The Impact of Supreme Court Precedent in a Judicial Hierarchy

My dissertation explores three core questions. First, how is information regarding the preferences of judicial actors communicated within the American federal judiciary? Second, can U.S. Supreme Court justices meaningfully signal their policy preferences, vis-á-vis their decisions, to judges on the U.S. Courts of Appeals? Finally, what impact do such signals have on the propensity of lower courts judges to follow the precedents of the Supreme Court? The primary objective of this project is to identify the conditions that either increase or decrease the likelihood that judges on the courts of appeals comply with the precedents of the Supreme Court. I develop a theory in which information regarding the preferences of judicial actors flows dynamically within the courts. Specifically, I theorize that key Supreme Court signals and circuitlevel influences, together, drive circuit court attentiveness to precedents. Lower court application of the Supreme Court’s decisions, in turn, communicate information up the judicial ladder of the policy position of precedents. My findings demonstrate that not only is the Supreme Court capable of communicating information, but that such cues substantially influence lower federal court decision making and their interpretations of precedent. My results notably depart from earlier findings in that they demonstrate that ideological preferences has a more nuanced impact on the adoption of the Court’s precedents. This study contributes to our understanding of learning within the judicial hierarchy by identifying new mechanisms through judicial decision makers are able to communicate their legal and policy preferences. The implications of my analysis offer new insights on the influence of stare decisis and decision-making behavior within the U.S. Supreme Court and the U.S. Courts of Appeals

A Machine Learning based Framework for KPI Maximization in Emerging Networks using Mobility Parameters

Current LTE network is faced with a plethora of Configuration and Optimization Parameters (COPs), both hard and soft, that are adjusted manually to manage the network and provide better Quality of Experience (QoE). With 5G in view, the number of these COPs are expected to reach 2000 per site, making their manual tuning for finding the optimal combination of these parameters, an impossible fleet. Alongside these thousands of COPs is the anticipated network densification in emerging networks which exacerbates the burden of the network operators in managing and optimizing the network. Hence, we propose a machine learning-based framework combined with a heuristic technique to discover the optimal combination of two pertinent COPs used in mobility, Cell Individual Offset (CIO) and Handover Margin (HOM), that maximizes a specific Key Performance Indicator (KPI) such as mean Signal to Interference and Noise Ratio (SINR) of all the connected users. The first part of the framework leverages the power of machine learning to predict the KPI of interest given several different combinations of CIO and HOM. The resulting predictions are then fed into Genetic Algorithm (GA) which searches for the best combination of the two mentioned parameters that yield the maximum mean SINR for all users. Performance of the framework is also evaluated using several machine learning techniques, with CatBoost algorithm yielding the best prediction performance. Meanwhile, GA is able to reveal the optimal parameter setting combination more efficiently and with three orders of magnitude faster convergence time in comparison to brute force approach

Rent-A-Car

The Rent-a-Car application will improve the efficiency of the web-based Rental Car business. A renter can reserve a car from anywhere in the world. Renters from all around the world will be able to book cars through our website. The owner enters their vehicle information, which is shown on the main page. A renter who has registered on the website has the option of reserving the car they require. The renter pays the owner for the car rental and can reserve it whenever they want. The money will be deposited into the car owner\u27s account. The vehicle\u27s condition and details have been approved by the administrator. This automatic method assists the renter and owner by filling out the information based on their requirements. Our application has three consoles. Owner, Admin, and Renters The administrator can manage both the owner and the renter. Owners can only manage their vehicles, bookings, and so on. Renters can view their profile, booking history, and other information. We are using .NET Core logic in Visual Studio to create the application that will handle the functionalities

Status of Health related Quality of life between HBV and HCV Patients of Pakistan

The aim of the study is to explore the factors those differentiate health related quality of life (HRQOL) among hepatitis B (HBV) and hepatitis C (HCV) patients. Different public and private hospitals of Sargodha district were visited and 120 patients of hepatitis B and C were interviewed. World health related quality of life-BREF (WHOQOL-BREF) questionnaire was used to construct HRQOL instrument. Multiple regression analysis was performed to observe the collision of demographic, medical, economic and physical and psychological factors on patients HRQOL. Results showed that HBV patients enjoyed better HRQOL then HCV patients. 86.4% HCV patients faces death threat while, 67.3% HBV faces this threat. 93.5% HBV patients feels depression while, 97.8% HCV patients feels depression. Urban patients HRQOL scores were superior then rural patients in both HCV and HBV case. Moreover, male patients HRQOL scores were better as compared to female patients. Age of the patient, disease severity, use of drug, pain, depression, financial hindrance and threat of death negatively influence the HRQOL of both HBV and HCV patients while, vaccination, income, sleep, opportunity of leisure and better living condition were positively related to HRQOL.Sargodha; HBV; HCV; Pakistan

The Full Non-Rigid Group Theory for cis- and trans-Dichlorodiammine Platinum(II) and Trimethylamine

The non-rigid molecule group theory (NRG), in which the dynamical symmetry operations are defined as physical operations, is a new field of chemistry. In a series of papers Smeyers applied this notion to determine the character table of restricted NRG (r-NRG) of some molecules. For example, Smeyers and Villa computed the r-NRG of the triple equivalent methyl rotation in pyramidal trimethylamine with inversion and proved that the r-NRG of this molecule is a group of order 648, containing two subgroups of order 324 without inversions (see J. Math. Chem. 28 (2000) 377–388). In this work, a simple method is described, by means of which it is possible to calculate character tables for the symmetry group of molecules consisting of a number of AH3 groups attached to a rigid framework. We have studied the full non-rigid group (f-NRG) of cis- and trans-dichlorodiammine platinum(II) and trimethylamine and we have proven that they are groups of orders 36, 72 and 1296 with 9, 18 and 28 conjugacy classes, respectively. This shows that the full non-rigid group and the restricted non-rigid group of these molecules are not isomorphic. The method can be generalized to apply to other non-rigid molecules. The f-NRG molecule group theory is shown to be used advantageously to study the internal dynamics of such molecules

Descriptive epidemiology of Karachi road traffic crash mortality from 2007 to 2014

Abstract According to World Health Organization\u27s estimate for Pakistan, there were 25,781 (95% CI: 20,979-30582) Road Traffic Collision (RTC) fatalities in year 2013. The Road Traffic Injury Research and Prevention Center, collects RTC data on injuries and fatalities from five major public and private hospitals\u27 emergency departments in Karachi. For the eight-year period, from 2007-2014, 9129 fatalities were recorded. Males accounted for 8008 (87.7%) all RTC fatalities. Highest number of fatalities were recorded in the 21-25 age group with 1329 (15.3%) fatalities, while fatalities in 16-30 years old, recorded 3446 (39.7%) of all fatalities out of the total 8684 records for which age information was available. Motorbikes as primary vehicles were responsible for 3871 (44.7%) RTC fatalities out of the 8654, for which this information was available. Among women, housewives were the single largest group to have died as a result of RTCs

Road traffic crash related injured and fatal victims in Karachi from 2007 to 2014: A time-series analysis

Injuries and deaths due to road traffic crashes (RTC) are major public health concern. The Road Traffic Injury Research and Prevention Center, collects RTC data on injuries and fatalities from five emergency departments in Karachi. Data generating process (DGP) for RTC from 2007 to 2014, for monthly number of fatal and injured victims were analyzed using autoregressive integrated moving average and vector auto regression, time series models. Results provide strong evidence that the DGP for the current levels of the number of fatalities and injured owing to RTCs are significantly influenced by the own past history of the two series. The analysis with the impulse-response function also indicated that there is a slight seasonality pattern in the number of injured and fatalities. The similar behaviour and association of the two variables suggest that certain conditions e.g. road conditions, weather, volume of vehicles, and accidents might be persistent in time in Karachi

SORPTION OF NICKEL IONS ONTO CHEMICALLY MODIFIED PARTHENIUM HYSTEROPHOROUS L. AND THEIR QUANTITATIVE DETERMINATION BY TITRATION.

The removal efficiency of Nickel ions from aqueous solution on chemically treated Parthenium  hysterophorous leaf powder (PHLP) has been investigated. The adsorbent was characterized by SEM images and FTIR spectra analysis.  The effect of several parameters such as pH, adsorbent dose, concentration of Ni ion solution and contact time was evaluated using batch experiments. Nickel ions removal was pH dependent and the maximum removal was found to be at pH 7. The maximum removal of Ni ions was achieved within 100 min after the start of every experiment. The equilibrium adsorption data were fitted to Langmuir, Freundlich, Temkin and Dubnin- Radushkevich (D-R) adsorption isotherm models to evaluate the models parameter. Experimental results showed that the Langmuir isotherm model best describes for the adsorption of metal than Freundlich isotherm model. Adsorption data were processed according to various kinetic models. Pseudo-first order and pseudo-second order were applied to fit the kinetic results. Pseudo-first order model was less applicable than pseudo-second order. Thermodynamic studies showed spontaneous and exothermic nature in the adsorption of Ni (II) onto PHLP

Epidemiology of Karachi road traffic crash mortality in 2013

Abstract Road Traffic Crash (RTC) is the eighth leading cause of death globally. In a recent World Health Organization report, there were 5,192 RTC deaths reported from Pakistan in 2010. The Road Traffic Injury Research and Prevention Center (RTIRPC) is a unique public-private public health enterprise in Karachi, and collects data from five major public and private hospitals\u27 emergency departments in the city. Cumulatively, 1130 deaths were recorded in the year 2013. Males accounted for 981 (86.8%) deaths. The most vulnerable decades of life were twenties and thirties; accounting for 307 (27.2%) of all deaths. In terms of involvement of vehicle type in fatalities; over half 577 (51.1%) of all fatalities involved motorbikes, while the second most common type of vehicle involved were buses/coasters which accounted for 108 (9.6%) fatalities. In the burgeoning cities of developing countries, road injury and fatality surveillance can fulfill a vital role in highlighting the human cost of rapid motorization