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The purpose of this paper is to find a real-time parking location for a four-wheeler.

Real-time parking availability using specific infrastructure requires a high cost of installation and maintenance cost, which is not affordable to all urban cities. The authors present statistical block matching algorithm (SBMA) for real-time parking management in small-town cities such as Bhavnagar using an in-built surveillance CCTV system, which is not installed for parking application. In particular, data from a camera situated in a mall was used to detect the parking status of some specific parking places using a region of interest (ROI). The method proposed computes the mean value of the pixels inside the ROI using blocks of different sizes (8 × 10 and 20 × 35), and the values were compared among different frames. When the difference between frames is more significant than a threshold, the process generates “no parking space for that place.” Otherwise, the method yields “parking place available.” Then, this information is used to print a bounding box on the parking places with the color green/red to show the availability of the parking place.

The real-time feedback loop (car parking positions) helps the presented model and dynamically refines the parking strategy and parking position to the users. A whole-day experiment/validation is shown in this paper, where the evaluation of the method is performed using pattern recognition metrics for classification: precision, recall and F1 score.

The authors found real-time parking availability for Himalaya Mall situated in Bhavnagar, Gujarat, for 18th June 2018 video using the SBMA method with accountable computational time for finding parking slots. The limitations of the presented method with future implementation are discussed at the end of this paper.

Discrimination law has evolved from litigating or prosecuting overt, individual cases of egregious behavior solely by means of anecdotal evidence and eyewitness testimony. Statistical evidence came to bear the imprimatur of the United States Supreme Court in the Seventies as a probative means of discerning guilt or liability, and has been used to shore up patterns of prejudice at a systemic level since. Courtrooms of the Twenty-First Century have struggled to define discrimination through a quantitative lens, nonetheless relying on qualitative evidence to assist the factfinder in rendering a verdict. Some definitions carry more precision and accuracy than others. Consider the inflammatory National Law Journal's indictment of the United States Environmental Protection Agency (‘EPA’) as an example of the latter. In 1992, the National Law Journal ran a Special Investigation of the EPA, claiming that the federal government had fostered a racist imbalance in hazardous site cleanup and its pursuit of polluters. Kudos to the columnists for bringing environmental equity into the spotlight of public debate and for forewarning and encouraging the EPA to conduct its enforcements reflectively, in order to avoid being on the receiving end of a Title VI lawsuit. Nonetheless, the methodology used by the National Law Journal belies a total understanding of the bureaucratic structure that pursued these actions and of the notion of statistical significance. This Article confines itself to Region X's actions between 1995 and 1999, applying linear regression and other statistical tests to determine whether biases, found using the National Law Journal's naive methodology, stand after due consideration of chance. The NLJ approach finds evidence of bias, but the author also conducts more complicated and appropriate analyses, such as those contemplated by the National Guidance. After issuing some provisos, the author dismisses charges of racism or classism. While the National Guidance represents a positive first step in identifying environmental justice communities, those with an above-average proportion of lower-class or non-Caucasian inhabitants, it lacks statistical sophistication and econometric depth. This Article concludes by recommending the use of normalized racial distributions, Gini coefficients, and Social Welfare Functions to the EPA and to other organizations conducting environmental justice analysis.

To achieve a full understanding of the role of marketing from plan to profit requires a knowledge of the basic building blocks. This textbook introduces the key concepts in the art or science of marketing to practising managers. Understanding your customers and consumers, the 4 Ps (Product, Place, Price and Promotion) provides the basic tools for effective marketing. Deploying your resources and informing your managerial decision making is dealt with in Unit VII introducing marketing intelligence, competition, budgeting and organisational issues. The logical conclusion of this effort is achieving sales and the particular techniques involved are explored in the final section.

The potential advantage of extreme value theory in modeling management phenomena is the central theme of this paper. The statistics of extremes have played only a very limited role in management studies despite the disproportionate emphasis on unusual events in the world of managers. An overview of this theory and related statistical models is presented, and illustrative empirical examples provided.

This article estimates the loan spread equation taking into account the endogenous matching between banks and firms in the loan market. To overcome the endogeneity problem, I supplement the loan spread equation with a two-sided matching model and estimate them jointly. Bayesian inference is feasible using a Gibbs sampling algorithm that performs Markov chain Monte Carlo (MCMC) simulations. I find that medium-sized banks and firms tend to be the most attractive partners, and that liquidity is also a consideration in choosing partners. Furthermore, banks with higher monitoring ability charge higher spreads, and firms that are more leveraged or less liquid are charged higher spreads.

On-orbit service technology is one of the key technologies of space manipulation activities such as spacecraft life extension, fault spacecraft capture, on-orbit debris removal and so on. It is known that the failure satellites, space debris and enemy spacecrafts in space are almost all non-cooperative targets. Relatively accurate pose estimation is critical to spatial operations, but also a recognized technical difficulty because of the undefined prior information of non-cooperative targets. With the rapid development of laser radar, the application of laser scanning equipment is increasing in the measurement of non-cooperative targets. It is necessary to research a new pose estimation method for non-cooperative targets based on 3D point cloud. The paper aims to discuss these issues.

In this paper, a method based on the inherent characteristics of a spacecraft is proposed for estimating the pose (position and attitude) of the spatial non-cooperative target. First, we need to preprocess the obtained point cloud to reduce noise and improve the quality of data. Second, according to the features of the satellite, a recognition system used for non-cooperative measurement is designed. The components which are common in the configuration of satellite are chosen as the recognized object. Finally, based on the identified object, the ICP algorithm is used to calculate the pose between two frames of point cloud in different times to finish pose estimation.

The new method enhances the matching speed and improves the accuracy of pose estimation compared with traditional methods by reducing the number of matching points. The recognition of components on non-cooperative spacecraft directly contributes to the space docking, on-orbit capture and relative navigation.

Limited to the measurement distance of the laser radar, this paper considers the pose estimation for non-cooperative spacecraft in the close range.

The pose estimation method for non-cooperative spacecraft in this paper is mainly applied to close proximity space operations such as final rendezvous phase of spacecraft or ultra-close approaching phase of target capture. The system can recognize components needed to be capture and provide the relative pose of non-cooperative spacecraft. The method in this paper is more robust compared with the traditional single component recognition method and overall matching method when scanning of laser radar is not complete or the components are blocked.

This paper introduces a new pose estimation method for non-cooperative spacecraft based on point cloud. The experimental results show that the proposed method can effectively identify the features of non-cooperative targets and track their position and attitude. The method is robust to the noise and greatly improves the speed of pose estimation while guarantee the accuracy.

The purpose of this paper is to propose an automatic pattern matching template generating method for the automatic optical inspection system in TFT LCD assembly and positioning process, to improve the conventional image technology. Besides, focusing on integrating the image system with the existing control system, the double aligner mark searching time is decreased to reduce the working time of the integrated system.

The improved pattern matching method of genetic algorithm was adopted, including setting for template image selecting, encoding, calculating fitness function, pattern matching, template generating and genetic algorithm steps. The predetermined pixels were selected from the target template based on the minimum difference to the block image to be tested by utilizing the genetic algorithm, and the other pixels which have not been selected were neglected.

The selected pixels were encoded for recording by sequence mode, and then the target template and the image to be tested were compared based on the calculated fitness function. This method has the advantages of using the fitness function to reduce the searching time, with the help of genetic algorithm to find the optimal target template, and saving memory space by recording target template based on the sequence mode.

The genetic algorithm used in this study is a kind of optimal tool free from gradient data. As long as the fitness function and after continuous iteration are determined, the optimal solution can be found out, and then the optimal target template can be generated.

This system uses fitness function to reduce the pattern matching time. Plural pixels are preset inside the target template, and its fitness function value is calculated. When the target template is compared with the image to be tested, only the fitness function value (also the difference of the plural pixels) is calculated and compared.

The remaining pixels are neglected, so that the searching time can be reduced greatly. The sequence mode is used to save the required memory space for recording target template. Since sequence mode is adopted to record the information of selected pixels, lots of required memory space for recording target template information will be saved.

We investigate the effect of the PCAOB’s Part II report on annually inspected firms’ audit fees and audit quality. The PCAOB replaced the peer review auditor program with an independent inspection of audit firms. Upon completion of each inspection, the PCAOB issued inspection reports that include a public portion (Part I) of identified audit deficiencies, and (in most cases) a nonpublic portion (Part II) of identified quality control weaknesses. The Part II report is only made public when the PCAOB deems that remediation was insuffcient after at least 12 months have passed. Starting around the time of the 2007 Deloitte censure (Boone et al., 2015), the PCAOB shifted from a soft synergistic approach to an antagonistic approach, such that Part II reports were imminent, despite delays that ultimately led to their release one to four years later than expected. Our study spans the period from 2007 to 2015, and examines the effect on audit fees and audit quality at the earliest date that the Part II report could have been released – 12 months after the Part I report was issued. We find that following the 12 month period, that annually inspected audit firms eventually lost reputation by lower audit fees, while they concurrently made remedial efforts to increase the quality of their client’s financial reporting quality (abnormal accruals magnitude and restatements). However, three years after the Part II report was actually released, audit fees increased.

The purpose of this paper is to show that despite the critical importance of using accurate data when identifying geographic patterns and studying hotspots, few have explored the data quality issues introduced by Geographic Information Systems (GIS) software applications. While software manufacturers provide some information about the address matching process, critical details are left out or are buried in technical, and sometimes proprietary, jargon. The purpose of this paper is to address these issues.

The paper demonstrates, with three datasets of 100 cases each, how the assumptions built into popular GIS software produce systematically missing data during the data importing process commonly referred to as address matching.

Inclusion of directional indicators and zip codes are more important than previously thought. The results highlight the critical need to provide complete descriptions of research methodology. All geographic analyses must be accompanied with: information about the hit rate (percent of cases plotted), details about the software and process used to import tabular crime data, information about the software parameters set for the importation process (geocoding preferences), reference information about the street file used; and, an examination of the missing cases to identify some of the sampling error. When forecasting crime issues or identifying hot spots, analysts must be cognizant of the differential impact this bias will have on the generalizability of the results.

The paper explores previously neglected issues in data quality introduced by GIS software applications.