Miracle-dz/UniFAR-FTUs huggingface dataset:
Chicken & Egg : Dependencies in Security Testing and Compliance with Common Criteria Evaluations

Common Criterion security evaluations require an analysis of test dependencies present (if any) during the testing activities of an application under evaluation. Such analysis is required to ensure that no fault masking occurs. In this paper, we present 1) a formalization of the notion of test dependencies from fault masking perspective in terms of a test dependency graph (TDG), 2 ) a model based approach for derivation of a TDG for a set of use cases, 3) an algorithm which derives a test order from a TDG to minimize the debugging cost, and 4) results from a case study using a secure smart card operating system. Our results indicate that fault masking in the presence of test dependencies is not a serious concern.
DIGITALIZED ELECTRONICALLY COMMUTATED MOTORS FOR E-BIKE

Now a day, environments get polluted due to more vehicle emission and having lack of source to a vehicle. To build less polluted environment and to reduce fuel cost for a vehicle, move to use E-bike. In today’s, market E-bike is available with controller, which triggers switches without sensing the hall sensor output . Due to insensible operation of controller, motor getting transient damages. In addition to this, controller supplied by high power range battery connected in series. Due to this, weight and cost of the overall e-bike To overcome this limitation, move to use of digital electronic commutation controller with dual boost controller. Because, the digital controller having precision control and high efficient outputs with low cost. This paper shows the implementation of 3-phase BLDC motor drive by digital commutator with double boost controller as a source. The method shown utilizes the HALL sensors in the motor to determine the motors rotor position and effect commutation. Finally, the proposed topology is simulated by MATLAB/SIMULINK and verified by using hardware. Main goal of this paper is increase the life span and efficiency of motor with low cost.
Incremental Visualization of Growing Music Collections

Map-based visualizations – sometimes also called projections – are a popular means for exploring music collections. But how useful are they if the collection is not static but grows over time? Ideally, a map that a user is already familiar with should be altered as little as possible and only as much as necessary to reflect the changes of the underlying collection. This paper demonstrates to what extent existing approaches are able to incrementally integrate new songs into existing maps and discusses their technical limitations. To this end, Growing Self-Organizing Maps, (Landmark) Multidimensional Scaling, Stochastic Neighbor Embedding, and the Neighbor Retrieval Visualizer are considered. The different algorithms are experimentally compared based on objective quality measurements as well as in a user study with an interactive user interface. In the experiments, the well-known Beatles corpus comprising the 180 songs from the twelve official albums is used – adding one album at a time to the collection.
Automatic Segmentation of the Papilla in a Fundus Image Based on the C-V Model and a Shape Restraint

For computer aided Glaucoma diagnostics it is essential to robustly and automatically detect and segment the main regions, e.g. the papilla (optic nerve head), in a fundus image. In this paper an effective method for automatic papilla segmentation based on the C-V model and a shape restraint is proposed. The method is a combination between the C-V model using level sets and the elliptic shape restraint for papilla segmentation. The combination of the level set framework with a shape restraint ensures that the evolving curve stays an ellipse. Experiments verify that the method shows a good performance in detecting the papilla shapes and computing the shape feature parameters within a broad variety of fundus images. The experiment results also show that the method is robust to noise and object deformity
An octree-based multiresolution approach supporting interactive rendering of very large volume data sets

Author(s): Pinskiy, Dimitriy V. ; Brugger, Eric S. ; Childs, Hank; Hamann, Bernd | Abstract: We present an octree-based approach supporting multiresolution volume rendering of large data sets. Given a set of scattered points without connectivity information, we impose an actree data structure of low resolution in the preprocessing step. The construction of this initial octree structure of low resolution in the preprocessing step. The construction of this initial octree structure is controlled by the original data resolution and cell-specific error values. Using the octree nodes, rather than the data points, as elementary units for ray casting, we first generate a crude rendering of a given data set. Keeping the pre-processing step independent from the rendering step, we allow a user to interactively explore a large data set by speicifying a region of interest (ROI), where a higher level of rendering accuracy is desired. To refine an ROI, we are making use of the octree constructed in the pro-processing step. Our approach is aimed at minimizing the number of computations and can be applied to large-scale data exploration tasks.
Living (dangerously) without a fiscal union. Bruegel Working Paper 2015/03

The euro area’s political contract requires member nations to rely principally on their own resources when confronted with severe economic distress. Since monetary policy is the same for all, national fiscal austerity is the default response to counter national fiscal stress. Moreover, the monetary policy was itself stodgy in countering the crisis, and banking-sector problems were allowed to fester. And it was considered inappropriate to impose losses on private sector creditors. Thus, the nature of the incomplete monetary union and the self-imposed taboos led deep and persistent fiscal austerity to become the norm. As a consequence, growth was hurt, which undermined the primary objective of lowering the debt burden. To prevent a meltdown, distressed nations were given official loans to repay private creditors. But the stress and instability continued and soon it became necessary to ease the repayment terms on official loans. When even that proved insufficient, the German-inspired fiscal austerity was combined with the deep pockets of the European Central Bank. The ECB’s safety net for insolvent or near-insolvent banks and sovereigns, in effect, substituted for the absent fiscal union and drew the central bank into the political process.
Regulation of Apoptosis in Human Cancer Cells

Nitric oxide is postulated to protect cancer cells from the deathinducing effects of tumour necrosis factor alpha by S-nitrosating the active site cysteines, inhibiting cleavage of caspase-9. We aimed to test this hypothesis and to determine its validity across cancer cell types. In addition, we hoped to explain the involvement of certain kinases in nitric oxide-induced apoptosis. The experimental setup involved stimulating human colorectal cancer cells, HT-29 and HCT116, and human prostate cancer cells, LNCaP, with cytokines in order to induce cell death. Then, we observed the effects of NO inhibitors, kinase inhibitors, and activation of Akt, a kinase up-stream of the caspase cascade, following transfection of a DNA sequence that was proven to protect cells against apoptosis induction. In our series of experiments, inhibition of the nitric oxide synthases removes nitric oxide protection from apoptosis, but inhibition of only the inducible synthase has opposite effects with prostate and colon cancer cells that are considered insignificant, and its effects on the two types of colon cancer cells are in discord. Transformation and transfection of ARK5 into the colorectal cancer cell line, HT29 did not prove beneficial. Similarly, glucosamine showed no clear pattern of reducing apoptosis in the cells. Therefore, we propose further exploration of the inhibition of constitutive nitric oxide synthases as a potential therapy. Thesis Supervisor: Steven R. Tannenbaum Title: Underwood Prescott Professor of Toxicology and Professor of Chemistry
The Elimination of Spatial-Temporal Uncertainty in Underwater Sensor Networks

Since data in underwater sensor networks (UWSNs) is transmitted by acoustic signals, the characteristics of a UWSN are different from those of a terrestrial sensor network. Specifically, due to the high propagation delay of acoustic signals in UWSNs, referred as spatial-temporal uncertainty, current terrestrial MAC schemes do not work well in UWSNs. Hence, we consider spatial-temporal uncertainty in the design of an energy-efficient TDMA-based MAC protocol for UWSNs. We first translate the TDMA-based scheduling problem in UWSNs into a special vertex-coloring problem in the context of a spatial-temporal conflict graph (ST-CG) that describes explicitly the conflict delays among transmission links. With the help of the ST-CG, we propose two novel heuristic approaches: 1) the traffic-based one-step trial approach (TOTA) to solve the coloring problem in a centralized fashion; and for scalability, 2) the distributed traffic-based one-step trial approach (DTOTA) to assign the data schedule for tree-based routing structures in a distributed manner. In addition, a mixed integer linear programming (MILP) model is derived to obtain a theoretical bound for the TDMA-based scheduling problem in UWSNs. Finally, a comprehensive performance study is presented, showing that both TOTA and DTOTA guarantee collision-free transmission. They thus outperform existing MAC schemes such as S-MAC, ECDiG, and T-Lohi in terms of network throughput and energy consumption.
Cooperative Computer System For Genome Sequence Analysis

Analysis of the huge volumes of data generated by large scale sequencing projects clearly requires the construction of new sophisticated computer systems. These systems should be able to handle the biological data as well as the results of the analysis of this data. They should also help the user to choose the most appropriate method for a simple task and to string together the methods needed to solve a global analysis task. In this paper we present the prototype of a software system that provides an environment for the analysis of large-scale sequence data. In a first approach this environment has been put to the test within the B. subtilis sequencing project. This system integrates both a descriptive knowledge of the entities involved (genes, regulatory signals etc.) and the methodological knowledge concerning an extendable set of analytical methods (i.e. how to solve a sequence analysis problem through task decomposition and method selection). A knowledge representation based on two existing object-oriented models, named Shirka and SCARP, is used to implement this integrated system. In addition, the present prototype provides a suitable user interface for both displaying the results generated by several methods and interacting with the objects. We present in this paper an overview of the knowledge-based models used to build this integrated system, and a description of the way in which biological entities and sequence analysis tasks are represented. We give illustrations of the co-operation between user and system during the problem solving process. Such a system constitutes a computer workbench for molecular biologists studying the genetic programs of living organisms.
Application of the steep ramp test for aerobic fitness testing in children with cancer.

BACKGROUND Children with and after cancer are found to have a decreased physical fitness, frequently resulting in decreased physical functioning. The gold standard test for assessing aerobic fitness, a component of physical fitness, is the respiratory gas analyses-based cardiopulmonary exercise test (CPET). However, equipment for gas analysis is often unavailable in local physical therapy centres and non-university hospitals. The steep ramp test (SRT), is a cycle ergometer test with a fast increase in workload, a short duration, and does not require respiratory gas analysis equipment. AIM The aim of this study was to compare the results of the CPET and the SRT, in children with cancer, and to assess whether the SRT can be used for aerobic fitness assessment in clinical practice in this population. DESIGN This study is a cross-sectional assessment using baseline data of a randomized controlled trial. SETTING The study was performed in a hospital setting. POPULATION Sixty-one children (mean age 12.9 years; 33 boys) with cancer were included in the analysis; 16 children were on non-intensive chemotherapy treatment, 45 were in the first year thereafter. METHODS Participants performed both the SRT and the CPET on a cycle ergometer with respiratory gas analysis. Data of the two tests were compared and regression analyses were performed. RESULTS CPET test results revealed a higher impact on the cardiovascular system, as shown by higher peak ventilation (47.8 versus 52.0 Litres per min) and peak heart rates (173 versus 191 beats per min), compared to the SRT. In addition, the test time was significantly longer (90 s versus 390 s). Yet, the primary outcome of the SRT (peak work rate) was able to reliably estimate the peak oxygen uptake of the CPET. CONCLUSION The peak oxygen uptake was comparable between the SRT and the CPET, although the peak work rate was significantly higher during the SRT. This study showed that the SRT is a valid instrument to assess aerobic fitness in children with cancer. CLINICAL REHABILITATION IMPACT The SRT is less time consuming and can be performed without gas analysis in a non-clinical setting, making it less demanding for children.
Performance Events Based Full System Estimation on Application Power Consumption

The value of run-time application power consumption in the full system is a prerequisite for energy optimization. Though past studies have demonstrated the use of performance events for building single component (CPU, Memory, Disk) power model, we propose a method to estimate application power consumption in the full system with performance events. In this paper, we identify different stress on components from CPU-intensive, memory-intensive and I/O-intensive applications. Combining these and the "trickle-down" effect of performance events, the feasibility of estimating application power consumption with a few performance events is demonstrated. Through measurement of actual systems running test sets, these models are shown to have an average error of less than six percent across the considered workloads. Besides, we demonstrated that these models can be applied to real-world applications. Moreover, power models proposed in this paper can provide software developers or system designers with visible power behaviors for the applications. Thus, software developers can make decisions or change code to develop more energy-efficient software.
Wall Clutter Mitigations for Compressive Imaging of Building Interiors

Exterior wall returns affect the accuracy and fidelity of the imaged scene in urban sensing and through-the-wall radar imaging applications. For reliable imaging of stationary indoor scenes, the front wall reflections need to be properly attenuated. In this chapter, wall mitigations are addressed in the context of compressive sensing for stepped-frequency radar operation. Wall mitigation schemes, originally proposed for imaging using full data volume, maintain their proper performance with few measurements, provided that the same reduced set of frequencies is used at each available antenna position. However, having the same frequency observations across all antennas may not always be feasible. For the more challenging case when different reduced frequencies are employed at different antennas, two alternate methods based on discrete prolate spheroidal sequences (DPSS) and partial sparsity can be applied. The former captures the wall clutter energy at each antenna individually using a DPSS basis and then removes it from the reduced set of measurements. The latter considers the stationary scene reconstruction problem when the support of the image corresponding to the exterior and interior walls is known a priori. 4.
A Non-Monotonic Description Logics Model for Merging Terminologies

In order to deal with the Ontology Change problem and considering an environment where Description Logics (DLs) are used to describe ontologies, the question of how to integrate distributed ontologies appears to be in touch with Belief Revision since DL terminologies may define same concept descriptions of a not necessarily same world model. A possible alternative to reason about these concepts is to generate unique concept descriptions in a different terminology. This new terminology needs to be consistently created, trying to deal with the minimal change problem, and moreover, yielding a non-monotonic layer to express ontological knowledge in order to be further updated with new distributed ontologies.
Network Role Analysis in the Study of Food Webs: An Application of Regular Role Coloration

In the last fifteen years, ecosystem ecologists have developed a theoretical approach and a set of computational methods called “ecological network analysis” (Ulanowicz, 1986; Kay et al. 1996). Ecological network analysis is based on input/output models of energy or material flows (e.g., carbon compound flows) through a trophic network (e.g., a food web describing which species eats which other species). Mathematically and conceptually, this ecological network analysis approach is strikingly similar to work in the field of social network analysis, particularly the influence models of Hubbell (1965), Katz (1963), and Friedkin and Johnsen (1990). In food web research, Yodzis and Winemiller (1999), have recently proposed a new way to operationalize the concept of a "trophospecies", which is a set of species with similar foods or predators. Their definition turns out to be identical to the notion of structural equivalence (Lorrain and White, 1971) in social network analysis, particularly as conceived by Burt (1976) and Burt and Talmud (1993). The striking convergence to date of the fields of ecology and sociology via independent invention of network concepts suggests that there may be considerable value in cross-fertilization of the two fields. With this paper we hope to begin a dialogue between the two fields, by applying advanced social role theory and methods to the study of food webs. In social network analysis, the introduction of the notion of structural equivalence thirty years ago was followed by the development of regular coloration (White & Reitz, 1983; Everett & Borgatti, 1991), an important advance over structural equivalence for modeling social roles. The objective of our paper is to answer a call in the ecological literature for greater clarity in thinking about the role of species in ecosystems (Simberloff and Dayan, 1991), by applying the notion of regular coloration to food webs.
Organizational Learning and the Error of Fixed Strategies in IT Innovation Investment Evaluation

Though many IT innovations do not meet the high expectations, the investment evaluation of fashionable IT innovations, that in contrast to mature IT innovations are currently hyped but lack broad institutionalization, often follow a gut feeling. To enhance a company's ability to innovate with IT, literature emphasizes organizational learning through continuous innovating. We extend existing IT innovation literature by developing a dynamic optimization model that determines the optimal allocation of an IT innovation budget to mature and fashionable IT innovations by considering organizational learning. As this theoretical optimum often cannot be implemented in practice, companies apply fixed strategies which seem to be suitable but do not consider the effect of organizational learning and the fashionable IT innovation's probability of success. We examine the evaluation error from under- or overinvestments in fashionable IT innovations and how this error is influenced by organizational learning and a fashionable IT innovation's probability of success.
Time-varying analysis of heart rate variability signals with a Kalman smoother algorithm

A time-varying parametric spectrum estimation method for analysing non-stationary heart rate variability signals is presented. As a case study, the dynamics of heart rate variability during an orthostatic test is examined. In this method, the non-stationary signal is first modelled with a time-varying autoregressive model and the model parameters are estimated recursively with a Kalman smoother algorithm. The benefit of using the Kalman smoother is that the lag error present in a Kalman filter, as well as in all other adaptive filters, can be avoided. The spectrum estimates for each time instant are then obtained from the estimated model parameters. Statistics of the obtained spectrum estimates are derived using the error propagation principle. The obtained spectrum estimates can further be decomposed into separate components and, thus, the time variation of low- and high-frequency components of heart rate variability can be examined separately. By using the presented method, high resolution time-varying spectrum estimates with no lag error can be produced. Other benefits of the method are the straightforward procedure for evaluating the statistics of the spectrum estimates and the option of spectral decomposition.
A Coverage-Driven Verification Platform for Evaluating NoC Performance and Test Structure

NoC (Network-on-Chip) has been proposed as a new solution to deal with the global communication problem of complex SoC(System-on-Chip). An evaluation tool is essential for optimizing the NoC design, through which the functionality and performance of the NoC are verified. This paper presents a coverage-driven and hierarchical NoC verification platform based on System Verilog language. It is applicable to various NoCs with arbitrary size, topology, multiple interface protocols and various test structure. To verify the effectiveness of this platform, Mesh and Totus topology and the corresponding XY or TXY routing algorithms were adopted and applied to random uniform and random hot distribution simultaneously. Furthermore, the platform is also applied for evaluating different test schemes. The results of performance and test structure evaluation show that the verification platform improves the verification efficiency and has good adaptability and scalability as well.
Software/Hardware Co-Design of Modular Exponentiation for Efficient RSA Cryptosystem

This paper presents an implementation of Rivest, Shamir and Adleman (RSA) cryptosystem based on hardware/software (HW/SW) co-design. The main operation of RSA is the modular exponentiation (ME) which is performed by repeated modular multiplications (MMs). In this work, the right-to-left (R2L) algorithm is used for the implementation of the ME as a programmable system on chip (PSoC). The processor MicroBlaze of Xilinx is used for flexibility. The R2L method is often suggested to improve the timing performance, since it is based on parallel computations of MMs. However, if the optimization of HW resources is a constraint, this method can be executed sequentially using a single modular multiplier as a custom intellectual property (IP). Consequently, the execution time of the ME becomes dependent of three factors, namely the capability of the custom IP to perform the MMs, the nonzero bit string of the exponent and the communication link between the processor and the custom IP. In order to achieve the best trade-off between area, speed and flexibility, we propose three implementations in this work. The first one is a pure software solution. The second one takes benefit of a HW accelerator dedicated to the MM execution. The last one is based on a dual strategy. Two parallel MMs are implemented within a custom IP and local memories are used close to the arithmetic units to minimize the communication link influence. The results show that in the application to RSA 1024-bits, the ME runs in 22,25 ms, while using only 1,848 slices.