Training structures have been defined as the order and arrangement of baseline conditional discriminations within stimulus equivalence training. The three training structures most often used are, linear (trains A:B and B:C discrimination), many-to-one (trains B:A and C:A discriminations) , and one-to-many (trains A:B and A:C discriminations). Each training structure trains a different set of simultaneous and successive discriminations that are then needed in the test for derived relations (symmetry, reflexivity, transitivity, and symmetrical transitivity). The present experiment seeks to extend the research on stimulus equivalence training structures by using a within-subject design and adult human subjects. Three sets of 9 arbitrary stimuli were trained concurrently each with a different training structure. From the beginning, training and testing trials were intermixed. The likelihood of producing stimulus equivalence formation was equal across structures.

Non-inferiority tests are well developed for randomized parallel group trials where the control and experimental groups are independent. However, these tests may not be appropriate for assessing non-inferiority in correlated one-to-many matched data. We propose a new statistical test that extends Farrington-Manning’s (FM) test to the case where many (≥1) control subjects are matched to each experimental subject. We conducted a Monte Carlo simulation study to compare the size and power of the proposed test with tests developed for clustered one-to-one matched pair data and tests based on generalized estimating equations (GEE). For various correlation patterns, the sizes of tests developed for clustered matched pair data and GEE-based tests are inflated when applied to the case where many control subjects are matched to each experimental subject. The size of the proposed test, on the other hand, is close to the nominal level for a variety of correlation patterns. There is a debate in the literature regarding whether or not statistical tests appropriate for independent samples can be used to assess the statistical significance of treatment effects in propensity-score matched studies. We used Monte Carlo simulations to examine the effect on assessing non-inferiority via risk difference when a method for independent samples (i.e. FM test) is used versus when a method for correlated matched samples is used in propensity-score one-to-many matched studies. If propensity-score matched samples are well-matched on baseline covariates and contain almost all of the experimental treated subjects, a method for correlated matched samples is preferable with respect to power and Type I error than a method for independent samples. Sometimes there are more experimental subjects to choose from for matching than control subjects. We conducted a Monte Carlo simulation study to compare the size and power of the previously mentioned tests when many (≥1) experimental subjects are matched to each control subject. In this case, the Nam-Kwon test for clustered data performs the best in controlling the type I error rate for a variety of correlation patterns. Therefore, the appropriate non-inferiority test to use for correlated matched data depends, in part, on the sample size allocation of subjects.

Implementing an effective social media marketing strategy campaign to engage customers and increase sales is a challenge for owners of small retail business owners The purpose of this multiple case study was to explore the social media marketing strategies owners of small retail businesses used to increase sales. The conceptual framework for this study was the social media marketing strategy theory. Data were collected from 5 small retail business owners in North Carolina through semistructured, face-to-face interviews and a review of company documents, websites, and social media sites. Data analysis through Yin's 5-step process of compiling, disassembling, reassembling, interpreting, and concluding data resulted in 3 emergent themes: social media engagement strategy, outsourcing strategy, and target market strategy. Owners of small retail businesses might benefit from the findings of this study to increase sales by understanding how to integrate a mix of social media marketing platforms, improve customer engagement, use third-party social media experts to improve advertising, and target customers using social media. The implications of this study for positive social change include the potential for small business owners to increase job opportunities, lower local unemployment rates, and improve local economic growth and stability.

Dans cette thèse, nous proposons une méthodologie de conception d’architectures de communication dédiées aux réseaux de capteurs basées sur la technique de radio impulsionnelle pour les transmissions ultralarge bande (ULB). La technique impulsionnelle proposée ici repose sur la modulation de forme d’impulsion. L’approche de conception architecturale présentée dans cette thèse se focalise plus particulièrement sur la forme des impulsions et leur génération, qui revêt un intérêt majeur puisqu’elle constitue le support de l’information échangée. L’étude sur le choix de la forme d’impulsion nous a conduit à proposer deux architectures différentes. Une première architecture repose sur les polynômes orthogonaux, et plus particulièrement sur les polynômes d’Hermite, pour la génération des impulsions, et sur une architecture de corrélation pour la détection et la reconnaissance des trains d’impulsions transmis. La deuxième architecture est basée sur la transformée en paquets d’ondelettes discrète et peut être exploitée selon deux modes d’utilisation différents, mono et multiutilisateurs. L’utilisation d’une architecture de synthèse à l’émission et d’analyse à la réception ouvre une nouvelle orientation pour les communications numériques, permettant à la transformée en ondelettes d’assurer à la fois la génération des impulsions à l’émission et leur reconnaissance à la réception. Un intérêt immédiat de la technique proposée permet notamment de faciliter l’accès multiutilisateurs au canal ultralarge bande, et d’autoriser des communications simultanées (Many-to-one, des nœuds vers le puits) ou du broadcast (One-to-many, du puits vers les nœuds) sans surcharger la couche MAC. L’architecture proposée s’inscrit donc à l’interface des couches PHY et MAC et permet de relâcher les contraintes de conception spécifiques à ces couches / In this thesis, we propose a design methodology for communication architectures dedicated to wireless sensor network based on impulse radio techniques for UWB communications. The impulse technique proposed in this work relies on pulse shape modulation. The architecture design approach proposed in this thesis focuses on pulses shape and their generation, which is of major interest as it constitutes the carrier of the information exchanged. The study on the choice of pulse shape led us to propose two different architectures. The first one is based on orthogonal polynomials, more especially on the Hermite polynomials, for impulse generation, and on a correlation architecture for detection and recognition of transmitted impulses. The second architecture is based on discrete wavelet packet transform and can be used according two different modes, mono and multi-users. The use of both synthesis and analysis architectures for emitter and receiver, respectively, offers a new way for digital communications and allows the wavelet transform to ensure the impulses generation on the transmitter and their recognition on the receiver. A major interest point of the proposed technique is to facilitate the multi-users access to the ultra-wideband channel and to allow simultaneous communications (many-to-one, from the sensors to the sink) or broadcast (one-to-many, from the coordinator to the nodes) but without overloading the MAC layer. Hence, the proposed architecture is part of the interface between both PHY and MAC layers, and allows to release their specific design constraints

Dans cette thèse, nous présenterons une architecture de communication multi-utilisateurs à base des réseaux de capteurs sans fil dans un environnement industriel fortement bruité. Deux modes de fonctionnement de cette architecture sont présentés ; un mode Many-To-One reliant plusieurs capteurs émetteurs à un seul récepteur et un mode One-To-Many reliant un émetteur à plusieurs capteurs récepteurs. La couche physique de ce système est basée sur une modulation par transformée par paquets d'ondelettes inverse (IDWPT) à l'émission et une transformée par paquets d'ondelette discrète (DWPT) en réception. Pour tester notre architecture, un modèle de canal industriel est proposé qui tient compte des phénomènes des multi-trajets et des évanouissements en plus du bruit additif. Ce dernier étant modélisé comme un bruit gaussien auquel s'additionne un bruit impulsionnel causant une dégradation significative des signaux. L'architecture est testée pour différentes configurations de communications sans fil et pour différentes formes d'ondelettes afin de proposer un mode de communication optimal. Aussi, une amélioration de la robustesse de notre système est effectuée en ajoutant un codage correcteur d'erreur du canal et un seuillage du bruit impulsionnel à la réception pour minimiser les effets du bruit industriel sur les signaux reçus. En utilisant un code correcteur d'erreur, la détection et reconstitution des signaux se fait sans erreur à partir d'un SNR de 8dB pour un taux de codage 1/4 pour une transmission sur à canal à évanouissement. Pour un récepteur optimal à base du seuillage du bruit, les performances en termes de taux d'erreur binaires sont améliorées de 10dB pour une transmission sur un canal à bruit industriel. Enfin, une comparaison de la robustesse de notre architecture impulsionnelle avec un système à base d'une modulation multi-porteuse classique OFDM est effectuée. Ceci nous amène à proposer un système de communication multi-utilisateurs robuste à base des réseaux de capteurs sans fil pour des communications en milieu industriel difficile. / In this thesis, we will present a multi-user communication architecture based on wireless sensor networks in a noisy industrial environment. Two modes of operation of this architecture are presented ; a Many-To-One mode linking several transmitter sensors to a single receiver and a One-To-Many mode linking a transmitter to several receiver sensors. The physical layer of this system is based on the inverse transform (IDWPT) at transmission and the discrete wavelet packet transform (DWPT) at reception. To test our architecture, an industrial channel model is proposed that takes into account the phenomena of multipath and fading in addition to additive noise. The latter being modelled as Gaussian noise to which is added an impulse noise causing significant signal degradation. The architecture is tested for different wireless communication configurations and wavelet shapes to provide an optimal communication mode. Also, an improvement in the robustness of our system is achieved by adding channel error correction coding and pulse noise thresholding at reception to minimize the effects of industrial noise on the received signals. Using an error-correcting code, the detection and reconstruction of signals is error-free from an SNR of 8dB for a coding rate of 1/4 for transmission on a fading channel. For an optimal receiver based on noise thresholding, the performance in terms of binary error rates is improved by 10dB for transmission over an industrial noise channel. Finally, a comparison of the robustness of our pulse architecture with a system based on a conventional OFDM multi-carrier modulation is carried out. This leads us to propose a robust multi-user communication system based on wireless sensor networks for communications in difficult industrial environments.

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This research looks at identifying and classifying changes in evolving software by making simple textual comparisons between groups of source code files. The two areas investigated are software origin analysis and collusion detection. Textual comparison is attractive because it can be used in the same way for many different programming languages. The research includes the first major study using machine learning techniques in the domain of software origin analysis, which looks at the movement of code in an evolving system. The training set for this study, which focuses on restructured files, is created by analysing 89 software systems. Novel features, which capture abstract patterns in the comparisons between source code files, are used to build models which classify restructured files fromunseen systems with a mean accuracy of over 90%. The unseen code is not only in C, the language of the training set, but also in Java and Python, which helps to demonstrate the language independence of the approach. As well as generating features for the machine learning system, textual comparisons between groups of files are used in other ways throughout the system: in filtering to find potentially restructured files, in ranking the possible destinations of the code moved from the restructured files, and as the basis for a new file comparison tool. This tool helps in the demanding task of manually labelling the training data, is valuable to the end user of the system, and is applicable to other file comparison tasks. These same techniques are used to create a new text-based visualisation for use in collusion detection, and to generate a measure which focuses on the unusual similarity between submissions. This measure helps to overcome problems in detecting collusion in data where files are of uneven size, where there is high incidental similarity or where more than one programming language is used. The visualisation highlights interesting similarities between files, making the task of inspecting the texts easier for the user.

Collective Communication Operations are widely used in MPI applications and play an important role in their performance. Hence, various projects have focused on optimization of collective communications for various kinds of parallel computing environments including LAN settings, heterogeneous networks and most recently Grid systems. The distinguishing factor of Grids from all the other environments is heterogeneity of hosts and network, and dynamically changing resource characteristics including load and availability. The first part of the thesis develops a solution for MPI broadcast (one-to-many) on Grids. Some current strategies take into consideration static information about network topology for determining an efficient broadcast tree for Grids. Some other strategies take into account only transient network characteristics. We combined both these strategies and cluster the network dynamically on the basis of link bandwidths. Given a set of network parameters we use Simulated Annealing (SA) to obtain the best schedule. Also, we can time tune individual. SAs, to adapt the solution finding process, on the basis of estimated available times before next broadcast invocations in the application. We also developed software architecture for updation of schedules. We compared our algorithm with the earlier approaches under loaded network conditions, and obtained average performance improvement of 20%. The second part of the thesis extends the work for MPI all gather (many-to-many) operation. Current popular techniques consider strict hierarchical schemes for this operation, wherein from each cluster a representative (or coordinator) node is chosen, and inter cluster communication is done through these representative nodes. This is non optimal as inter cluster communication is usually on high capacity links that can sustain more than one transfer with the same through- put. We developed a cluster based and incremental heuristic algorithm for allgather on Grids. We compared the time taken by allgather schedules determined by this algorithm with current popular implementations. We also compared our algorithm with a strategy where allgather is constructed from a set of broadcast trees. We obtained average performance improvement of 67% over existing strategies.

Indiana University-Purdue University Indianapolis (IUPUI) / Intrinsically disordered proteins are proteins characterized by lack of stable tertiary structures under physiological conditions. Evidence shows that disordered proteins are not only highly involved in protein interactions, but also have the capability to associate with more than one partner. Short disordered protein fragments, called “molecular recognition features” (MoRFs), were hypothesized to facilitate the binding diversity of highly-connected proteins termed “hubs”. MoRFs often couple folding with binding while forming interaction complexes. Two protein disorder mechanisms were proposed to facilitate multiple partner binding and enable hub proteins to bind to multiple partners: 1. One region of disorder could bind to many different partners (one-to-many binding), so the hub protein itself uses disorder for multiple partner binding; and 2. Many different regions of disorder could bind to a single partner (many-to-one binding), so the hub protein is structured but binds to many disordered partners via interaction with disorder. Thousands of MoRF-partner protein complexes were collected from Protein Data Bank in this study, including 321 one-to-many binding examples and 514 many-to-one binding examples. The conformational flexibility of MoRFs was observed at atomic resolution to help the MoRFs to adapt themselves to various binding surfaces of partners or to enable different MoRFs with non-identical sequences to associate with one specific binding pocket. Strikingly, in one-to-many binding, post-translational modification, alternative splicing and partner topology were revealed to play key roles for partner selection of these fuzzy complexes. On the other hand, three distinct binding profiles were identified in the collected many-to-one dataset: similar, intersecting and independent. For the similar binding profile, the distinct MoRFs interact with almost identical binding sites on the same partner. The MoRFs can also interact with a partially the same but partially different binding site, giving the intersecting binding profile. Finally, the MoRFs can interact with completely different binding sites, thus giving the independent binding profile. In conclusion, we suggest that protein disorder with post-translational modifications and alternative splicing are all working together to rewire the protein interaction networks.