Miracle-dz/UniFAR-FTUs huggingface dataset:
Global object placement relation for improving 3-D scene construction from single image

Object Placement Relation (OPR) is the set of properties with classified relations between two connected objects. OPR has been used to predict depth level and locate position of object in 3-D scene. However, since the OPR does not identify the relation of each object to overall scene, it lacks consistency when applied to complex 3-D scenes. The results show distortion and unsmoothness. This research proposes the use of Global Object Placement Relation to improve quality and continuity of the scene. Global OPR is an extended OPR using graph theory to identify relation among objects in the scene. Inner and outer conflicts in OPR classification are identified and eliminated. More steps to increase accuracy in depth estimation are added by measuring each object with the horizon line position, correcting position of occluded objects, and rechecking the result of Octree structure with camera parameters. Our experiment results show increase in accuracy of classification and deliver a more realistic, better quality of 3-D scene.
Procedural Justice and Innovation: Does Procedural Justice Foster Innovative Behavior?

The influence of procedural justice on intended innovative behavior was studied in a sample of students and employees. Although earlier studies suggests that procedural justice increases innovation-related behavior such as spontaneous cooperation, so far systematic research is scarce. Results indicated that the provision of voice increased participants’ intention to show innovative behavior such as task revision, creativity, and persistence in a business simulation task. Furthermore, the effects found were mediated by intrinsic motivation and identification, but not by occupational self-efficacy. These findings suggest that justice in organizations and procedural fair conditions in particular can drive innovations.
Spacetime in string theory

We give a brief overview of the nature of spacetime emerging from string theory. This is radically different from the familiar spacetime of Einstein's relativity. At a perturbative level, the spacetime metric appears as ‘coupling constants’ in a two-dimensional quantum field theory. Nonperturbatively (with certain boundary conditions), spacetime is not fundamental but must be reconstructed from a holographic, dual theory.
Approximate Integer Common Divisor Problem Relates to Implicit Factorization

In this paper, we analyze how to calculate the GCD of k ( ≥ 2) many large integers, given their approximations. This problem is known as the approximate integer common divisor problem in literature. Two versions of the problem, presented by Howgrave-Graham in CaLC 2001, turn out to be special cases of our analysis when k = 2. We relate the approximate common divisor problem to the implicit factorization problem as well. The later was introduced by May and Ritzenhofen in PKC 2009 and studied under the assumption that some of Least Significant Bits (LSBs) of certain primes are the same. Our strategy can be applied to the implicit factorization problem in a general framework considering the equality of (i) most significant bits (MSBs), (ii) least significant bits (LSBs), and (iii) MSBs and LSBs together. We present new and improved theoretical as well as experimental results in comparison with the state of the art work in this area.
Time, Third Space, and Counternarratives of Achievement for Young Mothers in High School

This article shares alternative conceptions of time in a qualitative study about the schooling experiences of teenage mothers. The counternarratives of three women of color are presented as alternatives for understanding temporally restricted discourses of achievement in high school. Using third space theory as a lens for understanding the participants' experiences, this article illustrates how each participant's school story creates room for thinking about school success differently. This understanding of participants' experiences provokes a deliberate reconsideration of time as it relates to student success and achievement in school. This article concludes with an analysis of the participants' counternarratives and implications for future work. This work is useful for practitioners and researchers in reconceptualizing difference among students and in creating room for school structures that support diversity in classrooms and schools.
Vertical Differentiation and a Comparison of Online Advertising Models

Designing business models that take into consideration the role of advertising support is critical to the success of online services. In this paper, we address the challenges of these business model strategies and compare different ad revenue models. We use game theory to model vertical differentiation in both monopoly and duopoly settings, in which online service providers may offer an ad-free service, an ad-supported service, or a combination of these services. Offering both ad-free and ad-supported services is the optimal strategy for a monopolist because ad revenues compensate for the cannibalistic effect of vertical differentiation. In a duopoly equilibrium, exactly one firm offers both services when the ad revenue rate is sufficiently high. Furthermore, we find that a higher ad revenue rate may lead to lower service prices. Consistently across both monopoly and duopoly settings, such price reductions are more severe in the cost-per-thousand-impressions model than in the cost-per-click model. Our findings emphasize the role of advertising revenues in vertical differentiation and offer strategic guidance for monetizing online services.
Twice-universal piecewise linear regression via infinite depth context trees

We investigate the problem of sequential piecewise linear regression from a competitive framework. For an arbitrary and unknown data length n, we first introduce a method to partition the regressor space. Particularly, we present a recursive method that divides the regressor space into O(n) disjoint regions that can result in approximately 1.5n different piecewise linear models on the regressor space. For each region, we introduce a universal linear regressor whose performance is nearly as well as the best linear regressor whose parameters are set non-causally. We then use an infinite depth context tree to represent all piecewise linear models and introduce a universal algorithm to achieve the performance of the best piecewise linear model that can be selected in hindsight. In this sense, the introduced algorithm is twice-universal such that it sequentially achieves the performance of the best model that uses the optimal regression parameters. Our algorithm achieves this performance only with a computational complexity upper bounded by O(n) in the worst-case and O(log(n)) under certain regularity conditions. We provide the explicit description of the algorithm as well as the upper bounds on the regret with respect to the best nonlinear and piecewise linear models, and demonstrate the performance of the algorithm through simulations.
The Socratic method, defeasibility, and doxastic responsibility

Abstract There is an extensive body of philosophical, educational, and popular literature explaining Socratic pedagogy’s epistemological and educational ambitions. However, there is virtually no literature clarifying the relationship between Socratic method and doxastic responsibility. This article fills that gap in the literature by arguing that the Socratic method models many of the features of an ideally doxastically responsible agent. It ties a robust notion of doxastic responsibility to the Socratic method by showing how using defeaters to undermine participants’ knowledge claims can facilitate responsible belief. It then argues that more robust notions of doxastic responsibility can be augmented by constructs found in the American Philosophical Association’s Delphi Report. Finally, it shows how considering challenges (that is, entertaining defeaters) and modifying beliefs accordingly are objectives of the Socratic method and crucial elements of what it means to be a responsible believer.
Conducting an Architecture Group in a Multi-team Agile Environment

An important agile principle is that the best designs and architectures are emergent. It is completely feasible in low-complexity systems and / or in a single development team context. However, when systems grow, development is usually split among many teams. When it happens, implementing agile principles that lead to emergent architecture becomes harder. Although there is discussion on scaling agile in general, it is not clear how to deal speciﬁcally with software architecture in a multi-team scenario. This article presents an experience report on how a medium-sized company created an architecture group to tackle this problem, and how this group adopted the same agile principles and practices that development teams use in its arrangement and operation.
Point-of-care vertical flow allergen microarray assay: proof of concept.

BACKGROUND Sophisticated equipment, lengthy protocols, and skilled operators are required to perform protein microarray-based affinity assays. Consequently, novel tools are needed to bring biomarkers and biomarker panels into clinical use in different settings. Here, we describe a novel paper-based vertical flow microarray (VFM) system with a multiplexing capacity of at least 1480 microspot binding sites, colorimetric readout, high sensitivity, and assay time of <10 min before imaging and data analysis. METHOD Affinity binders were deposited on nitrocellulose membranes by conventional microarray printing. Buffers and reagents were applied vertically by use of a flow controlled syringe pump. As a clinical model system, we analyzed 31 precharacterized human serum samples using the array system with 10 allergen components to detect specific IgE reactivities. We detected bound analytes using gold nanoparticle conjugates with assay time of ≤10 min. Microarray images were captured by a consumer-grade flatbed scanner. RESULTS A sensitivity of 1 ng/mL was demonstrated with the VFM assay with colorimetric readout. The reproducibility (CV) of the system was <14%. The observed concordance with a clinical assay, ImmunoCAP, was R(2) = 0.89 (n = 31). CONCLUSIONS In this proof-of-concept study, we demonstrated that the VFM assay, which combines features from protein microarrays and paper-based colorimetric systems, could offer an interesting alternative for future highly multiplexed affinity point-of-care testing.
Aspect Mining using Clone Class Metrics Magiel Bruntink

This paper outlines how clone detection results can be filtered such that useful aspect candidates remain. In particular, our goal is to identify aspect candidates that are interesting for the purpose of improving maintainability. To reach this goal, clone class metrics are defined that measure known maintainability problems such as code duplication and code scattering. Subsequently, these clone class metrics are combined into a grading scheme designed to identify interesting clone classes for the purpose of improving maintainability using aspects.
Analyzing Low-Level Visual Features Using Content-Based Image Retrieval

This paper describes how low-level statistical visual features can be analyzed in our content-based image retrieval system named PicSOM. The lowlevel visual features used in the system are all statistical by nature. They include average color, color moments, contrast-type textural feature, and edge histogram and Fourier transform based shape features. Other features can be added easily. A genuine characteristic of the PicSOM system is to use relevance feedback from the human user’s actions to direct the system in scoring the relevance of particular features in the present query. While the link from features to semantic concepts remains an open problem, it is possible to relate low-level features to subjective image similarity, as perceived instantaneously by human users. The efficient implementation of PicSOM allows tests using statistically sufficiently large and representative databases of natural images.
Optimal order yielding discrepancy principle for simplified regularization in Hilbert scales: finite-dimensional realizations

Simplified regularization using finite-dimensional approximations in the setting of Hilbert scales has been considered for obtaining stable approximate solutions to ill-posed operator equations. The derived error estimates using an a priori and a posteriori choice of parameters in relation to the noise level are shown to be of optimal order with respect to certain natural assumptions on the ill posedness of the equation. The results are shown to be applicable to a wide class of spline approximations in the setting of Sobolev scales.
Interference effects in electronic transport through metallic single-wall carbon nanotubes

In a recent paper Liang et al. [Nature (London) 411, 665 (2001)] showed experimentally, that metallic nanotubes, strongly coupled to external electrodes, may act as coherent molecular wave guides for electronic transport. The experimental results were supported by theoretical analysis based on the scattering matrix approach. In this paper we analyze theoretically this problem using a real-space approach, which makes it possible to control quality of interface contacts. Electronic structure of the nanotube is taken into account within the tight-binding model. External electrodes and the central part (sample) are assumed to be made of carbon nanotubes, while the contacts between electrodes and the sample are modeled by appropriate on-site (diagonal) and hopping (off-diagonal) parameters. Conductance is calculated by the Green function technique combined with the Landauer formalism. In the plots displaying conductance versus bias and gate voltages, we have found typical diamond structure patterns, similar to those observed experimentally. In certain cases, however, we have found new features in the patterns, such as a double-diamond substructure.
Mathematical Modeling of a Two Spool Flow Control Servovalve Using a Pressure Control Pilot

A nonlinear dynamic model for an unconventional, commercially available electrohydraulic flow control servovalve is presented. The valve is a two-stage valve and differs from the conventional servovalve in that it does not require a feedback wire and ball, and the boost stage uses two spools, instead of a single spool, to meter flow into and out of the valve separately. Consequently, the valve is significantly less expensive. The proposed model captures the nonlinear and dynamic effects not present in previous models. The model has been coded in Simulink and experimentally validated.
Comparative Analysis of Random Forests with Statistical and Machine Learning Methods in Predicting Fault-Prone Classes

There are available metrics for predicting fault prone classes, which may help software organizations for planning and performing testing activities. This may be possible due to proper allocation of resources on fault prone parts of the design and code of the software. Hence, importance and usefulness of such metrics is understandable, but empirical validation of these metrics is always a great challenge. Random Forest (RF) algorithm has been successfully applied for solving regression and classification problems in many applications. In this work, the authors predict faulty classes/modules using object oriented metrics and static code metrics. This chapter evaluates the capability of RF algorithm and compares its performance with nine statistical and machine learning methods in predicting fault prone software classes. The authors applied RF on six case studies based on open source, commercial software and NASA data sets. The results indicate that the prediction performance of RF is generally better than statistical and machine learning models. Further, the classification of faulty classes/modules using the RF method is better than the other methods in most of the data sets. DOI: 10.4018/978-1-61350-429-1.ch023
Human and Computer Evaluations of Face Sketches with Implications for Forensic Investigations

Because sketches represent the original faces in a much concise yet recognizable form, they play an important role in criminal investigations, human perceptions and biometrics. In this work, we compared the performances of humans and a PCA-based algorithm in recognizing face sketches. A total of 250 sketches of 50 subjects were involved. All sketches were drawn manually by five artists (each artist drew 50 sketches, one for each subject). Experiments were carried out by matching sketches in a probe set to photos in a gallery set. This study resulted in the following findings: (i) A large inter-artist variation in sketch recognition rate was observed; (ii) Fusing sketches from different artists significantly improved the performance; (iii) Human performance seems correlated with that of the algorithm; (iv) The algorithm was superior with sketches of less distinctive features, while humans used tonality (or pigmentation) cues more efficiently.
Intentions of College Students to Serve as Informal Caregivers for Their Older Relatives: Theory of Planned Behavior Approach

As the older adult population increases, the healthcare system is experiencing a shortage of professional health care providers and caregivers. Consequently, the role of family to serve as caregivers will expand to care for older relatives at home. Thus, a larger proportion of adult children will become caregivers, including young adults enrolled as college students. Therefore, a need exists to examine the intentions, attitudes, and subjective norms of typical college students to assume the role of informal caregivers. The present study is based on the theoretical framework of the Theory of Planned Behavior (TPB). The TPB assumes attitudes, subjective norms, and perceived control influence intentions which provide the best predictors of actual behavior. The cross-sectional study included an attitude scale, additional scales based on TPB, and a demographic profile. Data were collected from 750 currently enrolled university students then analyzed for descriptive statistics, Pearson correlation, and hierarchal multiple regression statistics. The students' quality of experiences and interaction with older relatives correlated significantly with intentions, subjective norms, and perceived behavioral control to serve as informal caregivers. Our study shows that, in the present context, TPB offers a viable explanation of students' intentions to serve as informal caregivers. Implications of the study suggest health care providers, geriatricians, health educators, and patient educators should become involved in the education and strategy development necessary to assist this young group of informal caregivers.
Early Kidney Allograft Dysfunction (Threatened Allograft): Comparative Effectiveness of Continuing Versus Discontinuation of Tacrolimus and Use of Sirolimus to Prevent Graft Failure: A Retrospective Patient-Centered Outcome Study

Background Due to lack of treatment options for early acute allograft dysfunction in the presence of tubular-interstitial injury without histological features of rejection, kidney transplant recipients are often treated with sirolimus-based therapy to prevent cumulative calcineurin inhibitor exposure and to prevent premature graft failure. Methods We analyzed transplant recipients treated with sirolimus-based (n = 220) compared with continued tacrolimus-based (n = 276) immunosuppression in recipients of early-onset graft dysfunction (threatened allograft) with the use of propensity score-based inverse probability treatment weighted models to balance for potential confounding by indication between 2 nonrandomized groups. Results Weighted odds for death-censored graft failure (odds ratio [OR], 1.20; 95% confidence interval [95% CI], 0.66-2.19, P = 0.555) was similar in the 2 groups, but a trend for increased risk of greater than 50% loss in estimated glomerular filtration rate from baseline in sirolimus group (OR, 1.90; 95% CI, 0.96-3.76; P = 0.067) compared with tacrolimus group. Sirloimus group compared with tacrolimus group had increased risk for death with functioning graft (OR, 2.01; 95% CI, 1.29-3.14; P = 0.002) as well as increased risk of late death (death after graft failure while on dialysis) (OR, 2.39; 95% CI, 1.59-3.59; P < 0.001). Analysis of subgroups based on the absence or presence of T cell–mediated rejection or tubulointerstitial inflammation in the index biopsy, or the use of different types of induction agents, and all subgroups had increased risk of death with functioning graft and late death if exposed to sirolimus-based therapy. Conclusions Use of sirolimus compared with tacrolimus in recipients with early allograft dysfunction during the first year of transplant may not prevent worsening of allograft function and could potentially lead to poor survival along with increased risk of late death.
Experimental verification of 3-D hysteresis multi-scroll chaotic attractors

This paper introduces a novel circuit design for experimental verification of 3D hysteresis multi-scroll chaotic attractors. A block circuit diagram is shown for realizing 1D 5/spl sim/11-scroll, 2D 3/spl times/5/spl sim/11-grid scroll, and 3D 3/spl times/3/spl times/5/spl sim/11-grid scroll chaotic attractors by operating the switches. Moreover, this design provides a theoretical principle for hardware implementation of chaotic attractors in multi-directions with a large number of scrolls.
Generating k Best Solutions to Winner Determination Problems : Algorithms & Application to Procurement

Auction participants often cannot easily articulate their requirements and preferences. The buyer in a procurement auction, for instance, may hesitate to quantify the value of non-price solution attributes, and she may have difficulty delineating between hard and soft constraints. Consequently it can be difficult to formulate the winner determination problem (WDP) as a straightforward optimization problem. Existing decisionsupport aids for such situations, including scenario navigation and preference elicitation, address this difficulty through extensions to an optimization framework. This paper presents a complementary approach that frames the procurement decision problem as one of exploration rather than optimization. The foundation of our approach is an algorithm that generates k best solutions to auction WDPs. Our algorithm can scale to practical problem sizes for an interesting class of procurement auctions, and furthermore can incorporate hard constraints into the generation process. We describe ways of extracting useful guidance for the decisionmaker from k-cheapest WDP solutions. We evaluate our method using real bids submitted by real suppliers in an HP material parts procurement auction.
The Rise of Collaborative Mapping: Trends and Future Directions

The nature of map production and the dissemination of spatially referenced information have changed radically over the last decade. This change has been marked by an explosion of user generated spatial content via Web 2.0, access to a rising tide of big data streams from remotely-sensed and public data archives, and the use of mobile phones and other sensors as mapping devices. All of these developments have facilitated a much wider use of geodata, transforming ordinary citizens into neogeographers. This increase in user-generated content has resulted in a blurring of the boundaries between the traditional map producer, i.e., national mapping agencies and local authorities, and citizens as consumers of this information. Citizens now take an active role in mapping different types of features on the Earth’s surface as volunteers, either by providing observations on the ground or tracing data from other sources, such as aerial photographs or satellite imagery. OpenStreetMap (OSM) and Ushahidi are two well-known examples of a growing collection of collaborative mapping communities that are building rich spatial datasets, which are openly accessible. [. ]