A Tag Type for Certifying Compilation of Java Program

2005 ◽  
Vol 16 (3) ◽  
pp. 346
Author(s):  
Hui CHEN
Keyword(s):  
Java Program ◽  
Certifying Compilation

scholarly journals Public Transport GPS Probe and Rail Gate Data for Assessing the Pattern of Human Mobility in the Bangkok Metropolitan Region, Thailand

2021 ◽  
Vol 13 (4) ◽  
pp. 2178
Author(s):  
Songkorn Siangsuebchart ◽  
Sarawut Ninsawat ◽  
Apichon Witayangkurn ◽  
Surachet Pravinvongvuth
Keyword(s):  
Performance Assessment ◽  
Public Transport ◽  
Human Mobility ◽  
Open Data ◽  
Capital City ◽  
Metropolitan Region ◽  
Traffic Information ◽  
Mobility Patterns ◽  
Transport Planning ◽  
Java Program

Bangkok, the capital city of Thailand, is one of the most developed and expansive cities. Due to the ongoing development and expansion of Bangkok, urbanization has continued to expand into adjacent provinces, creating the Bangkok Metropolitan Region (BMR). Continuous monitoring of human mobility in BMR aids in public transport planning and design, and efficient performance assessment. The purpose of this study is to design and develop a process to derive human mobility patterns from the real movement of people who use both fixed-route and non-fixed-route public transport modes, including taxis, vans, and electric rail. Taxi GPS open data were collected by the Intelligent Traffic Information Center Foundation (iTIC) from all GPS-equipped taxis of one operator in BMR. GPS probe data of all operating GPS-equipped vans were collected by the Ministry of Transport’s Department of Land Transport for daily speed and driving behavior monitoring. Finally, the ridership data of all electric rail lines were collected from smartcards by the Automated Fare Collection (AFC). None of the previous works on human mobility extraction from multi-sourced big data have used van data; therefore, it is a challenge to use this data with other sources in the study of human mobility. Each public transport mode has traveling characteristics unique to its passengers and, therefore, specific analytical tools. Firstly, the taxi trip extraction process was developed using Hadoop Hive to process a large quantity of data spanning a one-month period to derive the origin and destination (OD) of each trip. Secondly, for van data, a Java program was used to construct the ODs of van trips. Thirdly, another Java program was used to create the ODs of the electric rail lines. All OD locations of these three modes were aggregated into transportation analysis zones (TAZ). The major taxi trip destinations were found to be international airports and provincial bus terminals. The significant trip destinations of vans were provincial bus terminals in Bangkok, electric rail stations, and the industrial estates in other provinces of BMR. In contrast, electric rail destinations were electric rail line interchange stations, the central business district (CBD), and commercial office areas. Therefore, these significant destinations of taxis and vans should be considered in electric rail planning to reduce the air pollution from gasoline vehicles (taxis and vans). Using the designed procedures, the up-to-date dataset of public transport can be processed to derive a time series of human mobility as an input into continuous and sustainable public transport planning and performance assessment. Based on the results of the study, the procedures can benefit other cities in Thailand and other countries.

Implementing and using finite automata toolkits

1996 ◽  
Vol 2 (4) ◽  
pp. 295-302 ◽  
Author(s):  
BRUCE W. WATSON
Keyword(s):  
Flight Control ◽  
Program Verification ◽  
Finite Automata ◽  
Circuit Simulation ◽  
Implementation Strategies ◽  
Digital Circuit ◽  
General Purpose ◽  
Genetic Sequencing ◽  
Java Program ◽  
Fire Engine

Finite automata and various extensions of them, such as transducers, are used in areas as diverse as compilers, spelling checking, natural language grammar checking, communication protocol design, digital circuit simulation, digital flight control, speech recognition and synthesis, genetic sequencing, and Java program verification. Unfortunately, as the number of applications has grown, so has the variety of implementations and implementation techniques. Typically, programmers will be confused enough to resort to their text books for the most elementary algorithms. Recently, advances have been made in taxonomizing algorithms for constructing and minimizing automata and in evaluating various implementation strategies Watson 1995. Armed with this, a number of general-purpose toolkits have been developed at universities and companies. One of these, FIRE Lite, was developed at the Eindhoven University of Technology, while its commercial successor, FIRE Engine II, has been developed at Ribbit Software Systems Inc. Both of these toolkits provide implementations of all of the known algorithms for constructing automata from regular expressions, and all of the known algorithms for minimizing deterministic finite automata. While the two toolkits have a great deal in common, we will concentrate on the structure and use of the noncommercial FIRE Lite. The prototype version of FIRE Lite was designed with compilers in mind. More recently, computation linguists and communications protocol designers have become interested in using the toolkit. This has led to the development of a much more general interface to FIRE Lite, including the support of both Mealy and Moore regular transducers. While such a toolkit may appear extremely complex, there are only a few choices to be made. We also consider a ‘recipe’ for making good use of the toolkits. Lastly, we consider the future of FIRE Lite. While FIRE Engine II has obvious commercial value, we are committed to maintaining a version which is freely available for academic use.

scholarly journals Automated Workarounds from Java Program Specifications Based on SAT Solving

2017 ◽  
pp. 356-373
Author(s):  
Marcelo Uva ◽  
Pablo Ponzio ◽  
Germán Regis ◽  
Nazareno Aguirre ◽  
Marcelo F. Frias
Keyword(s):  
Sat Solving ◽  
Java Program

scholarly journals Correlation of Tweets Mentioning Influenza Illness and Traditional Surveillance Data

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Zachary Heth ◽  
Kelley Bemis ◽  
Demian Christiansen
Keyword(s):  
Social Media ◽  
Positive Relationship ◽  
Influenza Season ◽  
Local Level ◽  
Cook County ◽  
P Value ◽  
Java Program ◽  
Influenza Activity ◽  
Media Data ◽  
Traditional Surveillance

ObjectiveTo determine if social media data can be used as a surveillance tool for influenza at the local level.IntroductionThe use of social media as a syndromic sentinel for diseases is an emerging field of growing relevance as the public begins to share more online, particularly in the area of influenza. Several applications have been developed to predict or monitor influenza activity using publicly posted or self-reported online data; however, few have prioritized accuracy at the local level. In 2016, the Cook County Department of Public Health (CCDPH) collected localized Twitter information to evaluate its utility as a potential influenza sentinel data source. Tweets from MMWR week 40 through MMWR week 20 indicating influenza-like illness (ILI) in our jurisdiction were collected and analyzed for correlation with traditional surveillance indicators. Social media has the potential to join other sentinels, such as emergency room and outpatient provider data, to create a more accurate and complete picture of influenza in Cook County.MethodsWe developed a JAVA program which included a customized geofence around suburban Cook County to collect tweets from Twitter’s STREAM application programming interface (API) (available at https://github.com/FoodSafeCookCo/TwitterStream-Program). The JAVA program looked for tweets within the geofence or for tweets with a profile location naming a suburban Cook County municipality and copied them to a text file if the tweet contained “flu” or “influenza”. Captured data included the user’s Twitter handle, Tweet text, Tweet time and date, x and y coordinates (if available), and profile location. Tweets were then manually reviewed to determine if they met the following criteria: 1) language indicated the user was recently ill with influenza; 2) user appeared to reside in CCDPH jurisdiction. Tweets meeting these criteria were included in the analysis. Tweets were aggregated by MMWR week and analyzed for correlation, using Pearson methods (data were normal), with two traditional surveillance sources: 1) the percent of visits to all suburban Cook County emergency departments for ILI as reported to the Cook County Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE), and 2) the percent of laboratory specimens testing positive for influenza at seven local sentinel laboratories. Analysis was performed in Excel 2013 and SAS 9.4.ResultsFrom MMWR week 40-20, 113 tweets indicating influenza-like illness were collected within Cook County’s jurisdiction. Due to technical issues with the program, data were not collected for weeks 52, 2, and 17-19. Correlations were compared for the percent of laboratory specimens testing positive for influenza (LSL) and percent of visits to emergency departments for ILI (EDILI) to the total number of tweets per MMWR week. A strong correlation exists between LSL and EDILI r=0.92 (p-value<0.0001) indicating the traditional sentinels have a strong positive relationship. The correlation between number of tweets and LSL was 0.46 (p-value =0.0138), indicating a moderate positive relationship. Correlation between number of tweets and EDILI was similarly moderate, r=0.52 (p-value=0.0049). Correlations to EDILI stratified by age (0-4, 5-17, 18-64, 65+) also showed a moderate positive relationship (range 0.50 to 0.55, all p-values < 0.01). Twitter use peaked one week before the recorded peak of other surveillance indicators. When Twitter counts were shifted one week to align the peak in tweets with the peak of the influenza season, the correlations were 0.54 for LSL and 0.61 for EDILI (p-value=0.0034 and 0.0007, respectively).ConclusionsOverall, the tweets collected had a moderately positive relationship with the severity of influenza activity in Cook County. When the data were transitioned to match peaks, there was an increase in the correlations’ strength for both LSL and EDILI. This data indicates that publicly shared social media data may be an underutilized source of syndromic data at the local level, potentially capable of predicting seasonal influenza peaks before traditional data sources. Other jurisdictions may consider using the open source program created by CCDPH to determine the relationship of influenza related social media to their own local influenza surveillance data. For the 2017-2018 influenza season, we established a redundant system for tweet collection in case one of the systems goes down. Exploring machine learning (in place of manual review) to detect tweets indicating illness is also a promising avenue to simplify data collection and cleaning. Data will be collected using the same system for the 2017-2018 influenza season and correlations re-evaluated with more complete data. 

scholarly journals Formal Verification of Embedded Java Program

2005 ◽  
Vol 12D (7) ◽  
pp. 931-936
Author(s):  
Tae-Hoon Lee ◽  
Gi-Hwon Kwon
Keyword(s):  
Formal Verification ◽  
Java Program

scholarly journals A Simple Application Program Interface for Saving Java Program Data on a Wiki

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Takashi Yamanoue ◽  
Kentaro Oda ◽  
Koichi Shimozono
Keyword(s):  
Application Program Interface ◽  
Simple Application ◽  
Programming Environments ◽  
Java Applet ◽  
Application Program ◽  
Java Program ◽  
Java Programs ◽  
Local Host ◽  
Program Interface ◽  
Drawing Program

A simple application program interface (API) for Java programs running on a wiki is implemented experimentally. A Java program with the API can be running on a wiki, and the Java program can save its data on the wiki. The Java program consists of PukiWiki, which is a popular wiki in Japan, and a plug-in, which starts up Java programs and classes of Java. A Java applet with default access privilege cannot save its data at a local host. We have constructed an API of applets for easy and unified data input and output at a remote host. We also combined the proposed API and the wiki system by introducing a wiki tag for starting Java applets. It is easy to introduce new types of applications using the proposed API. We have embedded programs such as a simple text editor, a simple music editor, a simple drawing program, and programming environments in a PukiWiki system using this API.

Risk-taking and risk aversion in the period of before and after the 2008 crisis: evaluation with bibliometric analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Selim Aren ◽  
Hatice Nayman Hamamci
Keyword(s):  
Risk Aversion ◽  
Bibliometric Analysis ◽  
Risk Taking ◽  
Financial Risk ◽  
Investor Sentiment ◽  
The Other ◽  
Content Type ◽  
Risk Appetite ◽  
Java Program ◽  
Before And After

PurposeThis study aims to quantitatively classify the articles with risk-taking and risk aversion keywords and to investigate whether there is a similar emphasis in articles as parallel to the change in risk appetite in the market in the period before the crisis (bubble period) and after the crisis.Design/methodology/approachIn this study, a bibliometric analysis of the articles in which the keywords risk-taking and risk aversion are mentioned together with the word finance in the journals scanned in the Web of Science between 2004 and 2012 was performed. In this context, 936 articles were specified. Analyses were made using the CiteSpace Java program.FindingsThe three journals with the most articles with these characteristics are Journal of Banking and Finance, Journal of Financial Economics and Strategic Management Journal. Along with these two main keywords, the other two most used keywords were “model” and “performance”. In addition, the keywords “attitude”, “corporate governance”, “choice” and “determinant” were used more in the post-crisis period. On the other hand, concepts such as investor sentiment or emotions were not amongst the 10 most frequently used keywords during the nine years. This can be considered as an indicator that risk is being modelled, but emotions are relatively neglected. As a result, the findings of this study show that academic papers do not develop in connection with the mood and excitement in the market.Originality/valueThis study is one of the first studies to examine the reflection of risk appetite in the market on academic papers on financial risk-taking and aversion and to investigate whether the situation in the market and the development in publications are related.

Automated Detection and Removal of Cycles in a Concept Map

2021 ◽  
pp. 305-321
Author(s):  
Anal Acharya ◽  
Madhurima Ghosh ◽  
Saran Jha
Keyword(s):  
Online Learning ◽  
Graph Theory ◽  
Concept Maps ◽  
Concept Map ◽  
Automated Detection ◽  
Learning Systems ◽  
Depth First Search ◽  
Java Program ◽  
The Future ◽  
Effective Use

Over the years, concept maps have been used by several researchers to construct online learning systems. This is due to their flexibility in organizing knowledge. However, for effective use of concept maps in education, detection, and removal of cycles within them is necessary. Cycles in a concept map may result in ambiguity and confusion as one concept can lead back to itself. This study first gives brief details about concept maps and their applications in the field of education. A popular algorithm of graph theory depth-first search is then used for detection of cycles. If any cycles are found, they are removed from the graph in an iterative fashion until there are no more cycles in the graph. A Java program was written to simulate the proposed algorithm and found to yield desired results on sample graphs. Finally, the future uses of concept maps have been discussed.

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