Miracle-dz/UniFAR-FTUs huggingface dataset:
Modal warping: real-time simulation of large rotational deformation and manipulation

This work proposes a real-time simulation technique for large deformations. Green's nonlinear strain tensor accurately models large deformations; however, time stepping of the resulting nonlinear system can be computationally expensive. Modal analysis based on a linear strain tensor has been shown to be suitable for real-time simulation, but is accurate only for moderately small deformations. In the present work, we identify the rotational component of an infinitesimal deformation and extend traditional linear modal analysis to track that component. We then develop a procedure to integrate the small rotations occurring at the nodal points. An interesting feature of our formulation is that it can implement both position and orientation constraints in a straightforward manner. These constraints can be used to interactively manipulate the shape of a deformable solid by dragging/twisting a set of nodes. Experiments show that the proposed technique runs in real-time, even for a complex model, and that it can simulate large bending and/or twisting deformations with acceptable realism.
Physical Conditions in the Proto-Planetary Nebula CRL 618 Derived from Observations of Vibrationally Excited HC3N

We used the Effelsberg 100 m and IRAM 30 m telescopes to observe vibrationally excited cyanoacetylene (HC3N) in several rotational transitions toward the proto-planetary nebula CRL 618. Lines from nine different vibrationally excited states, with energies ranging up to 1600 K above ground, were detected. The lines show P Cygni profiles indicating that the HC3N emission originates from an expanding and accelerating molecular envelope. The HC3N rotational temperature varies with velocity, peaks at 520 K, 3 km s-1 blueshifted from the systemic velocity, and decreases with higher blueshift of the gas. The column density of the absorbing HC3N is (3-6) × 1017 cm-2. We modeled spectra based on spherical models of the expanding envelope that provided an excellent fit to the observations and discuss the implications of the models. Additionally, lines from 13C substituted cyanoacetylene were observed. They can be used to constrain the 12C/13C ratio in this source to 10 ± 2.
Trademarks and Venture Capital Valuation

This study investigates the role of trademarks in the start-up valuations of venture capitalists (VCs). Our results show that the number and breadth of trademark applications have inverted U-shaped relationships with the financial valuations of start-ups by VCs. The findings also indicate that in later funding rounds, the value of trademark applications decreases when the start-up progresses into more advanced development stages. Start-ups should consider these findings when seeking funding from VCs and should stress their market and growth orientations and their willingness to protect their marketing investments by highlighting their trademark activities.
The Titech large vocabulary WFST speech recognition system

In this paper we present evaluations on the large vocabulary speech decoder we are currently developing at Tokyo Institute of Technology. Our goal is to build a fast, scalable, flexible decoder to operate on weighted finite state transducer (WFST) search spaces. Even though the development of the decoder is still in its infancy we have already implemented a impressive feature set and are achieving good accuracy and speed on a large vocabulary spontaneous speech task. We have developed a technique to allow parts of the decoder to be run on the graphics processor, this can lead to a very significant speed up.
Agent based mobile recommender system

Social networking websites (SNS) are attaining a lot of recognition by researchers as they prove to be a reservoir of huge amount of data. These sites have revolutionized the world of technology by allowing their users to form a virtual world of their own. The main notion behind building the social networking websites is to bring people from all walks of life together, having some link with each other either on the base of their philosophies or ideas about life, or belonging to same occupational class, or sharing same thoughts and views, in a form of virtual community. SNSs provide a medium for people to remain in contact with their beloved ones, get global as well as local updates, and share their feelings with others. Additionally, these sites have also been used effectively for marketing and advertising almost every kind of products. Companies announce their pages while giving demonstrations of their items. Thus, SNS have basically emerged most common recommender engines. However, most of the times, unnecessary and irrelevant information are displayed on these social interaction pages which causes high data traffic and distract of user concentration. This issue becomes severe in case a user visits multiple social websites frequently. Thus, a personalized system is needed that could provide a single platform to make recommendations based on user's friends circle on different SNS sites. Different multi agent system architectures have been proposed to efficiently carryout different search and recommendation procedure but, little attention was given to the user interface. In this research, we solve this issue by the design and development of adaptable intelligent agent based interface. The objective is to intelligently present the personalize recommendations help a user to get what he needs from his social Web site in a blink of eye without wasting time in dealing with a complex search procedures.
NAND-Flash : Fast Storage or Slow Memory ? Kshitij Sudan

NAND-flash storage is a preferred method to accelerate I/O intensive applications because of its high throughput and fast random-read performance. However, the high cost per GB of flash, relative to magnetic disks, prevents large datacenters from moving their data entirely onto the flash media. Normally, limited amounts of flash is used “in front of” magnetic storage to speed up accesses to the persistent storage subsystem. Recently, there have been proposal that flash should alternatively be used “behind DRAM”, as a part of the volatile main memory system. In both configurations flash can be presented transparently to the application, making them competing architectural design points for where flash is to be best used in future systems. In this paper, we evaluate two state-of-the-art systems to compare the relative advantages of each approach. We present results for TPC-C, an on-line transaction processing benchmark, as database systems have been one of the largest adopters of flash technology due to the I/O intensive nature of the workloads. Our results show that when using flash for disk caching, application throughput improves by 56% and by 131% when using flash as part of a hybrid main-memory system.
Random Walks on Multiplex Networks

Multiplex networks are receiving increasing interests because they allow to model relationships between networked agents on several layers simultaneously. In this letter, we extend well-known random walks to multiplexes and we introduce a new type of walk that can exist only in multiplexes. We derive exact expressions for vertex occupation time and the coverage. Finally, we show how the efficiency in exploring the multiplex critically depends on the underlying topology of layers, the weight of their inter-connections and the strategy adopted to walk.
Real-Time Activity Recognition on Smartphones Using Deep Neural Networks

Real-time activity recognition is an important research problem, which has drawn the attention of many researchers for many years. All previous works of real-time activity recognition needed to manually extract features and then fed these features into the classifiers as the inputs. However, due to the recognition time limit, they could only extract a small amount of features, which might not achieve good accuracy and could be improved. Besides, these features were manually extracted according to the experience of the researchers. Because researchers did not know which features worked better for classification, it was hard to choose suitable features, thus these manually extracted features might not be related to the specific classification task and have poor discrimination ability and could be improved. In this paper, we recommend deep neural networks for real-time activity recognition, which automatically learn suitable features and then perform classification. We collected accelerometer data of seven activities of interest on an android smartphone, including walking, running, standing, sitting, lying, walking upstairs and walking downstairs, and conducted experiments on our collected dataset to compare our method with traditional methods. Besides, we implemented a deep neural network on a smartphone and tested the recognition time of the model. The results showed that deep neural networks could achieve real-time performance and got higher accuracy than traditional methods.
Exploring non linearities in Hedge Funds: An application of Particle Filters to Hedge Fund Replication

Of the three main challenges of hedge fund replication, only replication of the wellknown nonlinearities of their returns remains undisputed. Recent advances in hedge fund replication using factor models have shown that the use of Bayesian filters helps greatly in capturing the dynamic allocation of assets of hedge fund managers, particularly in the case of aggregates of hedge funds [33, 35]. Furthermore, from a practitioner’s perspective, access to the alpha of the funds can be provided on top of capturing the dynamic exposures by adopting a core/satellite approach to building the replication portfolio [35]. In this working paper, we explore tentatively the solutions that Bayesian filters could provide to the replication of hedge fund nonlinearities. Although, not entirely successful, our results show promises and open new grounds for the field.
Investigating the impact of code smells debt on quality code evaluation

Different forms of technical debt exist that have to be carefully managed. In this paper we focus our attention on design debt, represented by code smells. We consider three smells that we detect in open source systems of different domains. Our principal aim is to give advice on which design debt has to be paid first, according to the three smells we have analyzed. Moreover, we discuss if the detection of these smells could be tailored to the specific application domain of a system.
Essays on the Measurement of Economic Expectations

This chapter introduces the new measurement method of economic expectations – the visual analog scale (VAS) – and evaluates its reliability. Four classes of reliability are examined: Parallel-forms reliability, test-retest reliability, internal consistency and inter-rater reliability. As a side product of the study the reliability of the traditional three-category scale is also evaluated. The data set is based on an international panel of economists and contains 2,470 observations from eight consecutive quarterly survey waves in the years 2005-2007. VAS is found to be a reliable measurement method of economic expectations. Reliability of the Visual Analog Scale 2
Resource pooling in CDMA cell-based systems through uplink power control

For CDMA cell-based systems we propose an uplink power control scheme for low data packet queueing delay. The scheme can be seen as a simple extension to the Foschini-Miljanic algorithm which takes the transmit queue sizes at the mobile stations into account. The proposed scheme minimizes the draining time compared to all other policies with the same power consumption. This is because of resource pooling effects which arise when all queues empty at the same time. Although in CDMA systems there is no idle capacity as in wired systems, greater cummulative service is obtained by simultaneous transmissions than through time-sharing. Simulations exhibit significant reductions in queueing delay compared to other power control schemes proposed in the literature.
Artificial Cell Communication in Distributed Systems

Distributed systems like multi-agent systems, complex adaptive systems, or artificial immune systems use lots of small entities in order to reach the goals of the system, e.g. optimisation problems or network security. In all of these systems, lightweight entities exist and perform tasks autonomously in order to solve the problems. In addition, one of the main problems is the communication between these entities, which is mostly implemented using central servers. In this article, we introduce a novel approach for communication that uses the cell communication of the human body as archetype. The communication is reliable, efficient, and does not use central entities. We show that the artificial cell communication has several advantages compared to common used communication protocols.
Matching pursuit of images

A crucial problem in image analysis is to construct efficient low-level representations of an image, providing informations on features such as edges and texture components. An image usually contains very different types of features, which have been successfully modelized by the very redundant family of 2D Gabor functions. However, this model generates representations with a very large size. Instead of decomposing a given image over this whole set of Gabor functions, we use an adaptative algorithm to select a subset of Gabor elements that are best adapted to the image. This produces compact representation in terms of few features that reveal the local image properties. <<ETX>>
The Role of Parent and Peer Attachment in the Relationship between Abuse History and Adolescent Social and Behavioral Outcomes

Anna Christine Stagg: The Role of Parent and Peer Attachment in the Relationship between Abuse History and Adolescent Social and Behavioral Outcomes (Under the direction of Rune J. Simeonsson) Although associations between abuse and social and behavioral outcomes, abuse and attachment relationships, and attachment and social and behavioral outcomes are well documented in the literature, little research has examined all three of these variables together. The current study addresses gaps in past research by examining relationships between the experience of physical abuse, attachment to parents and peers, and social and behavioral outcomes in adolescents. Analyses were conducted using follow-up data from a large study examining outcomes of children with a history of abuse first studied in pre-adolescence and their case matched, non-abused classmates. The sample consisted of adolescents (N=153) with and without a history of abuse. Sociometric assessments were conducted to assess adolescent outcomes including interpersonal competence, internalizing and externalizing behaviors, total behavior problems, and attachment relationships to parents and peers. Findings revealed significant associations between abuse history, attachment, and social and behavioral outcomes. When adolescents with and without a history of abuse were examined separately, attachment was found to be predictive of outcomes only in adolescents without a history of abuse. When the sample was examined as a whole, significant mediation effects were found for parent attachment. Specifically, parent attachment was a mediator of the relationship between abuse and externalizing behavior problems, total behavior problems, and social competence. Attachment to peers was not found to play a significant role in the relationship between preadolescent abuse iv and adolescent social and behavioral outcomes. Implications of findings are discussed with a focus on prevention and attachment-based interventions. v ACKNOWLEDGEMENTS
PieCursor: merging pointing and command selection for rapid in-place tool switching

We describe a new type of graphical user interface widget called the "PieCursor. " The PieCursor is based on the Tracking Menu technique and consists of a radial cluster of command wedges, is roughly the size of a cursor, and replaces the traditional cursor. The PieCursor technique merges the normal cursor function of pointing with command selection into a single action. A controlled experiment was conducted to compare the performance of rapid command and target selection using the PieCursor against larger versions of Tracking Menus and a status quo Toolbar configuration. Results indicate that for small clusters of tools (4 and 8 command wedges) the PieCursor can outperform the toolbar by 20.8% for coarse pointing. For fine pointing, the performance of the PieCursor degrades approximately to the performance found for the Toolbar condition.
I / O Efficient Search of Large Social Networks

We introduce an I/O efficient algorithm and data structure to support fast decentralized search in large graphs modeling social networks. We structure network data in a homophily-based social hierarchy using an append-only, block-aligned skip list with an embedded tree microindex, which reduces I/O and cache line faults. We further minimize I/O when building the skip list by combining an extended memory sorting algorithm with buffered insertion. The system supports ad hoc queries efficiently: the combined cost of skip list construction and search improves performance in large social network graphs (11 million vertices and 150 million edges) by a factor of four over the fastest known external memory search algorithm and by several orders of magnitude over a traditional inmemory search algorithm. Subsequent searches that use the same skip list as an index are an order of magnitude faster still. Finally, these search structures work efficiently over a much wider range of homophily values than theory predicts.
Preferences, Poverty and Politics: Experimental and Survey Data from Vietnam

We conducted choice experiments in Vietnamese villages to investigate how wealth, political history, occupation, and other demographic variables (from a comprehensive earlier household survey) are correlated with risk, time discounting and trust measured in experiments. In villages with higher mean income, people are less loss-averse and more patient. Results from a trust game demonstrate people in the south are more altruistic toward the poor: they invest more in the poor without expecting repayment. This pattern is consistent with the idea that private norms of redistribution from rich to poor are active in the south but are crowded out in the north possibly by communist public institutions, although we observe a strong overall positive effect of communism on reciprocity across all income groups. Our findings also suggest market activities, like starting a small trade business, are correlated with trust and trustworthiness. The experiments also expand methodology by using choices that separate different aspects of risk aversion and time preferences as suggested by earlier behavioral economics experiments. JEL keywords: C93, D64, D81, D91 April 15, 2006. This research was supported by a Behavioral Economics Small Grant from the Russell Sage Foundation, Foundation for Advanced Studies on International Development, and internal Caltech funds to author Camerer. Comments from participants at the ESA meeting (Tucson, October 2005), SEA meeting (November 2005), SJDM (November 2005), audiences at Columbia, NYU, Bocconi (Milano), Emory, Hawaii, Caltech, UCSC, and anonymous readers were helpful. Thank you to our research coordinators, Phan Dinh Khoi, Huynh Truong Huy, Nguyen Anh Quan, Nguyen Mau Dung, and research assistants, Bui Thanh Sang, Nguyen The Du, Ngo Nguyen Thanh Tam, Pham Thanh Xuan, Nguyen Minh Duc, Tran Quang Trung, and Tran Tat Nhat. We also thank Nguyen The Quan, the General Statistical Office, for allowing us to access the 2002 household survey data.
Scene retrieval with color moment invariant

In this paper, a novel scene retrieval method has been proposed. Under this framework, homogeneous color regions are detected and then described by color moment invariants. Different from most existing methods, color and spatial information are combined as the uniform descriptor to capture the image property. Moreover, the image descriptor in our method has alterable data structure, whose size is adaptive to the context of the image itself by a two-stage clustering technique. Experimental results show that this method has improved efficiency and robustness of color based image retrieval methods, without the cost of simplicity and compactness.
Assessment of Trace Estrogenic Contaminants Removal by Coagulant Addition, Powdered Activated Carbon Adsorption and Powdered Activated Carbon/Microfiltration Processes

Increasing attention is being paid to health and environmental risk as a result of the presence of trace steroid estrogens in the effluent discharged from municipal sewage treatment plants. This paper focuses on assessment of removal of these trace compounds using 3H-labeled estrone as the model compound. Jar tests over a range of ferric chloride dosages and pH conditions showed that coagulation was ineffective in removal of estrone from secondary effluent. The experiments showed that the combination of powdered activated carbon (PAC) and microfiltration could be effective for removal of trace estrone from water. The rate and extent of estrone removal by PAC are functions of PAC dosage and retention time of PAC in the system. Mathematical analysis of the results using a homogeneous surface diffusion model indicates that the adsorption of estrone on PAC can be limited by film diffusion and internal surface diffusion. The surface and film mass transfer coefficients were determined to be 1.59x10\U-9\N cm\U2\N/min and 0.6 cm/min, respectively, under the conditions used.
Consistency of EKF-Based Visual-Inertial Odometry

In this report, we perform a rigorous analysis of EKF-based v isual-inertial odometry (VIO) and present a method for improving its performance. Specifically, we examine the pro pe ties of EKF-based VIO, and show that the standard way of computing Jacobians in the filter inevitably causes incon sistency and loss of accuracy. This result is derived based on an observability analysis of the EKF’s linearized system model, which proves that the yaw erroneously appears to be observable. In order to address this problem, we propose m difications to the multi-state constraint Kalman filter (MSCKF) algorithm [1], which ensure the correct observabil ity properties without incurring additional computationa l cost. Extensive simulation tests and real-world experimen ts demonstrate that the modified MSCKF algorithm outperform s competing methods, both in terms of consistency andaccuracy.
Global robust output regulation for Lur'e systems

We consider the global output regulation problem for systems with an output depending nonlinearity. If the system model is known and the corresponding regulator equations are solvable, an observer-based controller solving the global output regulation problem is presented. Sufficient conditions for the existence of such a controller are formulated in terms of an LMI. If the system parameters are not exactly known and the nonlinearity can vary over a given class, we show that there exists a robust controller provided that the robust output regulation problem for the system without the nonlinearity is solvable and that there exists a suboptimal solution to a certain H/sub /spl infin// optimization problem.