Miracle-dz/UniFAR-FTUs huggingface dataset:
Advanced antivirus evasion techniques

In this thesis we examine the use of Return-Oriented Programming (ROP) combined with other practices for local (i.e. infected executables on disk) antivirus evasion. ROP is considered as a polymorphism alternative to crypters and packers. The software product of this work is a tool written in Win32 C which, given any piece of shellcode and any non-packed 32-bit Portable Executable (PE) file, it transforms the shellcode into its ROP equivalent and patches it into (i.e. infects) the PE file. After trying various combinations of evasion techniques, the results show that certain methods can evade nearly and completely all antivirus software employed in the online VirusTotal service. From a theoretical standpoint, the main outcome of this research is a) the algorithms for analysis and manipulation of assembly code on the x86 instruction set (up to and excluding the SSE), and b) the highlighting of common antivirus software weaknesses.
Fast Complex Valued Dictionary Learning Method for Sparse Representation

Sparse representation is widely used in signal processing. The best representation is based on the adaptive dictionary that trained from the processing data. This paper proposes a new complex valued dictionary learning method which turns the dictionary learning into an optimization problem and performs the optimization on the dictionary atoms and coding alternately. An online training method with memory is used in the optimization on the dictionary atoms, and an insurance of alternated direction method of multipliers is solved in the optimization on the coding. The proposed algorithm is proved to be of high efficiency, minimizing the training time while converging to the optimized value. The presented method is also robust to the noise in the training set.
State Policies to Advance English Learners' Experiences and Outcomes in California's Schools. Technical Report. Getting Down to Facts II.

California school systems and lay the founda�on for substan�ve conversa�ons about what educa�on policies should be sustained and what might be improved to ensure increased opportunity and success for all students in California in the decades ahead. Getting Down to Facts II follows approximately a decade a�er the first Getting Down to Facts effort in 2007. This technical report is one of 36 in the set of Getting Down to Facts II studies that cover four main areas related to state educa�on policy: student success, governance, personnel, and funding. State Policies to Advance English Learners’ Experiences and Outcomes in California’s Schools Technical Report
Attunement and Affordance Learning in Infants

ABSTRACT From a perceptual learning perspective, infants use social information (like gaze direction) in a similar way as other information in our physical environment (like object movements) to specify action possibilities. In the current study, we assumed that infants are able to learn an affordance upon observing an adult failing to act out that affordance, without appreciating object-directed intentions, or, communicative intent towards the infant. Using a variation of the Re-enactment procedure, we found that when the attention of infants (N = 46, Mage = 20 months) was drawn towards the eyes of the person before she acted out the failed attempt, either by ostensive cues or non-ostensive cues, infants achieved more affordances than when their attention was not directed towards the eyes. As directing the attention of infants to the eyes of another person frequently results in gaze following, this suggests that infants use the gaze direction of another person in order to learn what affordance that other person is trying to realize. In addition, the results of a spatiotemporal analysis on the eye-movements of infants suggest that the gaze and the object movements of the person facilitate learning by directing the attention of infants towards important object-directed actions on crucial moments during the failed attempt demonstrations. These results are discussed in terms of perceptual attunement and affordance learning.
Modeling,Design and Implementation of Graph OLAPing

This paper presents a series of models and algorithms to implement OLAPing on graph data.The major contributions include(1) proposing a graph-oriented data warehouse model,called a double star model,(2) proposing the concept of graph data cube and its building algorithm,(3) designing an informational OLAPing algorithm,I-OLAPing,(4) designing topological dimensional OLAPing algorithm,T-OLAPing,and(5) building a Graph OLAPing prototype,Graph OLAPer1.0,based on the proposed approaches.Experimental results show that the Graph OLAPing algorithms designed and implemented in this paper,together with Graph OLAPing prototype,Graph OLAPer1.0 can work effectively on Co-Author Networks.
Electricity Consumption Patterns: Comparative Evidence from Pakistan’s Public and Private Sectors

This study examines the behavioral aspect of Pakistan’s energy crisis by comparing electricity consumption in the public and private sectors. Specifically, we compare consumption patterns of electricity across a sample of student hostels at two public sector universities and privately run student hostels. In addition, we collect household data for a sample of students at Quaid-i-Azam University (QAU) in Islamabad and compare their average electricity consumption with that of the public sector university hostels. We find that the latter’s average consumption of electricity is significantly higher than among private hostels and households. In assessing the moral hazard problem of the public sector in this context, we test the energy conservation behavior of QAU students and the university administration. The results show that students are largely indifferent to conserving electricity, while the administration pays little attention to the use of energy-efficient lights and equipment.
Subjective Household Income Risks And Schooling Investment In Rural India

ABSTRACT:Incomes and earnings are highly volatile in developing countries and credit and insurance markets are inadequately developed. At the same time schooling attainment and investment are low. This paper analyzes effects of household income risk on schooling investment in Bihar, India. Bihar is one of the poorest states in India. Schooling in Bihar faces several challenges including low investment and learning outcomes. This paper utilizes a unique primary survey data eliciting schooling indicators and subjective income distribution from households in twelve villages in Bihar. The survey contained a module designed to elicit information on the cumulative probability distribution of future income of households. Using this information, household-specific variance of future income is derived, which is used as an indicator of income risk. This is one of the first papers to use subjective income distribution data to analyze the effects income risks on schooling in a developing country. Data shows that there is a significant bias against female children in schooling investment in Bihar. Regression analysis suggests that this gender bias in schooling investment can partly be due to income risks faced by households. Results show that household income risk has a significant negative effect on schooling expenditure and time-spent by children on tuition and homework, particularly of female children in Bihar. It has significantly larger negative effect on schooling expenditure of low income households and time-spent by their children on tuition and homework relative to higher income households. Overall these findings suggest that income risk faced by poorer households is an important reason for the persistence of low educational achievement and outcomes in Bihar, particularly for female children. Government policies which reduce income risks such as provision of health insurance, unemployment insurance, old age pension scheme and easier availability of consumer credit targeted towards poor households, are likely to have significant positive effect on schooling. Microfinance institutions and NGOs can play an important role in the provision of insurance and labor market information. Public investment in irrigation and better weather information can reduce income risk and encourage schooling investment.
From super-hero to super-connector, changing the leadership culture in the NHS

ABSTRACT The NHS Long Term Plan recently published recognises the critical role of leadership to the delivery of high-quality, sustainable healthcare and sets out an ambition for compassionate and inclusive leadership behaviours. There is good evidence that the biggest influence on organisational culture is the quality of leadership, affecting patient outcomes and staff experience. However, the current NHS staff survey paints a sobering picture of the current experience of the 1.2 million staff who work in the NHS in England. Changing culture requires leadership effort and behavioural change at every level of the system, from the clinical microsystem to the national arms-length bodies. Leaders can take positive action by regularly seeking feedback, paying attention to the leadership behaviours within their team and finding ways to ensure the team can reflect and improve their team working. This opinion article offers an introduction to compassionate and inclusive leadership in healthcare. Our intention is to provide the reader with a sense of agency to act and improve local culture for the benefits of patients and staff.
Adapting scientific computing algorithms to distributed computing frameworks

Scientific computing applies computational methods to solve problems in genetics, biology, material science, chemistry etc., where complex real life processes need to be modeled and simulated or where a large amount of data needs to be analyzed. It is strongly associated with parallel programming and high-performance computing (HPC) as it typically requires utilization of a large amount of computer resources from local clusters and grids to supercomputers. Public clouds can provide these resources on-demand and in real–time but they are often built on commodity hardware and it’s not simple to design applications that can efficiently utilize their resources en masse and in fault tolerant manner. Frameworks based on distributed computing models such as MapReduce can significantly simplify this work by providing near automatic parallelization and fault recovery. Our first research task was to investigate the suitability of Hadoop MapReduce for more complex scientific computing algorithms and to identify what algorithm characteristics affect the parallel efficiency of the results. Hadoop MapReduce could easily handle more simple, embarrassingly parallel algorithms, such as trial division or Monte Carlo methods. However, it had serious issues with more complex and especially iterative algorithms, such as the conjugate gradient method. To be able to exploit MapReduce advantages (such as near automatic parallelization and fault recovery) for more complex algorithms, we proposed and investigated three different approaches. The first approach was to reduce the number of iterations by restructuring the algorithms or using alternative methods that might be less efficient, but would suit the MapReduce model better. The second approach was evaluating alternative MapReduce frameworks (such as Twister, HaLoop or Spark) that are specifically designed for iterative algorithms and analyzing whether they provide the same aforementioned advantages as Hadoop.
P2P load-balance model based on multi-layer Bayesian trust network

A Peer-to-Peer(P2P) load balance model based on multi-layer Bayesian trust network was designed to deal with the load balance problems in the trust-based P2P network.Some load indexes and their relations were added to the model to predict the workload of the peers.Experiments were done for the presented model and the dynamic load model,respectively.The results show that,by exploiting the interactions history and the Bayesian prediction theories,the load balance model based on multi-layer Bayesian trust network influences the peer selection process and can effectively balance the load of the P2P network,thereafter improving the resource utilization ratio,the quality and reliability of the peers services.
Design and Implementation of 8-Bit SAR ADC with Built-in-Self- Calibration and Digital-Trim Technique

The successive approximation register (SAR) topology is probably the one that has benefited most from CMOS technology evolution, and is now a strong competitor with other architectures as the pipeline, for medium-resolution medium speed ADCs, and the flash, for low-resolution high-speed ADCs. In this system, propose a SAR ADC with a very low-power background calibration technique that continuously nullifies the comparator offset and operates within the supply-voltage range of the ADC. This method allows the comparator to be implemented with small transistors, reducing the power consumption. Furthermore, being a continuous calibration procedure, it is automatically adapting to changes in process, voltage, and temperature (PVT). For operating with a supply voltage as low mV compare with existing methods, close to the transistors threshold voltage V , the ADC employs local voltage boosting for all the MOS switches. To avoid this TH solution to be a strong penalty to the available area/power budget, a voltage-booster (VB) with minimal complexity is employed.
Learning the Evolution Regularities for BigService-Oriented Online Reliability Prediction

Service computing is an emerging technology in System of Systems Engineering (SoS Engineering or SoSE), which regards a System as a Service, and aims at constructing a robust and value-added complex system by outsourcing external component systems through service composition. The burgeoning Big Service computing just covers the significant challenges in constructing and maintaining a stable service-oriented SoS. A service-oriented SoS runs under a volatile and uncertain environment. As a step toward big service, service fault tolerance (FT) can guarantee the run-time quality of a service-oriented SoS. To successfully deploy FT in an SoS, online reliability time series prediction, which aims at predicting the reliability in near future for a service-oriented SoS arises as a grand challenge in SoS research. In particular, we need to tackle a number of big data related issues given the large and fast increasing size of the historical data that will be used for prediction purpose. The decision-making of prediction solution space be more complex. To provide highly accurate prediction results, we tackle the prediction challenges by identifying the evolution regularities of component systems’ running states via different machine learning models. We present in this paper the motifs-based Dynamic Bayesian Networks (or m_DBNs) to perform one-step-ahead online reliability time series prediction. We also propose a multi-steps trajectory DBNs (or multi_DBNs) to further improve the accuracy of future reliability prediction. Finally, a Convolutional Neural Networks (CNN)-based prediction approach is developed to deal with the big data challenges. Extensive experiments conducted on real-world Web services demonstrate that our models outperform other well-known approaches consistently.
Tumor desmoide de intestino delgado: relato de caso e revisão

Desmoid tumor of the small bowel: a case study and review Desmoid tumors are rare, affecting two to five individuals per million inhabitants every year, and a scarce number of cases has been reported. Its cause is unclear. The authors report a case of intra-abdominal desmoid tumor in a 66-year-old man, presenting with diffuse abdominal pain for two months and acute colic symptoms in the hypogastrium. He had undergone prostatectomy two years before. A hypogastric mass was palpated and computed tomography imaging showed a pelvic-abdominal heterogeneous tumor, with contrast enhancement, and displacement of the small bowel and urinary bladder. Suspecting gastrointestinal stromal tumor, doctors excised the mass with the involved ileal loop and performed small bowel anastomosis. Diagnosis of mesenteric fibromatosis was established by histological and immunohistochemical findings. One-year follow-up Wendel dos Santos Furtado e cols. • Tumor desmoide de intestino delgado Brasília Med 2013;50(4):336-341 • 337 shows that the patient remains asymptomatic. A short review of the literature was conducted.
Emigration and Brain DrainEvidence From the Caribbean

This paper quantifies the magnitude and nature of migration flows from the Caribbean and estimates their costs and benefits. The Caribbean countries have lost 10-40 percent of their labor force due to emigration to OECD member countries. The migration rates are particularly striking for the highskilled. Many countries have lost more than 70 percent of their labor force with more than 12 years of completed schooling-among the highest emigration rates in the world. The region is also the world's largest recipient of remittances as a percent of GDP. Remittances constituted about 13 percent of the region's GDP in 2002. Simple welfare calculations suggest that the losses due to high-skill migration (ceteris paribus) outweigh the official remittances to the Caribbean region. The results suggest that there is indeed some evidence for brain drain from the Caribbean.
Partisan Policymaking: Research and Advocacy in an Era of Polarization

PARTISAN POLICYMAKING: RESEARCH AND ADVOCACY IN AN ERA OF POLARIZATION MAY 2019 ZACHARY ALBERT B.A., FAIRFIELD UNIVERSITY Ph.D., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Raymond J. La Raja In recent decades, partisan polarization has not only grown but also extended to a wide variety of political processes. Despite this fact, we lack a strong understanding of the policy process under conditions of relatively extreme polarization. The roles of interest groups and think tanks in this environment are particularly understudied. How have research producing institutions changed in response to partisan polarization? And which types of organizations are most influential under the current system? Existing theories often lack an appreciation of the role of partisanship and assume relatively unstructured pluralistic competition in the development and debate of public policy. To help rectify this limitation, I view actors in the policy process as part of a system structured mainly by partisan dynamics. This changing “marketplace for ideas” has incentivized some interest groups and think tanks to invest in a single political party to enhance their influence and accomplish their goals. The result is a
The Intended and Unintended Effects of Drunk Driving Policies

Taking advantage of merged administrative data, we estimate the intended and unintended effects of two public policies aimed at combating driving under influence (DUI) of alcohol in Taiwan: the three‐month‐long campaign of random sobriety checkpoints in mid‐2012, and the legal reform carried out in mid‐2013 leading to much harsher punishments for DUI offenders. Our study gives rise to several important findings: (i) The checkpoint campaign substantially reduced DUI deaths and injuries, and the effect persisted after the campaign ended; (ii) the campaign also had a strong spillover effect of reducing non‐DUI deaths and injuries, and this unintended effect was four times the size of the intended effect on DUI cases; (iii) these effects were not driven by social pressure or self‐awareness arising from the intensive media coverage taking place at the same time; and (iv) there was little response to either policy among repeat DUI offenders and those who caused serious injuries.
Moroccan agriculture, climate change, and the Moroccan Green Plan: A CGE analysis

This paper provides estimates of the economic impacts of climate change and estimates the adaptation potential of the current Moroccan agricultural development and investment strategy, the Moroccan Green Plan (MGP). We develop a regionalised Morocco Computable General Equilibrium model to analyse the linkages of climate-induced productivity losses (gains) at the level of administrative and economic regions in Morocco. We model the climate change impacts as productivity shocks in the agricultural sector. The yield projections are for 2050, which we introduce with respect to a 2003 baseline. The results indicate no major differences between the climate change impacts without and with the MGP. With no MGP adaptation, GDP impacts range from -3.1% to +0.4%. When including the MGP targets, GDP impacts range from -2.9% to +0.43%. A potential cause for such results is the limited scope in terms of agricultural sector coverage of our MGP simulations owing to modelling and data constraints.
Effects of Synchronization Error on Space Time Block Codes Equipped with FSK Waveforms

Space-time Coding (STC) for Multiple-Input Multiple-Output (MIMO) wireless communication systems is an effective technique for providing robust wireless link performance in telemetry systems. This paper investigates the degradation in system performance when synchronization errors between the transmitter and receiver are present. Specifically, expressions that quantify the increase in symbol-error-rate as a function of symbol synchronization error are derived for a two-transmit and single receive antenna MISO system using binary frequency shift keying waveforms. These results are then extended to the MIMO case. The analytic results are verified with simulation results that show close agreement between the theoretical expressions and Monte Carlo simulation runs.
Measurements and analysis of spectrum occupancy

In order to grasp actual spectrum utilization of the"digital dividend"spectrum,guided by ITU-R SM 1880 and handbook of spectrum measurement(2011edition),actual measurement are arranged in the two cities(three monitoring stations)by setting up the hardware and software environment.The obtained data are analysed and the time-frequency-occupancy rate comparison charts are obtained.Results show that the spectrum utilization of digital dividend frequency rate in measured city is low.Therefore it is suggested to speed up the implementation of television system analog/digital conversion,to get the release of"digital dividend spectrum",and to ultimately improve the utilization of spectrum resources.