Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling Complexity: Analysing Between-Individual and Between-Place Variation—A Multilevel Tutorial

Geography is centrally concerned with difference and heterogeneity, yet much quantitative modelling has been concerned with finding average or general relationships thereby relegating variability to a single catchall ‘error’ term. Multilevel modelling, in contrast, anticipates complex between-individual and between-place heterogeneity. Previous accounts of the approach have stressed the modelling of higher level, between-place differences, but here the emphasis is placed on the simultaneous consideration of complex variation at all levels. A parade of models is presented each of which considers a particular facet of the model specification. Attention is drawn to the important contrasts between the modelling of categorical and continuous predictors. Illustrative results are provided for variations in British house prices, modelled with the MLn software. An appendix provides an example of the use of this software.
IMPLEMENTAÇÕES PARALELAS PARA FECHO TRANSITIVO

The computation of the transitive closure of a graph is an problem that was first considered in 1959. Many sequential algorithms for solving this problem have been proposed and parallel algorithms have been considered since 1990. We present a parallel algorithm for computing the transitive closure in general graphs (oriented or not). The proposed algorithm uses the BSP/CGM model, based on the use of breadth-first search in graphs (BFS). We present three parallel implementations based on the BFS algorithm: one for MPI, one for OpenMP and one hybrid (MPI/OpenMP). To evaluate the efficiency of the algorithm and developed implementations, experiments were performed with graphs of different sizes and characteristics. The computational complexity of the algorithm is O( n 2 p (n+m)).
Performance of multilayer neural networks in binary-to-binary mappings under weight errors

The probability of misclassification error of a multilayer neural network used in binary-to-binary mappings is derived. The connection weights, determined through training, are assumed to be subject to an additive, random, normally distributed error. The probability of misclassification is derived through simulation. The simulation results and the theoretical results are shown to match very closely. The results give predictability to neural network performance and allow for changing neural network design parameters, such as weight vectors and number of nodes, in order to obtain a certain tolerance to weight errors. <<ETX>>
A comparative approach to the implementation of drug pedigree discovery systems

As the use of RFID technology penetrates and reforms the supply-chain industry, standards are being produced at all levels of the RFID technology spectrum, ranging from hardware to software. The Electronic Product Code (EPC) standard uniquely identifies RFID-tagged products. An application that supports the usage of EPCs is an Electronic Drug Pedigree (E-Pedigree), which is a historical record that indicates the chain of custody of a particular drug product being passed from one supply-chain partner to another. In order to fully implement track-and-trace of pharmaceutical products, software systems need to be built so that pedigree documents can be effectively stored and searched. In this Thesis, two approaches that address the issue of pedigree document discovery are presented-one centralized, one decentralized. The centralized pedigree discovery service extracts metadata from pedigree documents submitted to a centralized server and uses them in a search engine, such as Google Base, to located desired documents that match client queries. The decentralized service allows pedigree documents to be stored locally by individual business owners. Each local server is attached to a Discovery Service Unit containing metadata of local pedigree documents, and these units communicate with each other to form a network. Both approaches are implemented as Web Services. Thesis Supervisor: John R. Williams Title: Associate Professor, Director of MIT Auto-ID Labs Thesis Supervisor: Abel Sanchez Title: Research Scientist, Laboratory of Manufacturing and Productivity
An API for Dynamic Partial Evaluation under DynamoRIO

Dynamic optimization systems have available runtime (dynamic) data and can cross more boundaries than traditional static optimization systems in the pursuit of program transformations. However, dynamic optimization systems are limited by the fact that any time spent in analysis or transformation is included in the running time of the program; thus any transformations must not only improve the performance of the program, but also make up for the time spent in analysis. Interpreters in general confound current heuristics for dynamic optimization. In previous work, the dynamic optimization system DynamoRIO was extended with DynamoRIO-with-Log-PC to address this issue by maintaining extra state; this thesis generalizes the additions made by DynamoRIO-with-Log-PC and develops a useful API for a wider range of programs running under the DynamoRIO system. Thesis Supervisor: Gregory T. Sullivan Title: Research Scientist Thesis Supervisor: Saman Amarasinghe Title: Associate Professor
Integrated Data and Recovery: The UC CEISMIC Federated Archive

The UC CEISMIC Canterbury Earthquakes Digital Archive was built following the devastating earthquakes that hit the Canterbury region in the South Island of New Zealand from 2010 – 2012. 185 people were killed in the 6.3 magnitude earthquake of February 22 nd 2011, thousands of homes and businesses were destroyed, and the local community endured over 10,000 aftershocks. The program aims to document and protect the social, cultural, and intellectual legacy of the Canterbury community for the purposes of memorialization and enabling research. The nationally federated archive currently stores 75,000 items, ranging from audio and video interviews to images and official reports. Tens of thousands more items await ingestion. Significant lessons have been learned about data integration in post-disaster contexts, including but not limited to technical architecture, governance, ingestion process, and human ethics. The archive represents a model for future resilience-oriented data integration and preservation products.
Logiciel NotaBene pour l'annotation linguistique. Annotations et conceptualisations multiples

Resume Nous presentons le logiciel libre NotaBene. Il s’agit d’un logiciel destine principalement a l’annotation linguistique de ressources textuelles ecrites en ancien francais, mais dont les principes se veulent suffisamment generiques pour servir a l’exploitation d’autres types de ressources et eventuellement dans d’autres disciplines. NotaBene est base sur des standards (XML, RDF et OWL) et permet l’affichage simultane d’analyses de nature differentes (p. ex. : lemmatisations vs arbres syntaxiques ou de progression thematique) ou simplement concurrentes (effectuees par deux chercheurs differents). Le logiciel permet egalement a chaque utilisateur de definir son propre modele d’annotation et son jeu d’etiquettes personnalise. Le modele est enregistre de maniere formalisee pour permettre les echanges et les traitements automatiques. Mots cles LINGUISTIQUE, VISUALISATION MULTIPLE, ONTOLOGIES, RDF, LOGICIEL LIBRE
Visible Light Communication

: Visible light Communication (VLC) creates technology revolution in network sector. In this technology, visible light is used to transmit or receive data. In this paper, OOK [ON-OFF keying] modulation is used to send and receive data's using LED lights and the audio signal is transmitted through 1W LED and received by solar cell and the played in loudspeaker. It does not require front end and receiver end antenna and any light emitting devices with faster switching rates can be converted into internet modem with small integrated chip. It has very wide range of applications apart from the internet such as traffic management and places where RF radio waves are restricted.
An Analytical Review on Load Balancing Heuristic Approach and Related Issues in Manets

Ad hoc networks have gained more attention of researchers/ academicians last decades, with the proliferation of mobile processing platforms and small sized wireless equipment. Mobile ad hoc network consists of freely moving nodes responsible of not only forwarding packets for other nodes but also perform computations. Routing in such networks is very challenging and difficult due to mobility of nodes. Therefore, in such networks imbalance of loads over the nodes can occur. This paper, analyzed security and routing techniques involved in packet forward along with balancing the load with the best possible scheme (heuristic approach).
FLEXnav: Fuzzy Logic Estimation for Mobile Expert Rule-based Position Robots on Rugged Terrain

AESTRACT Most mobile robots use a combination of absolute and relative sensing techniques for position estimation. Relative positioning techniques are generally known as deadreckoning. Many systems use odometry as their only dead-reckoning means. However, in recent years fiber optic gyroscopes have become more affordable and are being used on many platforms to supplement odometry, especially in indoor applications. Still, if the terrain is not level (i.e., rugged or rolling terrain), the tilt of the vehicle introduces errors into the conversion of gyro readings to vehicle heading. In order to overcome this problem vehicle tilt must be measured and factored into the heading computation. This paper introduces a new Fuzzy Logic Expert rulebased wiga t ion (FLEXinav) method for fusing data from multiple lowto medium-cost gyroscopes and accelerometers in order to estimate accurately the heading and tilt of a mobile robot. Experimental results of mobile robot runs over rugged terrain are presented, showing the effectiveness of our FLEXnav method.
Effective Secure Storage and Retrieve In Cloud Computing

In Cloud computing, user can remotely store and retrieve their data based on-demand service, without the burden of local data storage and maintenance. However, the protection of the confidential data processed and generated during the computation is becoming the major security concern. The main objective of cloud computing enables customers with limited computational resources to outsource their large computation workloads to the cloud, and economically enjoy the massive computational power, bandwidth, storage, and even appropriate software that can be shared in a pay-per-use manner. The main concern of this paper is optimal storing, retrieval of data with effective security in cloud computing. The proposed methodology suggests the encryption of the files to be uploaded on the cloud. The integrity and confidentiality of the data uploaded by the user is ensured doubly by not only encrypting it but also providing access to the data only on successful authentication. The proposed system takes care of data security while it is in transit and also has mechanisms to support verification of data for correctness.
The Cart-Pole Experiment as a Benchmark for Trainable Controllers

It is widely believed that balancing an inverted pendulum is a difficult nonlinear control task. Many researchers have used a variant of the inverted pendulum problem, the cart-pole, for demonstrating the success of their neural network learning methods. It has been known for a long time that a linear control law, implemented by a single artificial neuron, can control the cart-pole. Not noted before was that a random search in weight space can quickly uncover coefficients (weights) for controllers that work over a wide range of initial conditions. This result indicates that success in finding a satisfactory neural controller is not sufficient proof for the effectiveness of unsupervised training methods. By analysing the dynamics of the linear controller we reformulate the cart-pole problem to make it a more stringent test for neural training methods. A review of the literature on unsupervised training methods for cart-pole controllers shows that the published results are difficult to compare and that for most of the methods there is no clear evidence of better performance than the random search method.
The Kernel Two-Sample Test for Brain Networks

In clinical and neuroscientific studies, systematic differences between two populations of brain networks are investigated in order to characterize mental diseases or processes. Those networks are usually represented as graphs built from neuroimaging data and studied by means of graph analysis methods. The typical machine learning approach to study these brain graphs creates a classifier and tests its ability to discriminate the two populations. In contrast to this approach, in this work we propose to directly test whether two populations of graphs are different or not, by using the kernel two-sample test (KTST), without creating the intermediate classifier. We claim that, in general, the two approaches provides similar results and that the KTST requires much less computation. Additionally, in the regime of low sample size, we claim that the KTST has lower frequency of Type II error than the classification approach. Besides providing algorithmic considerations to support these claims, we show strong evidence through experiments and one simulation.
Secure Single Sign-On using CAS and OpenID

As the number of connected applications increases, user convenience makes them use the same password, which can create vulnerabilities in an organization’s infrastructure. Therefore, those with security concerns regarding these activities, conducted in the electronic environment, came to support the idea of ​​Single Sign-On systems, having the user in mind. This concept facilitates the authentication process to various resources available on the Internet, or locally, using a single pair of credentials, only once, so it makes the „one for all” password, the method of writing passwords on post-it’s glued to the monitor , or keeping them stored in unsecured text files, sent into oblivion. This paper aims to make a comprehensive analysis of the infrastructure of security and authentication systems on the market. On the other hand, the project presents the implementation of several open source solutions such as OpenID, NTLM in PHP or the Central Authentication Service. For the application that uses OpenID an online store that has an administration page, to which access is restricted using OpenID credentials, was further secured by filtering these IDs in a MySQL database to prevent access to anyone having a valid OpenID credential. For the demonstration of NTLM enabled SSO, another website is used in which access has been blocked to a page. For accessing the page, a valid Windows authentication credential is required. Both the online-shop and demonstration site for NTLM are written in PHP. In addition, the systems using them are implemented also using PHP. For implementing the CAS demo, two Tomcat servlets have been used for demonstration purposes, additional filtering being done by an ApacheDS server.
SCPS: A Social-Aware Distributed Cyber-Physical Human-Centric Search Engine

Advances in ubiquitous sensing, computing and wireless communication technologies are leading to the development of cyber-physical systems (CPS), which promise to revolutionize the way we interact with the physical world. CPS applications, such as healthcare monitoring, may involve many users and objects scattered over a wide area. One critical function of CPS is object search in the physical world through the cyber sphere that enables interaction between the cyber and physical spheres. Some of the previously proposed physical object search engines use RFID tracking, and others collect the information of object locations into a hierarchical centralized server. The difficulty of widely deploying RFID devices, the centralized search, and the need for periodical location information collection prevent CPS from achieving higher scalability and efficiency. To deal with this problem, we propose a Social-aware distributed Cyber-Physical human-centric Search engine (SCPS) that leverages the social network formed by wireless device users for object search. Without requiring periodical location information collection, SCPS locates objects held by users based on the routine user movement pattern. Moreover, using a social-aware Bayesian network, it can accurately predict the users' locations even at the occurrence of exceptional (i.e., non-routine) events (e.g., raining) that break user movement pattern. Thus, SCPS is more advantageous than all previous social network based works which assume that user behaviors always follow a certain pattern. Further, SCPS conducts the search in a fully distributed manner by relying on a distributed hash table (DHT) structure. As a result, SCPS achieves high scalability, efficiency and location accuracy. Extensive real-trace driven simulation results show the superior performance of SCPS compared to other representative search methods including a hierarchical centralized method, a decentralized method, and two social network based methods. The results also show the effectiveness of different components of SCPS.
Obsługa asynchronicznego przepływu danych w komponentowych podsystemach percepcji robotów

Handling of asynchronous data flows in complex computational systems such as robot sensor subsystems requires appropriate tools facilitating their implementation. The article proposes a solution to the aforementioned problem. The solution enables the activation of a conditional behaviour of the individual computational blocks, depending on the presence of data in their input buffers. Theoretical considerations led to the implementation of these mechanisms in a component-oriented framework for development of diverse robot perception subsystems: DisCODe. Operation of the solution is illustrated in two simple exemplary tasks.
The Adaptive Network Coding-Routing (ANCR) Based on Graph Minors for Multicast Networks

The multicast wireless network, where a source needs to deliver packets of data to a set of destination through a group of relays over a network topology, is degraded by a limited bandwidth and capacity regime. Network throughput can be improved using network coding. However, the network coding might or might not be helpful to increase throughput due to an unpredictable network topology. In this paper, we propose an adaptive network coding-routing (ANCR) algorithm to automatically select whether a packet can construct a network code at a relay node before forwarding to destination or not based on the minor of network graphs. If there is no an appropriate packet, the relay will forward a data packet using routing protocol. The results show that this technique can significantly improve both throughput and timeslot usage. The throughput gain at a bottleneck relay node is increased by 35%, while the timeslot usage is decreased for more than 30%.
Sparse Signal Recovery via a Pruning-based Tree Search

In this paper, we propose a sparse signal reconstruction method referred to as the matching pursuit with a pruning-based tree search (PTS-MP). Two key ingredients of PTS-MP are the pre-selection to put a restriction on columns of the sensing matrix to be investigated and the tree pruning to eliminate unpromising paths from the search tree. In our simulations, we confirm that PTS-MP is effective in recovering sparse signals and outperforms conventional sparse recovery algorithms
Development, Characterization and Transferability of Peach Genic SSRs to some Rosaceae species

Aims: The present study was carried out to extract expressed sequence tags-simple sequence repeats (EST-SSRs) for peach (Prunus persica L.) and to study their transferability across some Rosaceae species such as apricot, apple, rose and strawberry. Study Design: Cross-transferability check of Prunus EST-SSRs to some Rosaceae species. Place and Duration of Study: Sample: Department of Biotechnology, Dr Y. S. Parmar University of Horticulture and Forestry, Nauni, Solan-173230, Himachal Pradesh, India, between January 2012 and November 2012. Methodology: SSRs were identified in EST sequences using SSR Identification Tool (SSRIT) and PRIMER3 software was used to design primers which were used to carry out PCR. Data generated by PCR for all the genotypes was used to calculate transferability of Prunus persica EST-SSRs to other Rosaceae species under study. Data analysis was done through NTSYSpc Version 2.02h by creating dendrograms in all the species under study. Original Research Article Kaur et al.; AIR, 3(2): 165-180, 2015; Article no.AIR. 2015.013 166 Results: 2000 EST sequences were downloaded from the National Centre for Biotechnology Information (NCBI) web site. Sequences were assembled into contigs and singletons. 124 sequnces were found to contain SSRs using SSRIT. Out of these 43 were used for primer designing using PRIMER3 software which were custom synthesized and used for polymorphism study in six genotypes of peach. Thirty-eight primers showed scorable amplification, 20 being polymorphic. These 20 polymorphic primers of peach were then further used to carry out transferability studies in apricot, apple, rose and strawberry revealing 50%, 95%, 95% and 45% transferability, respectively. Dendrograms were generated using NTSYS ver.2.02h. The coefficient values were found to range from 0.483 to 0.711 in six peach genotypes and 0.451 to 0.975 in all 22 genotypes under study. Conclusion: Thus it can be concluded from the present study that ESTs of peach produce high polymorphism in different Rosaceous species, indicating their cross-transferability to different members of Rosaceous family.
Analysis of Software Release Problems Based on Fault Detection and Correction Processes

Grant sponsor: State Key Laboratory of Software Development Environment (SKLSDE-2013ZX-12); Aeronautical Science Foundation of China (20121951021) Abstract-In this paper, the modeling of fault-correction process from the viewpoint of correction time is first discussed. By proposing a new cost model, further analysis on the optimal release time determination is presented, which is also based on the model incorporating both fault detection and correction processes. The experiment results show it is more suitable to the reality. Finally, we propose a new solution to the assignment of testing resource. The approach is also illustrated with an actual data set from a software development project. Index Terms fault detection process, fault correction process, cost model, optimal release time
Approaching plWordNet 2.0

The Polish Wordnet, plWordNet, has been in steady development for five years. We are building it from scratch, all the time making provisions for its general compatibility with the other major wordnets. We are very close to reaching a milestone of 100000 lexical units in 70000 synsets. In addition to a fairly comprehensive coverage of common nouns, there already is in plWordNet a significantly built-up verb component, and a similarly enlarged adjective component is under construction. We present the background, the assumptions, the relation set (essential for any wordnet, and central for our inflectionand derivation-rich language) and the current state of the project, and we map the near future.