Developing cost management system for Adil Foods

Applied project submitted to the Department of Business Administration, Ashesi University, in partial fulfillment of Bachelor of Science degree in Business Administration, May 2021Adil Foods Corporation is a food company that has recently stepped into the agricultural industry. The company operates in Multan, Pakistan, and has been operating since 2001. The company provides white meat and eggs to suppliers of the domestic market. The management of Adil Foods expressed that their business failed to achieve the profitability goal for the year 2020. Mr. Rashid, the CEO of Adil Foods, noted issues with the cost monitoring and data analysis. The tools used for data collection were structured interviews, observation, and the company’s financial & internal reports. The CEO, Financial manager, and production manager were interviewed. Framework analyses were used to analyze the data. The results revealed that the business failed to achieve its profitability goal due to a lack of data analyses. The lack of data analyses was leading to poor decision-making. The literature review explored functionalities, conceptual frameworks, and limitations of the Enterprise resource planning software (ERPs) and excel-based cost management system. The existing literature coupled with the primary research indicated that an excel-based cost management system is better for Adil Foods as it is cheaper and Adil Foods management is familiar with the software. The proposed solution is a tailor-made cost management system that uses variable costing and sensitivity analysis to compute valuable information and generate signals. The excel based cost management system also forecasts data which will assist managers in making rational and prompt decisions.Ashesi Universit

Effect of Individualized vs Standard Blood Pressure Management Strategies on Postoperative Organ Dysfunction Among High-Risk Patients Undergoing Major Surgery

Objective: To determine the effect of individualized blood pressure management targeted upon the physiology of individual patient could help in decreasing the risk postoperative organ dysfunction.  Methodology It was a randomized trial carried out in department of general medicine from March 2016 to March 2017. An approval from Ethics committee was taken. An informed consent in the form of a written document was taken from every patient. Data was analyzed by using SPSS version 24. Student t-test and χ2 test that was unadjusted was performed for the analysis of primary outcome. P value ≤ 0.05 was considered as significant. Results: in the Individualized group, Primary composite outcome was noted as (36.7%) n=55. Acute kidney injury according to RIFLE criteria; Risk, injury and failure was observed as (17.3%) n=26, (9.3%) n=14 and (6%) n=9 respectively. Use of renal replacement therapy was noted as (8%) n=12. Acute heart failure occurred in (6%) n=9. respectively. For Standard treatment group, Primary composite outcome was noted as (48.7%) n=73. Use of renal replacement therapy was noted as (6.7%) n=10. Acute heart failure occurred in (1.3%) n=2. Need for noninvasive or invasive ventilation and sepsis was noted as (30.7%) n=46 and (18%) n=27 respectively. Conclusion: High Postoperative risk patients having major abdominal surgery, the mode of management directed towards the individual blood pressure as compared to standard mode of management proves to be fruitful in decreasing the risk for postoperative organ dysfunction. Keywords: Blood Pressure, Organ Dysfunction, Postoperative complications, Sepsis

The sleep quality using Pittsburgh sleep quality index.

Good quality and enough sleep are necessary for the proper cognitive performance of medical students. There is a wide prevalence of sleep disturbances among Pakistani medical students and there is a need to spread awareness regarding the problems concerning sleep patterns. OBJECTIVE: To determine the quality of sleep among first and final year medical students. METHODOLOGY: It’s a cross sectional study conducted at Services Institute of Medical College Lahore from the 10th May to 15th June 2016.A total of 300 Male and female medical students of first and final year were administered PSQI and their socio-demographic profile along with academic performance was noted. The results were collected and analyzed in SPSS ver.21.0. RESULTS: Of the 300 students approached,63.67% were females and 36.33% were males. Overall, PSQI score \u3e5 (indicating poor sleep quality) was found to be 64.7%. The mean PSQI score among first year males was 7.68 with a standard deviation of 3.95 and among females was 7.47 with a standard deviation of 3.02. On the other hand, the mean PSQI score among final year males was found to be 6.97 with a standard deviation of 3.86 and among final year females was 5.65 with a standard deviation of 1.40. 69.7% of the males and 61.8% of the females were classified as poor sleepers

Technological Dramas and the Punjab Police: The Downfall of Front Desk

Electronic dependence and utilization have been emerging as one of the driving forces towards departmental growth and development in this new era of globalization and modernization in Punjab police. The Front Desk (FD) project has a sign of change in Punjab police. It was changing the face of the police from the very first day it was started, but with the passage of time, it has changed its motive and began to change in the color of police. Hence, this paper highlights the issues and their solutions regarding the implementation and utilization of the FD project in the Punjab police department. It also highlights the working of Punjab police with and without FD and the importance of FD in the police department to delivering the grievance and of analysis the true nature of crimes. It discusses various aspects of police department myths and mistakes undertaken by the Punjab police officials and suggests various solutions for changing the face of the department. Keywords: Front Desk Project, Information Technology, Police Culture, Policing, Police Myths, Working of FD, Training & Development. DOI: 10.7176/PPAR/11-1-07 Publication date: February 28th 202

Identification of Flash floods using Soil Flux and CO2: An implementation of Neural Network with Less False Alarm Rate

Flash floods are very sudden and abrupt and are the major root cause of casualties and loss of infrastructure. Flash floods can be regarded as the topmost natural disasters in many countries. Usually floods are due to high precipitation, wind velocity, water wave current and melting of ice bergs. Diversified strategies have been designed and applied to identify the flash floods. Mainly dozen of sensors have been utilized to detect the flash floods like upstream level, rainfall intensity, run-off magnitude, run-off speed, color of the water, precipitation velocity, pressure, temperature, wind speed, wave current pattern and cloud to ground (CG flashes). Ultrasonic and passive infrared (PIR) sensors have also been utilized for this purpose. Sensors generate high amount of fake alerts due to the incompetent algorithms. In our research we have proposed a novel approach analysis of soil flux depicting atmospheric carbon dioxide level as the plants take smaller amount of water from the soil due to the heightened levels of carbon dioxide. Due to this newly discovered research the soil is saturated abruptly causes more floods and run-offs. In our research we have reduced the false alarms and reduced the false alarms by using scaled conjugate gradient back propagation. Simulation results showed that scaled conjugate gradient propagation performed better than the other previous methods

Fly Ash an Alternative of Clay in Bricks: A Sustainable Solution for Future Constructions

Clay (CL) bricks have been commonly used in construction industry for centuries. The negative environmental impacts of use of CL bricks include rapidly depleting fertile clayey layer of soil and the high energy consumption of CL bricks, which have led to the development of alternative brick units incorporating waste materials. Fly ash (FA) brick has been identified as a sustainable and environmental friendly alternative of traditional CL brick, which reduces carbon dioxide (CO2) emissions and hence global warming. This study aims to develop eco-friendly geopolymer mortar brick mixes using FA and CL without heat curing and applying molding pressure. This study investigates influences of percentage replacements of CL with FA and curing period on the compressive strength (CS) of geopolymer mortar brick mixes. In the preparation of geopolymer mortar mixes, the percentage replacements of CL with FA varied from 0 to 100% (0%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100%) using 12 M sodium hydroxide (NaOH) solution. A total of 11 geopolymer mortar mixes were cast and cured at 14, 28, 56 and 90 days. The optimum CS of 49.7 MPa with 80% replacement of CL with FA using 12 M NaOH solution at 90 days was achieved. This study is expected to contribute in reducing the level of CO2 emissions, which will subsequently reduce global warming and smog formation in Pakista

Two Different Classes of Shrinkage Estimators for the Scale Parameter of the Rayleigh Distribution

Shrinkage estimators are introduced for the scale parameter of the Rayleigh distribution by using two different shrinkage techniques. The mean squared error properties of the proposed estimator have been derived. The comparison of proposed classes of the estimators is made with the respective conventional unbiased estimators by means of mean squared error in the simulation study. Simulation results show that the proposed shrinkage estimators yield smaller mean squared error than the existence of unbiased estimators

Two Different Classes of Shrinkage Estimators for the Scale Parameter of the Rayleigh Distribution

Shrinkage estimators are introduced for the scale parameter of the Rayleigh distribution by using two different shrinkage techniques. The mean squared error properties of the proposed estimator have been derived. The comparison of proposed classes of the estimators is made with the respective conventional unbiased estimators by means of mean squared error in the simulation study. Simulation results show that the proposed shrinkage estimators yield smaller mean squared error than the existence of unbiased estimators

A review of medicinal herbs in the management of male infertility

Male infertility can be caused by a variety of factors, including neurohormonal imbalances, reproductive tissue disturbances, and qualitative and quantitative degradation of semen. There is a global decline in male reproductive health, and modern therapeutic options to tackle male infertility are expensive, less accessible and have extended treatment durations and adverse effects. When it comes to male reproductive health, herbal therapies are in a much better position to provide more holistic approaches. As aphrodisiacs, a unique class of herbs defined in herbal pharmacology, nourish and stimulate the body's sexual tissues. A careful evaluation of the current information on drugs and their probable functions in treating male infertility is the purpose of this paper

A semantic rule based digital fraud detection

Digital fraud has immensely affected ordinary consumers and the finance industry. Our dependence on internet banking has made digital fraud a substantial problem. Financial institutions across the globe are trying to improve their digital fraud detection and deterrence capabilities. Fraud detection is a reactive process, and it usually incurs a cost to save the system from an ongoing malicious activity. Fraud deterrence is the capability of a system to withstand any fraudulent attempts. Fraud deterrence is a challenging task and researchers across the globe are proposing new solutions to improve deterrence capabilities. In this work, we focus on the very important problem of fraud deterrence. Our proposed work uses an Intimation Rule Based (IRB) alert generation algorithm. These IRB alerts are classified based on severity levels. Our proposed solution uses a richer domain knowledge base and rule-based reasoning. In this work, we propose an ontology-based financial fraud detection and deterrence model