A case study of a district's intended and unintended results connected to the implementation of a required ninth-grade algebra 1 strategic initiative

There is a long history of debate around mathematics standards, reform efforts, and accountability. This research identified ways that national expectations and context drive local implementation of mathematics reform efforts and identified the external and internal factors that impact teachers’ acceptance or resistance to policy implementation at the local level. This research also adds to the body of knowledge about acceptance and resistance to policy implementation efforts. This case study involved the analysis of documents to provide a chronological perspective, assess the current state of the District’s mathematics reform, and determine the District’s readiness to implement the Common Core Curriculum. The school system in question has continued to struggle with meeting the needs of all students in Algebra 1. Therefore, the results of this case study will be useful to the District’s leaders as they include the compilation and analysis of a decade’s worth of data specific to Algebra 1.

Design and implementation of a floating point unit for rigel, a massively parallel accelerator

Scientific applications rely heavily on floating point data types. Floating point operations are complex and require complicated hardware that is both area and power intensive. The emergence of massively parallel architectures like Rigel creates new challenges and poses new questions with respect to floating point support. The massively parallel aspect of Rigel places great emphasis on area efficient, low power designs. At the same time, Rigel is a general purpose accelerator and must provide high performance for a wide class of applications. This thesis presents an analysis of various floating point unit (FPU) components with respect to Rigel, and attempts to present a candidate design of an FPU that balances performance, area, and power and is suitable for massively parallel architectures like Rigel.

Preventing encrypted traffic analysis

Many existing encrypted Internet protocols leak information through packet sizes and timing. Though seemingly innocuous, prior work has shown that such leakage can be used to recover part or all of the plaintext being encrypted. The prevalence of encrypted protocols as the underpinning of such critical services as e-commerce, remote login, and anonymity networks and the increasing feasibility of attacks on these services represent a considerable risk to communications security. Existing mechanisms for preventing traffic analysis focus on re-routing and padding. These prevention techniques have considerable resource and overhead requirements. Furthermore, padding is easily detectable and, in some cases, can introduce its own vulnerabilities. To address these shortcomings, we propose embedding real traffic in synthetically generated encrypted cover traffic. Novel to our approach is our use of realistic network protocol behavior models to generate cover traffic. The observable traffic we generate also has the benefit of being indistinguishable from other real encrypted traffic further thwarting an adversary's ability to target attacks. In this dissertation, we introduce the design of a proxy system called TrafficMimic that implements realistic cover traffic tunneling and can be used alone or integrated with the Tor anonymity system. We describe the cover traffic generation process including the subtleties of implementing a secure traffic generator. We show that TrafficMimic cover traffic can fool a complex protocol classification attack with 91% of the accuracy of real traffic. TrafficMimic cover traffic is also not detected by a binary classification attack specifically designed to detect TrafficMimic. We evaluate the performance of tunneling with independent cover traffic models and find that they are comparable, and, in some cases, more efficient than generic constant-rate defenses. We then use simulation and analytic modeling to understand the performance of cover traffic tunneling more deeply. We find that we can take measurements from real or simulated traffic with no tunneling and use them to estimate parameters for an accurate analytic model of the performance impact of cover traffic tunneling. Once validated, we use this model to better understand how delay, bandwidth, tunnel slowdown, and stability affect cover traffic tunneling. Finally, we take the insights from our simulation study and develop several biasing techniques that we can use to match the cover traffic to the real traffic while simultaneously bounding external information leakage. We study these bias methods using simulation and evaluate their security using a Bayesian inference attack. We find that we can safely improve performance with biasing while preventing both traffic analysis and defense detection attacks. We then apply these biasing methods to the real TrafficMimic implementation and evaluate it on the Internet. We find that biasing can provide 3-5x improvement in bandwidth for bulk transfers and 2.5-9.5x speedup for Web browsing over tunneling without biasing.

On the fly type specialization without type analysis

Les langages de programmation typés dynamiquement tels que JavaScript et Python repoussent la vérification de typage jusqu’au moment de l’exécution. Afin d’optimiser la performance de ces langages, les implémentations de machines virtuelles pour langages dynamiques doivent tenter d’éliminer les tests de typage dynamiques redondants. Cela se fait habituellement en utilisant une analyse d’inférence de types. Cependant, les analyses de ce genre sont souvent coûteuses et impliquent des compromis entre le temps de compilation et la précision des résultats obtenus. Ceci a conduit à la conception d’architectures de VM de plus en plus complexes. Nous proposons le versionnement paresseux de blocs de base, une technique de compilation à la volée simple qui élimine efficacement les tests de typage dynamiques redondants sur les chemins d’exécution critiques. Cette nouvelle approche génère paresseusement des versions spécialisées des blocs de base tout en propageant de l’information de typage contextualisée. Notre technique ne nécessite pas l’utilisation d’analyses de programme coûteuses, n’est pas contrainte par les limitations de précision des analyses d’inférence de types traditionnelles et évite la complexité des techniques d’optimisation spéculatives. Trois extensions sont apportées au versionnement de blocs de base afin de lui donner des capacités d’optimisation interprocédurale. Une première extension lui donne la possibilité de joindre des informations de typage aux propriétés des objets et aux variables globales. Puis, la spécialisation de points d’entrée lui permet de passer de l’information de typage des fonctions appellantes aux fonctions appellées. Finalement, la spécialisation des continuations d’appels permet de transmettre le type des valeurs de retour des fonctions appellées aux appellants sans coût dynamique. Nous démontrons empiriquement que ces extensions permettent au versionnement de blocs de base d’éliminer plus de tests de typage dynamiques que toute analyse d’inférence de typage statique.

Negative symptoms of schizophrenia and psychosocial treatment: thematic analysis of stakeholders’ perspectives

Objectives. Recent literature indicates variance in psychosocial treatment preferences for negative symptoms of schizophrenia. Attempts at defining therapeutic aims and outcomes for negative symptoms to date have not included major stakeholder groups. The aim of the present study was to address this gap through qualitative methods. Design. Thematic Analysis was applied to qualitative semi-structured interview data to gather the opinions of people who experience negative symptoms, carers, and healthcare professionals. Participants were recruited from two mental health sites (inpatient/community) to increase generalisability of results. Ten people participated in the research. Methods. Semi-structured interview scripts were designed utilising evidence from the review in Chapter 1 of effective psychosocial intervention components for specific negative symptoms. Interviews were audio recorded and transcribed verbatim. Thematic analysis was employed to analyse data. Results. A common theme across groups was the need for a personalised approach to intervention for negative symptoms. Other themes indicated different opinions in relation to treatment targets and the need for a sensitive and graded approach to all aspects of therapy. This approach needs to be supported across systemic levels of organisation with specific training needs for staff addressed. Conclusions. There is disparity in treatment preferences for negative symptoms across major stakeholders. The findings suggest an individualised approach to intervention of negative symptoms that is consistent with recovery. Implementation barriers and facilitators were identified and discussed. There remains a need to develop a better understanding of treatment preferences for patients.

EMMA 2--a MAGE-compliant system for the collaborative analysis and integration of microarray data

Background: Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. Results: The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services. Conclusion: Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays.

Content analysis model to analyze facets of social mission of public library on the Facebook and in the websites

In this paper we present the development and the implementation of a content analysis model for observing aspects relating to the social mission of the public library on Facebook pages and websites. The model is unique and it was developed from the literature. There were designed the four categories for analysis Generate social capital and social cohesion, Consolidate democracy and citizenship, Social and digital inclusion and Fighting illiteracies. The model enabled the collection and the analysis of data applied to a case study consisting of 99 Portuguese public libraries with Facebook page. With this model of content analysis we observed the facets of social mission and we read the actions with social facets on the Facebook page and in the websites of public libraries. At the end we discuss in parallel the results of observation of the Facebook of libraries and the websites. By reading the description of the actions of the social mission, the general conclusion and the most immediate is that 99 public libraries on Facebook and websites rarely publish social character actions, and the results are little satisfying. The Portuguese public libraries highlight substantially the actions in the category Generate social capital and social cohesion.

Dual layer solid phase extraction based on molecular imprinting technology: Seeking a route to enhance selectivity for trace analysis of pesticide residues in olive oil.

Aiming to introduce a multiresidue analysis for the trace detection of pesticide residues belonging to organophosphorus and triazine classes from olive oil samples, a new sample preparation methodology comprising the use of a dual layer of “tailor-made” molecularly imprinted polymers (MIPs) SPE for the simultaneous extraction of both pesticides in a single procedure has been attempted. This work has focused on the implementation of a dual MIP-layer SPE procedure (DL-MISPE) encompassing the use of two MIP layers as specific sorbents. In order to achieve higher recovery rates, the amount of MIP layers has been optimized as well as the influence of MIP packaging order. The optimized DL-MISPE approach has been used in the preconcentration of spiked organic olive oil samples with concentrations of dimethoate and terbuthylazine similar to the maximum residue limits and further quantification by HPLC. High recovery rates for dimethoate (95%) and terbuthylazine (94%) have been achieved with good accuracy and precision. Overall, this work constitutes the first attempt on the development of a dual pesticide residue methodology for the trace analysis of pesticide residues based on molecular imprinting technology. Thus, DL-MISPE constitutes a reliable, robust, and sensitive sample preparation methodology that enables preconcentration of the target pesticides in complex olive oil samples, even at levels similar to the maximum residue limits enforced by the legislation.

Performance Analysis of IP based WSNs in real time systems

Wireless sensor networks (WSNs) are the key enablers of the internet of things (IoT) paradigm. Traditionally, sensor network research has been to be unlike the internet, motivated by power and device constraints. The IETF 6LoWPAN draft standard changes this, defining how IPv6 packets can be efficiently transmitted over IEEE 802.15.4 radio links. Due to this 6LoWPAN technology, low power, low cost micro- controllers can be connected to the internet forming what is known as the wireless embedded internet. Another IETF recommendation, CoAP allows these devices to communicate interactively over the internet. The integration of such tiny, ubiquitous electronic devices to the internet enables interesting real-time applications. This thesis work attempts to evaluate the performance of a stack consisting of CoAP and 6LoWPAN over the IEEE 802.15.4 radio link using the Contiki OS and Cooja simulator, along with the CoAP framework Californium (Cf). Ultimately, the implementation of this stack on real hardware is carried out using a raspberry pi as a border router with T-mote sky sensors as slip radios and CoAP servers relaying temperature and humidity data. The reliability of the stack was also demonstrated during scalability analysis conducted on the physical deployment. The interoperability is ensured by connecting the WSN to the global internet using different hardware platforms supported by Contiki and without the use of specialized gateways commonly found in non IP based networks. This work therefore developed and demonstrated a heterogeneous wireless sensor network stack, which is IP based and conducted performance analysis of the stack, both in terms of simulations and real hardware.

Implementation of the CDM model to the analisys of the hotel sector

The main aim of this study was to determine the impact of innovation on productivity in service sector companies — especially those in the hospitality sector — that value the reduction of environmental impact as relevant to the innovation process. We used a structural analysis model based on the one developed by Crépon, Duguet, and Mairesse (1998). This model is known as the CDM model (an acronym of the authors’ surnames). These authors developed seminal studies in the field of the relationships between innovation and productivity (see Griliches 1979; Pakes and Grilliches 1980). The main advantage of the CDM model is its ability to integrate the process of innovation and business productivity from an empirical perspective.

Internationalization venture analysis of NMusic to the Spanish market

Field lab: Entrepreneurial and innovative ventures

Analysis of maternal and child health policies in Malawi: The methodological perspective

The question of why most health policies do not achieve their intended results continues to receive a considerable attention in the literature. This is in the light of the recognized gap between policy as intent and policy as practice, which calls for substantial research work to understand the factors that improve policy implementation. Although there is substantial work that explains the reasons why policies achieve or fail to achieve their intended outcomes, there are limited case studies that illustrate how to analyze policies from the methodological perspective. In this article, we report and discuss how a mixed qualitative research method was applied for analyzing maternal and child health policies in Malawi. For the purposes of this article, we do not report research findings; instead we focus our dicussion on the methodology of the study and draw lessons for policy analysis research work. We base our disusssion on our experiences from a study in which we analyzed maternal and child health policies in Malawi over the period from 1964 to 2008. Noting the multifaceted nature of maternal and child health policies, we adopted a mixed qualitative research method, whereby a number of data collection methods were employed. This approach allowed for the capturing of different perspectives of maternal and child health policies in Malawi and for strengthening of the weaknesses of each method, especially in terms of data validity. This research suggested that the multidimensional nature of maternal and child health policies, like other health policies, calls for a combination of research designs as well as a variety of methods of data collection and analysis. In addition, we suggest that, as an emerging research field, health policy analysis will benefit more from case study designs because they provide rich experiences in the actual policy context.

Point-of-care lactate and creatinine analysis for sick obstetric patients at Queen Elizabeth Central Hospital in Blantyre, Malawi: A feasibility study

Background: To achieve good outcomes in critically ill obstetric patients, it is necessary to identify organ dysfunction rapidly so that life-saving interventions can be appropriately commenced. However, timely access to clinical chemistry results is problematic, even in referral institutions, in the sub-Saharan African region. Reliable point-of-care tests licensed for clinical use are now available for lactate and creatinine. Aim: We aimed to assess whether implementation of point-of-care testing for lactate and creatinine is feasible in the obstetric unit at the Queen Elizabeth Central Hospital (QECH) in Blantyre, Malawi, by obtaining the opinions of clinical staff on the use of these tests in practice. Methods: During a two-month evaluation period nurse-midwives, medical interns, clinical officers, registrars, and consultants were given the opportunity to use StatStrip® and StatSensor® (Nova Biomedical, Waltham, USA) devices, for lactate and creatinine estimation, as part of their routine clinical practice in the obstetric unit. They were subsequently asked to complete a short questionnaire. Results: Thirty-seven questionnaires were returned by participants: 22 from nurse-midwives and the remainder from clinicians. The mean satisfaction score for the devices was 7.6/10 amongst clinicians and 8.0/10 amongst nurse-midwives. The majority of participants stated that the obstetric high dependency unit (HDU) was the most suitable location for the devices. For lactate, 31 participants strongly agreed that testing should be continued and 24 strongly agreed that it would influence patient management. For creatinine, 29 strongly agreed that testing should be continued and 28 strongly agreed that it would influence their patient management. Twenty participants strongly agreed that they trust point-of-care devices. Conclusions: Point-of-care clinical chemistry testing was feasible, practical, and well received by staff, and was considered to have a useful role to play in the clinical care of sick obstetric patients at this referral centre.

Financial Statement Analysis for Enterprise Network Design

Part 8: Business Strategies Alignment

Bayesian analysis of a mastitis control plan to investigate the influence of veterinary prior beliefs on clinical interpretation

The fundamental objective for health research is to determine whether changes should be made to clinical decisions. Decisions made by veterinary surgeons in the light of new research evidence are known to be influenced by their prior beliefs, especially their initial opinions about the plausibility of possible results. In this paper, clinical trial results for a bovine mastitis control plan were evaluated within a Bayesian context, to incorporate a community of prior distributions that represented a spectrum of clinical prior beliefs. The aim was to quantify the effect of veterinary surgeons’ initial viewpoints on the interpretation of the trial results. A Bayesian analysis was conducted using Markov chain Monte Carlo procedures. Stochastic models included a financial cost attributed to a change in clinical mastitis following implementation of the control plan. Prior distributions were incorporated that covered a realistic range of possible clinical viewpoints, including scepticism, enthusiasm and uncertainty. Posterior distributions revealed important differences in the financial gain that clinicians with different starting viewpoints would anticipate from the mastitis control plan, given the actual research results. For example, a severe sceptic would ascribe a probability of 0.50 for a return of <£5 per cow in an average herd that implemented the plan, whereas an enthusiast would ascribe this probability for a return of >£20 per cow. Simulations using increased trial sizes indicated that if the original study was four times as large, an initial sceptic would be more convinced about the efficacy of the control plan but would still anticipate less financial return than an initial enthusiast would anticipate after the original study. In conclusion, it is possible to estimate how clinicians’ prior beliefs influence their interpretation of research evidence. Further research on the extent to which different interpretations of evidence result in changes to clinical practice would be worthwhile.