Miracle-dz/UniFAR-FTUs huggingface dataset:
Cryptϵ: Crypto-Assisted Differential Privacy on Untrusted Servers

Differential privacy (DP) is currently the de-facto standard for achieving privacy in data analysis, which is typically implemented either in the "central" or "local" model. The local model has been more popular for commercial deployments as it does not require a trusted data collector. This increased privacy, however, comes at the cost of utility and algorithmic expressibility as compared to the central model. In this work, we propose, Cryptε, a system and programming framework that (1) achieves the accuracy guarantees and algorithmic expressibility of the central model (2) without any trusted data collector like in the local model. Cryptε achieves the "best of both worlds" by employing two non-colluding untrusted servers that run DP programs on encrypted data from the data owners. In theory, straightforward implementations of DP programs using off-the-shelf secure multi-party computation tools can achieve the above goal. However, in practice, they are beset with many challenges like poor performance and tricky security proofs. To this end, Cryptε allows data analysts to author logical DP programs that are automatically translated to secure protocols that work on encrypted data. These protocols ensure that the untrusted servers learn nothing more than the noisy outputs, thereby guaranteeing DP (for computationally bounded adversaries) for all Cryptε programs. Cryptε supports a rich class of DP programs that can be expressed via a small set of transformation and measurement operators followed by arbitrary post-processing. Further, we propose performance optimizations leveraging the fact that the output is noisy. We demonstrate Cryptε's practical feasibility with extensive empirical evaluations on real world datasets.
The Tourist Attractions Recommender System for Bangkok Thailand

 Abstract —The objective of this research is to design and develop a tool to evaluate tourists' satisfaction with the attractions recommendation system in Bangkok, Thailand. We have four main stages for the tourist attraction recommendation system. The first stage is to fill imputed missing values with association rules and multiple imputations. The second stage is constructing the tourist attractions recommendation model by ranking the tourist attractions with a ranking method and similarity measurements based on a personal recommender system with cosine algorithm. The third stage is to design and develop the personal recommender website. And the last stage is to evaluate the personal recommender system with four measurements: accuracy, precision, f-measure, and g-mean. The experiment results from a sampling of thirty people found that the tourist attraction recommendation system can: 1) make a positive recommendation 340 times, but 105 times will not meet the needs, and 2) make a negative recommendation 708 times, but 77 times will meet the needs. The results show that the tourist attractions recommendation system has satisfactory performance and reliability with high accuracy, precision, and f-measure, and g-mean values of 85.20%, 76.40%, 78.89%, and 84.26%, respectively. In addition, it was found that the users’ satisfaction towards the system was at a high level with a value of 4.60. This means that the proposed tourist attractions recommendation system can be used to recommend personal preferences as well.
Selection of tree species for cambium consumption by the Bornean orang-utan (Pongo pygmaeus wurmbii)

Cambium is a major fall-back food for orang-utans when fruit availability is low. Although recognised as a major source of food in these times, the motivation behind the preference for certain species is unclear. Energy content and nutritional composition of cambium was studied to see if there were differences between eaten and not-eaten species that might explain the choices made by Bornean orang-utans (Pongo pygmaeus wurmbii). Bark samples were collected from the Sabangau peat swamp forest, Central Kalimantan, and the cambium layer removed. Physical properties measurements were taken and nutritional analyses were performed to determine nutrient composition of the organic matter. Available energy was calculated and compared between eaten and not-eaten species. Due to small sample size and non-normal data distribution non-parametric tests were used to test for differences between species eaten and avoided. Cambium thickness and water content were both significantly different between eaten and not-eaten species, with not-eaten species being thicker (p=0.001) and containing more water (p=0.010). There were no significant differences between eaten and not-eaten species in terms of total available energy, the different fractions of organic matter or the energy gained from them. Eaten cambium is not chosen on the basis of energy content alone and it is probable that other factors, especially toughness, are important for limiting species eaten in this area. It is unlikely that hardness and secondary plant compounds play a role in cambium preference, but it is possible that essential fatty acid spectrum may also be important.
The determinants of the unlikely-to-pay and the flows towards performing and bad loans

Using a novel panel data set, we study the determinants of the unlikely-to-pay loans (UTP) and the out-flows from UTP to performing and to other categories of non-performing loans (NPL) of Italian banks during the period from 2010 to 2016. The paper investigates a specific category of NPL, which given their increasing importance in bank credit portfolios is a category which has attracted recent interest from supervisors, regulators and market operators. Results are that the determinants of UTP ratio are the same as determinants of bad loans ratio, and determinants of flows of new UTP match determinants of flows of new bad loans. But using stocks or flows of UTP with a dynamic GMM model yields conflicting results with regard to quality of management, bank efficiency and capitalization. This emphasizes the importance of choosing the measure of credit portfolio quality for both researchers and supervisory authorities. Lastly, considering the flows of UTP that either become performing loans again or worsen by becoming NPL, findings suggest that having a specific office/unit to manage NPL increases flows to performing loans and reduces flows to other categories of NPL. With regard to the coverage of UTP, banks with a higher ratio of loan loss provisions specific for UTP show higher flows to other categories of NPL.
The effect of training on older workers’ wage: evidence from Europe

Financial deficits of many social security systems caused by ageing populations and stagnating economies are forcing workers to retire later from the labour market. An extended working life, combined with rapid technological progress undergoi n in many sectors, may likely make older workers’ skills attained at school obsolete. In thi s context, lifelong investment in training is widel y recognized among the international research and pol icy community as a key element to increase or, at least, limit the decline in productivity of older w orkers. This paper investigates the impact of train ing undertaken by European older workers on their wages , relying on the Survey of Health, Ageing and Retirement in Europe (SHARE). Taking part in training activities increases wages of European workers aged 50 years and older by up to 6.5 %. This return is sizable: it is comparable to attaining a upper and post-secondary instead of a primary and lower-secondary education degree. Retur n to training is prima facie higher in Continental and Southern than in Northern European countries, t he latter group of countries being characterized by the highest incidence. Our results suggest that investment in training at older ages is an effectiv e way to counteract human capital depreciation.
THE DOUBLE DIFFERENCE RELOCATION OF AFTERSHOCK SEQUENCE OF 2017 EZGELEH EARTHQUAKE

On November 12, 2017, an earthquake with moment magnitude of 7.3 occurred in vicinity of Sarpol-e Zahab town, Kermanshah, Iran. The main earthquake of November 12 has been proceeded by a large number of aftershocks; from that date until January 2019, 5078 earthquakes have been recorded by Iranian Seismological Center (IRSC). This earthquake has been the largest event in this region in the last hundred years, the previous largest event in the area had occurred in 1909 AD in Silakhor with magnitude of 7.4. In this study in order to relocate 2017-2019 earthquakes in the region, double difference earthquake location method of Waldhauser and Ellsworth (2000) is applied. The double-difference algorithm minimizes errors due to unmodeled velocity structure without the use of station corrections. The method incorporates ordinary absolute travel-time measurements and/or cross-correlation P-and S-wave differential travel-time measurements. Two waveforms recorded at the same station are considered similar when half of the squared coherency value, in a specified frequency range and time window is exceeding the chosen correlation coefficient (Waldhauser and Ellsworth, 2002). Residuals between observed and theoretical travel-time differences are minimized for pairs of earthquakes at each station while linking together all observed event-station pairs. Using the cross correlation method on similar seismograms to obtain accurate phase arrivals, could reduce the location uncertainty that will lead to more efficient detection of waveforms that are more similar to already known events (Ottemȍ ller and Thomas, 2007). In this study, In order to improve the image of the seismogenic features, relocation has been done with both catalog data (P and S phases) and cross correlations data (P phases) combined, for simultaneous relocation for all events. Using Cross Correlation has improved the accuracy of the phase picking (Figure 1).
ANALYSIS OF THE THERMAL IGNITION AND INDUCTION TIME OF PREMIXED ETHANOL AND AIR COMBUSTION

Here we analyze the thermal ignition of ethanol (C2H5OH) and dry standard air using a zero-dimensional model with detailed chemistry. The variation with time of the species concentrations and the induction period for the thermal ignition process are analyzed as a function of the pressure and mixture stoichiometric ratio. The Marinov and the Konnov detailed chemical kinetic mechanisms are used in CANTERA and CHEMKIN for the simulations of ignition in constant pressure, adiabatic, perfectly stirred reactor conditions. Computational chemistry methods are used to complement the thermodynamic database and to obtain other molecular structural information. It is observed that the induction period for the thermal ignition decreases with the increase of pressure and increases with the increase of stoichiometric ratio and that the variation of induction time becomes smaller as the pressure increases. This is the same behavior as observed for the thermal ignition of aliphatic non-saturated hydrocarbons.
A Big Data Placement Strategy in Geographically Distributed Datacenters

With the pervasiveness of the "Big Data" characteristic together with the expansion of geographically distributed datacenters in the Cloud computing context, processing large- scale data applications has become a crucial issue. Indeed, the task of finding the most efficient way of storing massive data across distributed locations is increasingly complex. Furthermore, the execution time of a given task that requires several datasets might be dominated by the cost of data migrations/exchanges, which depends on the initial placement of the input datasets over the set of datacenters in the Cloud and also on the dynamic data management strategy. In this paper, we propose a data placement strategy to improve the workflow execution time through the reduction of the cost associated to data movements between geographically distributed datacenters, considering their characteristics such as storage capacity and read/write speeds. We formalize the overall problem and then propose a data placement algorithm structured into two phases. First, we compute the estimated transfer time to move all involved datasets from their respective locations to the one where the corresponding tasks are executed. Second, we apply a greedy algorithm in order to assign each dataset to the optimal datacenter w.r. t the overall cost of data migrations. The heterogeneity of the datacenters together with their characteristics (storage and bandwidth) are both taken into account. Our experiments are conducted using Cloudsim simulator. The obtained results show that our proposed strategy produces an efficient placement and actually reduces the overheads of the data movement compared to both a random assignment and a selected placement algorithm from the literature.
on ‘relative deprivation’ theory as an essential mechanism to show how satisfaction with democracy depends on relative comparisons through time and individuals. I will show that satisfaction with democracy is higher when the overall economic situation of society

Satisfaction with democracy is supposed to be correlated with institutional performance. However, it is not clear what the real meaning of satisfaction with democracy is, and how to measure institutional performance. Secondly, there is a lack of theoretical research about the link between institutional performance and satisfaction with democracy at the individual level. Finally, in order to understand this link we have to deal with variables and indicators at different levels (aggregate and individual), which imposes some econometric restrictions over model specification. In this paper I propose a model to represent the influence of institutional performance over satisfaction with democracy, and I test some empirical hypothesis derived from the model, using a multilevel approach. The results show that economic performance is one of the most important dimensions of institutional performance that affect the overall level of satisfaction with democracy. Results also show that other dimensions of institutional performance, such as accountability, have a significant impact on democratic satisfaction. *Paper presented at the Comparative Study of the Electoral Systems Plenary held in Seville (Spain) in March 2006. Preliminary draft. Not to be quoted.
Hyperscaling Violation in N = 2 Gauged Supergravity Jakob

In recent years there has been much interest in the application of holography to condensed matter physics. In particular, gravity duals with non-relativistic scaling symmetries have been constructed for this purpose. These are known as Lifshitz and Schrödinger spacetimes. Recently, metrics with hyperscaling violation have also become important. These are not invariant under the non-relativistic scaling, but instead scale covariantly. In this thesis, the equations of motion of four-dimensional N = 2 gauged supergravity are derived in order to find Lifshitz solutions with non-zero hyperscaling violation. Both vector multiplets and gauged hypermultiplets are included in this general analysis. Focussing then on the F = −iX0X1 model, which contains a single vector multiplet coupled to gravity, explicit solutions are found. Further, it is shown that one of these solutions solves first-order flow equations. This implies that the solution is supersymmetric. Along the way, relevant topics are introduced, such as special Kähler manifolds, quaternionic Kähler manifolds, gauging of N = 2 supergravity, and also some aspects of non-relativistic holography and the formalism of first-order flow equations.
Center for Indian Country Development

Affordable access to capital and quality housing is a challenge facing Native Americans. In this paper, we demonstrate that mortgage loans with Native Americans as the primary borrower are systematically more likely to be higher-priced. These loans have an average interest rate nearly 2 percentage points above the average loan for non-Native Americans. We also demonstrate that these higher-priced home loans are predominately found on reservation lands and that manufactured homes account for nearly 25 percent to 35 percent of the difference in the cost of financing. These results potentially suggest that without other institutional market reforms, promoting homeownership as a method of increasing Native American equity and assets may be less effective than for other populations.
A collaborative digital game using storytelling to foster empathy in children

Context:​ Empathy, as the ability to feel for others and take their perspective, is shown to be an important skill for good daily functioning. Simultaneously, multidisciplinary professions are working together in the game industry to create serious games with the purpose of teaching a lesson or skill. Storytelling has always been a natural way for humans to learn about the experience of others. However, very few of the serious games being made today look at the potential of storytelling as a means of fostering empathy, and in consequence, this is a topic that deserves further exploration. Objective:​ In this project, storytelling is used in a digital game for fostering empathy. This vision inspired the following research questions: ● RQ1: How can digital games be used to foster empathy in children? ● RQ2: What elements are needed in a serious game to sustain the interest of the players? ● RQ3: What methods are available to measure the impact of a digital game on players’ empathy? ● RQ4: What elements of a serious game using storytelling appear to be the most effective in increasing children’s empathic abilities? Method: ​A classification of available research methods to be used in the master’s thesis is presented in this report. Results: ​A design prototype of a digital game that uses collaborative storytelling to foster empathy has been created. The target audience is set to 10-14 years and the gameplay is designed to give the players ownership of a character and their goal, before asking them to collectively tell the story of their struggles and triumphs. Furthermore, this report’s literature review contributes to answering RQ1 and RQ2. Conclusion: ​This specialization project has presented a literature review in the related areas, which resulted in a set of revised research questions. A design prototype for a new game concept has been presented, with prioritised functional and non-functional requirements. Additionally, a discussion of the methodology is given, along with a detailed evaluation plan.
ON THE GRID REFINEMENT RATIO FOR ONE-DIMENSIONAL ADVECTIVE PROBLEMS WITH NONUNIFORM GRIDS

The purpose of this work is to analyse the usual definition of grid refinement ratio used with irregular grids (unstructured, nonuniform and nonorthogonal), as weel as to define its aplicability. The main reasons for this subject are as follows: the grid refinement ratio is a parameter that directly affect the estimated discretization error made by several estimators; and irregular grids are largely used to obtain numerical solutions. The mathematical model used in this work is the one-dimensional advection of a scalar with source term. This model has known analytical solution, which is compared to numerical solution obtained through the finite difference method. It was verified that the usual definition of grid refinement ratio used with irregular grids is incorrect, even for the simpliest irregular grid, i.e. onedimensional and nonuniform grid. But it is correct if a nonuniform grid is refined of a uniform way.
Leachate Quality from Simulated Landfills Containing CCA-Treated Wood

Landfills represent the predominant disposal method for discarded CCA-treated wood in the US. The current lack of economically viable recycling options for this material will likely result in continued reliance on landfill disposal for the foreseeable future. Previous research has shown that arsenic, copper and chromium leach from CCA-treated wood when in contact with water. Leaching is expected to occur in a landfill as rainwater infiltrates into the waste. In a landfill, however, the biological, chemical and physical reactions that occur may have a great impact the mobility of the metals from CCA-treated wood. Research was conducted to explore this issue. Experimental landfills were constructed to represent three different disposal scenarios: construction and demolition (C&D) debris landfills, municipal solid waste (MSW) landfills, and wood-only monofills. CCA-treated wood is often managed in C&D debris landfills; in many US locations these facilities are unlined. In other locations, CCA-treated wood is disposed in lined MSW landfills. These two disposal scenarios have different chemical environments and the metals may thus behave differently in each environment. While CCA-treated wood is not currently managed in monofills, this option represents conditions where maximum metals concentrations would likely occur. Six lysimeters (simulated landfill columns), two for each disposal scenario, were constructed and operated; both a control lysimeter (containing no CCA-treated wood) and an experimental lysimeter containing CCA-treated wood were included for each scenario. Natural and simulated rainwater were allowed to infiltrate and percolate through the waste in the lysimeters creating leachate. Leachate generated by the lysimeters was collected and analyzed for arsenic, copper and chromium concentrations, as well as general leachate indicator parameters from the fall of 2001 through the summer of 2003. This paper summarizes the preliminary results of metal concentrations in the leachate over time and explores possible mechanisms for leaching. The potential environmental impacts of disposal in each scenario are discussed.
Clone Swarm: A Cloud Based Code-Clone Analysis Tool

A code clone is defined as a pair of similar code fragments within a software system. While code clones are not always harmful, they can have a detrimental effect on the overall quality of a software system due to the propagation of bugs and other maintenance implications. Because of this, software developers need to analyse the code clones that exist in a software system. However, despite the availability of several clone detection systems, the adoption of such tools outside of the clone community remains low. A possible reason for this is the difficulty and complexity involved in setting up and using these tools. In this paper, we present Clone Swarm, a code clone analytics tool that identifies clones in a project and presents the information in an easily accessible manner. Clone Swarm is publicly available and can mine any open-sourced GIT repository. Clone Swarm internally uses NiCad, a popular clone detection tool in the cloud and lets users interactively explore code clones using a web-based interface at multiple granularity levels (Function and Block level). Clone results are visualized in multiple overviews, all the way from a high-level plot down to an individual line by line comparison view of cloned fragments. Also, to facilitate future research in the area of clone detection and analysis, users can directly download the clone detection results for their projects. Clone Swarm is available online at clone-swarm.usask. ca. The source code for Clone Swarm is freely available under the MIT license on GitHub.