Number Of Tickets Research Articles

Does revenue‐motivated policing alter who receives traffic citations? Evidence from driver race and income in Indiana

AbstractRevenue‐motivated policing is a common explanation for law enforcement behavior. This means in times of fiscal stress police alter their behavior to increase the financial returns to their actions. But does variation in the institutional features of local governments lead to variation in law enforcement behavior? Using a plausibly exogenous measure of revenue need, this research explores how fiscal institutions that determine a local government's ability to retain ticketing revenue interact with revenue need to affect the number of tickets issued and the type of driver ticketed. There are four major findings. First, revenue‐motivated policing only occurs when local governments retain the revenues from ticketing. Second, in the context of revenue retention and high revenue need, wealthier drivers are more likely to receive tickets. Third, these effects are particularly pronounced among White drivers. Finally, revenue‐motives extend beyond law enforcement by altering judicial decision‐making. When general purpose governments do not retain ticketing revenues from law enforcement action, there is little evidence of revenue‐motivated policing. Municipal courts play a vital role in revenue‐motivated policing by determining the distribution of ticketing revenues. When a municipality has an increased need for additional revenue, judges pursue unpaid ticketing debts more aggressively. Judicial behavior is thus affected by the same fiscal pressures that lead police to engage in revenue‐motivated policing. Increased revenue need leads police to target drivers who are not typically the subject of enforcement actions: wealthier, white drivers. We find no such effect for Black drivers. Policies altering revenue retention are a promising way to reduce revenue‐motivated policing. But reducing revenue‐motivated policing might not improve outcomes for Black drivers.

Influence of SARS-CoV-2 coronavirus pandemic on the dynamics of tourism in selected national parks in Poland

The SARS-CoV-2 pandemic that began in 2020 hit the tourist services sector very hard. This article aims to determine the impact of the coronavirus pandemic and its consequences on the tourism dynamics in nine Polish national parks. The statistical (descriptive) analysis method was used based on data collection regarding the number of tickets sold in parks in 2019 and 2020. Studies have shown that despite health concerns and several restrictions, the number of tourists in all parks, expressed in ticket sales in 2020, only decreased by 0.06%. Polish national parks, which are less popular, recorded increases in visitors by up to 66%, while in gardens with usually high attendance, there were decreases, especially during the spring lockdown. The obtained analyses allow the development of tourist mobility patterns in unique situations.

Assessing the impacts of sunday trading restrictions on urban public transport: An example of a big city in central Poland

The paper evaluates the temporal and spatial variability of the use of city public transport resulting from statutory Sunday trading restrictions and the COVID-19 pandemic as exemplified by Łódź, a big city in central Poland. Data on the number of tickets validated in urban public transport vehicles is provided in three forms. The first one presents the number of validations in all vehicles in an hourly distribution, the second one shows the number of validations according to individual tram and bus lines, while the third one gives information on the number of validated tickets assigned to a tram/bus stop within the range of which the validation was made. The outcomes from the conducted research show an increased fluctuation in public transport load on Sundays depending on whether it was possible to conduct all types of commercial activity. This variability is observed to a much lesser extent in the presence of other mobility constraints (the pandemic situation). A spatial shift in mobility towards the periphery and inter-district connections is also observed, which may indicate changes in travel destinations.

A Hundred from a Bus Ticket

We consider the comic task of obtaining the number 100 from a six-digit bus ticket number by placing parentheses and symbols for arithmetic operations between some digits. The solution algorithm for a fixed number is reduced to enumerating all binary trees having exactly six terminal nodes with the signs of operations in internal nodes. For six-digit numbers that do not contain duplicate digits and the digit 0, the problem has a solution for all numbers except the only number 746189. It is impossible to obtain a hundred from this strange number 746189.

Analysis of mobile phone use engagement during naturalistic driving through explainable imbalanced machine learning

While driver distraction remains an issue in modernized societies, technological advancements in data collection, storage and analysis provide the means for deeper insights of this complex phenomenon. In this research, factors influencing when driver distraction through mobile phone use occurs during naturalistic driving are investigated. Naturalistic data from a 6-stage, 230-driver experiment are exploited, in which drivers installed a non-intrusive driving recording application in their devices and conducted their trips normally across a 21-month timespan, coupled with corresponding questionnaire data. The various experiment stages involved providing progressively more behavioral feedback to drivers while continuing to record them. Subsequently, supervised Machine Learning XGBoost algorithms were employed to model the contributions of naturalistic driving and questionnaire features to the decision to engage mobile phone use. Mobile phone use percentages were heavily skewed towards zero, therefore imbalanced ML with a minority-oversampling approach in a binary format was employed. To increase the explainability offered by the algorithm, SHAP values were calculated for the informative features. Results indicate that the decision of drivers to use a mobile while driving is governed by a number of complex, non-linear relationships. Total trip distance is the most significant predictor variable by a wide margin, with mean SHAP values of 0.79 towards affecting the model decisions for the probability of mobile phone use of each driver. However, other variables influence the final predictions as well, such as the number of tickets in the last three years (m.SHAP = 0.30), declared mobile phone use (m.SHAP = 0.26), the amount and variety of provided feedback (m.SHAP = 0.17) (i.e. experiment phase number) and family member numbers (m.SHAP = 0.09) decrease the probability of using a mobile phone while driving. Conversely, increases in driver experience (m.SHAP = 0.22), driver age (m.SHAP = 0.11), engine capacity (m.SHAP = 0.11) and total kilometers driven annually (m.SHAP = 0.08) increase the probability of using a mobile phone in naturalistic driving conditions. SHAP dependency plots reveal non-linear effects present in almost all variables. Fuel consumption had a particularly strong non-linear effect, as higher values of this variable lead to both higher and lower probability of drivers using a mobile phone, deviating from the safer average. Legislation, campaigns and enforcement measures can be restructured to take advantage of gains margins in terms of understanding and predicting driver distraction behavior, as explored in the present study.

The Pengembangan Data Warehouse untuk Mengetahui Tren Aktivitas Trouble Ticket

This research started from the need for XYZ company to be able to present reports or data quickly when needed. There are so many trouble tickets per month, so PT XYZ needs information from historical data that can be seen from various dimensions, especially regarding trends that occur in trouble tickets. With this research, it is possible to develop a data warehouse originating from the operational database from PT XYZ, perform data warehouse analysis with Tableau software to find out trends in trouble ticket activity transactions. The data warehouse development method is to use the nine step design methodology development method using pentaho software. Based on the obtained trends, an information analysis of the number of Trouble tickets was carried out based on two dimensions, namely location and time, and it was found that in the 2nd and 3rd week of each month they had the most trouble tickets. This is due to the influence of the weather in these locations. Then an evaluation was carried out through a questionnaire using the Technology Acceptance Model (TAM), and the average rating from users was 3.83-4.22 which stated that this research could provide benefits and be accepted by PT XYZ.

The relationship between self-reported ability emotional intelligence and risky driving behaviour: Consequences for accident and traffic ticket rate

Road safety represents one of the main public health issues worldwide, and risky driving behaviour is one of the most predominant factors in traffic road accidents. The primary objective of this research was to clarify the relationship between emotional intelligence (EI) abilities and the probability of engaging in risky behaviour during driving. Previous literature linking these constructs is limited, and research has yielded mixed findings. In the present study, 555 drivers from a Spanish community sample (Mage = 39.34, ranging from 18 to 79 years old; 49.19% women) were assessed on risky driving behaviour using the Dula Dangerous Driving Index while self-reported ability EI was measured using the Wong and Law Emotional Intelligence Scale. Gender, age, and driving experience were controlled. The results of this study revealed that a higher self-reported ability EI, particularly the ability to regulate emotions, was related to a lower tendency to engage in risky driving behaviours. In turn, self-reported ability EI was negatively and indirectly related to the number of road accidents and traffic tickets through the mediating effect of risky driving. The regulation of emotions (via direct and indirect effect) and the appraisal of the emotions of others (via direct effect) were the EI abilities that better predicted the number of accidents and traffic tickets. We discuss the practical implications of these findings, along with suggested future lines of research.

Gambling During the Covid-19 Pandemic

IntroductionWith the Covid-19 pandemic numerous questions about the behaviour of gambling addicts have risen, with the lockdown causing a lack of structure, peer supervision and support. The first reports have suggested an increase in activity and riskier choices.ObjectivesOur aim was to explore how the Covid-19 pandemic has influenced gambling habits.MethodsData was collected from companies in Germany and Croatia which provide online gambling services, and statistically analyzed.ResultsIn Germany in April 2020, there was a 51.19% decrease in number of players when compared to April 2019, but a 116.46% rise in the number of tickets per player. In comparison, in April 2021 a rise of 704.43% occurred in number of active players compared to April 2020, with a 277.56% increase in ballots and a decrease in number of tickets per player by 53%. Additional results showed a 1.2% decrease in spendings on sports events in April 2020 compared to April 2019, but a 277.88% increase for sporting events spendings in April 2021. Preliminary results from Croatia show an increase in online gambling activities.ConclusionsIn 2020, despite a drop in active players, the increase in stakes and frequency of play resulted only in a slight decrease in sporting events spendings. In 2021 the recorded increase in all categories except in frequency, points to the idea that restoring life to usual rhythm reduces the frequency of an individual’s play. In conclusion, further research and monitoring of gambling addicts’ behaviour in the “new normal” is needed.DisclosureNo significant relationships.

Implementation of Cloud Computing Technology for Ticket Booking

Abstract: The current railway or bus ticket booking system is human dependent and tedious with regards to the ticket booking process. The core objective of our project is to develop the web-application which will serve as a medium for students/employees/anyone to book the tickets to travel through trains or bus. The principle motive force of this web-application is to ease the process of ticket booking by avoiding the hectic and boisterous processto stand in a queue and book the ticket for the short distance for travelling in the trains. Several applications are available in the market which gives information about the travelling destinations and their fares. However, none of these applications incorporate the ticket booking process coordinated for both train and bus. Our applicationcontrasts from such a lot of existing applications as it would book the ticket as well as save the ticket in the clouddatabase for both train and bus. Ticket can be bought with the help of smart phone, laptop using the web-application where your railway tickets can be carried in your phone. The ticketing information of the user is securely stored in the cloud database.Additionally, the ticket checker is given the checker application which is utilized for the approval of the ticket appeared by the user. This framework gives the ticket checker web-application to look for the user's ticket with the ticket number or other appropriate information in the cloud database for checking purposes. Consider that the user's display is being damaged and not able to show the ticket due to other reasons like battery failure we have another safeguard alternative to check the ticket by searching in the ticket database with the ticket numberor user’s other relevant information for validation purpose. Keywords: Ticket Booking, Railway, Cloud Database, Ticket Checker.

Online Account Opening System with Wadiah Contract at PT Bank Syariah Indonesia KCP Binjai Soetta

Strategy for opening a web-based account (Burekol) at Bank Syariah Indonesia Kcp Binjai Soetta is completed by the administrative center's requests. For this record opening strategy, the client initial steps to download the BSi mobile, after it is introduced, then, at that point, opens the Mandiri Syariah Portable application, then, at that point, picks the record to be made, in the wake of choosing the client's record, fills in the information to be made a record, after every one of the information is finished, the client gets a ticket number. Video Call to check client information. The Necessities for opening an internet based account at Bank Syariah Mandiri are forthcoming individual Indonesian Residents (WNI) clients who have an E-KTP, with a base equilibrium of Rp. 50,000, free month to month organization expense (excluding charge office expenses), Extra managerial expenses under a base equilibrium of Rp. 5,000, account shutting charge of Rp. 20,000. During the Coronavirus time frame, there was a lot of public premium in opening a web-based account, as a result of the simplicity of opening it, by just utilizing the Mandiri Syariah Portable application, clients don't have to line by and large, in light of the fact that the interaction is less complex..

Analisis Sistem Antrian pada Pelayanan Help Desk UPT TIK Institut Teknologi Sumatera Menggunakan Teori Antrian

The analysis of the queuing system at the Help Desk service of the UPT TIK Institut Teknologi Sumatera includes the number of ticket arrivals, the average length of service time, and the number of service facilities (admin). The data for the number of Help Desk tickets are Poisson distributed and the service time is the Exponential distribution. The size of the steady-state in the service has a value of so that an analysis of the performance size of the queue system can be carried out. The data used in the study are Help Desk ticket data for the period November 2020-February 2021. The results obtained indicate that the queue model for the Help Desk service can be added to the server (admin). The addition of a server in the service can reduce the workload significantly. The queue model that can be applied is M/M/3:FCFS/∞/∞ by adding one server (admin), from the previous model, namely M/M/2:FCFS/∞/∞.

Implementation of Cloud Computing Technology for M-Ticket Booking

Abstract: The current railway or bus ticket booking system is human dependent and tedious with regards to the ticket booking process. The core objective of our project is to develop the web-application which will serve as a medium for students/employees/anyone to book the tickets to travel through trains or bus. The principle motive force of this web-application is to ease the process of ticket booking by avoiding the hectic and boisterous process to stand in a queue and book the ticket for the short distance for travelling in the trains. Several applications are available in the market which gives information about the travelling destinations and their fares. However, none of these applications incorporate the ticket booking process coordinated for both train and bus. Our application contrasts from such a lot of existing applications as it would book the ticket as well as save the ticket in the cloud database for both train and bus. This website is for railway and bus ticket booking and one can easily validate those booked tickets using mobile. Ticket can be bought with the help of smart phone, laptop using the web-application where your railway tickets can be carried in your phone. The ticketing information of the user is securely stored in the cloud database. Additionally, the ticket checker is given the checker application which is utilized for the approval of the ticket appeared by the user. This framework gives the ticket checker web-application to look for the user's ticket with the ticket number or other appropriate information in the cloud database for checking purposes. Consider that the user's display is being damaged and not able to show the ticket due to other reasons like battery failure we have another safeguard alternative to check the ticket by searching in the ticket database with the ticket number or user’s other relevant information for validation purpose. Keywords: Ticket Booking, Railway, Mobile, Cloud Database, Ticket Checker.

Impact of Critical and Auto Ticket: Analysis for Management and Workers Productivity in using a Ticketing System

Purpose – Ticketing system is common in Technical Support in Information Technology Industry. At present time, even management is using it. It serves as a way to connect the company and the client, end to end. Support Industry used this also to monitor and log all solutions and processes that come up to resolve the ticket. Client and the resources that will troubleshoot this, use the ticket to have an idea for what is the problem, when the client encountered it, and even the business impact. The researchers conducted research entitled “Impact of Critical and Auto Ticket’s: Analysis for Management and Workers Productivity in using Ticketing System" where it aims to come up with a solution on how we are going to prevent, troubleshoot, and give insight for possible business impact to those everyday issues. This will help the management’s business process to have an analysis to prevent critical issues that will affect the live production as well as give time to their resource to focus on their tasks. Method – Researchers used data collection to gather data from management, support workers, and Service Now’s open-source ticketing system to visualize the ticketing system application. Also, a purposive sampling type of survey has been used to highly represent the data. Results – Critical ticket gives a lot of pressure to the resources as they needed to resolve the incident in accordance with the service level agreement. It affects their productivity to maximize their time to resolve other escalated incidents as they need to focus with critical ones. Instead of maximizing time management and prioritizing employee’s welfare like work and life balance, auto ticket’s affects it because of continuous re-occurring and sometimes needed to be escalated as it will affect the live production. Having knowledge management helps resource to find references on how to deal with the incident. It helps them to execute workaround quickly and think of a way on how to resolve it permanently. Conclusion – It is concluded that critical and auto ticket’s affects the everyday productivity of the worker especially teaching new employees despite ongoing critical incidents. Researchers provided solutions such as knowledge Management and Dashboard to document all the solutions encountered and monitor the SLA’s and incoming tickets. Recommendation – It is recommended to have further research on how critical and auto ticket affects the mental health of resources and its direct impact to businesses. It is also recommended to have a study on how knowledge management work and help resources to identify correct workaround despite of having a lot of troubleshooting guides. Practical Implication – This research benefits data warehousing companies that can be used as a third-party application to connect support team, management, and clients. Management can create a dashboard and identify how their support team provides good quality of service with their response and resolution time. Support team can have a reference to quickly fix escalated incidents and provide ticket number to the client for easily follow up an update.

Methods of Using Twitter in Marketing the Activities of Public Relations Departments in the Saudi Airline Market: أساليب استخدام تويتر في الأنشطة التسويقية لإدارات العلاقات العامة بسوق الطيران السعودي

The study aimed to identify the most important marketing activities of public relations departments in the Saudi aviation market, and to identify the methods of using Twitter in the marketing activities of public relations departments in the Saudi aviation market. It also aimed to reveal its strengths and weaknesses, and to monitor the content of marketing tweets published by public relations departments in the Saudi aviation market via Twitter. The study sample consists of the twitter accounts of the General Authority of Civil Aviation, Saudi Arabian Airlines, and Flynas. The study concluded that the most important marketing activities of the public relations departments in Saudi Airlines and flynas were to respond to the customer in private, and then allocate a number for the customer to follow up with him. The study concluded by extracting the most prominent methods of using Twitter in the marketing activities of public relations departments in the Saudi aviation market, where these methods consisted of communicating with the customer with the reservation number for his service, then responding to the customer in private, and then welcoming the customer. The study also showed that the most important strengths in the marketing activities of public relations departments in the Saudi aviation market are the immediate response to the customer's inquiry, and then allocating a number to follow up the customer's complaint. On the other hand, the most important weaknesses in the marketing activities of the public relations departments in the Saudi aviation market are that communication takes place only via the ticket number or the reservation reference number, and then the weakness of scheduling new flights. The study showed that the most prominent contents of the marketing tweets published by the public relations departments in the Saudi aviation market consisted of re-tweets and admiration, and then directing customers to their inquiries.

The Lucky Tickets

Summary “Lucky tickets” are n-digit numbers whose digits satisfy various arithmetical equations. For example, a Moscow lucky ticket is a six-digit number in which the sum of the first three digits is the same as the sum of the last three digits. We summarize the story of lucky tickets, and introduce the notion of k-lucky tickets. Then we find formulas for calculating of the total numbers of such tickets.

The Importance of Entrepreneurship in Micro and Small Enterprises in Uncertainty and Barrier Scenarios

Economic, political, and technological uncertainties require organizations to prepare adequately for new events that occur each day. Economic crisis, changes in the policies of each country and technological developments are classic examples of these changes in organizations. Seasonality is one of the economic phenomena that occur, and different forms of management are required. The seasonality that is described as a systematic and temporal imbalance of the tourist phenomenon that does not need to be regular, caused by the climate or by the vacation periods, and is based on the consumer behavior that can be expressed in terms of the number of visitors, traffic, highways, jobs, and tickets at attractions. Therefore, through a careful analysis of seasonality, it is possible that the losses are predicted, and the negative impact is not so grotesque on the company. For this, it is good that the manager uses the cost assessment methods to assume the seasonality of sales and thus be able to guard against the negative effects of the same. The objective of this research is to understand how owners of micro and small businesses in coastal cities consider themselves entrepreneurs or not and how they deal with obstacles such as seasonality through cost management. The methodology used was based on an exploratory and bibliographic research with a qualitative approach, seeking to analyze the triad: Entrepreneurship, Seasonality and Cost Management. The field research was applied through a semi-structured questionnaire to the sample of 100 Microentrepreneurs in the trade of goods and services in Caraguatatuba and São Sebastião, central cities of the North Coast of São Paulo. The main results show that most of the interviewed entrepreneurs perceive a certain impact caused by seasonality, understand the use of Cost Management to improve their processes and are adapted to one of the main costing methods highlighted by the bibliography.

Investigation of Stretch Properties of Different Stitch Types in Garments Made of Elastane Woven Fabrics

In recent years, garments made of fabrics with elastane are highly preferred. A garment made of fabric with elastane is able to stretch by about 10-30% and recovery immediately after release. In the apparel industry, sewing should not prevent the fabric from stretching in the garments made from woven fabrics with elastane. The elasticity of the seams of the garments consisting of elastic fabrics is very important. 
 
 In this study, it is aimed to examine the stretch and permanent elongation properties of different stitch types of garments made of elastane woven fabrics. For this purpose, 5 different stitch types were selected as lockstitch, zig zag stitch, two thread chain stitch, three thread overlock stitch and five thread overlock stitch, and these stitches were sewn at different stitch densities (3 - 4 and 5 stitches / cm), with different sewing threads (spun polyester, core spun (poly / poly), nylon and elastic sewing thread) with different ticket numbers (80 and 120). The stretch and permanent elongation values of the sewn fabric samples were examined.

Parallel Lotteries: Insights from Alaskan Hunting Permit Allocation

We analyze the parallel lottery that is used to allocate hunting permits in the state of Alaska. Each participant is given tickets to distribute among lotteries for different types of items. Participants who win multiple items receive their favorite, and new winners are drawn from the lotteries with unclaimed items. When supply is scarce, equilibrium outcomes of parallel lotteries approximate a competitive equilibrium from equal incomes (CEEI), which is Pareto efficient. When supply is moderate, parallel lotteries exhibit two sources of inefficiency. First, some agents may benefit from trading probability shares. Second, outcomes may be “wasteful”: agents may receive nothing even if acceptable items remain unallocated. We bound both sources of inefficiency and show that each is eliminated by giving applicants a suitable number of tickets k: trades are never beneficial when k = 1, and waste is eliminated as [Formula: see text]. In addition, we show that the wastefulness of the k-ticket parallel lottery has some benefits: agents with strong preferences may prefer parallel lottery outcomes to those of any nonwasteful envy-free mechanism. These agents prefer small values of k, while agents with weak preferences prefer large values of k. Together, these results suggest that the k-ticket parallel lottery performs well under most circumstances and may be suitable for other settings where items are rationed. This paper was accepted by Gabriel Weintraub, revenue management and market analytics.

Perbandingan Metode TF-ABS dan TF-IDF Pada Klasifikasi Teks Helpdesk Menggunakan K-Nearest Neighbor

Distribution of tickets to the destination unit is a very important function in the helpdesk application, but the process of distributing tickets manually by admin officers has drawbacks, namely ticket distribution errors can occur and increase ticket completion time if the number of tickets is large. Helpdesk text classification becomes important to automatically distribute tickets to the appropriate destination units in a short time. This study was conducted to compare the performance of helpdesk text classification at the Directorate General of State Assets of the Ministry of Finance using the K-Nearest Neighbor (KNN) method with the TF-ABS and TF-IDF weighting methods. The research was conducted by collecting complaint documents, preprocessing, word weighting, feature reduction, classification, and testing. Classification using KNN with parameters n_neighbor (k) namely k=1, k=3, k=5, k=7, k=9, k=11, k=13, k=15, k=17, and k=19 to classify 10,537 helpdesk texts into 8 categories. The test uses a confusion matrix based on the accuracy value and score-f1. The test results show that the TF-ABS weighting method is better than TF-IDF with the highest accuracy value of 90.04% at 15% and k=3.

A multiapproach generalized framework for automated solution suggestion of support tickets

Nowadays, customer support systems are one of the key factors in maintaining any big company's reputation and success. These systems are capable of handling a large number of tickets systemically and provides a mechanism to track/logs the communication between customer and support agents. Companies invest huge amounts of money in training support agents and deploying customer care services for their products and services. Support agents are responsible for handling different customer queries and implementing required actions to solve a particular issue or problem raised by the service/product user. In a bigger picture, customer support systems could receive a large amount of ticket raised depending upon the number of users and services being offered. Customer care service gets directly affected due to the high volume of tickets and a limited number of support agents. Therefore, providing support agents with the recommendations about the possible resolution actions for a new ticket would be helpful and can save a lot of time. This study is focused on the development of an end-to-end framework for suggesting resolution actions rather than recommending free form resolution text against a newly raised ticket. To develop such a system, the pipeline is broadly divided into four components that are data preprocessing, actions extractor, resolution predictor, and evaluation. In actions extractor module, we have proposed a technique to identify and extract actionable phrases from resolution text. For resolution predictor, we have proposed two different pipelines that are referred as “Similarity Search Model” and “End-to-End Model.” The similarity search method is based on a ticket similarity search to find the most relevant historical tickets which then leads to corresponding resolution actions. On the other hand, end-to-end model make use of actions extractor module directly and implemented in a way to directly predict resolution actions. To compare and evaluate the mentioned methods on the same ground, we also proposed an actions evaluation criterion which uses BertScore and METEOR score jointly to compute the score against actual and predicted actions for a particular test ticket. The analysis and experiments are performed on the real-world IBM ticket data set. Overall, we observed that end-to-end model outperformed similarity search-based methods and achieved better performance and scores comparatively. The trained models and code are available at https://bit.ly/2GbUBVk.