Miracle-dz/UniFAR-FTUs huggingface dataset:
Discovery of a Low Surface Brightness Object near Seyfert’s Sextet

We report the discovery of a low surface brightness (LSB) object serendipitously found during deep CCD imaging of a compact group of galaxies, Seyfert's Sextet, in the VR and I bands. The LSB object is located 2. ′3 southwest from the group's center. Its surface brightness within the angular effective radii of reff(VR) = 4. ″8 and reff(I) = 4. ″8 is very low: μeff(VR) = 25.28 mag arcsec-2 and μeff(I) = 24.47 mag arcsec-2, respectively. The apparent magnitudes are mAB(VR) = 19.87 and m(I) = 19.06. The object is most likely an LSB dwarf galaxy, but other possibilities are also discussed.
Hybrid Evolutionary Algorithm-based Schemes for Subcarrier, Bit, and Power Allocation in Multiuser OFDM Systems

Multiuser orthogonal frequency division multiplexing (OFDM) is a very promising multiple access technique to efficiently utilize limited RF bandwidth and transmit power in wideband transmission over multipath fading channels. When a wideband spectrum is shared by multiple users in multiuser OFDM-based systems, different users may experience different fading conditions at all subcarriers. Each user is assigned a subset of all subcarriers by some allocation algorithm. Thus, multiuser diversity can be achieved by adaptively adjusting subcarrier, bit, and power allocation depending on channel status among users at different locations (Wong et al., 1999a). In (Wong et al., 1999a), Wong applies a Lagrangian optimization technique and an iterative algorithm to solve the subcarrier, bit and power allocation problem. The suboptimal scheme for the NP-hard joint optimization problem is decoupled into two steps while it has a high computational complexity. A sub-optimal algorithm has been proposed to solve a related problem (Wong et al., 1999b). In (Wong et al., 1999b), Wong presents a real-time subcarrier allocation (SA) algorithm. It is a two-phase algorithm, including the constructive initial assignment (CIA) and the subcarrier swapping steps. The initial subcarrier allocation algorithm needs to pre-determine the numbers of subcarriers for each user before the allocation process starts. The performance of the SAbased algorithm will be compared in the simulation. In (Kim et al., 2006), Kim shows that the allocation problem in (Wong et al., 1999a) can be transformed into an integer programming (IP) problem. The branch-and-bound algorithm (Wolsey, 1998) can be employed to find the optimal solution of the allocation problem which has exponential computational complexity in the worse cases. We utilize the approach to obtain the optimal solution as the performance bound for comparison. Evolutionary algorithms (EA) are used to solve extremely complex search and optimization problems which are difficult to solve through simple methods. EAs are intended to provide a better solution, as it is based on the natural theory of evolution. Evolutionary algorithm (EA)-based schemes have been applied to solve subcarrier, bit, and power allocation problems (Wang et al., 2005) (Reddy et al., 2007) (Reddy & Phora, 2007) (Pao & Chen, 2008). In general, chromosomes can be designed with binary, integer, or real representation. The chromosome lengths are related to the number of subcarriers. Each element in the chromosome is a subcarrier allocated to a user. In this research, a subset of subcarriers can be assigned to one user depending upon the availability of subcarriers at a particular time
Social Equality: Cognitive Modeling Based on Emotional Coherence Explains Attitude Change

Why do people have conflicting views of equality concerning the distribution of income, wealth, and satisfaction of vital needs? How do people form and sometimes change their views of equality and related issues, such as gender identity? Answers to such questions can benefit from cognitive science—the interdisciplinary field that includes neuroscience and computer modeling as well as psychology. According to principles of emotional coherence, attitudes develop and change because of connections among the values attached to systems of concepts, beliefs, and goals. People attach a positive value to concepts such as equality, if the concept fits with other positive concepts such as human needs, and opposes negative concepts such as poverty. Emotional coherence balances positive and negative values to yield an overall conclusion. Computer models based on emotional coherence explain people’s differing attitudes about equality and issues such as transgender rights. They also model how people sometimes change their minds.
Dydruma : A Dynamic Drug Map for Exploring the Associations Among Drug Therapeutic Indications and Side-Effects

Inferring potential therapeutic indications and identifying clinically important side-effects are both important and challenging tasks in modern drug development. Previous studies have utilized drug chemical structures and protein targets to construct predictive models for both tasks. According to our study, the drug therapeutic information itself is highly predictive for side-effects, and drug side-effect information highly predictive of therapeutic indication. This confirms that there exist underlying associations among drug therapeutic indications and side-effects. Exploring these associations can lead to better understanding of the drugs as well as more informed hypotheses for drug repositioning and adverse effect monitoring. In practice however, it is impractical to check all possible associations using an exhaustive list. In this study, we present Dydruma, a dynamic drug map which encodes drug therapeutic indications and side-effects as well as their associations. The map can be dynamically adjusted based on a significance value attached to each association, where the significance value is derived from a statistical test such as Fisher’s exact test. We describe an optimization-based approach for dynamic bipartite graph layout to ensure visual continuity among successive layouts at different significance thresholds, to help the user maintain a consistent mental map throughout the exploration. We demonstrate the effectiveness of dytruma for exploring the associations among drug indications and side effects and for hypothesis generation using real world data sets.
Survey of Text Clustering

Clustering text documents into different category groups is an important step in indexing, retrieval, management and mining of abundant text data on the Web or in corporate information systems. Text clustering task can be intuitively described as finding, given a set vectors of some data points in a multi-dimensional space, a partition of text data into clusters such that the points within each cluster are similar to each other. Good text clustering enables better information services by browsing and organizing documents into meaningful cluster hierarchies and provides a useful complement for traditional text search engines when key-word based search returns too many documents. Among others, the challenging problems of text clustering are big volume, high dimensionality and complex semantics. In this paper we are interested in the solutions to these problems. For the first two problems, subspace clustering can provide bright future, ontology can provide promising solution to the third one.
Robust control for markov jump linear system in fixed time interval

This paper is concerned with the finite-time control problem of continuous-time linear system that posses randomly jumping parameters which can be described by finite-state Markov processes. The main results provided are sufficient conditions for mean square finite-time stability (MSFTS) and mean square finite-time boundedness (MSFTB) via state feedback. Such sufficient conditions can be turned into feasibility problems involving LMIs. A detailed example is presented to illustrate the proposed methodology.
Beyond Hyper-Minimisation---Minimising DBAs and DPAs is NP-Complete

In this paper we study the problem of minimising deterministic automata over finite and infinite words. Deterministic finite automata are the simplest devices to recognise regular languages, and deterministic \buchi, \cobuchi, and parity automata play a similar role in the recognition of $\omega$-regular languages. While it is well known that the minimisation of deterministic finite and weak automata is cheap, the complexity of minimising deterministic \buchi\ and parity automata has remained an open challenge. We establish the NP-completeness of these problems. A second contribution of this paper is the introduction of almost equivalence, an equivalence class for strictly between language equivalence for deterministic \buchi\ or \cobuchi\ automata and language equivalence for deterministic finite automata. Two finite automata are almost equivalent if they, when used as a monitor, provide a different answer only a bounded number of times in any run, and we call the minimal such automaton relatively minimal. Minimisation of DFAs, hyper-minimisation, relative minimisation, and the minimisation of deterministic \buchi\ (or \cobuchi) automata are operations of increasing reduction power, as the respective equivalence relations on automata become coarser from left to right. Besides being a natural equivalence relation for finite automata, almost equivalence is language preserving for weak automata, and can therefore also be viewed as a generalisation of language equivalence for weak automata to a more general class of automata. From the perspective of \buchi\ and \cobuchi\ automata, we gain a cheap algorithm for state-space reduction that also turns out to be beneficial for further heuristic or exhaustive state-space reductions put on top of it.
Comparison of wireless gateway concepts for industrial real-time-communication

Wireless industrial communication systems are increasingly deployed for process automation and sensor/actuator networks with moderate requirements on latency and reliability. Many closed-loop control systems with more challenging latency and reliability requirements would benefit from wireless communication as well and have therefore become a research field of increasing interest in recent year. In the German research project ParSec novel concepts for deterministic and highly reliable wireless communication are developed. In this paper we discuss gateway concepts to enable seamless integration of such wireless communication systems into isochronous Industrial Ethernet systems with short cycle-times of 1 ms and below.
HMM-based dance step estimation for dance partner robot -MS DanceR$

We have proposed a dance partner robot, which has been developed as a platform for realizing the effective human-robot coordination with physical interactions. In this paper, especially, we improve an estimation system for dance steps, which estimates a next dance step intended by a human. For estimating the dance step, time series data of force/moment applied by a human to the robot are utilized. The time series data of force/moment measured during dancing by a human and the robot include the uncertainty such as time-lag and variations for each repeated trial, because a human can not always apply the same force/moment to the robot exactly. In order to treat the time series data including such uncertainty, hidden Markov models are utilized for designing the dance step estimation system. With the proposed system, the robot estimates a next dance step based on human intention successfully.
Social self-efficacy training programme for basketball-playing students: A case study

In this study, the effectiveness of an educational programme for enhancing social self-efficacy prepared for basketball-playing students was investigated. Fifty-four male basketball-playing students ( M age = 16.47; SD = .73), practicing on two teams, participated in this study. The teams were randomly assigned into an experimental (n=26) and a control (n=28) group. The intervention was designed to help basketball-playing students to determine their social self-efficacy by engaging in interactive activities and role play scenarios. To assess the effectiveness, a Social Self-efficacy Subscale, and a Multi-dimensional Control, Agency, and Means-ends Inventory for Friends were used. The findings showed that this educational programme for enhancing social self-efficacy was effective for basketball-playing students’ social self-efficacy, and social self-efficacy beliefs in personal controllability and in control expectancy.
Comparing reward-based optimal behaviors in user-adapted Recommender Systems

Conversational Recommender Systems (CRSs) are intelligent E-commerce applications that interactively assist online users by following a default recommendation strategy. Typically, the strategy remains hard-coded during the interaction, thus making it impossible for CRSs to adapt to the dynamic user needs. In a previous paper, we have proposed and validated a novel technology that allows CRSs to autonomously improve a default strategy and learn the optimal (best) one. Our approach is based on the Reinforcement Learning (RL) paradigm, and uses a numerical reward model that is pre-selected arbitrarily by the system designers. In this context, it becomes important to determine the effect of using different reward models on the optimal system behavior. In this paper, we investigate the issue of strategy-learning under different reward model selections. We show that, even in a limited (simulated) setting, different and intelligent optimal behaviors are learnt under different rewards, and that our results largely correlate with our hypotheses about the expected optimal system behavior. We also deduce the importance of selecting the reward model carefully, based on the users' contextual needs.
Privacy-Preserving Interdomain Routing at Internet Scale

Abstract The Border Gateway Protocol (BGP) computes routes between the organizational networks that make up today’s Internet. Unfortunately, BGP suffers from deficiencies, including slow convergence, security problems, a lack of innovation, and the leakage of sensitive information about domains’ routing preferences. To overcome some of these problems, we revisit the idea of centralizing and using secure multi-party computation (MPC) for interdomain routing which was proposed by Gupta et al. (ACM HotNets’12). We implement two algorithms for interdomain routing with state-of-the-art MPC protocols. On an empirically derived dataset that approximates the topology of today’s Internet (55 809 nodes), our protocols take as little as 6 s of topology-independent precomputation and only 3 s of online time. We show, moreover, that when our MPC approach is applied at country/region-level scale, runtimes can be as low as 0.17 s online time and 0.20 s pre-computation time. Our results motivate the MPC approach for interdomain routing and furthermore demonstrate that current MPC techniques are capable of efficiently tackling real-world problems at a large scale.
Comment on ‘‘Present-day expansion of American beech in northeastern hardwood forests: Does soil base status matter?’’

In a recent rapid communication, Duchesne and Ouimet (2009. Can. J. For. Res. 39: 2273–2282) reported that the current expansion of American beech (Fagus grandifolia Ehrh.) in Quebec is mainly caused by soil base cation depletion due to atmospheric acid deposition. They based their conclusions on an examination of the relationships between stem densities in the sapling and tree strata compared against canopy composition and the availability of base cations in 426 sample plots. Here in this comment, we raise some shortcomings with their study and provide a more prudent and complete perspective on the complex dynamics associated with fluctuations in American beech and sugar maple (Acer saccharum Marsh.).
Modeling Human Behavior to Reduce Navigation Time of Menu Items: Menu Item Prediction Based on Markov Chain

With the increase in the number of menu items and the menu structure complexity, users have to spend more time in locating menu items when using menu-based interfaces. Recently, adaptive menu techniques have been explored to reduce the time and menu item prediction plays a crucial role in the techniques. Unfortunately, there still lacks effective prediction models for menu items. This chapter per the authors explores the potential of three prediction models based on Markov chain in predicting top n menu items with human behavior data while interacting with menus the users’ historical menu item selections. The results show that Weighted Markov Chain using Genetic Algorithm can obtain the highest prediction accuracy and significantly decrease navigation time by 22.6% when N equals 4 as compared to the static counterpart. Two application scenarios of these models on mobile devices and desktop also demonstrated the potentials in daily usage to reduce the time spent to search target menu items.
Performance Evaluation of Power Aware VM Consolidation using Live Migration

Power Efficiency is the efficient use of power and is a crucial come forth in cloud computing environment. Green Computing is nothing but is a cloud computing with efficient use of power and green refers to make the environment friendly to the user by saving heat and power. Data centre power efficiency in cloud environment will be reduced when virtualization is used as contrary to physical resource deployment to book adequate to grant all application requests. Nevertheless, in any case of the resource provisioning approximation, occasion remains in the way in which they are made attainable and workload is scheduled. The objective of this research work is therefore to pack workload into servers, selected as a function of their cost to operate, to achieve (or as close to) the utmost endorsed employment in a cost-efficient manner, avoiding occurrences where devices are under-utilized and management cost is acquired inefficiently. This work has enhanced the existing work by introducing the dynamic wake up calls either to shut down the active servers or restart the passive server. The wakeup calls has been initiated dynamically. The overall objective is to decrease the response time of users which will be increased during wakeup time in existing research work.
Deconstructing Complexity in Air Traffic Control

While previous research has addressed air traffic controller workload as a function of cognitive complexity due to environmental and to a lesser degree, organizational factors, significantly less attention has been paid to the role of displays and complexity in the ATC environment. One drawback to new display technology is that in dynamic human supervisory control domains, it is not always clear whether a decision support interface actually alleviates or contributes to the problem of complexity. In an attempt to quantify the influence of environmental and display complexity factors on cognitive complexity, an experiment was conducted to determine if these two components could be effectively measured. Results revealed that the environmental factor of increasing aircraft number affected subject performance only slightly more than the display complexity factor of increased color categories. These findings are important because the use of color in displays is meant to reduce environmental complexity, not add to it.
Structuring host communication software for quality-of-service guarantees

STRUCTURING HOST COMMUNICATION SOFTWARE FOR QUALITY OF SERVICE GUARANTEES by Ashish Mehra Chair: Kang G. Shin This dissertation addresses several issues involved in structuring communication software at end hosts to provide per-connection quality of service (QoS) guarantees. Our primary thrust is on realizing deterministic QoS guarantees in an experimental setting. We design a novel QoS-sensitive communication subsystem architecture that provides components and mechanisms to manage communication resources in a QoS-sensitive fashion. This architecture is based on three key design principles: maintenance of QoS guarantees, overload protection via per-connection tra c enforcement, and fairness to best-e ort tra c. We demonstrate the e cacy of the architecture via experiments using our x-kernel-based prototype implementation. We develop admission control extensions to capture important implementation-related aspects not considered by theoretical resource management policies proposed in the literature. Communication performance is signi cantly a ected by implementation-related aspects such as preemption overheads and constraints, simultaneous management of CPU and link bandwidth, link scheduling paradigms at sending hosts, and packet input mechanisms at receiving hosts. We build a fulledged guaranteed-QoS communication service on a contemporary microkernel operating system using a new service architecture integrating a QoS-aware application programming interface, a reliable signalling and resource reservation protocol, and QoS-sensitive data transmission and reception. We develop architectural and admission control enhancements that capture new overheads and constraints imposed by a microkernel server con guration. The service is implemented and evaluated on Pentium-based PCs running OSF MK 7.2 and communicating across switched Ethernet. To enhance the portability of guaranteed-QoS communication services, we design selfparameterizing protocol stacks that pro le and parameterize themselves appropriately during data transfer. We experimentally evaluate a self-parameterizing guaranteed-QoS communication service to demonstrate the feasibility of our approach. Self-parameterizing protocol stacks are a natural way to design portable QoS-sensitive communication software. To provide \better than best-e ort" Internet connectivity, the performance impact of supporting integrated services in TCP/IP protocol stacks must be assessed. We have designed, implemented, and evaluated an RSVP-based QoS architecture for TCP/IP protocol stacks supporting an integrated services Internet. Using detailed kernel-based pro ling of RS/6000-based servers running AIX 4.2, we explore the performance impact of QoS support in TCP/IP protocol stacks. We conclude by outlining strategies for integrating QoS-sensitive communication subsystems with QoS-sensitive application scheduling policies within host operating systems. ii CHAPTER
Does morphological convergence imply functional similarity? A test using the evolution of quadrupedalism in ornithischian dinosaurs

Convergent morphologies are thought to indicate functional similarity, arising because of a limited number of evolutionary or developmental pathways. Extant taxa displaying convergent morphologies are used as analogues to assess function in extinct taxa with similar characteristics. However, functional studies of extant taxa have shown that functional similarity can arise from differing morphologies, calling into question the paradigm that form and function are closely related. We test the hypothesis that convergent skeletal morphology indicates functional similarity in the fossil record using ornithischian dinosaurs. The rare transition from bipedality to quadrupedality occurred at least three times independently in this clade, resulting in a suite of convergent osteological characteristics. We use homology rather than analogy to provide an independent line of evidence about function, reconstructing soft tissues using the extant phylogenetic bracket and applying biomechanical concepts to produce qualitative assessments of muscle leverage. We also optimize character changes to investigate the sequence of character acquisition. Different lineages of quadrupedal ornithischian dinosaur stood and walked differently from each other, falsifying the hypothesis that osteological convergence indicates functional similarity. The acquisition of features correlated with quadrupedalism generally occurs in the same order in each clade, suggesting underlying developmental mechanisms that act as evolutionary constraints.