Miracle-dz/UniFAR-FTUs huggingface dataset:
Demonstration of Damson: Differential Privacy for Analysis of Large Data

We demonstrate Damson, a novel and powerful tool for publishing the results of biomedical research with strong privacy guarantees. Damson is developed based on the theory of differential privacy, which ensures that the adversary cannot infer the presence or absence of any individual from the published results, even with substantial background knowledge. Damson supports a variety of analysis tasks that are common in biomedical studies, including histograms, marginals, data cubes, classification, regression, clustering, and ad-hoc selection-counts. Additionally, Damson contains an effective query optimization engine, which obtains high accuracy for analysis results, while minimizing the privacy costs of performing such analysis.
MULTOVL: fast multiple overlaps of genomic regions

We present the MULTOVL application suite that detects and statistically analyses multiple overlaps of genomic regions in a fast and efficient manner. The package supports the detection of multiple region intersections, unions and 'solitary' genomic regions. The significance of actually observed overlaps is estimated by comparing them with empirical null distributions generated by random shuffling of the input regions.
Gene and Protein Expression following Exposure to Radiofrequency Fields from Mobile Phones

Background Since 1999, several articles have been published on genome-wide and/or proteome-wide response after exposure to radiofrequency (RF) fields whose signal and intensities were similar to or typical of those of currently used mobile telephones. These studies were performed using powerful high-throughput screening techniques (HTSTs) of transcriptomics and/or proteomics, which allow for the simultaneous screening of the expression of thousands of genes or proteins. Objectives We reviewed these HTST-based studies and compared the results with currently accepted concepts about the effects of RF fields on gene expression. In this article we also discuss these last in light of the recent concept of microwave-assisted chemistry. Discussion To date, the results of HTST-based studies of transcriptomics and/or proteomics after exposure to RF fields relevant to human exposure are still inconclusive, as most of the positive reports are flawed by methodologic imperfections or shortcomings. In addition, when positive findings were reported, no precise response pattern could be identified in a reproducible way. In particular, results from HTST studies tend to exclude the role of a cell stressor for exposure to RF fields at nonthermal intensities. However, on the basis of lessons from microwave-assisted chemistry, we can assume that RF fields might affect heat-sensitive gene or protein expression to an extent larger than would be predicted from temperature change only. But in all likelihood, this would concern intensities higher than those relevant to usual human exposure. Conclusions The precise role of transcriptomics and proteomics in the screening of bioeffects from exposure to RF fields from mobile phones is still uncertain in view of the lack of positively identified phenotypic change and the lack of theoretical, as well as experimental, arguments for specific gene and/or protein response patterns after this kind of exposure.
Representation and Control in IxTeT, a Temporal Planner

This paper presents a temporal planner, called IxTeT. It focuses on the representation and control issues, arguing for a compromise between the expressiveness and the efficiency of the search. The representation relies on a point-based reified logic, associated to multi-valued domain attributes. Hierarchical planning operators offer an expressive description, with parallelism, durations, effects and conditions at various moments of the action. Time in the input scenario enables to take into account predicted forthcoming events and to plan in a dynamic world. A compilation procedure checks the consistency of the operators specified by the user. The control relies on the use of causal-links, Ae, algorithm, and an extended least-commitment strategy. It uses two important procedures, called "feasibility" and "satisfiability", dealing respectively with goal decomposition and conflict resolution:
Austerity and Anarchy: Budget Cuts and Social Unrest in Europe, 1919-2009

Does fiscal consolidation lead to social unrest? Using cross-country evidence for the period 1919 to 2008, we examine the extent to which societies become unstable after budget cuts. The results show a clear correlation between fiscal retrenchment and instability. We test if the relationship simply reflects economic downturns, and conclude that this is not the case. While autocracies and democracies show a broadly similar responses to budget cuts, countries with more constraints on the executive are less likely to see unrest after austerity measures. Growing media penetration does not strengthen the effect of cut-backs on the level of unrest.
Use of Eye Movement Desensitization and Reprocessing (EMDR) on Tsunami Victims with Posttraumatic Stress Disorder (PTSD) in Indonesia

After a traumatic experience such as Tsunami, individuals differ in their rate and extent of recovery. Many Indonesian developed symptoms of post-traumatic stress disorder (PTSD), which include re-experiencing the trauma memory, avoidance of thoughts and feelings associated with the trauma, and hyperarousal symptoms. The Tsunami causes symptoms of PTSD in Indonesian students who lived in Malaysia. The objectives of the present study were to determine the prevalence of PTSD among Indonesian students after five year who are studying in Malaysia and to determine the effectiveness of EMDR as a program in reducing PTSD symptoms among these students. The participants of this study were 40 Indonesian students (20 male and 20 female). The Impact of the Events Scale (IES-R) was used. Then . EMDR was used in students who diagnosed with PTSD, and the results suggested that EMDR was effective in reducing PTSD.
Opposition based levy flight search in differential evolution algorithm

Differential Evolution (DE) is a simple and fast population based Nature Inspired Algorithm (NIA). When it is experimented for benchmark problems as well as real world problems it outperformed other population based NIAs and other search metaheuristics in terms of rate of convergence. But it is not an exception in class of population based algorithms, it also show premature convergence and stagnates at suboptimal points. Therefore this paper tries to sustain a better convergence speed and keep away from stagnation by introducing levy flight random search process along with opposition based learning strategy in original DE algorithm. The proposed algorithm named as Opposition Based Levy Flight Search in DE (OLFDE) Algorithm. The newly proposed algorithm OLFDE tested over fourteen benchmark problems and three real world problems (Pressure Vessel Design, Parameter estimation for frequency modulated sound wave and Compression Spring problem) in order to prove its efficiency over some recent variants of DE.
Co-Evolution of Genomic Structure and Selective Forces Underlying Sexual Development and Reproduction

Genomic structure affects the expression and evolution of phenotypes via its effect on genomic function. One example is the presence of sex chromosomes and the development of the sexual phenotype. Multiple forces account for the evolution of genomic structure and function, some acting synergistically and some in an antagonistic manner, in a co-evolutionary process between genomic architecture and environmental effects at different time scales. Here I review the evolution of sex chromosomes and how they affect sex determination, sex ratios, sexual selection, and sexual conflict, at the same time that these phenomena influence the evolution of genome organization. Because of this reciprocal interaction, the need to correctly identify sex chromosome systems in order to understand the causes and consequences of their evolution is emphasized. Importantly, it is argued that the existence of taxa lacking sex chromosomes poses a challenge to current evolutionary models and a unique opportunity to test them empirically using reptiles as a model system.
Not for distribution or attribution : for review purposes only . Protecting Freedom of Information Online with Freenet

Privacy and free expression online are coming increasingly under threat from pervasive monitoring and filtering technologies as well as from corporate and governmental actions against those who disseminate controversial information. In response to these challenges, we are developing Freenet, an adaptive peer-to-peer file storage network that permits the publication and retrieval of data while protecting the anonymity of information producers, consumers, and storers. Freenet operates as a self-organizing collaborative network of individual nodes that pool spare storage space to store files and route requests in decentralized yet scalable manner. Files are accessed by location-independent keys and are dynamically replicated and relocated to provide efficient use of resources in response to demand. Freenet makes it extremely difficult to discover the ultimate origin or destination of files passing through the network while providing for strong authentication and flexible file management. Node operators are also given protection against liability for the contents of their nodes. We present simulation results to demonstrate Freenet’s scalability and fault-tolerance characteristics with reference to a smallworld network model.
A partial differential equation variational approach for simultaneous image denoising and contrast enhancement

Reducing noise while enhancing contrast and preserving edges is one of the most fundamental operations of image processing. However, noise reduction and contrast enhancement are conflicting requests, thus it is difficult to realize these two requests at the same time. In this paper, we propose two novel models for simultaneous image denoising and contrast enhancement using partial difference equation variational approach. The first model is based on modification of the classical simultaneous model, the other is total variation based image restoration. Both models are found to be effective in reducing staircasing effect while suppressing the artifacts along with both the theoretical and empirical analyses. Specifically, we resort to the total variation minimization method for image denoising and the piecewise linear stretching function to perform contrast enhancement. This paper seeks to combine these two different procedures with the same equation in a principled way. For numerical implementation, the step size of finite difference is adaptively chosen according to the curvature, leading to fewer iteration steps and satisfactory image quality. Experimental results demonstrate significant improvement over widely used algorithms in both objective and subjective image quality both quantitatively and visually.
Graph classification: a diversified discriminative feature selection approach

A graph models complex structural relationships among objects, and has been prevalently used in a wide range of applications. Building an automated graph classification model becomes very important for predicting unknown graphs or understanding complex structures between different classes. The graph classification framework being widely used consists of two steps, namely, feature selection and classification. The key issue is how to select important subgraph features from a graph database with a large number of graphs including positive graphs and negative graphs. Given the features selected, a generic classification approach can be used to build a classification model. In this paper, we focus on feature selection. We identify two main issues with the most widely used feature selection approach which is based on a discriminative score to select frequent subgraph features, and introduce a new diversified discriminative score to select features that have a higher diversity. We analyze the properties of the newly proposed diversified discriminative score, and conducted extensive performance studies to demonstrate that such a diversified discriminative score makes positive/negative graphs separable and leads to a higher classification accuracy.
PhTM: Phased Transactional Memory

Hybrid transactional memory (HyTM) [3] works in today’s systems, and can use future “best effort” hardware transactional memory (HTM) support to improve performance. Best effort HTM can be substantially simpler than alternative “unbounded” HTM designs being proposed in the literature, so HyTM both supports and encourages an incremental approach to adopting HTM. We introduce Phased Transactional Memory (PhTM), which supports switching between different “phases”, each implemented by a different form of transactional memory support. This allows us to adapt between a variety of different transactional memory implementations according to the current environment and workload. We describe a simple PhTM prototype, and present experimental results showing that PhTM can match the performance and scalability of unbounded HTM implementations better than our previous HyTM prototype when best effort HTM support is available and effective, and is more competitive with state-of-the-a rt software transactional memory implementations when it is not.
Designing X Control Chart Using DEA Approach

Control charts are widely implemented in firms to establish and maintain statistical control of a process which leads to the improved quality and productivity. Design of control charts requires that the engineer selects a sample size, a sampling frequency and the control limits for the chart. In this paper, a possible combination of design parameters is considered as a decision making unit which is identified by three attributes: hourly expected cost, detection power of the chart and in-control average run length. Optimal design of control charts can be formulated as multiple objective deci sion making (MODM). We have extended cost function from single to multiple assignable causes to near the model to the real situations. An algorithm using DEA is applied to solve the MODM model. A numerical example is used to illustrate the algorithm procedure.
HIDDEN MARKOV MODELS TO ANALYZE USER BEHAVIOUR IN NETWORK TRAFFIC

Understanding the nature of information flowing int o a system or network is fundemantal to determining anomalies and characterizing workload. Traditional methods rely heavily on port numbers carried in the packet headers to classify p rotocols.These methods can fail in the presence of proxy servers,that re-map port numbers, or compromised host services. Another fact is that in encrypted traffic, we do no t have more than packet-level information provided.We present a novel approach to protocol de tection with less information than one might consider.We only carry out the detection proc ess with timing and connected server informations.
MILPRIT*: A Constraint-Based Algorithm for Mining Temporal Relational Patterns

In this article, we consider a new kind of temporal pattern where both interval and punctual time representation are considered. These patterns, which we call temporal point-interval patterns, aim at capturing how events taking place during different time periods or at different time instants relate to each other. The datasets where these kinds of patterns may appear are temporal relational databases whose relations contain point or interval timestamps. We use a simple extension of Allenâ€™s Temporal Interval Logic as a formalism for specifying these temporal patterns. We also present the algorithm MILPRIT* for mining temporal point-interval patterns, which uses variants of the classical levelwise search algorithms. In addition, MILPRIT* allows a broad spectrum of constraints to be incorporated into the mining process. An extensive set of experiments of MILPRIT* executed over synthetic and real data is presented, showing its effectiveness for mining temporal relational patterns.
Active Learning in Research Methods Classes Is Associated with Higher Knowledge and Confidence, Though not Evaluations or Satisfaction

Research methods and statistics are regarded as difficult subjects to teach, fueling investigations into techniques that increase student engagement. Students enjoy active learning opportunities like hands-on demonstrations, authentic research participation, and working with real data. However, enhanced enjoyment does not always correspond with enhanced learning and performance. In this study, we developed a workshop activity in which students participated in a computer-based experiment and used class-generated data to run a range of statistical procedures. To enable evaluation, we developed a parallel, didactic/canned workshop, which was identical to the activity-based version, except that students were told about the experiment and used a pre-existing/canned dataset to perform their analyses. Tutorial groups were randomized to one of the two workshop versions, and 39 students completed a post-workshop evaluation questionnaire. A series of generalized linear mixed models suggested that, compared to the students in the didactic/canned condition, students exposed to the activity-based workshop displayed significantly greater knowledge of the methodological and statistical issues addressed in class, and were more confident about their ability to use this knowledge in the future. However, overall evaluations and satisfaction between the two groups were not reliably different. Implications of these findings and suggestions for future research are discussed.
A linear mixed finite element scheme for a nematic Ericksen–Leslie liquid crystal model

In this work we study a fully discrete mixed scheme, based on continuous finite elements in space and a linear semi-implicit first-order integration in time, approximating an Ericksen–Leslie nematic liquid crystal model by means of a Ginzburg–Landau penalized problem. Conditional stability of this scheme is proved via a discrete version of the energy law satisfied by the continuous problem, and conditional convergence towards generalized Young measure-valued solutions to the Ericksen–Leslie problem is showed when the discrete parameters (in time and space) and the penalty parameter go to zero at the same time. Finally, we will show some numerical experiences for a phenomenon of annihilation of singularities.
Recognizing Human Actions in Video Sequences

Recognizing human actions is a challenging problem in computer vision. In this work, a bag-of-words approach is taken to solving this problem. Each video sequence is represented as a document and each frame in a sequence corresponds to a ”‘word”’. Although a bag-of-words model may not seem intuitive for data other than text, it has shown to be quite successful in object recognition problems in computer vision, and may prove to be a simple yet powerful model for recognizing human actions in video sequences. This particular model is probabilistic one trained in a semi-supervised way using a variant of the Latent Dirichlet Allocation model.
Applying set based methodology in submarine concept design

Abstract : Early stage ship design decisions continue to be a challenge for naval architects and engineers. The complex interactions between the different elements of the ship and the broad spectrum of disciplines required in ship design make it difficult to fully realize the effects and limitations early decisions place on design flexibility. U.S. Navy design is exploring the use of Set Based Design (SBD) principles and methodology in designing the fleet for the 21st century. Existing research has shown the merits of SBD in other industries; however, research on the use of SBD in naval design does not exist. The thesis explores how to execute SBD in light of the recent restructuring of the U.S. Navy acquisition process calling for the use of SBD in pre-preliminary design. This is undertaken using the knowledge gained from exploration of the Ship-to-Shore Connector (SSC) program, the first use of SBD in a new start acquisition program. The thesis concludes by applying the derived information to an early stage submarine concept design. This effort focused on how to develop submarine design parameters and exploration of how to create and reduce integrated concepts.
Efficient access control for service-oriented IT infrastructures: enabling secure distributed service compositions

Service-oriented architectures provide high levels of inter-operability and high means of adaptability. Nevertheless, distributed service-based business processes demand for robust, flexible and - bearing scalability in mind - efficient security mechanisms. This book presents access control models and procedures for intra- and inter-organizational service compositions. It introduces a framework for distributed access control in Web service federations and highlights optimizations through the consolidation of security policies and the caching of access control information. In combination, these concepts enable efficient and reliable access control for current and upcoming service-oriented architectures. As the presented techniques build up on prevalent security standards like WS-Security and XACML, application developers, system designers, and security experts will be able to seamlessly transfer them to their particular Web service-based projects.
Noise Reduction Based on Partial-Reference, Dual-Tree Complex Wavelet Transform Shrinkage

This paper presents a novel way to reduce noise introduced or exacerbated by image enhancement methods, in particular algorithms based on the random spray sampling technique, but not only. According to the nature of sprays, output images of spray-based methods tend to exhibit noise with unknown statistical distribution. To avoid inappropriate assumptions on the statistical characteristics of noise, a different one is made. In fact, the non-enhanced image is considered to be either free of noise or affected by non-perceivable levels of noise. Taking advantage of the higher sensitivity of the human visual system to changes in brightness, the analysis can be limited to the luma channel of both the non-enhanced and enhanced image. Also, given the importance of directional content in human vision, the analysis is performed through the dual-tree complex wavelet transform (DTWCT). Unlike the discrete wavelet transform, the DTWCT allows for distinction of data directionality in the transform space. For each level of the transform, the standard deviation of the non-enhanced image coefficients is computed across the six orientations of the DTWCT, then it is normalized. The result is a map of the directional structures present in the non-enhanced image. Said map is then used to shrink the coefficients of the enhanced image. The shrunk coefficients and the coefficients from the non-enhanced image are then mixed according to data directionality. Finally, a noise-reduced version of the enhanced image is computed via the inverse transforms. A thorough numerical analysis of the results has been performed in order to confirm the validity of the proposed approach.