Miracle-dz/UniFAR-FTUs huggingface dataset:
Object Detection with Appearance-based Mixture Models Anonymous CVPR submission

Object detection is typically formulated as a binary classification problem in which the positive examples are bounding boxes containing instances of the object and negative examples are the randomly sampled boxes not containing the object. Due to large intra-class variation in the object pose, appearance and camera viewpoint, object detectors often have a tough time learning a single discriminative classifier that can achieve good performance on a challenging testset. To relieve the classifier of this Sisyphean burden, mixture models have been advocated, where positive examples are segregated into sub-categories such that all instances within a sub-category share a common characteristic. However, most approaches resort to heuristic techniques or rely on additional label/3D information for clustering the data. In this paper, we present a simple mixture model for object detection based on unsupervised appearance-based clustering of object instances. The approach is general, requiring no additional labels or heuristics, and it yields improved performance in the detection task.
An Evaluation of Bone-conducted Ultrasonic Hearing-aid regarding Transmission of Japanese Prosodic Phonemes

Human listeners can perceive speech signals from a voice-modulated ultrasonic carrier which is presented through a bone-conduction stimulator (bone-conducted ultrasound, BCU), even if they are sensorineural hearing loss patients. As an application of this phenomenon, we have been developing a bone-conducted ultrasonic hearing aid (BCUHA). The performance of BCUHA has been evaluated considering syllable articulation and word intelligibility. These studies showed that the syllable articulation scores when using BCU were over than 60%, and the word intelligibility scores for words with high familiarity were over than 85%. The patterns of confusion in speech perception in the case of BCU have many points of similarities with those for air-conduction (AC). Although performance of BCUHA regarding perception of segmental units were evaluated, performance of perception of suprasegmental or prosodic units have not been evaluated. Japanese is a pitch accent language. Many words are contrasted by its tonal features, for example, “a’ka” (red) vs. “aka” (dirt). Also Japanese is a mora-timed language. All vowels and some consonants are contrasted by its lengths, like “obasan” (aunt) vs. “oba:san” (grandma), “kita” (came) vs. “kit:a” (cut). Since prosodic units of Japanese function as phonemes as described above, thus the perception of prosodic elements plays important role for Japanese. The purpose of this study is to evaluate the performance of perception of prosodic phoneme through BCUHA. A series of experiments which consist of minimal pairs judgement task was conducted. The minimal pairs were differentiated by prosodic elements. A pair of logatomes “etete” and “ete:te” was selected for long/short vowel discrimination task, “etete” and “etette” were for single/geminate consonant, and a pair of real words “a’ka” and “aka” was for pitch accent. Stimuli were speech sounds continua which manipulated its prosodic element. Experiments were designed as singlestimulus two-alternative forced-choice identification tasks. Ten native Japanese listeners participated in the experiments. To examine whether difference between normal air-conducted hearing (AC) and BCU hearing regarding perception pattern of prosodic elements was observed, the same tasks were conducted in AC and BCU condition. From results of the experiments, the position and the sharpness of categorical boundaries were computed by using logistic regression analyses, and then examined whether significant differences were observed by using t-tests. From analysis of t-tests, significant difference between AC and BCU conditions was not observed in all tasks. This result indicates that the BCUHA can effectively transmit prosodic phoneme as well as segmental element.
Labour Market Entry Conditions, Wages and Job Mobility

Economic conditions at the time of labour market entry can induce wage differentials between workers entering the labour market at different points in time. While the existence and persistence of these entry wage differentials are well documented, little is known about their interaction with employees' mobility behaviour. This paper contributes to this research area by analyzing the interaction between job mobility and entry wage differentials using German administrative data. The results suggest that labour market entrants earning less than the average starting wage are more likely to change jobs, directly from employer to employer as well as indirectly via an unemployment spell. In addition they are more likely to change occupation. Moreover, job mobility tends to reduce the effects of labour market entry conditions, implying that job mobility operates as an adjustment mechanism that mitigates entry wage differentials. These results hold not only for high-skilled, but also for medium-skilled and unskilled workers.
Estimating future demand for hospital emergency services at the regional level

The level of demand for hospital emergency services is closely connected to the demographic characteristics of a region's population. The objective of this study is to examine the influence of changes in population size and structure on the volume of emergency service needs exhibited by patients arriving at hospital emergency departments in the area. The Monte Carlo simulation model examines demographic trends at the regional level, formulates forecasts for population changes, and extrapolates the simulated patterns of the demand for acute services. The model includes data on the population in 9 districts that surround Wrocław, the capital of Lower Silesia (Poland) and data on acute visits to emergency departments located in the region. Our analysis suggests that two age groups, i.e., children aged 0-4 and elderly people aged 60 and over, are responsible for a large share of the changes in the demand level.
Māori and Pacific secondary student and parent perspectives on achievement, motivation and the NCEA

New Zealand's previous examination-based secondary assessment system can be viewed as encompassing cultural values presenting unfair challenges for indigenous and other nonmajority students. The standards-based National Certificate of Educational Achievement (NCEA) incorporates enhanced flexibility, student choice and grading practices independent of comparisons with others. These features may be a better match for the educational aspirations of collectivist cultures, yet little is known about the views of Maori and Pacific students and their parents on NCEA. In this study, Maori and Pacific students and parents were interviewed about NCEA and its impact on motivation and achievement. Participants reported valuing the opportunities and outcomes associated with NCEA while emphasising where further work is needed. The implications of these findings are discussed for policy and practice within the NCEA framework.
Introducing PALLA, a novel input device for leisure activities: a case study on a tangible video game for seniors

In this paper we introduce PALLA, a spherical wireless input device with simple feedback capabilities to be used in video games and leisure activities. PALLA allows users to exploit their perceptual-motor skills and primarily targets people who may not be used to technologies, such as seniors. We first provide a description of the human interaction possibilities that PALLA enables, enriched by a brief presentation of the device hardware design and of the algorithmic solutions we adopted. Then, we present the results of a user study we conducted with senior players in the context of PandaGolf, a tangible video game we developed and used as a test bed, with the aim of assessing the acceptability of PALLA.
Decreasing greenhouse emissions through an intelligent traffic information system based on inter-vehicle communication

Traffic congestion is an urban mobility problem, which generates stress to drivers and economic losses. In 2012, greenhouse gas emissions from transportation accounted for about 28% of total U.S. greenhouse gas emissions. Intelligent transportation systems can assist in the identification and reduction of vehicular traffic congestion. In this context, this work proposes an intelligent traffic information system based on inter-vehicle communication to avoid vehicle traffic congestion. The main goal of the proposed solution is to decrease CO2 emissions, the average trip time and fuel consumption by avoiding congested roads. Simulation results show that our proposed solution can reduce the average trip time, and the overall CO2 emission and fuel consumption. In particular, the trip time was decreased approximately 86%, the fuel consumption 40% and the CO2 emission 55%. This shows the potential of the proposed solution.
Online Learning of Uneven Terrain for Humanoid Bipedal Walking

We present a novel method to control a biped humanoid robot to walk on unknown inclined terrains, using an online learning algorithm to estimate in real-time the local terrain from proprioceptive and inertial sensors. Compliant controllers for the ankle joints are used to actively probe the surrounding surface, and the measured sensor data are combined to explicitly learn the global inclination and local disturbances of the terrain. These estimates are then used to adaptively modify the robot locomotion and control parameters. Results from both a physically-realistic computer simulation and experiments on a commercially available small humanoid robot show that our method can rapidly adapt to changing surface conditions to ensure stable walking on uneven surfaces.
Preliminary theoretical framework for the study of business ecosystems

In this paper a preliminary theoretical framework for the study of business ecosystems is constructed. It is based on theories from the fields of complexity and evolutionary economics. Important concepts include the following: coevolution, self-organization, emergence, conscious choice, limited knowledge, interconnectedness, feedback and the interaction of variation, selection and development.
Minimization on the Lie Group SO(3) and Related Manifolds

This paper presents a novel approach to carrying out numerical minimization procedures on the Lie Group SO(3) and related manifolds. The approach constructs a sequence of local parameterizations of the manifold SO(3) rather than relying on a single global parameterization such as Euler angles. Thus, the problems caused by the singularities in these global parameterizations are avoided. 1 This research was supported by the NSF under grant number NYI IRI-9257990.
Composite Interval Mapping Based on Lattice Design for Error Control May Increase Power of Quantitative Trait Locus Detection

Experimental error control is very important in quantitative trait locus (QTL) mapping. Although numerous statistical methods have been developed for QTL mapping, a QTL detection model based on an appropriate experimental design that emphasizes error control has not been developed. Lattice design is very suitable for experiments with large sample sizes, which is usually required for accurate mapping of quantitative traits. However, the lack of a QTL mapping method based on lattice design dictates that the arithmetic mean or adjusted mean of each line of observations in the lattice design had to be used as a response variable, resulting in low QTL detection power. As an improvement, we developed a QTL mapping method termed composite interval mapping based on lattice design (CIMLD). In the lattice design, experimental errors are decomposed into random errors and block-within-replication errors. Four levels of block-within-replication errors were simulated to show the power of QTL detection under different error controls. The simulation results showed that the arithmetic mean method, which is equivalent to a method under random complete block design (RCBD), was very sensitive to the size of the block variance and with the increase of block variance, the power of QTL detection decreased from 51.3% to 9.4%. In contrast to the RCBD method, the power of CIMLD and the adjusted mean method did not change for different block variances. The CIMLD method showed 1.2- to 7.6-fold higher power of QTL detection than the arithmetic or adjusted mean methods. Our proposed method was applied to real soybean (Glycine max) data as an example and 10 QTLs for biomass were identified that explained 65.87% of the phenotypic variation, while only three and two QTLs were identified by arithmetic and adjusted mean methods, respectively.
An Energy Efficient Risk Notification Message Dissemination Protocol for Vehicular Ad hoc Networks

We propose the design and development of an energy-efficient Risk Notification Message Dissemination Protocol (RNMDP) for vehicular ad hoc networks (VANETs). RNMDP propagates Risk Notification Messages (RNMs) from their location of origin (called the Risk Zone) to vehicles approaching the Risk Zone. RNMDP assumes each node is aware of its current location in the network. The protocol works as follows: A RNM is broadcast in the neighborhood of the Risk Zone. A node receiving the RNM from another node waits for a Rebroadcast-Wait-Time before deciding to rebroadcast the message. The Rebroadcast-Wait-Time for a node is modeled based on the ratio of the distance between the node and the immediate sender of the RNM and the direction of movement of the node. Priority for rebroadcast is given for nodes farthest away from the sender and traveling towards the Risk Zone. Nodes that are traveling in lanes in direction away from the Risk Zone are also considered for rebroadcast, albeit with a larger Rebroadcast-Wait-Time. During the Rebroadcast-Wait-Time, if a node hears the same RNM again rebroadcast in the neighborhood, then the node stops from further broadcasting the message. If a node does not hear the RNM in its neighborhood during the RebroadcastWait-Time, the node broadcasts the message in its neighborhood. A RNM is considered to have been delivered to all the vehicles in the road, if the message reaches the Target Zone. The performance of RNMDP has been compared with that of the commonly used flooding strategy through extensive simulations conducted for highway networks with different number of lanes and lane density. Simulation results indicate that with a slightly larger delay (i.e., no more than 35% of the delay incurred for flooding), RNMDP can achieve the same message delivery ratio attained by flooding, but at a relatively much lower energy loss compared to flooding.
Domain Decomposition Preconditioned GMRES Algorithms for High-Order Compact Discretisations of Convection-Diffusion Problems

In this paper, we present some preliminary work based on domain decomposition preconditioned GMRES algorithms for solving non-symmetric linear systems arising from the high-order compact discretisations of some elliptic model problems. We describe numerical experiments with domain decomposition based preconditioners. The additive and multiplicative Schwarz preconditioners are considered. The results obtained from the computational experiments indicate that the multiplicative variant of the Schwarz preconditioned GMRES algorithm performs better than the additive variant.
Partial evaluation of the reversible language janus

A reversible programming language is a programming language in which you can only write reversible programs, i.e., programs that can be run both forwards (computing outputs from inputs) and backwards (computing inputs from outputs). It is interesting to study reversible programs and languages because computations on reversible computers (computers that only allow reversible programs) in theory can be done using less energy than computations on traditional irreversible computers. Janus is a reversible, structured imperative programming language. We present a partial evaluator for the full Janus language with the exception of procedure calls. The partial evaluator converts Janus programs into reversible flowcharts, specialises these using polyvariant specialisation and converts the result back to structured form. Reversibility adds some complications, which we address in the paper. We demonstrate the results by some small examples. We believe this to be the first partial evaluator for a deterministic reversible programming language.
ADD-1/SREBP-1 is a major determinant of tissue differential lipogenic capacity in mammalian and avian species.

Fatty acid synthase (FAS), a key lipogenic enzyme, is expressed in the two major sites of fatty acid production in the body, that is, the liver and the adipose tissue. Surprisingly, the relative contribution of these sites to lipogenesis is highly variable among species. For example, besides the situation in rodents, where liver and fat are equally active, lipogenesis in some mammals such as the pig occurs principally in adipose tissue, whereas in avian species, the liver is the main lipogenic site. We addressed the question concerning the factors determining the site of fatty acid synthesis. We show that the expression of adipocyte determination and differentiation-dependent factor 1/sterol regulatory element-binding protein (ADD-1/SREBP-1) mRNA, but not SREBP-2, is linked to FAS protein content or activity in adipose tissues and livers of pig, chicken, and rabbit. Tissue differences in ADD-1/SREBP-1 mRNA expression between species were paralleled by commensurate variations in the nuclear concentration of SREBP-1 protein. Moreover, overexpression of ADD-1/SREBP-1 by adenoviral gene transfer induces FAS in chicken adipocytes, where lipogenesis is normally low. Conversely, the expression of a dominant negative form of ADD-1/SREBP-1 in pig adipocytes downregulates FAS expression. These results reinforce the role of ADD-1/SREBP-1 as a key regulator of lipogenesis, by extending its importance to nonrodent mammals and birds. Furthermore, they establish that differential expression of ADD-1/SREBP-1 is a key determinant of the site of fatty acid synthesis in the body. -Gondret, F. , P. Ferré, and I. Dugail. ADD-1/SREBP-1 is a major determinant of tissue differential lipogenic capacity in mammalian and avian species. J. Lipid Res. 2001. 42: 106;-113.
Approximate Planning for Factored POMDPs using Belief State Simplification

We are interested in the problem of planning for factored POMDPs. Building on the recent results of Kearns, Mansour and Ng, we provide a planning algorithm for factored POMDPs that exploits the accuracy efficiency tradeoff in the belief state simplification introduced by Boyen and Koller.
Towards a benchmark for graph data management and processing

Graph data is used in an increasing number of analytical data processing applications, ranging from social network analysis, to monitoring of network traffic, and to ontologies in the semantic web. Both application-specific and general graph data management systems have been proposed to address this trend. Nevertheless, it would be foolish to dismiss relational and object databases as possible solutions for graph data management and processing, due to the vast amount of experience that they encompass. As a consequence, graph data analysts are faced with a broad variety of choices and approaches. However, regardless of the approach taken, users need to be able to evaluate and assess which of the many possible solutions works best in their use case. We propose a benchmark in terms of a data model, query workload, sample data sets, and usage scenarios. We also report performance figures measured based on an opensource graph database as well as commercial relational and object databases. Finally, we discuss how our benchmark can be used to characterize databases with respect to particular application scenarios.
Imaging ER-to-Golgi transport: towards a systems view

Summary Proteins synthesised at the endoplasmic reticulum (ER) have to undergo a number of consecutive and coordinated steps to reach the Golgi complex. To understand the dynamic complexity of ER-to-Golgi transport at the structural and molecular level, light microscopy approaches are fundamental tools that allow in vivo observations of protein dynamics and interactions of fluorescent proteins in living cells. Imaging protein and organelle dynamics close to the ultra-structural level became possible by combining light microscopy with electron microscopy analyses or super-resolution light microscopy methods. Besides, increasing evidence suggests that the early secretory pathway is tightly connected to other cellular processes, such as signal transduction, and quantitative information at the systems level is fundamental to achieve a comprehensive molecular understanding of these connections. High-throughput microscopy in fixed and living cells in combination with systematic perturbation of gene expression by, e.g. RNA interference, will open new avenues to gain such an understanding of the early secretory pathway at the systems level. In this Commentary, we first outline examples that revealed the dynamic organisation of ER-to-Golgi transport in living cells. Next, we discuss the use of advanced imaging methods in studying ER-to-Golgi transport and, finally, delineate the efforts in understanding ER-to-Golgi transport at the systems level.
A Stage‐Based Population Model for Loggerhead Sea Turtles and Implications for Conservation

Management of many species is currently based on an inadequate under- standing of their population dynamics. Lack of age-specific demographic information, particularly for long-lived iteroparous species, has impeded development of useful models. We use a Lefkovitch stage class matrix model, based on a preliminary life table developed by Frazer (1983a), to point to interim management measures and to identify those data most critical to refining our knowledge about the population dynamics of threatened log- gerhead sea turtles (Caretta caretta). Population projections are used to examine the sen- sitivity of Frazer's life table to variations in parameter estimates as well as the likely response of the population to various management alternatives. Current management practices appear to be focused on the least responsive life stage, eggs on nesting-beaches. Alternative protection efforts for juvenile loggerheads, such as using turtle excluder devices (TEDs), may be far more effective.
New sensorless fuzzy logic control strategy of wind energy conversion systems

In this manuscript, we propose to compare two novel sensorless strategies control of doubly fed induction generator (DFIG) based on the output electrical power, and rotor and stator current with stator voltage measurement. The performances of the proposed sensorless strategies are compared. The developed control strategy was tested for different operating modes: real wind speed with balanced and unbalanced grid voltage, stepped wind speed with balanced and unbalanced grid voltage. The principle of the rotational speed estimation is described and implemented using Matlab/Simulink software. The simulation results demonstrate the feasibility of the control strategy based on the measurement of the output power.