Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization Methods for Large Scale Combinatorial Problems and Bijectivity Constrained Image Deformations

This thesis treats two separate but connected themes. This affiliation originates in optimization being the common choice of method for solving most of the occurring challenges. The first theme of the thesis is image segmentation. This is usually defined as the task of distinguishing objects from background in unseen images. This visual grouping process is typically based on low-level cues such as intensity, homogeneity or image contours. Popular approaches include thresholding techniques, edge based methods and region-based methods. Regardless of the method, the difficulty lies in formulating and describing the perception of what constitutes foreground and background in an arbitrary image. Furthermore, such a grouping is also highly contextually driven, certain image regions may be labeled differently depending on the task at hand - are we looking for people, buildings or trees? If one also allows for more labels than only foreground and background, the problem becomes increasingly harder and requires a much higher level of scene understanding. Once a formulation of the problem has been established and properly stated the question of how to efficiently solve it still remains. The complexity of this task and the size of most natural images typically leads to very large and difficult optimization problems. It is these issues we make an attempt at addressing in this thesis. We are interested in how to efficiently find visually relevant image partitions as well as how prior information can be included into the segmentation process. The second theme of this thesis concerns non-linear deformations of images and its applications. Functions that map $R^2$ onto itself are widely used in computer vision, medical imaging and computer graphics. What is common to all three is that mappings are used to model deformation occurring in natural images. As such deformations are highly complex they are near impossible to characterize. A reasonable and widely accepted assumption, or approximation, is that as the overall structure of the objects depicted will remain intact after deformation, hence folding or tearing of the images should never occur. Under these premises there must exist a dense mapping that is both one-to-one and onto. The deformations must be bijective. This is not entirely correct as for instance self-occlusion can not be described by bijective mappings. There exist an abundance of methods for parameterizing non-linear deformations. This part of the thesis concerns conditions for bijectivity of, perhaps the most commonly used method of describing non-linear deformations, the thin-plate spline mapping and its applications in computer vision. (Less)
100+ VoIP Calls on 802.11b: The Power of Combining Voice Frame Aggregation and Uplink-Downlink Bandwidth Control in Wireless LANs

The bandwidth efficiency of voice over IP (VoIP) traffic on the IEEE 802.11 WLAN is notoriously low. VoIP over 802.11 incurs high bandwidth cost for voice frame packetization and MAC/PHY framing, which is aggravated by channel access overhead. For instance, 10 calls with the G.729 codec can barely be supported on 802.11b with acceptable QoS - less than 2% efficiency. As WLANs and VoIP services become increasingly widespread, this inefficiency must be overcome. This paper proposes a solution that boosts the efficiency high enough to support a significantly larger number of calls than existing schemes, with fair call quality. The solution comes in two parts: adaptive frame aggregation and uplink/downlink bandwidth equalization. The former reduces the absolute number of MAC frames according to the link congestion level, and the latter balances the bandwidth usage between the access point (AP) and wireless stations. When used in combination, they yield superior performance, for instance, supporting more than 100 VoIP calls over an IEEE 802.11b link. The authors demonstrate the performance of the proposed approach through extensive simulation, and validate the simulation through analysis.
Bilateral symmetry detection based on scale invariant structure feature

Symmetry is a salient visual pattern in images. Symmetrical structure attracts human eye more than other regions. Therefore, detecting symmetry in an image is one of the crucial tasks in pattern recognition and computer vision research. Sparse key point based symmetry detection methods have been proposed which are fast and robust to noise showing superior detection performance. However, such local appearance-based methods have difficulties in capturing structure based patterns mostly supported by edges and contours. In this paper, we propose a scale invariant structure feature which describes points on extremum curvature along edges. We propose to use a histogram of curvature responses at respective scale space for description. Experimental evaluation on public shape dataset and real world images show that our structure feature works better in detecting visually salient structure based symmetry patterns.
0.5-V 5.6-GHz CMOS Receiver Subsystem

The building blocks of a 0.5-V receiver, including a receiver front-end and a low-pass filter (LPF), are fabricated using 0.18-mum CMOS technology. At 5.6 GHz, the receiver front-end achieves a voltage gain of 17.1 dB and a noise figure of 8.7 dB, while dissipating at 19.4 mW. The fifth-order low-pass Chebyshev filter achieves a corner frequency of 2.6 MHz and an input-referred noise of 28.5 nV/sqrt (Hz) at 6.8 mW. The receiver front-end is further integrated with the LPFs to form a highly integrated receiver subsystem at ultra-low voltage.
New fatherhood and psychological distress: a longitudinal study of Australian men.

Despite growing interest and concern about men's mental health during the perinatal period, we still do not know whether men are more vulnerable to mental health problems during this time. The current study is one of the first to use longitudinal, population-based data to investigate whether becoming an expectant and/or new father is associated with increases in psychological distress. We analyzed 10 waves of data collected annually (from 2001 to 2010) from the nationally representative Household, Income, and Labour Dynamics in Australia (HILDA) Survey. Over this time, 349 men were identified as new fathers (first child aged <1 year), and 224 of these men had been identified as "expectant fathers" during the previous wave. A total of 1,658 men remained "never fathers. " Psychological distress was measured using the 5-item Mental Health Inventory before the partner's pregnancy, during the partner's pregnancy, and during the first year of fatherhood. Longitudinal mixed models showed no significant increase in psychological distress as a function of expectant or new fatherhood; instead, some improvement in mental health was observed. The finding suggests that expectant and new fathers are not at greater risk of poor mental health. Future epidemiologic research should continue to identify those men who are most (and least) at risk during the perinatal period in order to target resources and assistance most effectively.
Manufacturing Capacity Revenue Management

Contract (custom) manufacturers of components and manufactured materials such as steel sell capacity under different contract terms to different buyers. In a common practice, the supplier offers a market standard price and lead time combination for products listed in its catalog. At the same time, it strikes annual contracts with some high-volume customers who require recurring delivery of a custom product at a short notice, usually timed to meet the buyer’s production schedule. Whereas the manufacturer is contractually bound to satisfy demand from these customers, it can dynamically choose which transactional orders to accept. In this article, we analyze two scenarios to help the manufacturer extract more revenue from its production capacity, which is used to serve both markets. In the first scenario, the manufacturer produces contractual orders on a make-to-order basis, and in the second scenario, it maintains finished goods inventory for such orders. At each decision epoch, the manufacturer decides (a) how much capacity to allocate to the production of contractual and transactional items, and (b) which transactional orders to accept, in order to maximize its long-run expected profit. We establish the structure of the optimal policies, propose scalable heuristics when optimal policies are hard to compute/implement, and obtain bounds. Our models are then used to study the effect of capacity choices and demand uncertainty on the optimal profit. We also show how the amount of capacity available, relative to demand, changes the desirability of serving either transactional-only, or both markets.
Small movements as communicational cues in HRI

In this short paper full body movements as communicational actions (such as steps), which are intuitively used to incite someone’s reaction, will be examined. Those movements are referred to as prompts. An observational study was conducted to examine those prompts in a narrow spatial configuration in a “make each other room” scenario. The observed small communicational movements are presented in this paper.
The Role of Proteins in Biosilicification

Although the use of silicon dioxide (silica) as a constituent of living organisms is mainly restricted to diatoms and sponges, the ways in which this process is controlled by nature continue to inspire and fascinate. Both diatoms and sponges carry out biosilificiation using an organic matrix but they adopt very different strategies. Diatoms use small and heavily modified peptides called silaffins, where the most characteristic feature is a modulation of charge by attaching long chain polyamines (LCPAs) to lysine groups. Free LCPAs can also cooperate with silaffins. Sponges use the enzyme silicatein which is homologous to the cysteine protease cathepsin. Both classes of proteins form higher-order structures which act both as structural templates and mechanistic catalysts for the polycondensation reaction. In both cases, additional proteins are continuously being discovered which modulate the process further. This paper concentrates on the role of these proteins in the biosilification process as well as in various applications, highlighting areas where focus on specific protein properties may provide further insight. The field of biosilification is a crossroads of different disciplines, where insight into the energetics and mechanisms of molecular self-assembly combine with fundamental biology, complex multicomponent colloidal systems, and an impressive array of potential technological applications.
Achieving Classification and Clustering in One Shot Lesson Learned from Labeling Anonymous Datasets

We propose an algorithm LADSCOMPLETE which can holistically assign label for tabular web data. We categorize columns into three types: Disjoint Set Column (DSC), Repeated Prefix / Suffix Column (RPS) and Numerical Column (NUM). For labeling DSC column, our method rely on hits count from web search engine (e.g Google, Yahoo and MSN). We formulate speculative queries to web search engine and use the principle of disambiguation by maximal evidence to come up with our solution. Experimental results from large number of sites in different domains and subjective evaluation of our approach show that the proposed algorithm LADSCOMPLETE works fairly well. In this line we claim that our algorithm LADSCOMPLETE is sound and complete. In order to assign label for the Disjoint Set Column, we need a candidate set of labels (e.g label library) which can be collected on-the-fly from user SQL query variable as well as from Web Form label tag. We classify a set of homogeneous anonymous datasets into meaningful label and at the same time cluster those labels into a label library by learning user expectation and materialization of her expectation from a site. We hypothesize that our proposed algorithm LADSCOMPLETE will do a good job for autonomous label assignment. We bridge the gap between two orthogonal research directions: wrapper generation and ontology generation from web site (i.e label extraction). We are NOT aware of any such prior work that address to connect these two orthogonal research for value added services such as online comparison shopping.
Ultrasound image segmentation by Bhattacharyya distance with Rayleigh distribution

In this paper, we study the problem of ultrasound image segmentation of kidney images. We propose a new region based active contour algorithm. The energy function of our algorithm is based on Chan-Vese energy function and the Bhattacharyya distance. In our framework, a curve is evolved to partition the image into two parts. Our algorithm minimizes the differences between each part and maximizes the distance of density function between each part. In the experiments, we use images of kidney phantoms and real ultrasound medical images to validate the performance our method. The results show that by taking into account the similarity of two different regions, the proposed method is able to deal with blurry boundaries in an ultrasound image and provide good results on both phantom and patient US images.
Segmentation of building models from dense 3 D point-clouds

This paper proposes an approach for the detection and partition of planar structures in dense 3D point clouds from facades. The aim is the creation of a polygonal model with a considerably lower complexity than the original data set. We perform a robust detection of the dominant facade planes and apply a sweep based scheme in order to detect structures like windows, doors, balconies in those planes.
Shock-excited Maser Emission from Supernova Remnants: G32.8−0.1, G337.8−0.1, G346.6−0.2, and the HB 3/W3 Complex

We present the results of VLA observations in the ground-state hydroxyl (OH) transition at 1720 MHz toward 20 supernova remnants (SNRs). We detect compact emission from four objects. For three of these objects (G32.8-0.1, G337.8-0.1, and G346.6-0.2), we argue that the emission results from masers that are shock-excited due to the interaction of the SNR and an adjacent molecular cloud. We observe a characteristic Zeeman profile in the Stokes V spectrum, which allows us to derive a magnetic field of 1.5 and 1.7 mG for G32.8-0.1 and G346.6-0.2, respectively. The velocity of the masers also allows us to determine a kinematic distance to the supernova remnants (SNRs). Our criteria for a maser to be associated with an SNR along the line of sight are that the position and velocity of the maser and SNR must agree and the OH (1720) emission must be unaccompanied by other OH lines.
The Practice of Imputation Methods with Structural Equation Models

When using survey data, researchers must evaluate how to eectively handle missing data. For social survey data, full information maximum likelihood methods are often implemented when the researcher is interested in structural equation models. This strategy is convenient to implement and provides acceptable results. Yet it does not incorporate any imputation methods for assessing the missing information. We examine the benets of imputation methods as an alternative for managing missing data, particularly in longitudinal surveys where missingness may be conditioned on previous panel data. Our goal is to outline the practical use of imputation and resulting gains in estimation. We apply these procedures to the Family Transitions Project, a longitudinal survey of more than 550 participants, which focuses on familial relationships and socioeconomic stress induced by economic hardships.
Binary biometric template generation towards security and class separability

Due to the wide usage of biometrics, its security issues deserve more attention. Many of biometric protection systems require the biometric templates to be presented in a binary form. Therefore, extracting binary templates from real-valued biometric data is a key step in biometric data protection systems. In addition to meeting the security and privacy requirements, binary biometric templates allow fast matching and reduced storage. The main challenge of these approaches is how to convert the real-valued templates into corresponding binary representation which retains the original information. In this paper, we present a novel method that employs Genetic Algorithms(GA)to generate a binarization scheme which used to transform the real-valued templates into robust binary ones. The main role of GA is to search for the optimal quantization and encoding parameters to generate the binarization scheme. Experiments were conducted with ORL face database for recognition. Our results demonstrated that binary templates achieved promising performance in terms of equal error rate for face recognition using a simple hamming distance classifier.
New Stable Isotope Record of Paleoecological Change in the Late Neogene of the Western Great Plains from Enamel in Large Mammals

An expansion of C 4 grasslands occurred between 6 and 8 million years ago in the Great Plains of North America, as evidenced by a marked shift to more 13 C-enriched carbon isotope compositions from large fossil mammal tooth enamel and paleosol carbonates. Prior to this expansion, habitats were comprised of exclusively C 3 vegetation. To explore this problem I present a compilation of bulk stable carbon (δ 13 C) and oxygen (δ 18 O) isotope values from a variety of large mammals from 6 localities that span from the late Clarendonian to the late Blancan in Nebraska. As expected, late Miocene taxa had δ 13 C values indicating that they exclusively exploited C 3 vegetation with habitats ranging from open forests in northern Nebraska to C 3 grasslands in southwest Nebraska. A shift to higher δ 13 C values occurs in Pliocene camelids, equids, and gomphotheres suggesting that they began to consume C 4 vegetation. In contrast, a peccary (Platygonus sp.) still consumed only C 3 vegetation indicating that C 3 niches were still present. Through this Miocene-Pliocene transition there is an overall shift to lower δ 18 O values in tooth enamel suggesting a long-term decrease in mean annual temperature. This agrees with previous work in the Great Plains and the marine realm. In addition, δ 18 O values from serial samples suggest that seasonality decreased from the Miocene to the Pliocene. These data agree with previous studies indicating global change in climate and vegetation from the late Miocene to the Pliocene.
Long-Lasting Effects of Oxy- and Sulfoanalogues of L-Arginine on Enzyme Actions

Arginine residues are very important for the structure of proteins and their action. Arginine is essential for many natural processes because it has unique ionizable group under physiological conditions. Numerous mimetics of arginine were synthesized and their biological effects were evaluated, but the mechanisms of actions are still unknown. The aim of this study is to see if oxy- and sulfoanalogues of arginine can be recognized by human arginyl-tRNA synthetase (HArgS)—an enzyme responsible for coupling of L-arginine with its cognate tRNA in a two-step catalytic reaction. We make use of modeling and docking studies of adenylate kinase (ADK) to reveal the effects produced by the incorporation of the arginine mimetics on the structure of ADK and its action. Three analogues of arginine, L-canavanine (Cav), L-norcanavanine (NCav), and L-sulfoarginine (sArg), can be recognized as substrates of HArgS when incorporated in different peptide and protein sequences instead of L-arginine. Mutation in the enzyme active center by arginine mimetics leads to conformational changes, which produce a decrease the rate of the enzyme catalyzed reaction and even a loss of enzymatic action. All these observations could explain the long-lasting nature of the effects of the arginine analogues.
Stability theory for hybrid dynamical systems

Hybrid systems which are capable of exhibiting simultaneously several kinds of dynamic behavior in different parts of a system are of great current interest. In the present paper we first formulate a definition of hybrid dynamical system which covers a very large number of classes of hybrid systems and which is suitable for the qualitative analysis of such systems. Next, we introduce the notion of invariant set (e.g., equilibrium) for hybrid dynamical systems and we define several types of (Lyapunov-like) stability concepts for an invariant set. We then establish sufficient conditions for the uniform stability and the uniform asymptotic stability of an invariant set of a hybrid dynamical system. Under some mild additional assumptions, we also establish necessary conditions for some of the above stability types (converse theorems). To demonstrate the applicability of the developed theory, we present two specific examples of hybrid dynamical systems and we conduct a stability analysis of one of these examples (a sampled-data feedback control system with a nonlinear (continuous-time) plant and a linear (discrete-time) controller).
Coaching Qualities, Gender, and Role Modeling

Male (N=121) and female (N=135) high school girls’ basketball coaches responded to three forced-choice questions related to gender and role modeling. Both genders said they preferred coaching girls to boys. Male coaches thought female athletes preferred a male coach, female coaches thought they preferred a female coach. Coaches of each gender perceived themselves as equal or better role models than their counterparts. Coaches were then asked to rank order the importance of six coaching qualities previously identified as either expressive or instrumental. First they ranked the qualities in importance as they perceived them, then in the order they thought players would rank them. Coaches differed significantly by gender on the rankings of the qualities, as well as their perceptions of how athletes might rank the same qualities. Implications for modeling and young female athletes are discussed in relation to gender differences in these perceptions.
Obstacle Avoidance

Given the a priori knowledge of the environment and the goal position, mobile robot navigation refers to the robot’s ability to safely move towards the goal using its knowledge and the sensorial information of the surrounding environment. Even though there are many different ways to approach navigation, most of them share a set of common components or blocks, among which path planning and obstacle avoidance (may) play a key role. Given a map and a goal location, path planning involves finding a geometric path from the robot actual location to the goal. This is a global procedure whose execution performance is strongly dependent on a set of assumptions that are seldom observed in nowadays robots. In fact, in mobile robots operating in unstructured environments, or in service and companion robots, the a priori knowledge of the environment is usually absent or partial, the environment is not static, i.e., during the robot motion it can be faced with other robots, humans or pets, and execution is often associated with uncertainty. Therefore, for a collision free motion to the goal, the global path planning has to be associated with a local obstacle handling that involves obstacle detection and obstacle avoidance. Obstacle avoidance refers to the methodologies of shaping the robot’s path to overcome unexpected obstacles. The resulting motion depends on the robot actual location and on the sensor readings. There are a rich variety of algorithms for obstacle avoidance from basic re-planning to reactive changes in the control strategy. Proposed techniques differ on the use of sensorial data and on the motion control strategies to overcome obstacles. The Bug’s algorithms (section 2:1), [1], [2], follow the easiest common sense approach of moving directly towards the goal, unless an obstacle is found, in which case the obstacle is contoured until motion to goal is again possible. In these algorithms only the most recent values of sensorial data are used. Path planning using artificial potential fields, [3], (section 2:2) is based on a simple and powerful principle that has an embedded obstacle avoidance capabil-