Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Adaption of Resource Aware Distributed Applications

Dynamic adaptation has become an important issue when designing and developing distributed applications in order to manage their Quality of Service (QoS). This is especially challenging when distributed applications run in environments in which resources vary unpredictably over time. To deal with fluctuations in resource availability and inherent heterogeneity of distributed environments requires dynamic adaptation of each application. This trend motivates the design of resource-aware applications ensuring a given performance level by adapting their behavior to changing contexts. To tune the use of resources, adaptive systems include the necessary mechanisms to modify applications' behavior. This paper presents a general distributed middleware for enabling behavior adaptation of distributed applications. The middleware combines application designer specification of alternative execution behaviors with information about the execution environment context for deciding when and how to adapt itself according to the available resources. A description language specifies applications' behavior and the description of their related resource use. The QoS management requires a common execution model for all applications. Simulations of the QoS management of heterogeneous applications illustrate our proposal and show the benefits. In addition, we discuss lessons learned from our experience.
An improved current mode instrumentation amplifier

A current mode instrumentation amplifier in CMOS technology, is presented. The circuit is based on the use of two second generation positive current conveyors and a current differential output stage. The device exhibits high common-mode rejection ratio which is gain unaffected in a wide frequency band. SPICE simulation results are promising for high frequency medical applications.
Software Architecture: Extending the class structure for intelligent system development

The class structure in object-oriented paradigm where entities encapsulate data and operations into single computational units has made great stride in system development. All objects were seen to have attributes and behaviours as in real life. Intelligent objects in addition to having attributes and behaviours remember their behaviours unlike non- intelligent objects. In this paper the class structure is extended to include "mind" as the third core of the architecture of classes and in extension objects. This extension will improve the architecture of intelligent computing software and ease the implementation of complex artificial learning algorithms.
Topological optimization of computer networks

Modeling, analysis, and design problems and methodologies for centralized and distributed computer-communication networks are discussed. The basic problem is to specify the location and capacity of each communication link within the network. The design objective is to provide a low-cost network which satisfies constraints on response time, throughput, reliability, and other parameters. Fundamental network models for queuing and reliability analysis are described, as are basic properties of various network structures. A number of approaches to the topological design problem are presented; areas where further research is needed are indicated; possible approaches to several unsolved problems are suggested.
ACAFD: Secure and Scalable Access Control with Assured File Deletion for Outsourced Data in Cloud

Cloud storage has emerged as a popular paradigm to outsource data to third party and share it with the collaborators. Wh ile this new paradigm enables users to outsource their sensitive data and reduces data management costs, it brings forth the new challenges to the user to keep their data secure. Data storage security and access control in the cloud is one of the challenging ongoing research works to alleviate the data leakage proble m from unauthorized users. Existing solutions that use pure cryptographic tech niques suffers from heavy computation work with respect to key management and key distribution. Attribute based encryption is an alternative soluti on that map the user access structure with the data file attributes to control the data access. However any of the existing schemes doesn't address the access con trol with assured deletion of the files upon revocation of user access. This arti cle addresses this open issue using a trusted authority that manages the access c ontrol list and takes care of key management and key distribution and file deleti on upon user revocation. The prototype of model has been presented and analyzed the security features over existing scheme.
A novel method based on concept map for expert finding in online communities

Nowadays, online communities or virtual communities on the Internet are one of the most interactive environment in which people can express their opinions freely. There is too amount of information shared in online communities and there is no way to determine its authenticity, this is the most important challenge in the field of knowledge sharing in online communities. Expert finding in the online communities and determine their level of knowledge, can be used to determine the accuracy of posted comments. In this paper a new method for expert finding in online communities based on concept mapping, is presented. In the proposed method, two measures are used. One measure is distance between concepts of user response and concepts of question. Other measure is the number of concepts that are used in the user response. Proposed method is implemented and evaluated on Java Online Communities, and the results showed that the correlation exceeds 0.9.
Changes in vascular plant species composition, top-soil and seed-bank along coppice rotation in an Ostrya carpinifolia forest

Abstract Ostrya carpinifolia forests are formations traditionally managed as coppice, with a high biodiversity that characterizes much of the Italian and Balkan low mountain and hill landscapes. Here, we analyze changes in vegetation, seed-bank, soil and litter at six different stages during the coppicing rotation and after 10 years of abandonment of an Ostrya carpinifolia forest located in the central Apennines. Data show that the dynamism characterizing this coenose during traditional coppice rotation alters after cessation of the management practices. Although from the phytosociological point of view all the forest stands belonged to the same association, the highest biodiversity was achieved in the early stages after cutting. This was ascribed to the canopy removal, which creates favourable conditions for the germination of pre-mantels and mantels species stored in the soil seed-bank, while suitable conditions for the nemoral flora are maintained around the tree stumps. In later years, a reduction of non-strictly forest species and an increase in the relative thicknesses of the more superficial top-soil horizons occurred, reaching the maximum around 18 years after cutting. With the abandonment, simplification of the top-soil morphology, total loss of seed bank viability and increase of open-environments species were observed.
Calculating the Dimensionality of the Brain, and Other Applications of an Optimized Generalized Ising Model in Predicting Brain's Spontaneous Functions

Understanding a system as complex as the human brain is a very demanding task. Directly working with structural and functional neuroimaging data has led to most of the understanding we have gained about the human brain. However, performing only the direct statistical comparisons on the empirical function and the structure does not fully explain the observed long-range functional correlations. Therefore, implementations of mathematical models to gain further understanding of the relationship between the structure and function of the brain is critical. Additionally, spontaneous functions of the brain can only be predicted using computer simulated models; which will be pivotal for studying the patients with accidental brain injuries. Therefore, this research aims to present an optimized computer simulated model not only to further understand the structure-function relationship of the brain, but also to predict the functional changes when anatomy is altered. Based on prior work, 2-dimensional classical Ising model stands out among the other models in modeling the functions of the brain due to its simplicity. Hence, a 2-dimentional Ising model was simulated on a structural connectome (generalized Ising model) that acts as a proxy for the anatomical connectivity in the brain. Simulations allowed the prediction of functional connectivity using the structure, at criticality. It also enabled the introduction of a novel methodology to calculate the “dimensionality” of the brain. Our results showed the dimensionality of a healthy brain is two when it is defined using the information flow in the brain. Further research illustrated the dependency of dimensionality on the diffusion tractography method used to obtain the structural connectome. It was also concluded that an optimized generalized Ising model has to be simulated using a structural connectome generated by deterministic tractography to acquire the best predictions of empirical function. Additional investigations into a more generalized version of the Ising model—Potts model with different number of spin states—illustrated that increasing the number of spin states does not increase the predictability. It also supported the hypothesis that the model could be simulating the digi-
FashionAsk: A Multimedia based Question-Answering System

We demonstrate a multimedia-based question-answering system, named FashionAsk, by allowing users to ask questions referring to pictures snapped by mobile devices. Instead of asking verbose questions to depict visual instances, direct pictures are provided as part of the question. The signicance of our system is that (1) our system is fully automatic such that no human expert is involved; (2) and we bypass the requirement of the name for the object under query, which is mostly unknown to the asker. To answer these multi-modal questions, FashionAsk performs a large-scale instance search and metadata pooling to name the instance under query, and then matches with similar questions from communitycontributed QA websites as answers. This demonstration is conducted on a million-scale dataset of Web images and QA pairs in the domain of fashion products. Asking a multimedia question through FashionAsk can take as short as ve seconds to retrieve the candidate answer as well as suggested questions.
Development of a Tool for Simplified Web Service Cooperation and Its User Adaptation

Today, while information to be processed by computers is rapidly increasing, user activities on the Internet have been more diverse and services there have been more dynamic. Furthermore, search engines, infrastructures of the page based Web, are getting poor in scooping massive useful information behind superficial information on the Web, which is known as the problem of the Deep Web. Meanwhile, Web services, which can be invoked by standardized procedures , provide efficient access to dynamic information on the Web and can satisfy diverse user needs with composition. Therefore, composing public web services according to user's intent realizes diverse user needs on the dynamic Web. Automatic or semi-automatic composition of web services requires knowledge base on services and user's goal. When dealing with a wide area such as the Web, preparing cost of this knowledge base becomes much larger. To cope with this problem of preparing cost of knowledge base, this research proposes an approach that acquires knowledge on services from accumulation of activities of many users using visual programming on the Web and acquires user's goal from web browsing histories and correlates them. However, there are following problems to realize such a service composition against diverse web services. Descriptiveness and operability of visualization models When diverse services are produced because of composition, it is required to understand the functions of services enough and operate them by relying on an visual expression of composite services. However, in function unit level visu-alization of existing web service composition environments, it is hard to understand detailed functions of services and manipulate them. Correlation of web browsing histories and services When recommending diverse services to users, it is difficult to correlate web services with web browsing histories from the metadata of existing web service composition environments. It is required to correlate them with web browsing histories lowering the cost of annotating the metadata as less as possible. ii Against the former issue, the author proposed a web service composition model: the Patchwork model and its interface which visualizes individual input/output units instead of functional units. The Patchwork model is the one whose basic components are patches (operational units), ports (input/output units), and port links (dataflows). As a result of development of a tool based on the proposed model and putting it into effect on the Internet, over 460 diverse web services have been produced composing existing web services and validity of the model and …
Best Combination of Machine Learning Algorithms for Course Recommendation System in E-learning

Data Mining is the extraction of hidden predictive information from large database which can be used in various commercial applications like bioinformatics, Ecommerce etc. Association Rule, classification and clustering are three different algorithms in data mining. Course Recommender System plays an important role in identifying the behavior of students interested in particular set of courses. We collect the data regarding the course enrollment for specific set of data. For collecting this data, we use the learning management system like Moodle. After collecting the data, we apply the different combination of data mining algorithm like classification & association rule algorithm, clustering & association rule algorithm, association rule mining in classified & clustered data, combining clustering & classification algorithm in association rule algorithms or simply the association rule algorithm. Here in this paper we use ADTree classification algorithm, Simple K-means Algorithm & Apriori Association Rule algorithm as different machine learning algorithm. So we propose the five different methods to find the best combination of algorithm in recommending the courses to students in E-learning. We compare the result of this combined approach as well as only the association rule algorithm & present the best combination of algorithm for recommendation of courses in E-learning according to our simulation.
A hybrid genetic algorithm for optimal reactive power planning based upon successive linear programming

A hybrid methodology is presented for the solution of the problem of the optimal allocation of reactive power sources. The technique is based upon a modified genetic algorithm, which is applied at an upper level stage, and a successive linear program at a lower level stage. The objective is the minimization of the total cost associated to the installation of the new sources. The genetic algorithm is devoted to defining the location of the new reactive power sources, and therefore to handle the combinatorial nature of the fixed costs problem. At the lower level, the variable cost problem is solved by calculating the magnitude of the sources to be installed at the previously determined locations by means of a linear program iterated successively with a fast decoupled load flow. Results are presented for the application of the proposed methodology when applied to the Venezuelan electric network.
Investigating Student Engagement in First-Year Biology Education: A Comparison of Major and Non-Major Perception of Engagement Across Different Active Learning Activities

Educational techniques that improve student engagement have repeatedly been shown to improve performance at the class level at many institutions and in multiple disciplines. However, knowledge of engagement in individual activities in large first-year classes, where there may be several sub-populations of students in different programs reflecting varied interests, is limited. In this study, we examined two large, lecture-based, introductory first-year biology classes to determine whether there were any relationships between specific learning activities and student engagement and performance, both at the class level and as broken down by program of study. Surveys were used to quantify the level of student engagement through four activities: (a) student response systems (clickers), (b) in-class discussions and activities, (c) lab and seminar activities, and (d) interdisciplinary learning. Engagement scores were then compared to students’ final grades. Students in all majors who reported higher levels of participation in most activities studied also reported feeling more engaged overall and achieved higher grades than their less-engaged peers; however, students in non-biology majors demonstrated notably weaker relationships between their engagement and performance in biology courses, where such relationships existed at all. In this paper, we discuss the learning activities which are associated with the greatest performance increases in both biology and non-biology majors and suggest how these results may be used to inform instructional techniques to benefit all students, regardless of major, in future course offerings.
A characterization of robust SPR synthesis for systems with l_p parametric uncertainty

The filter synthesis problem for robust strict positive realness (RSPR) of systems with lp parametric uncertainty is addressed. A general characterization of the solutions of the RSPR problem in this framework is derived. The proposed characterization is then exploited in order to devise synthesis procedures which yield polynomial or rational filters of bounded degree with guaranteed SPR robustness margin in the l2, l∞, and l1 cases.
Efficient multi-tone distortion analysis of analog integrated circuits

This paper introduces a novel approach to analyze distortion behavior in analog integrated circuits using a nonlinear frequency-domain method. This approach circumvents the difficulties and inaccuracies associated with device modeling required for the traditional Volterra series method and can handle circuits operating in more strongly nonlinear regimes. The efficiency of the method renders the analysis of large analog blocks practical. We present examples of multi-tone distortion analyses of industrial amplifiers and continuous time filters. The trend towards higher levels of integration, particularly for wireless applications, renders this method especially useful.
A COMPARISON BETWEEN SINGLE AND MULTI- CAMERA SWIMMING RACE ANALYSIS SYSTEMS

This study compared the reliability of single and multi-camera race analysis systems. Thirteen swimmers were analysed during 25 different swims using two methods of data collection. The parameters selected for further investigation were start time, average swim velocity, average stroke rate, average stroke length and turn time. Mixed modelling was used to compare the mean differences and amount of random error of each system in between swims. Some differences between the means of each parameter exist, however the only meaningful difference was 1 st turn time (0.21 s difference). There were also errors associated with both systems particularly with turn times and average velocity. This study reveals that a single camera analysis system is just as accurate as a multicamera system.
Oracle SQL*Loader: The Definitive Guide

From the Publisher: SQL*Loader is a ubiquitous tool in the Oracle world. It has been shipped with Oracle since at least Version 6 and continues to be supported and enhanced with each new version of Oracle, including Oracle8 and Oracle8i. The job of SQL*Loader is to load data from flat files into an Oracle database. It's optimized for loading large volumes of data, and is flexible enough to handle virtually any input format. Almost every Oracle user has to use SQL*Loader at one time or another, and DBAs are frequently called upon to load data for the users in their organization. Despite SQL*Loader's wide availability and usage, few DBAs and developers know how to get the most out of it. Oracle SQL*Loader: The Definitive Guide has everything you need to know to put SQL*Loader to its best use: an introduction to SQL*Loader, a reference to all of its syntax options, and most importantly, step-by-step instructions for all the SQL*Loader tasks you'd want to performand maybe some you didn't realize you COULD perform. You'll learn how to construct the necessary control files and load from different types of files containing different types of data (e.g., fixed-width data, delimited data, and data of various datatypes). You'll also learn how to validate data, load it selectively, transform it as it is loaded, and recover after failure. This book explains how to optimize SQL*Loader performance by adjusting the transaction size and using the new direct path option. It also covers the newest SQL*Loader featuresthe loading of large object (LOB) columns and the new object types (nested tables, varying arrays, and object tables). Oracle SQL*Loader: The DefinitiveGuide is an indispensable resource for anyone who is new to SQL*Loader; a task-oriented learning tool for those who are already using it; and a quick reference for every user. If you want to take best advantage of an essential Oracle tool, you need this book.
Type Synthesis of Six-DOF Wrist-Partitioned Fully Parallel Manipulators

A six-DOF wrist-partitioned fully parallel manipulator is a parallel manipulator in which three of the six actuated joints are used to control the position of a point on the moving platform while the other three are further used to control the orientation of the moving platform. Such parallel manipulators are in fact the parallel counterparts of the wrist-partitioned serial manipulators, which are widely used in industry. Unlike parallel manipulators of a general structure, a six-DOF wrist-partitioned fully parallel manipulator usually has simple kinematic characteristics such as its forward displacement analysis and singularity analysis are easy to solve. This paper deals with the type synthesis of six-DOF wrist-partitioned fully parallel manipulators. An approach is first proposed for the type synthesis of this class of parallel manipulators. Using the proposed approach, six-DOF wrist-partitioned fully parallel manipulators can be constructed from the types of three-DOF non-overconstrained spherical parallel manipulators. A large number of six-DOF wrist-partitioned fully parallel manipulators are then obtained, and several types of practical relevance are also identified.Copyright © 2007 by ASME
The synchronization of chaotic systems applying the parallel synchronization method

In this paper, we present a novel synchronization method for chaotic systems—the so-called parallel synchronization method. The proposed technique provides a condition whereby an optimal control problem can be applied in order to achieve active control whenever we use an active control strategy for synchronization. In this way, by transforming the synchronization problem to an optimal control problem, we can define an appropriate error function such that by minimizing it while the active control is obtained, the synchronization error approaches zero. Some different chaotic systems are considered for synchronization, and the numerical simulations are presented graphically to confirm the validity of the proposed method.