Use Of Wrap Research Articles

A new bound for A(A + A) for large sets

For a large prime number p and a set A⊂Fp we prove the following:(1)If A(A+A) does not cover all nonzero residues in Fp, then |A|⩽p/8+o(p).(2)If A is both sum-free and satisfies A=A⁎, then |A|⩽p/9+o(p).(3)If |A|≫log⁡log⁡plog⁡pp, then |A+A⁎|⩾(1+o(1))min⁡(2|A|p,p). Here the constants 1/8, 1/9, 2 are the best possible. Proofs make use of wrappers, subsets of a finite abelian group G, which ‘wrap’ popular values in convolutions of dense sets A,B⊆G. These objects carry certain structural features, making them capable of addressing additive-combinatorial and enumerative problems.

Reinforcement Learning with an Ensemble of Binary Action Deep Q-Networks

CC’s (Cloud Computing) networks are distributed and dynamic as signals appear/disappear or lose significance. MLTs (Machine learning Techniques) train datasets which sometime are inadequate in terms of sample for inferring information. A dynamic strategy, DevMLOps (Development Machine Learning Operations) used in automatic selections and tunings of MLTs result in significant performance differences. But, the scheme has many disadvantages including continuity in training, more samples and training time in feature selections and increased classification execution times. RFEs (Recursive Feature Eliminations) are computationally very expensive in its operations as it traverses through each feature without considering correlations between them. This problem can be overcome by the use of Wrappers as they select better features by accounting for test and train datasets. The aim of this paper is to use DevQLMLOps for automated tuning and selections based on orchestrations and messaging between containers. The proposed AKFA (Adaptive Kernel Firefly Algorithm) is for selecting features for CNM (Cloud Network Monitoring) operations. AKFA methodology is demonstrated using CNSD (Cloud Network Security Dataset) with satisfactory results in the performance metrics like precision, recall, F-measure and accuracy used.

Adaptive Kernel Firefly Algorithm Based Feature Selection and Q-Learner Machine Learning Models in Cloud

CC’s (Cloud Computing) networks are distributed and dynamic as signals appear/disappear or lose significance. MLTs (Machine learning Techniques) train datasets which sometime are inadequate in terms of sample for inferring information. A dynamic strategy, DevMLOps (Development Machine Learning Operations) used in automatic selections and tunings of MLTs result in significant performance differences. But, the scheme has many disadvantages including continuity in training, more samples and training time in feature selections and increased classification execution times. RFEs (Recursive Feature Eliminations) are computationally very expensive in its operations as it traverses through each feature without considering correlations between them. This problem can be overcome by the use of Wrappers as they select better features by accounting for test and train datasets. The aim of this paper is to use DevQLMLOps for automated tuning and selections based on orchestrations and messaging between containers. The proposed AKFA (Adaptive Kernel Firefly Algorithm) is for selecting features for CNM (Cloud Network Monitoring) operations. AKFA methodology is demonstrated using CNSD (Cloud Network Security Dataset) with satisfactory results in the performance metrics like precision, recall, F-measure and accuracy used.

Description and comparison of exam wrapper learning strategy use in baccalaureate and associate degree nursing students: A descriptive study

BackgroundExam wrapper, a structured self-regulated learning strategy, assists students to review study habits and performance on an exam with the goal of improving future study habits. Little is known about the use of this strategy in nursing students, particularly associate degree students. ObjectivesTo describe and compare demographic characteristics, study habits, reasons for getting content wrong on an exam and future study plans between associate degree and baccalaureate nursing students. DesignA cross sectional, descriptive comparative study of exam wrapper use in associate degree and baccalaureate nursing students. SettingsA medium-sized public university and small private college in the northeastern United States. ParticipantsA convenience sample 102 prelicensure baccalaureate (n = 63) and associate degree (n = 39) nursing students. Mean age of 21.9 ± 5.6, GPA of 3.46 ± 0.38, 7% male, 57% commuter students, 75% employed an average of 14 ± 11.4 h per week. MethodsData were collected by course faculty during an in-class exam review following a multiple-choice examination. Students completed a demographic form and exam wrapper that assessed pre-exam study habits, reasons for getting items wrong on an exam and future study habits. ResultsAssociate degree students had lower GPAs (3.19 vs 3.57, p = .000), were older (27 vs 19.2, p = .000), more often commuted (100% vs 31%, p = .000), were employed (95% vs 65%, p < .001), were more likely to study at home (39.5% vs 13.1%, p = .000) and spent significantly longer on each study activity (p = .000) than baccalaureate students. When comparing reasons for getting a question wrong and intended study habits, baccalaureate and associate degree students did not differ. ConclusionsUse of the exam wrapper strategy allows nursing students at all levels of prelicensure education to actively reflect upon their learning with the goal of improving future learning.

Using the LMS for Exam Wrapper Feedback to Prompt Metacognitive Awareness in Large Courses

Exam wrappers, a reflective exercise completed after an exam, are designed to help foster students’ metacognition and self-regulation. Typical exam wrappers ask students how they studied, what they missed and why, and how they would change their study behaviors to improve on the next exam. In small classes, exam wrappers can be administered as paper documents, with instructors providing feedback in writing or through one-on-one appointments. In large classes, however, this approach can be unrealistically time-consuming. In this paper, we describe the design and use in a large introductory chemistry course of an online exam wrapper administered using our institutional learning management system’s test tool. This tool allows the instructor to provide automated, targeted feedback based on students’ responses. We analyzed the effect of this tool on students’ course outcomes and on their metacognitive awareness as measured by the Metacognitive Awareness Inventory (MAI). For first-year students, despite low completion rates of the wrapper, course grade was significantly related to exam wrapper use, independent of several academic variables. MAI scores were not related to exam wrapper use. In this paper, we discuss the effect of multiple metacognitive awareness opportunities provided by the instructor, including the exam wrapper, on students’ performance in the chemistry course. In large courses such as this, the success of this online exam wrapper may depend on providing both incentives for students to complete it and additional support for students to develop the metacognitive awareness to appreciate its value.

Exam Wrapper Use and Metacognition in a Fundamentals Course: Perceptions and Reality.

An exam wrapper is a structured debriefing questionnaire designed to help students understand examination performance and develop improvement strategies. This mixed-methods pilot study sought to examine its impact on students' metacognitive skills in a fundamentals nursing class and to assess student perceptions of its usefulness. Metacognition was assessed using the Metacognitive Inventory for Nursing Students. Quantitative data were analyzed using the nonparametric Friedman test. Qualitative data were taken from four focus groups. Students who used the exam wrapper throughout the semester demonstrated significant improvement in metacognition over time (p = .014). Focus group data revealed that students did not find the exam wrapper to be helpful. The analysis revealed three themes: Reliance on Faculty, Overlap With Established Self-Regulated Learning Strategies, and Difficulty in Answering Exam Wrapper Questions. Although students may not perceive this tool as useful, those who repeatedly used it over time had increased metacognition. [J Nurs Educ. 2019;58(7):417-421.].

Occupancy estimation from environmental parameters using wrapper and hybrid feature selection

Occupancy information is essential to facilitate demand-driven operations of air-conditioning and mechanical ventilation (ACMV) systems. Environmental sensors are increasingly being explored as cost effective and non-intrusive means to obtain the occupancy information. This requires the extraction and selection of useful features from the sensor data. In past works, feature selection has generally been implemented using filter-based approaches. In this work, we introduce the use of wrapper and hybrid feature selection for better occupancy estimation. To achieve a fast computation time, we introduce a ranking-based incremental search in our algorithms, which is more efficient than the exhaustive search used in past works. For wrapper feature selection, we propose the WRANK-ELM, which searches an ordered list of features using the extreme learning machine (ELM) classifier. For hybrid feature selection, we propose the RIG-ELM, which is a filter–wrapper hybrid that uses the relative information gain (RIG) criterion for feature ranking and the ELM for the incremental search. We present experimental results in an office space with a multi-sensory network to validate the proposed algorithms.

Evolutionary computation for feature selection in classification problems

Feature subset selection (FSS) has received a great deal of attention in statistics, machine learning, and data mining. Real world data analyzed by data mining algorithms can involve a large number of redundant or irrelevant features or simply too many features for a learning algorithm to handle them efficiently. Feature selection is becoming essential as databases grow in size and complexity. The selection process is expected to bring benefits in terms of better performing models, computational efficiency, and simpler more understandable models. Evolutionary computation (EC) encompasses a number of naturally inspired techniques such as genetic algorithms, genetic programming, ant colony optimization, or particle swarm optimization algorithms. Such techniques are well suited to feature selection because the representation of a feature subset is straightforward and the evaluation can also be easily accomplished through the use of wrapper or filter algorithms. Furthermore, the capability of such heuristic algorithms to efficiently search large search spaces is of great advantage to the feature selection problem. Here, we review the use of different EC paradigms for feature selection in classification problems. We discuss details of each implementation including representation, evaluation, and validation. The review enables us to uncover the best EC algorithms for FSS and to point at future research directions. WIREs Data Mining Knowl Discov 2013, 3:381–407. doi: 10.1002/widm.1106This article is categorized under: Technologies &gt; Classification Technologies &gt; Computational Intelligence Technologies &gt; Data Preprocessing

Component adaptation for event-based application integration using active rules

Enterprise applications integrate information and applications in a distributed, networked environment to develop a global application of interconnected components and applications. This paper presents the design and implementation of the wrappers generated to adapt components to a middleware environment that employs active rules to build an enterprise application using an event-driven approach to integrating distributed black-box components. The components adapted in this implementation are based on the Enterprise JavaBeans component model. An application integrator declares the components to be integrated, and may define additional attributes, relationships, and events to be used in the integration process. The metadata for the components to be integrated is used to adapt and enhance the black-box components through the use of wrappers. The wrappers act as a proxy to the black-box component. The adaptation of the wrappers provides for the storage of additional properties for component instances and for the detection of events within the components to generate event notifications. The wrappers are automatically generated from the component metadata using the Extensible Stylesheet Language. The design and implementation of the wrappers establishes a framework that supports an active approach to component-based software integration.

Wrapper Maintenance: A Machine Learning Approach

The proliferation of online information sources has led to an increased use of wrappers for extracting data from Web sources. While most of the previous research has focused on quick and efficient generation of wrappers, the development of tools for wrapper maintenance has received less attention. This is an important research problem because Web sources often change in ways that prevent the wrappers from extracting data correctly. We present an efficient algorithm that learns structural information about data from positive examples alone. We describe how this information can be used for two wrapper maintenance applications: wrapper verification and reinduction. The wrapper verification system detects when a wrapper is not extracting correct data, usually because the Web source has changed its format. The reinduction algorithm automatically recovers from changes in the Web source by identifying data on Web pages so that a new wrapper may be generated for this source. To validate our approach, we monitored 27 wrappers over a period of a year. The verification algorithm correctly discovered 35 of the 37 wrapper changes, and made 16 mistakes, resulting in precision of 0.73 and recall of 0.95. We validated the reinduction algorithm on ten Web sources. We were able to successfully reinduce the wrappers, obtaining precision and recall values of 0.90 and 0.80 on the data extraction task.

Providing Security and Interoperation of HeterogeneousSystems

Interoperation and information sharing among databases independently developed and maintained by different organizations is today a pressing need, if not a practice. Governmental, military, financial, medical, and private institutions are more and more required to become part of a distributed infrastructure and selectively share their data with other organizations. This sharing process inevitably opens the local system to new vulnerabilities and enlarges the space of possible threats to the data and resources it maintains. As a complicating factor, in general, data sources are heterogeneous both in the data models they adopt and in the security models by which protection requirements are stated. We present a modeling and architectural solution to the problem of providing interoperation while preserving autonomy and security of the local sources based on the use of wrappers and a mediator. A wrapper associated with each source provides a uniform data interface and a mapping between the source's security lattice and other lattices. The mediator processes global access requests by interfacing applications and data sources. The combination of wrappers and mediator thus provides a uniform data model interface and allows the mapping between restrictions stated by the different security policies. We describe the practical application of these ideas to the problem of trusted interoperation of health care databases, targeted to enforcing security in distributed applications referring to independent heterogeneous sources protected by mandatory policy restrictions. We describe the architecture and operation of the system developed, and describe the tasks of the different components.

The implementation and evaluation of the use of CORBA in an engineering design application

Many computer applications today require some form of distributed computing to allow different software components to communicate. Several different commercial products now exist based on the Common Object Request Broker Architecture (CORBA) of the Object Management Group. The use of such tools, however, often requires the modification of existing systems, rather than the development of new applications. The objective of this research has been to integrate the use of a CORBA tool into an existing engineering design application for the purpose of (1) evaluating the amount of re-engineering that is involved to effectively integrate distributed object computing into an existing application, and (2) evaluating the use and performance of distributed object computing in an engineering domain, which often requires the transfer of large amounts of information. The results of this work demonstrate that CORBA technology can be easily integrated into existing applications. The ease of the integration as well as the efficiency of the resulting system, however, depends upon the degree of modification that developers are willing to consider in the re-engineering process. The most transparent approach to the use of CORBA requires less modification and generally produces less efficient performance. The less transparent approach to the use of CORBA can potentially require significant system modification but produce greater performance gains. This work outlines issues that must be considered for the partitioning of functionality between the client and the server, development of an IDL interface, development of client and server-side wrappers, and support for concurrent, multi-user access. In addition, this work also provides performance and implementation comparisons of different techniques for the use of wrappers and for the transfer of large data files between the client and the server. Performance comparisons for the incorporation of concurrent access are also presented. Copyright © 1999 John Wiley & Sons, Ltd.

Is information security an oxymoron?

Although weaknesses have been demonstrated in some security techniques (encryption, protocols, mobile code such as Java, etc.), current security technology is quite strong in many areas. Despite this, information security has proved difficult to achieve in large modern software systems. Many problems have been reported in which supposedly secure systems have been penetrated and, in some cases, significant damage done. One problem considered is a buffer-overrun attack. The idea called a <wrapper xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> which is a layer of software that logically surrounds a software artifact and enhances the functionality of the artifact in some way, is then discussed. Most proposals for the use of wrappers assume that their presence is transparent to the artifact being wrapped. In other words, the artifact sees its operating environment as unchanged and the artifact does not have to be modified in i order to permit it to be wrapped. Wrappers have been proposed as an approach to dealing with deficiencies in existing systems, deficiencies in security for example. The use of shells as a feasible solution to the problem of security is also considered.</wrapper>

Template-based wrappers in the TSIMMIS system

In order to access information from a variety of heterogeneous information sources, one has to be able to translate queries and data from one data model into another. This functionality is provided by so-called (source) wrappers [4,8] which convert queries into one or more commands/queries understandable by the underlying source and transform the native results into a format understood by the application. As part of the TSIMMIS project [1, 6] we have developed hard-coded wrappers for a variety of sources (e.g., Sybase DBMS, WWW pages, etc.) including legacy systems (Folio). However, anyone who has built a wrapper before can attest that a lot of effort goes into developing and writing such a wrapper. In situations where it is important or desirable to gain access to new sources quickly, this is a major drawback. Furthermore, we have also observed that only a relatively small part of the code deals with the specific access details of the source. The rest of the code is either common among wrappers or implements query and data transformation that could be expressed in a high level, declarative fashion. Based on these observations, we have developed a wrapper implementation toolkit [7] for quickly building wrappers. The toolkit contains a library for commonly used functions, such as for receiving queries from the application and packaging results. It also contains a facility for translating queries into source-specific commands, and for translating results into a model useful to the application. The philosophy behind our “template-based” translation methodology is as follows. The wrapper implementor specifies a set of templates (rules) written in a high level declarative language that describe the queries accepted by the wrapper as well as the objects that it returns. If an application query matches a template, an implementor-provided action associated with the template is executed to provide the native query for the underlying source 1 . When the source returns the result of the query, the wrapper transforms the answer which is represented in the data model of the source into a representation that is used by the application. Using this toolkit one can quickly design a simple wrapper with a few templates that cover some of the desired functionality, probably the one that is most urgently needed. However, templates can be added gradually as more functionality is required later on. Another important use of wrappers is in extending the query capabilities of a source. For instance, some sources may not be capable of answering queries that have multiple predicates. In such cases, it is necessary to pose a native query to such a source using only predicates that the source is capable of handling. The rest of the predicates are automatically separated from the user query and form a filter query . When the wrapper receives the results, a post-processing engine applies the filter query. This engine supports a set of built-in predicates based on the comparison operators =,≠,&lt;,&gt;, etc. In addition, the engine supports more complex predicates that can be specified as part of the filter query. The postprocessing engine is common to wrappers of all sources and is part of the wrapper toolkit. Note that because of postprocessing, the wrapper can handle a much larger class of queries than those that exactly match the templates it has been given. Figure 1 shows an overview of the wrapper architecture as it is currently implemented in our TSIMMIS testbed. Shaded components are provided by the toolkit, the white component is source-specific and must be generated by the implementor. The driver component controls the translation process and invokes the following services: the parser which parses the templates, the native schema, as well as the incoming queries into internal data structures, the matcher which matches a query against the set of templates and creates a filter query for postprocessing if necessary, the native component which submits the generated action string to the source, and extracts the data from the native result using the information given in the source schema, and the engine , which transforms and packages the result and applies a postprocessing filter if one has been created by the matcher. We now describe the sequence of events that occur at the wrapper during the translation of a query and its result using an example from our prototype system. The queries are formulated using a rule-based language called MSL that has been developed as a template specification and query language for the TSIMMIS project. Data is represented using our Object Exchange Model (OEM). We will briefly describe MSL and OEM in the next section. Details on MSL can be found in [5], a full introduction to OEM is given in [1].

Relations Between Fe in Irrigation Water and Leaf Quality of Cigar Wrapper Tobacco1

AbstractDamage, appearing to result from irrigation water, reduced the value of cigar wrapper tobacco (Nicotiana tabacum L.) from about $4.00 per pound to 0.25 in 1969. Dark leaf tips and dark spots over the entire leaf rendered damaged leaves unfit for wrapper use. Leaf analysis indicated that Fe and Mn were associated with the dark coloration.A study was made in 1970 to determine the effect of Fe in irrigation water on quality of cured wrapper tobacco leaves and to find a potential source of Fe contamination of irrigation ponds. Two forms of Fe were added to irrigation water applied to field plots, and Fe content of leaves, leaf quality, and leaf tensile strength were used to evaluate the effects. Soil and organic material were collected from a shallow area of a “problem” pond, after it had been drained, for use in laboratory studies.Damaged tobacco, similar to that observed in commercial fields, was produced in field plots in 1970 when Fe was added to the irrigation water. Laboratory incubation studies showed that pond sediments were a potential source of Fe buildup in irrigation water. Leaf strength decreased with increasing content of Fe in the tissue. A visible coating was produced on green leaves in the greenhouse when 5 and 10 ppm Fe in water were sprayed on the plants.