Card Problems Research Articles

Evaluating the Impact and Awareness of the Ayushman Bharat Scheme in Bihar

The Ayushman Bharat Scheme, India's largest health insurance initiative, was launched in 2018 with the goal of achieving Universal Health Coverage as outlined in the National Health Policy 2017. This scheme comprises two components: the National Health Mission, which focuses on strengthening health services and promoting awareness in rural and urban areas, and the National Health Protection Mission, which provides free treatment up to Rs. 5 lakhs for 50 crore individuals from economically disadvantaged families. A survey conducted in four districts of Bihar—Bhagalpur, Banka, Munger, and Khagaria—revealed that rural areas have a higher registration rate (58%) compared to urban areas (37%). Social media (31%) and newspapers (21%) are the primary sources of information about the scheme, while gender participation is relatively balanced, with 44% women and 56% men registered. Despite these positive indicators, issues such as paperwork, Aadhaar card problems, and lack of information hindered some from registering. The scheme received an average rating of 3.83 out of 5, reflecting general satisfaction and strong trust (97%) among respondents, though no respondents had yet used the card. To improve the scheme’s reach and effectiveness, it is recommended to increase awareness through targeted social media and newspaper campaigns, simplify the registration process, expand information dissemination, address technical issues, and encourage active usage of the Ayushman Bharat card.

Credit Card Fraud Protection Application

Abstract – Credit card fraud detection is presently the most frequently occurring problem in the present world. This is due to the rise in both online transactions and e-commerce platforms. Credit card fraud generally happens when the card was stolen for any of the unauthorized purposes or even when the fraudster uses the credit card information for his use. In the present world, we are facing a lot of credit card problems. To detect the fraudulent activities the credit card fraud detection system was introduced. This project aims to focus mainly on machine learning algorithms. The algorithms used are random forest algorithm and the Adaboost algorithm. The results of the two algorithms are based on accuracy, precision, recall, and F1-score. The ROC curve is plotted based on the confusion matrix. The Random Forest and the Adaboost algorithms are compared and the algorithm that has the greatest accuracy, precision, recall, and F1-score is considered as the best algorithm that is used to detect the fraud.

EFEKTIVITAS MODEL PROBLEM BASED LEARNING METODE TUTOR SEBAYA BERBANTUAN CARD PROBLEM TERHADAP HASIL BELAJAR MATEMATIKA

Learning mathematics is frequently regarded as difficult by students, resulting in a lack of problem-solving ability. This problem occurred at SMPN 8 Jember, where, based on the results of observations, grade VII students have low problem-solving skills due to the conventional learning model used. If the problem is not addressed immediately, it is feared that it will continue with the next generation of students. This study aims to determine the effectiveness of PBL model of the peer tutor method assisted by card problems on mathematics learning outcomes in seventh-grade junior high school students with quadrilateral material. This research includes a quasi-experimental design. The data collection technique uses pretest and posttest tests to be tested with the paired samples T test and regression test (ANOVA) on the SPSS application. The results of the paired samples T test in the experimental class gave a sig value of 0.000, while in the control class it was 0.003. The sig value for the regression test for the experimental class is 0.014, while the sig value for the control class is 0.033. These results show that the PBL model of the peer tutor method assisted by card problems is more effective and influential than the PBL model of the peer tutor method to improve student mathematics learning outcomes. The study concludes that incorporating card problem learning media into the PBL model of the peer tutor method produces effective results in terms of quadrilateral material mathematics learning outcomes.

Credit Card Fraud Detection using Big Data Technologies

The use of credit cards is prevalent in modern day society. But it is obvious that the number of credit card fraud cases is constantly increasing in spite of the chip cards worldwide integration and existing protection systems. This is why the problem of fraud detection is very important now. Credit card fraud detection is the most frequently occurring problem in the present world. This is due to the rise in both online transactions and e-commerce platforms. Credit card fraud generally happens when the card was stolen for any of the unauthorized purposes or even when the fraudster uses the credit card information for his use. In the present world, we are facing a lot of credit card problems. To detect the fraudulent activities the credit card fraud detection system was introduced. This project aims to focus mainly on validating various Business Rules to Identify whether the transaction happened is Fraud/Genuine and report the same accordingly.

Survey Paper on Credit card Fraud Detection System

Abstract: Credit card fraud detection is presently the most frequently occurring problem in the present world. This is due to the rise in both online transactions and e-commerce platforms. Credit card fraud generally happens when the card was stolen for any of the unauthorized purposes or even when the fraudster uses the credit card information for his use. In the present world, we are facing a lot of credit card problems. To detect the fraudulent activities the credit card fraud detection system was introduced.

The Effectiveness of Jigsaw Type Assisted with Card Problems on Learning Outcomes and Responsibilities of Cell Material

The research aims to analyse the effectiveness of the implementation of cooperative learning of jigsaw-type with the card problem on learning outcomes and responsibilities of student cell material in high school. This is done because students ' understanding of the cell material is still lacking, about 60% of students have not reached the KKM. This research was conducted at the Sint Louis High School in Semarang at the time of school year 2019/2020. The samples in this study were all learners with saturated sampling techniques. The design of this research is One Group Pretest-Posttest Design. The results show the value of N-gain students in medium and high categories, the average character score of student responsibilities reaches good and very good category, so that cooperative learning of Jigsaw type assisted with card problem for effective learning outcomes and student responsibility character.

PENGARUH MODEL PROCESS ORIENTED GUIDED INQUIRY LEARNING (POGIL) DENGAN MEDIA KARTU MASALAH TERHADAP PEMAHAMAN KONSEP DAN AKTIVITAS BELAJAR SISWA PADA MATERI MOMENTUM DAN IMPULS DI SMA

AbstractThe type of this research was experimental research with post-test only controlgroup design in SMA Negeri 1 Panji Situbondo 2016/2017. This research purposed toknow the influence of POGIL models with media card problems with understandingstudents and student learning activities. Determination of research sample is usedcluster random sampling, X MIA 4 as experiment class and X MIA 2 as control class.The technique of data analysis were independent sample t-test with program SPSS 22.Based on analysis of Mann-Whitney test result, showed that model of POGIL withmedia card problems have significantly effect to the understanding of the student'sconcept. Based on the analysis of the independent sample t-test results showed thatmodel of POGIL with media card problems have significantly effect to student learningactivities.Keyword: POGIL, understanding the concept, student learning activities

Daily global stress is associated with nocturnal asthma awakenings in school-age children

Daily global stress is associated with nocturnal asthma awakenings in school-age children

КЕЙС-МЕТОД У ПІДГОТОВЦІ НАУКОВО-ПЕДАГОГІЧНИХ ПРАЦІВНИКІВ ДО ВИКОРИСТАННЯ СЕРВІСІВ ЕЛЕКТРОННОЇ БІБЛІОТЕКИ

This article describes a technique using a case method in preparing teaching staff to use digital library services as an example of a training exercise. It has been suggested program, which will be trained users, editors and administrators DL. Developed scale assessment of knowledge and skills of teaching staff for the results of card problems. Created test questions for the training sessions. Discovered the case-method as type of learning method. Discovered the basic characteristics of situational teaching method: analytical and cognitive. Analytical activities may include problem analysis and/or systems analysis and/or causal analysis, and/or praxeological analysis, and/or prognostic analysis and/or target-oriented analysis. Investigated the principle of formation of bibliographic descriptions DL resource based metadata concept of «quality metadata DL». Proved that mistake when making metadata may somehow block access to the DL.

ВИБІР МЕТОДУ ФІНАНСУВАННЯ ІНВЕСТИЦІЙНИХ ПРОЕКТІВ НАФТОПЕРЕРОБНОГО ПІДПРИЄМСТВА

The article discusses the choice of the method of financing investment projects refinery. Updates the existing material and technical base, increasing production, developing new activities - all of this makes it necessary investment. The value of economic analysis for planning and implementation of investment activity can not be overestimated. Therefore actualized the issue of effective evaluation methods of financing investment projects. Was proposed consideration of issues such as card problems enterprises, construction wood purposes of solving the problem, the division of enterprises into four groups, which allowed to determine the dependence of the method of financing investment projects of refineries Ukraine of ownership of the company and country of origin of the controlling shareholder, and hence the effectiveness of the method of financing .

FINDING PROBLEM SPECIFIC SHANNON INFORMATION IN HIGH DIMENSIONAL INPUT SPACE FOR ARTIFICIAL NEURAL NETWORKS

Artificial neural networks, due to their ability to find the underlying model even in complex highly nonlinear and highly coupled problems, have found significant use as prediction engines in many domains. However, in problems where the input space is of high dimensionality, there is the unsolved problem of reducing dimensionality in some optimal way such that Shannon information important to the prediction is preserved. The important Shannon information may be a subset of total information with an unknown partition, unknown coupling and linear or nonlinear in nature. Solving this problem is an important step in classes of machine learning problems and many data mining applications. This paper describes a semi-automatic algorithm that was developed over a 5-year period while solving problems with increasing dimensionality and difficulty in (a) flow prediction for a magnetically levitated artificial heart (13 dimensions), (b) simultaneous chemical identification/concentration in gas chromatography (22 detection dimensions with wavelet compressed time series of 180,000 points), and finally in (c) financial analytics portfolio prediction in credit card and sub-prime debt problems (80 to 300 dimensions of sparse data with a portfolio value of approximately US$300,000,000.00). The algorithm develops a map of input space combinations and their importance to the prediction. This information is used directly to construct the optimal neural network topology for a given error performance. Importantly, the algorithm also produces information that shows whether the space between input nodes is linear or nonlinear; an important parameter in determining the number of training points required in the reduced dimensionality of the training set. Software was developed in the MatLAB environment using the Artificial Neural Network Toolbox, Parallel and Distributed Computing toolboxes, and runs on Windows or Linux based supercomputers. Trained neural networks can be compiled and linked to server applications and run on normal servers or clusters for transaction or web based processing. In this paper, application of the algorithm to two separate financial analytics prediction problems with large dimensionality and sparse data sets are shown. The algorithm is an important development in machine learning for an important class of problems in prediction, clustering, image analysis, and data mining. In the first example application for subprime debt portfolio analysis, performance of the neural network provided a 98.4% prediction rate, compared to 33% rate using traditional linear methods. In the second example application regarding credit card debt, performance of the algorithm provided a 95% accurate prediction (in terms of match rate), and is 10% better than other methods we have compared against, primarily logistic regression.

Still Waiting: Green Card Problems Persist for High Skill Immigrants - NFAP Policy Brief

Over the past several months, skilled foreign nationals have seen no improvement in their prospects for obtaining green cards and, in fact, wait times are likely to increase in employment-based immigration categories, according to a new report released by the National Foundation for American Policy (NFAP), an Arlington, Va.-based policy research group.An earlier analysis by the National Foundation for American Policy concluded (in October 2011) that wait times for employment-based green cards sponsored today can last 5 years or even decades, depending on the category and country of origin. And now, according to the U.S. Department of State, a wait time may be developing for prospective immigrants in the employment-based first preference (EB-1) category (outstanding researchers and professors, aliens of extraordinary ability), which previously had no backlog. Moreover, in another new development, skilled foreign nationals from countries other than China and India in the employment-based second preference (EB-2), for persons of “exceptional ability” and “advanced degree” holders, will soon experience backlogs. And for at least the rest of Fiscal Year 2012, the U.S. Department of State is not accepting new green card applications for nationals of China and India in the EB-2 category.

A LEMPEL-ZIV COMPLEXITY-BASED NEURAL NETWORK PRUNING ALGORITHM

This paper presents a pruning method for artificial neural networks (ANNs) based on the 'Lempel-Ziv complexity' (LZC) measure. We call this method the 'silent pruning algorithm' (SPA). The term 'silent' is used in the sense that SPA prunes ANNs without causing much disturbance during the network training. SPA prunes hidden units during the training process according to their ranks computed from LZC. LZC extracts the number of unique patterns in a time sequence obtained from the output of a hidden unit and a smaller value of LZC indicates higher redundancy of a hidden unit. SPA has a great resemblance to biological brains since it encourages higher complexity during the training process. SPA is similar to, yet different from, existing pruning algorithms. The algorithm has been tested on a number of challenging benchmark problems in machine learning, including cancer, diabetes, heart, card, iris, glass, thyroid, and hepatitis problems. We compared SPA with other pruning algorithms and we found that SPA is better than the 'random deletion algorithm' (RDA) which prunes hidden units randomly. Our experimental results show that SPA can simplify ANNs with good generalization ability.

Atsiskaitymų mokėjimo kortelėmis saugumo spragos ir patirti nuostoliai

In the article the payment card problems are connected with a gap and damage in the security system. The main purpose of the article is to evaluate security level of the payment card system and find its security gap and damage. Tasks of the article are as follows: to evaluate the damage level of the payment card system for the card system members, to measure the payment card security features, security of the work organization and systems, to examine and evaluate the merits and demerits of security models used in European Banks, to propose the solution how to minimize the damage in payment card system. The Method of research: analysis of nonfiction, continuous census of fraud cases, information analysis using statistical methods, comparative analysis, experts opinion, analysis of material of case investigation and reports, analysis according to the dominating fraud types and indicators, document process analysis. The article’s research shows the weakness of physical card security features, nonsecure customer financial - credit possibility and card parameters management, outworn equipment and methods of system analysis and monitoring, the lack of co-operation between the members of the payment card system. The big part of indicated demerits could be covered by migrating to the new card system and equipment. In addition, it was proposed to create the co-operation schemes between system members and third party service providers, to set the loyalty programme for the merchants and police, to introduce more secure authorisation system modules.

Ten years in the wilderness — a retrospective Part 2: Cyber Security = National Security

Security experts, Richard Power and Dario Forte believe that it is only a matter of time until there is a serious cyber attack on the National Information Infrastructure. They believe that a cyber attack will occur in tandem with a physical one. Many information warfare attacks have occurred and are likely ongoing. A Japanese cult, which launched a gas attack on the Tokyo subway system, nearly succeeded in getting software that it developed implanted in the Japanese Defence Agency computer system. Al-Qaeda has also reportedly attacked the US infrastructure. In addition, it emerged in December that Chinese attackers made highly professional attempts to penetrate US Government computers without leaving barely a trace. Experts believe the attacks to be state-sponsored. Despite the evidence of information warfare activity, it has gone down in priority in the US Government defence agenda. Under the Clinton administration, the Government released a National Strategy to Secure Cyberspace (NSSC). It also had a dedicated cyber security Tzar - Richard Clarke. But the emphasis fell away after the September 11 terrorist attacks in New York and the appointment of the new Bush administration. And citizens don't only have to worry about foreign information invasions. Information warfare can also be conducted domestically. Some experts believe that it is possible to meddle with electronic voting systems, causing a threat to democracy. The US General Accountability Office has voiced concerns including lack of encryption and memory card problems… This month's column is the second in a three part retrospective on this past decade in the field of Cyber Security. Where are we? How far have we come? Where are we going? Last month, we took inventory with “Nine False Notions About Cyber Security” and “Nine Steps to Success.” This month, we will explore the threat of Information Warfare both foreign and domestic in “Cyber Security = National Security.” Next month, in the third and final section of our retrospective, we will report on outstanding technical issues and industry trends.

Consumers’ resolution of credit card problems and exit behaviors

Using data from the Survey of Consumers, this study focuses on consumer’s resolution efforts with credit card problems and the likelihood of “exiting” – that is, discontinuing the use of a given credit card or of the financial institution associated with the card. Among all households with a problem, nearly two‐thirds (63 percent) were able to resolve their problem, while over half (55 percent) exited. Exit was associated with marital status, race, how dissatisfied the consumer was, number of problems related to credit cards, and attribution. Holding all else constant, consumers who were likely to resolve their problem were only half as likely to exit. Thus, credit card companies need to carefully and quickly address their customers’ problems and resolve their complaints.