect to age, gender and history of the smoking. But the union was noted in 45% cases in the intramedullary group and 54% in the functional brace group (p-value>0.05).  But it was observed that at the 6th week there was a significant difference with respect to the union in both operative groups. P-value of the union at 6th week was <0.05 shows that difference is significant.Conclusion: Functional brace method is more effective for the union of the disphyseal humerus fracture

Inflation Forecasting in Pakistan using Artificial Neural Networks

An artificial neural network (hence after, ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. In previous two decades, ANN applications in economics and finance; for such tasks as pattern reorganization, and time series forecasting, have dramatically increased. Many central banks use forecasting models based on ANN methodology for predicting various macroeconomic indicators, like inflation, GDP Growth and currency in circulation etc. In this paper, we have attempted to forecast monthly YoY inflation for Pakistan by using ANN for FY08 on the basis of monthly data of July 1993 to June 2007. We also compare the forecast performance of the ANN model with conventional univariate time series forecasting models such as AR(1) and ARIMA based models and observed that RMSE of ANN based forecasts is much less than the RMSE of forecasts based on AR(1) and ARIMA models. At least by this criterion forecast based on ANN are more precise

Inflation Forecasting in Pakistan using Artificial Neural Networks

An artificial neural network (hence after, ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. In previous two decades, ANN applications in economics and finance; for such tasks as pattern reorganization, and time series forecasting, have dramatically increased. Many central banks use forecasting models based on ANN methodology for predicting various macroeconomic indicators, like inflation, GDP Growth and currency in circulation etc. In this paper, we have attempted to forecast monthly YoY inflation for Pakistan by using ANN for FY08 on the basis of monthly data of July 1993 to June 2007. We also compare the forecast performance of the ANN model with conventional univariate time series forecasting models such as AR(1) and ARIMA based models and observed that RMSE of ANN based forecasts is much less than the RMSE of forecasts based on AR(1) and ARIMA models. At least by this criterion forecast based on ANN are more precise

Performance Analysis of Hardware Protection & System Security in Different Operating Systems

The intention of article is to protect the hardware, which includes protecting CPU, I/O, and memory. This article portrays and relates the security in different operating systems. Therefore, helping us to choose the best. We can evaluate the security in different operating systems like Windows, UNIX, Linux to secure over all data to access unauthorized users

Clinico-Laboratory Profile And Drug Sensitivity Pattern In Urinary Tract Infection Of Children In A Tertiary Care Hospital

Background: Any component of the urinary system can get infected with bacteria, which is known as a urinary tract infection (UTI). It is one of the most common bacterial diseases in children. The study's objectives included identifying the clinical symptoms of UTI in children between the ages of one month and fifteen, as well as the bacteria responsible for the illness and their sensitivity to various medicines.Methods: This cross-sectional study was conducted at the CMH Rawalpindi, Pakistan, from January to June of 2022. Our analysis comprised 137 strongly suspected instances of UTI in children (1 month to 15 years old).Results: A total of 137 urine samples from paediatric patients suspected of having UTI were obtained in which the 93 samples (67.88%) generated significant bacteria. The two most common clinical symptoms of UTI patients in our research were fever and dysuria. E. coli was the most prevalent isolate in cases with paediatric UTI. Ampicillin, cephalosporins, and co-trimoxazole were the medications that were most effective against E. coli and Klebsiella, respectively.Conclusions: The age range between 1 and 5 years old was the one most usually affected by UTI. We must be aware of the need of doing a urine culture sensitivity test before to starting antimicrobial medicine in order to detect UTI early, avoid recurrent UTI, and reduce paediatric morbidity and mortality

A SYSTEMATIC REVIEW ON THE IMPACT OF FACEBOOK USAGE ON ACADEMIC PERFORMANCE

Facebook has become an essential part of nearly every individual’s daily life. Though it is beneficial for students in terms of connectivity such as exchanging information, socialization, and other constructive activities, the literature shows that Facebook has become dangerously addictive, causing disruption in routinely activities and academic goals of students. The purpose of this review is to investigate the impact of Facebook usage on the academic performance of university students and how can these be assimilated in order to enhance students’ academic performance. Papers were retrieved from academic databases and Google from 2011 to 2017. All studies that were included appraised critically by using Mixed Method Appraisal Tool Appraisal tool. The results showed that both positive and negative impacts of using Facebook on the academic performance of university students. The conclusions propose that, despite the variance of findings, the overall outcome is negative when it comes to the use of Facebook in academic performance. Furthermore, it highlights the ways that how Facebook can help to enhance the academic performance of university students