Miracle-dz/UniFAR-FTUs huggingface dataset:
THREE-DIMENSIONAL MAPPING WITH AIRBORNE IFSAR BASED STAR TECHNOLOGY INTERMAP ' S EXPERIENCES

Airborne Interferometric Synthetic Aperture Radar (IFSAR or INSAR) is maturing as a cost-effective three-dimensional mapping technology. It is attracting increased attention in the geospatial community because of its unique operational advantages. Various mapping products are being generated by Intermap’s STAR technology which is based on high-resolution airborne IFSAR. More significantly, these STAR derived products are being used for applications traditionally supported by other mapping technologies and this list of applications is growing. This trend is due to the ever-increasing customer confidence towards the STAR derived data. Involved with IFSAR technology since 1993, Intermap is diligently working to exploit the potential of this technology and to develop new, market specific applications. To reach a more widespread acceptance and a deeper and wider application base, Intermap’s STAR technology and its mapping products are continuously presented to the general geospatial public from the early adopters through the general provider. Experiences obtained from those applications are highly beneficial to potential users. The objective of this paper is to give the reader a general picture of airborne IFSAR mapping in order for them to better understand the strengths and limitations of the technology and the products.
Life After Self-Healing : Assessing Post-Repair Program Behavior

One promising technique for defending software systems against vulnerabilities involves the use of self–healing. Such efforts, however, carry a great deal of risk because they largely bypass the cycle of human–driven patching and testing used to vet both vendor and internally developed patches. In particular, it is difficult to predict if a repair will keep the behavior of the system consistent with “normal” behavior. Assuring that post–repair behavior does not deviate from normal behavior is a major challenge to which no satisfactory solutions exist. We investigate the feasibility of automatically measuring behavioral deviations in software that has undergone a self–healing repair. We provide a first examination of the problem of assessing a repair’s impact on execution behavior, and we define a model for representing post–repair behavior using machine–level intraprocedural control flow. In essence, we advocate performing anomaly detection on an application’s execution after it has been attacked and subsequently repaired. Our goal, however, is not to detect an attack, but rather to provide a tool for assisting a system administrator to perform vulnerability triage. Our system can help them discover the relative impact of a repair so that they can begin to track down and analyze the cause of post–repair execution anomalies.
Coval: Improving Alignment Quality and Variant Calling Accuracy for Next-Generation Sequencing Data

Accurate identification of DNA polymorphisms using next-generation sequencing technology is challenging because of a high rate of sequencing error and incorrect mapping of reads to reference genomes. Currently available short read aligners and DNA variant callers suffer from these problems. We developed the Coval software to improve the quality of short read alignments. Coval is designed to minimize the incidence of spurious alignment of short reads, by filtering mismatched reads that remained in alignments after local realignment and error correction of mismatched reads. The error correction is executed based on the base quality and allele frequency at the non-reference positions for an individual or pooled sample. We demonstrated the utility of Coval by applying it to simulated genomes and experimentally obtained short-read data of rice, nematode, and mouse. Moreover, we found an unexpectedly large number of incorrectly mapped reads in ‘targeted’ alignments, where the whole genome sequencing reads had been aligned to a local genomic segment, and showed that Coval effectively eliminated such spurious alignments. We conclude that Coval significantly improves the quality of short-read sequence alignments, thereby increasing the calling accuracy of currently available tools for SNP and indel identification. Coval is available at http://sourceforge.net/projects/coval105/.
Vision-based railroad track extraction using dynamic programming

Most of the common driver assistant systems for detection of obstacles work on unstructured environments. These environments generally include many non-planar surfaces which pose a big challenge for vision systems. Similar problems exist for railroad environments which often contain complex shapes and surfaces like hills and vegetation along railroad tracks. In railroad transportation, the main task of a train driver is to carefully focus on the track. Therefore the field of view of a train driver must contain the space between two rails in front of the train and the near lateral area (left and right side) of these rails. In this paper, we present an algorithm to extract the train course and railroad track space in front of the train using dynamic programming in railroad environments. We use dynamic programming to compute the optimal path which gives the minimum cost to extract the railroad track space. The proposed algorithm extracts the left and right rails using dynamic programming simultaneously. Our method does not need any static calibration process. For this purpose, a camera system was installed in front of a locomotive. Experimental results show the effectiveness of the algorithm.
A Specialization of the k { Nearest Neighbor Classi cation Rule forthe Prediction of Dynamical Systems Using FIR

Fuzzy Inductive Reasoning (FIR) is a methodology for qualitative modeling and simulation of systems behavior. FIR inference engine is based on the k-nearest neighbor (k-NN) rule, commonly used in the Pattern Recognition eld. The adaptation of the k-NN in an ad hoc 5-NN method has been proved to be very successful in the past, obtaining good results for diierent kind of systems. However, in some circumstances the prediction is not as good as expected. This paper describes the specialization of the k-NN for the prediction of dynamic systems using FIR, and introduces the concept of Causal Relevancy as an important reenement in the inference engine in order to overcome some deeciencies during the forecast stage. Shannon Entropy measures have been applied to take into account the relative importance of each element in the input vector, a semi{Euclidean distance measure is obtained to found neighbors of a better quality.
An efficient scheduling policy for edge routers to speedup the Internet access

Recent Internet traffic measurements reveal that Internet traffic exhibits high coefficient of variability (CoV). That is, the Internet traffic consists of many small jobs and very few large jobs, and less than 1% of the largest jobs constitute more than half of the load. Consequently, we propose to use policies that take advantage of this attribute to favor small jobs over large jobs. If such a policy is implemented in an edge router, this would mean that short jobs such as HTTP sessions will see their latency reduced. The shortest remaining processing time first (SRPT) scheduling policy has been known to be an optimal policy in minimizing the mean response time. Recent work [2] has shown that for job size distributions with high coefficient of variability (CoV), SRPT favors small jobs without unfairly penalizing large jobs. An implementation of SRPT requires that the sizes of all jobs be known, which can not be assumed in most networking environments. In this paper, we analyze the ForegroundBackground-Infinity ( ) scheduling policy, which is a priority policy that is known to favor small jobs the most among the scheduling policies that do not require the knowledge of job sizes. However, when evaluated under the M/M/1 queueing model, has been shown to highly penalize many large jobs in favor of small jobs. In this paper, we analyze the M/G/1/ queue the objective being to investigate the fairness of by comparing its slowdown to the slowdown offered by PS, to quantify the response time improvement that offers when used instead of FIFO, and to compare to an optimal policy SRPT, for service distributions with varying CoVs. Finally, we consider under overload where we analyze its stability and derive its expression for the
Optimal Design of Structure Using Relative Diffrence Quotient Algorithm and Improved Genetic Agorithm

The optimization design of structure with discrete variables is generally a combinatorial optimization problem. Being simple genetic algorithm has the defects of premature phenomenon, slow convergence speed and poor stability, a hybrid genetic algorithm is proposed to deal with structure optimization based on relative difference quotient method and improved genetic algorithm. The advantages of genetic algorithm in global optimization and relative difference quotient method in local searching ability are both included in this method. A numerical example of a 25-bar frame was given to demonstrate the validity and feasibility in its application, and the experimental results show that the hybrid GA can obtain better results than other optimal design methods in structure optimal design.
The CMVAI-File: An Efficient Approximation-Based High-Dimensional Index Structure

Similarity-Search based index structure is an important topic in many application areas, such as content-based multimedia information retrieval, data mining, cluster analysis, etc. In order to improve query performance in high-dimensional vector spaces, lots of index structures have been proposed. However, many well-known index structures encounter “dimensional curse” while the dimension of feature vector increase. In order to solve such problem, researchers analyzed the nearest-neighbor search problem in high-dimensional vector spaces deeply and proposed some approximation-based index structures. The VA-File which is the first implement approximation-based index structures has done well in solving “dimensional curse” problem. However, approximate vectors in VA-File are just simply placed in flat structure files without other optimization methods. In this paper, we propose the Collecting and Multi-Vector-Approximation Indexed-File (CMVAI-File). The CMVAI-File is still an approximate-based index structure and uses a filter-based approach. Unlike the VA-File, the CMVAI-File uses multi-level approximate, collect the same vector-approximations and a segmental structure to improve query performance. Experimental results show that CMVAI-File has a promising improvement in performance.
Ultrasound-guided sacroiliac joint injection in patients with established sacroiliitis: precise IA injection verified by MRI scanning does not predict clinical outcome.

OBJECTIVE IA injections of SIJs with corticosteroids are often performed in patients suffering from low back pain due to active sacroiliitis. However, SIJ injections are technically demanding, and therefore the clinical outcome of ultrasound-guided corticosteroid SIJ injections was analysed in relation to the accuracy of the injection. METHODS Ultrasound-guided injections were performed with 40 mg triamcinolone and 0.78 mg gadolinium in 20 SIJ of 14 consecutive patients suffering from active sacroiliitis. Immediately following SIJ injection, MRI scanning was initiated to verify the correct placement of the drug. Clinical outcome of the intervention was determined using a numerical pain rating scale (NRS) at Days 1 and 28. RESULTS Despite ultrasound guidance, only 8 injections (40%) were exactly positioned into the SIJ space, whereas the other 12 injections (60%) missed the SIJ. However, there were no significant differences observed in the clinical outcome between the IA-injected group and the peri-articular-injected group. There was similar pain relief observed in both groups 24 h and 28 days following the intervention [IA injection group: mean NRS-baseline: 6.8 (range 4-9), NRS-24 h: 4.3 (range 1-7) and NRS-day 28: 3.5 (range 1-5); peri-articular injection group: mean NRS-baseline: 7.0 (range 5-10), NRS-24 h: 4.1 (range 1-10) and NRS-day 28: 4.5 (range 1-8)]. CONCLUSION These results demonstrate that IA SIJ injections remain technically challenging despite ultrasound guidance. However, peri-articular deposition of triamcinolone appears sufficient for pain and symptom control in patients suffering from active sacroiliitis.
Pulmonary Epithelial Integrity in Children: Relationship to Ambient Ozone Exposure and Swimming Pool Attendance

Airway irritants such as ozone are known to impair lung function and induce airway inflammation. Clara cell protein (CC16) is a small anti-inflammatory protein secreted by the nonciliated bronchiolar Clara cells. CC16 in serum has been proposed as a noninvasive and sensitive marker of lung epithelial injury. In this study, we used lung function and serum CC16 concentration to examine the pulmonary responses to ambient O3 exposure and swimming pool attendance. The measurements were made on 57 children 10–11 years of age before and after outdoor exercise for 2 hr. Individual O3 exposure was estimated as the total exposure dose between 0700 hr until the second blood sample was obtained (mean O3 concentration/m3 × hours). The maximal 1-hr value was 118 μg/m3 (59 ppb), and the individual exposure dose ranged between 352 and 914 μg/m3hr. These O3 levels did not cause any significant changes in mean serum CC16 concentrations before or after outdoor exercise, nor was any decrease in lung function detected. However, children who regularly visited chlorinated indoor swimming pools had significantly lower CC16 levels in serum than did nonswimming children both before and after exercise (respectively, 57 ± 2.4 and 53 ± 1.7 μg/L vs. 8.2 ± 2.8 and 8.0 ± 2.6 μg/L; p < 0.002). These results indicate that repeated exposure to chlorination by-products in the air of indoor swimming pools has adverse effects on the Clara cell function in children. A possible relation between such damage to Clara cells and pulmonary morbidity (e.g., asthma) should be further investigated.
U SING C OMMERCIAL D ATA I NTEGRATION T ECHNOLOGIES TO I MPROVE THE Q UALITY OF A NONYMOUS E NTITY R ESOLUTION IN THE P UBLIC S ECTOR

: This paper describes a method for using new customer data integration and customer recognition technologies that have been developed in the private sector to solve the problem of anonymous entity resolution across multiple, non-shared data stores held in government agencies. In the method described, new commercial technologies that link records using anonymous tokens and encoded links allow indicative information across disparate data stores to participate in the entity resolution process without violating information-sharing policies. The benefit is that the resolution can be more complete and accurate through the broader inclusion of indicative data from many agencies and sources. The method also posits a trusted broker, an agent or agency that serves two primary functions. The first is to maintain the cross-reference table of encoded links for the participating agencies. The second is to translate the representation of the anonymous tokens presented by one agency into their corresponding representations in the other agency in those cases where information sharing is permissible and authorized. Although this paper describes the case where the entities are persons and locations, the same method is generally applicable to a broader range of entity types.
Homo Economicus Belief Inhibits Trust

As a foundational concept in economics, the homo economicus assumption regards humans as rational and self-interested actors. In contrast, trust requires individuals to believe partners’ benevolence and unselfishness. Thus, the homo economicus belief may inhibit trust. The present three experiments demonstrated that the direct exposure to homo economicus belief can weaken trust. And economic situations like profit calculation can also activate individuals’ homo economicus belief and inhibit their trust. It seems that people’s increasing homo economicus belief may serve as one cause of the worldwide decline of trust.
An adaptive and customizable feedback system for VR-based training simulators

This paper describes a proposal to build an intelligent feedback selection system for Virtual Reality-based training simulators. The system is aimed at generating multimodal feedback in real-time for advising the students while training with the simulator. Focused on driving tasks, we analyze how to customize the system to exhibit different behaviors. We examine educational and human factors that have influence on the behavior, so that the instructors can use or refine the behavior they prefer in each training session. The selection process is based on the analysis of the information coming from a diagnostic component and adapts the feedback to the performance of each student, since the process takes into account whether previous feedbacks were ineffective. The objective is to emulate the behavior of the instructor. In this way, the feedback system can be helpful for him/her, as while the system decides which the appropriate feedback is, the instructor can focus on other instructional tasks.
Ray Casting Algebraic Surfaces using the Frustum Form

We propose an algorithm for interactive ray‐casting of algebraic surfaces of high degree. A key point of our approach is a polynomial form adapted to the view frustum. This so called frustum form yields simple expressions for the Bernstein form of the ray equations, which can be computed efficiently using matrix products and pre‐computed quantities. Numerical root‐finding is performed using B‐spline and Bézier techniques, and we compare the performances of recent and classical algorithms. Furthermore, we propose a simple and fairly efficient anti‐aliasing scheme, based on a combination of screen space and object space techniques. We show how our algorithms can be implemented on streaming architectures with single precision, and demonstrate interactive frame‐rates for degrees up to 16.
Probable detection of H2D+ in the starless core Barnard 68

Context. The presence of H2D + in dense cloud cores underlies ion-molecule reactions that strongly enhance the deuterium fractionation of many molecular species. Aims. We determine the H2D + abundance in one starless core, Barnard 68, that has a particularly well established physical, chemical, and dynamical structure. Methods. We observed the ortho-H2D + ground-state line 110–111 ,t he N 2H + J = 4–3 line, and the H 13 CO + 4–3 line with the APEX telescope. Results. We report the probable detection of the o-H2D + line at an intensity Tmb = 0.22 ± 0.08 K and exclusively thermal line width, and find only upper limits to the N2H + 4–3 and H 13 CO + 4–3 intensities. Conclusions. Within the uncertainties in the chemical reaction rates and the collisional excitation rates, chemical model calculations and excitation simulations reproduce the observed intensities and that of o-H2D + in particular.
Adaptive fast finite time control of a class of uncertain nonlinear systems

This paper concerns the adaptive fast finite time control of a class of nonlinear uncertain systems of which the upper bounds of the system uncertainties are unknown. By using the fast non-smooth control Lyapunov function and the method of so-called adding a power integrator merging with adaptive technique, a recursive design procedure is provided, which guarantees the fast finite time stability of the closed-loop system. It is proved that the control input is bounded, and a simulation example is given to illustrate the effectiveness of the theoretical results.
Systematic land climate and evapotranspiration biases in CMIP5 simulations

Land climate is important for human population since it affects inhabited areas. Here we evaluate the realism of simulated evapotranspiration (ET), precipitation, and temperature in the CMIP5 multimodel ensemble on continental areas. For ET, a newly compiled synthesis data set prepared within the Global Energy and Water Cycle Experiment‐sponsored LandFlux‐EVAL project is used. The results reveal systematic ET biases in the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations, with an overestimation in most regions, especially in Europe, Africa, China, Australia, Western North America, and part of the Amazon region. The global average overestimation amounts to 0.17 mm/d. This bias is more pronounced than in the previous CMIP3 ensemble (overestimation of 0.09 mm/d). Consistent with the ET overestimation, precipitation is also overestimated relative to existing reference data sets. We suggest that the identified biases in ET can explain respective systematic biases in temperature in many of the considered regions. The biases additionally display a seasonal dependence and are generally of opposite sign (ET underestimation and temperature overestimation) in boreal summer (June–August).
Fostering the Uptake of Secure Multiparty Computation in E-Commerce

Secure multiparty computation (SMC) protocols enable a group of mutually distrustful parties to perform a joint computation with private inputs. Novel e-commerce applications have emerged that could benefit from strong privacy protection, e.g., benchmarking, auctions, and collaborative supply chain management and planning. However, the uptake of SMC in these applications is still rare. We argue that this is due to poor performance, functionality, and scalability, as well as architectures that do not meet the needs of e-commerce applications. This paper explores SMC approaches and research directions, aiming at providing better support for e-commerce applications.
Renormalization Group in Quantum Mechanics

The running coupling constants are introduced in quantum mechanics and their evolution is described with the help of the renormalization group equation. The harmonic oscillator and the propagation on curved spaces are presented as examples. The Hamiltonian and the Lagrangian scaling relations are obtained. These evolution equations are used to construct low energy effective models. Copyright {copyright} 1996 Academic Press, Inc.
Perspective on Research and Teaching in Psychology: Enrichment or Burden?

In Germany, most PhD psychology students are engaged in research and teach as well. As a result, they may experience both synergy and competition between these two activities. How do PhD psychology students themselves perceive the relationship between research and teaching? And how does this perception depend on their conceptions of research and teaching? The present study assessed conceptions of teaching (student vs teacher-focused, ATI-R), conceptions of research (CoRI) and the perceived relationship between research and teaching (open-ended question) as far as 63 PhD students in psychology were concerned. The perceived relationship was represented in terms of Compatibility (Commonality vs Dissimilarity) and Valence (Enrichment vs Burden). Results showed that conceptions of teaching were decisive for the research–teaching relationship. A teacher-focused conception of teaching was associated positively with the perceived Commonality of research and teaching, but negatively with perceived Enrichment. It is concluded that conceptions of teaching provide a promising approach for studying the research–teaching relationship. Theoretical and practical implications are discussed.