Miracle-dz/UniFAR-FTUs huggingface dataset:
DIGITAL THREE-DIMENSIONAL MODELING OF HERITAGE BY FREQUENCY-MODULATED LASER RADAR : THE CASE OF DONATELLO'S DAVID

In this paper the application of a novel CW FM Laser radar is demonstrated through the acquisition of a three dimensional model of the world famous "David" by Donatello. The steps of the acquisition procedure and the related technical solutions are reported. The scientific focus was centered on the processing pipeline simplification due to this new acquisition methodology. Detailed results are presented, demonstrating how the use of this new generation of sensors allows the digitalization of artwork, made of materials that are normally very difficult to acquire, and to improve the overall level of modeling accuracy.
The Rate-of-Return Regulated Firm: Cost and Production Duality

A duality between cost and production is established for a firm subject to rate-of-return regulation. To this end, a rate-of-return regulated production function is defined and shown to exist. It is then shown how information regarding the unregulated technology can be obtained from the rate-of-return regulated cost function. With knowledge of the rate-of-return constraint, the rate-of-return regulated production function can be reconstructed.
The Effects of Political Connections on the Level and Value of Cash Holdings: International Evidence

In this paper, we examine the role of political connections on corporate liquidity policies and their consequences in an international setting. We find that managers of politically connected firms have a tendency to hoard more cash than their non-connected counterparts. Moreover, presence of political connections reduces the value of cash holdings. Further analysis reveals that our main findings are more pronounced for firms in emerging markets as well as for firms in countries with weak legal protection of investors and high levels of corruption. Overall, our empirical results corroborate previous findings on the agency cost explanation for corporate cash holdings. JEL Classification: F50; F54; G15; G34
Software Calibration for Stereo Camera on Stereo Vision Mobile Robot using Tsai's Method

An improvement for image distortion in cameras has been an important issue for as long as users have wanted to reproduce or utilize observed information. In this paper, it described about mobile robot using uncalibrated cameras rig which installed on top of it to work as stereo pair. These cameras have to be calibrated by software using Tsai's method. The block matching algorithm is using Sum of Absolute Differences (SAD) to solve the correspondence problem. The image processing part is implemented in Matlab software. The result is a lot of matching points discovered using a software calibration result from Tsai's method.
Time series forecasting with appetitive reward-based pseudo-outer-product fuzzy neural network

Appetitive operant conditioning in Aplysia for feeding behavior via electrical stimulation of esophageal nerve contingently reinforced upon each spontaneous bite resulted in contingently reinforced animals acquiring operant memory. Analysis of the cellular and molecular mechanisms of the feeding motor circuitry revealed activity-dependent neuronal modulation occurs at interneurons that mediate the feeding behaviors, providing one evidence that interneurons are possible loci of plasticity and contribute a mechanism to memory storage in addition to memory storage contributed by activity-dependent synaptic plasticity. In this paper, an associative ambiguity correction-based neuro-fuzzy network called ARPOP-CRI(S), is trained based on an appetitive reward learning algorithm that is biologically inspired from the appetitive operant conditioning of feeding behavior in Aplysia. ARPOP-CRI(S) is evaluated and compared with other modelling techniques by employing benchmark time series data sets. Experimental results are encouraging and shows that ARPOP-CRI(S) is a viable modelling technique for time series forecasting.
The Meaning of Types From Intrinsic to Extrinsic Semantics

A definition of a typed language is said to be "intrinsic" if it assigns meanings to typings rather than arbitrary phrases, so that ill-typed phrases are meaningless. In contrast, a definition is said to be "extrinsic" if all phrases have meanings that are independent of their typings, while typings represent properties of these meanings. For a simply typed lambda calculus, extended with recursion, subtypes, and named products, we give an intrinsic denotational semantics and a denotational semantics of the underlying untyped language. We then establish a logical relations theorem between these two semantics, and show that the logical relations can be "bracketed" by retractions between the domains of the two semantics. From these results, we derive an extrinsic semantics that uses partial equivalence relations.
An open and free speech corpus for speaker recognition: The FSCSR speech corpus

Speech corpora are considered as the basic requirement for the development and evaluation of speaker recognition systems. However, the vast majority of speech corpora intended for speaker recognition research is not free for researchers, and the remaining freely available speech databases are not sufficiently large for the development and evaluation of robust speaker recognition systems. This lack of free and large speech corpora represents a major obstacle for promoting research on speaker recognition systems, especially in less-resourced laboratories. To overcome this problem, we have developed a free and large speech corpus of more than 530 speakers from several languages. A part of the proposed speech corpus is collected and recorded under our supervision, and the remaining part is collected from the Voxforge website using a new semi-automatic approach. In this paper, the detailed description of the proposed speech corpus and the complete procedure of data collection are presented. The results of the preliminary experiments conducted on the proposed speech corpus, using speaker recognition state-of-art approaches (MFCC for features extraction, GMM-UBM for speaker modeling), are also presented.
A Dynamic Landslide Simulation Algorithm Based on Multitask Spatio- temporal Data Model

In traditional real-time landslide dynamic simulation, many problems such as cumbersome and inefficiency data interaction process would lead to the limit in landslide dynamic simulation engineering application. 4D spatio-temporal data model event-driven process will be adopted to address those problems. Aiming at intricacy of influent factors in moving process and multi-factor, the original model was improved and enlarged to support the landslide process in data and logical. We use this algorithm in a real test data, show an efficient landslide dynamic simulation. It solved the problems in landslide movement and sophisticated spatio-temporal process which can be hardly described, finally provided a new idea to solve the similar question.
Fall Detection Based on Body Part Tracking Using a Depth Camera

The elderly population is increasing rapidly all over the world. One major risk for elderly people is fall accidents, especially for those living alone. In this paper, we propose a robust fall detection approach by analyzing the tracked key joints of the human body using a single depth camera. Compared to the rivals that rely on the RGB inputs, the proposed scheme is independent of illumination of the lights and can work even in a dark room. In our scheme, a pose-invariant randomized decision tree algorithm is proposed for the key joint extraction, which requires low computational cost during the training and test. Then, the support vector machine classifier is employed to determine whether a fall motion occurs, whose input is the 3-D trajectory of the head joint. The experimental results demonstrate that the proposed fall detection method is more accurate and robust compared with the state-of-the-art methods.
Crime, Contraband, and Property Rights: Explaining Variations in Violent Crime Rates

Author(s): Paris, Jeffrey Jonathan | Advisor(s): Ross, Michael L; Geddes, Barbara | Abstract: Violent crime affects quality of life on an individual level and development on a national level (Kleiman, 2009), and could be the most important factor in determining whether many low and middle-income countries develop stable governments and implement effective economic policies. I propose a political and natural resource based explanation of the variation in crime rates in order to overcome the lack of connections between macro-level statistical data and causal mechanisms identified up to this point. My explanation involves the dynamics between state strength, property rights formation and enforcement, and the specific nature of criminal markets.When the state is weak crime rates usually increase due to the state's inability to enforce property rights, including the inability to control contraband markets (or adequately taxing legal markets), and the inability to effectively punish defectors. Property rights are established through a political bargaining process between actors that generally depends on the capacity for violence of interested parties (DeSoto, 2000; Umbeck, 1981). Well-defined and enforced property rights reduce transaction costs, and therefore reduce levels of violence (Anderson and Hill, 2003). The specific properties of markets, including the resources they are based on, can shape the market environment, including legality, and affect the resulting "institutions of extraction" (Snyder, 2006, 952). Lootable resources make property rights harder to enforce and interact with the state's ability to provide the rule of law, especially in the case of prohibitions. Illicit markets engender violence because normal business disputes are often settled with violence (Kleiman, 1993, 104-107, 115). My hypotheses examine the relationship between the production of lootable products, while controlling for other factors commonly attributed to crime. My analysis suggests that, all else being equal, the production of lootable resources increases crime rates, while the enforcement of property rights, whether by a state, non-state actor, or community, reduces violent crime rates. To test my hypotheses I use a mix of statistical analysis, case studies based on archival research, and structured interviews. Cross-national data was collected through archival research and existing databases, spanning over seventy countries and fifty years. Local level data comes from fieldwork in Colombia, and includes quantitative data for every municipality in Colombia over a span of nine years, and qualitative data for several regions critical to testing my hypotheses.
Review of Prediction Models to Estimate Activity-Related Energy Expenditure in Children and Adolescents

Purpose. To critically review the validity of accelerometry-based prediction models to estimate activity energy expenditure (AEE) in children and adolescents. Methods. The CINAHL, EMBASE, PsycINFO, and PubMed/MEDLINE databases were searched. Inclusion criteria were development or validation of an accelerometer-based prediction model for the estimation of AEE in healthy children or adolescents (6–18 years), criterion measure: indirect calorimetry, or doubly labelled water, and language: Dutch, English or German. Results. Nine studies were included. Median methodological quality was 5.5 ± 2.0 IR (out of a maximum 10 points). Prediction models combining heart rate and counts explained 86–91% of the variance in measured AEE. A prediction model based on a triaxial accelerometer explained 90%. Models derived during free-living explained up to 45%. Conclusions. Accelerometry-based prediction models may provide an accurate estimate of AEE in children on a group level. Best results are retrieved when the model combines accelerometer counts with heart rate or when a triaxial accelerometer is used. Future development of AEE prediction models applicable to free-living scenarios is needed.
Ranking related entities: components and analyses

Related entity finding is the task of returning a ranked list of homepages of relevant entities of a specified type that need to engage in a given relationship with a given source entity. We propose a framework for addressing this task and perform a detailed analysis of four core components; co-occurrence models, type filtering, context modeling and homepage finding. Our initial focus is on recall. We analyze the performance of a model that only uses co-occurrence statistics. While this method identifies the potential set of related entities, it fails to rank them effectively. Two types of error emerge: (1) entities of the wrong type pollute the ranking and (2) while somehow associated to the source entity, some retrieved entities do not engage in the right relation with it. To address (1), we add type filtering based on category information available in Wikipedia. To correct for (2), we complement our related entity finding method with contextual information, represented as language models derived from documents in which source and target entities co-occur. To complete the pipeline, we find homepages of top ranked entities by combining a language modeling approach with heuristics based on Wikipedia's external links. Our method achieves very high recall scores on the end-to-end task, providing a solid starting point for expanding our focus to improve precision. Our framework can effectively incorporate additional heuristics and these extensions lead to state-of-the-art performance.
Proving expansion in three steps

This text is meant to be an introduction to a recent strategy introduced by Bourgain and Gamburd (following a work of Helfgott) for proving graph-expansion. The strategy is designed for graphs H that are defined using some underlying group G. The strategy consists of three steps, which, in Sarnak's terminology, correspond to the three steps of a chess game: opening, middle-game and endgame. In the opening, the objective is to prove that the girth of H is logarithmic. In the middle-game, the goal is to prove a productgrowth theorem for subsets of G. The endgame consists of establishing a "mixing property" for G. There are two methods for proving a mixing property: using pairwise independence and using basic representation theory.
Releasing Cloud Databases for the Chains of Performance Prediction Models

The onset of cloud computing has brought about computing power that can be provisioned and released on-demand. This capability has drastically increased the complexity of workload and resource management for database applications. Existing solutions rely on query latency prediction models, which are notoriously inaccurate in cloud environments. We argue for a substantial shift away from query performance prediction models and towards machine learning techniques that directly model the monetary cost of using cloud resources and processing query workloads on them. Towards this end, we sketch the design of a learning-based service for IaaS-deployed data management applications that uses reinforcement learning to learn, over time, low-cost policies for provisioning virtual machines and dispatching queries across them. Our service can eﬀectively handle dynamic workloads and changes in resource availability, leading to applications that are continuously adaptable, cost eﬀective, and performance aware. In this paper, we discuss several challenges involved in building such a service, and we present results from a proof-of-concept implementation of our approach.
A Pilot Study Comparing HPV-Positive and HPV-Negative Head and Neck Squamous Cell Carcinomas by Whole Exome Sequencing

Background. Next-generation sequencing of cancers has identified important therapeutic targets and biomarkers. The goal of this pilot study was to compare the genetic changes in a human papillomavirus- (HPV-)positive and an HPV-negative head and neck tumor. Methods. DNA was extracted from the blood and primary tumor of a patient with an HPV-positive tonsillar cancer and those of a patient with an HPV-negative oral tongue tumor. Exome enrichment was performed using the Agilent SureSelect All Exon Kit, followed by sequencing on the ABI SOLiD platform. Results. Exome sequencing revealed slightly more mutations in the HPV-negative tumor (73) in contrast to the HPV-positive tumor (58). Multiple mutations were noted in zinc finger genes (ZNF3, 10, 229, 470, 543, 616, 664, 638, 716, and 799) and mucin genes (MUC4, 6, 12, and 16). Mutations were noted in MUC12 in both tumors. Conclusions. HPV-positive HNSCC is distinct from HPV-negative disease in terms of evidence of viral infection, p16 status, and frequency of mutations. Next-generation sequencing has the potential to identify novel therapeutic targets and biomarkers in HNSCC.
The Search for the Missing Baryons at Low Redshift

At low redshift, only about one-tenth of the known baryons lie in galaxies or the hot gas seen in galaxy clusters and groups. Models posit that these “missing baryons” are in gaseous form in overdense filaments that connect the much denser virialized groups and clusters. About 30% is cool (<10 5 K) and is detected in Lyα absorption studies, but about half is predicted to lie in the 10 5 –10 7 K regime. Gas is detected in the 2–5 × 10 5 K range through OVI absorption studies (7% of the baryons) and possibly near 10 5 K from broad Lyα absorption (20% of the baryons). Hotter gas (0.5–2 × 10 6 K) is detected at zero redshift by OVII and OVIII Kα X-ray absorption, and the OVII line strengths seem to correlate with the Galactic soft X-ray background, so it is probably produced by Galactic halo gas, rather than a Local Group medium. There are no compelling detections of the intergalactic hot gas (0.5–10 × 10 6 K) either in absorption or emission and these upper limits are consistent with theoretical models. Claimed X-ray absorption lines are not confirmed, while most of the claims of soft emission are attributable to artifacts of background subtraction and field-flattening. The missing baryons should become detectable with moderate improvements in instrumental sensitivity.
Massless Flows II:. the Exact S-Matrix Approach

We study the spectrum, the massless S matrices and the ground-state energy of the flows between successive minimal models of conformal field theory, and within the sine-Gordon model with imaginary coefficient of the cosine term (related to the minimal models by “truncation”). For the minimal models, we find exact S matrices which describe the scattering of massless kinks, and show using the thermodynamic Bethe ansatz that the resulting non-perturbative c function (defined by the Casimir energy on a cylinder) flows appropriately between the two theories, as conjectured earlier. For the nonunitary sine-Gordon model, we find unusual behavior. For the range of couplings we can study analytically, the natural S matrix deduced from the minimal one by “undoing” the quantum-group truncation does not reproduce the proper c function with the TBA. It does, however, describe the correct properties of the model in a magnetic field.
Applying Tests of Equivalence for Multiple Group Comparisons: Demonstration of the Confidence Interval Approach.

Assessing the comparability of different groups is an issue facing many researchers and evaluators in a variety of settings. Commonly, null hypothesis significance testing (NHST) is incorrectly used to demonstrate comparability when a non-significant result is found. This is problematic because a failure to find a difference between groups is not equivalent to showing that the groups are comparable. This paper provides a comparison of the confidence interval approach to equivalency testing and the more traditional analysis of variance (ANOVA) method using both continuous and rating scale data from three geographically separate medical education teaching sites. Equivalency testing is recommended as a better alternative to demonstrating comparability through its examination of whether mean differences between two groups are small enough that these differences can be considered practically unimportant and thus, the groups can be treated as equivalent.
Sequential use of human-derived medium supplements favours cardiovascular tissue engineering

For clinical application of tissue engineering strategies, the use of animal‐derived serum in culture medium is not recommended, because it can evoke immune responses in patients. We previously observed that human platelet‐lysate (PL) is favourable for cell expansion, but generates weaker tissue as compared to culture in foetal bovine serum (FBS). We investigated if human serum (HS) is a better human supplement to increase tissue strength. Cells were isolated from venous grafts of 10 patients and expanded in media supplemented with PL or HS, to determine proliferation rates and expression of genes related to collagen production and maturation. Zymography was used to assess protease expression. Collagen contraction assays were used as a two‐dimensional (2D) model for matrix contraction. As a prove of principle, 3D tissue culture and tensile testing was performed for two patients, to determine tissue strength. Cell proliferation was lower in HS‐supplemented medium than in PL medium. The HS cells produced less active matrix metallo‐proteinase 2 (MMP2) and showed increased matrix contraction as indicated by gel contraction assays and 3D‐tissue culture. Tensile testing showed increased strength for tissues cultured in HS when compared to PL. This effect was more pronounced if cells were sequentially cultured in PL, followed by tissue culture in HS. These data suggest that sequential use of PL and HS as substitutes for FBS in culture medium for cardiovascular tissue engineering results in improved cell proliferation and tissue mechanical properties, as compared to use of PL or HS apart.
Novel Authentication & Authorization Management for Sensitive Information Privacy Protection Using Dynamic Key Based Group Key Management

This paper presents a secure authentication and authorization management mechanism for protecting privacy in sensitive information systems. It allows involved individuals and group participants to achieve high security levels and tight authorization control. The need of sharing long term secrets to authenticate individuals and group users is eradicated in the proposed protocol by dynamic keys. It overcomes the secrets compromising during authentication via open networks. Furthermore, it also offers an ability allowing information owners to have fine-gained control of their critical information. Finally, the paper gives a formal analysis to demonstrate how secure the proposed work together with discussions of security issues. It is argued that the proposed work achieves strong authentication and authorization, and solves the involved participants’ plausible deniability issues.
Bakebot: Baking Cookies with the PR2

We present BakeBot, a PR2 robot system that bakes cookies autonomously, from mise en place presentation through baking in a toaster oven. The baking planning and control system is implemented as a hierarchical finite state machine. We developed parameterized motion primitives for baking. The motion primitives utilize the existing sensing and manipulation capabilities of the PR2 platform and also our new compliant control techniques to address environmental uncertainty. The system was tested through 27 baking attempts, 16 of which successfully resulted in edible cookies.