Miracle-dz/UniFAR-FTUs huggingface dataset:
Happiness and Social Exclusion of Indigenous Peoples in Taiwan - A Social Sustainability Perspective

Introduction Happiness and social inclusion are important indicators of social sustainability, as recommended in the Sustainable Development Goals; however, little is known about the social sustainable development of ethnic minorities. To fill this knowledge gap, special attention is paid to understanding the issues of social exclusion and happiness in relation to the indigenous peoples in Taiwan. Methods Data used were drawn from a nationwide representativeness survey of the Taiwanese Indigenous People in 2007; it included 2,200 respondents. This study employed binary logistic regression to examine the effects of different domains of social exclusion on the likelihood of perceiving happiness; other exogenous factors, were controlled. Results The results show that among the respondents, mountain indigenous peoples, females, the elderly and those who are healthier, wealthier, highly educated, possessing western beliefs, and are more likely to be happy, compared to their counterparts. As expected, the results reveal that the likelihood of being happy is higher for those who have received medical benefits, as well as those persons without housing problems or financial difficulties, compared to their excluded counterparts. However, no significant association is found between happiness and some social exclusion domains, such as child and youth benefits, and unemployment benefits. Conclusions The disengagement of the indigenous peoples in mainstream society, with respect to the accessibility of welfare provisions, is a crucial element in regard to social exclusion and happiness. Several policy implications for the social sustainability of indigenous peoples can be inferred from these findings. For example, providing a mobile clinical tour, on-site health counseling, or homecare service can contribute to the removal of institutional and geographic barriers to medical welfare provisions for the mountain indigenes. Moreover, the government may devote more welfare resources to assist indigenous families and tribal communities to develop their own social safety net, instead of the individual-oriented welfare provisions.
Show Your Pride

Three experiments provide converging evidence that pride has a distinct, recognizable expression. Experiment 1 showed that judges can agree in identifying a posed expression as showing pride and can reliably distinguish pride expressions from expressions of related emotions such as happiness. Experiment 2 showed that judges can identify the pride expression when the task uses an open-ended response format that does not cue them with the label “pride. ” Experiment 3 showed that the pride expression includes a small smile, with head tilted slightly back, visibly expanded posture, and arms raised above the head or hands on hips. Overall, these findings challenge the assumption that all positive emotions share the same expression, and suggest that pride may be added to the pantheon of basic emotions generally viewed as evolved responses.
Cortical encoding of speech acoustics: Effects of noise and amplification

Abstract Objective: To investigate speech stimuli and background-noise-dependent changes in cortical auditory-evoked potentials (CAEPs) in unaided and aided conditions, and determine amplification effects on CAEPs. Design: CAEPs to naturally produced syllables in quiet and in multi-talker babble were recorded, with and without a hearing aid in the right ear. At least 300 artifact-free trials for each participant were required to measure latencies and amplitudes of CAEPs. Acoustic characteristics of the hearing-aid-transduced stimuli were measured using in-the-canal probe microphone measurements to determine unaided versus aided SNR and to compare stimulus acoustic characteristics to CAEP findings. Study sample: Ten participants with normal hearing, aged 19 to 35 years. Results: CAEP latencies and amplitudes showed significant effects of speech contrast, background noise, and amplification. N1 and P2 components varied differently across conditions. In general, cortical processing in noise was influenced by SNR and the spectrum of the speech stimuli. Hearing-aid-induced spectral and temporal changes to the speech stimuli affected P1-N1-P2 components. Amplification produced complex effects on latencies and amplitudes across speech stimuli and CAEP components, and for quiet versus noise conditions. Conclusion: CAEP components reflect spectral and temporal characteristics of speech stimuli and acoustic changes induced by background noise and amplification.
Proposing Plausible Answers for Open-ended Visual Question Answering

Answering open-ended questions is an essential capability for any intelligent agent. One of the most interesting recent open-ended question answering challenges is Visual Question Answering (VQA) which attempts to evaluate a system's visual understanding through its answers to natural language questions about images. There exist many approaches to VQA, the majority of which do not exhibit deeper semantic understanding of the candidate answers they produce. We study the importance of generating plausible answers to a given question by introducing the novel task of `Answer Proposal': for a given open-ended question, a system should generate a ranked list of candidate answers informed by the semantics of the question. We experiment with various models including a neural generative model as well as a semantic graph matching one. We provide both intrinsic and extrinsic evaluations for the task of Answer Proposal, showing that our best model learns to propose plausible answers with a high recall and performs competitively with some other solutions to VQA.
Optimization and GIS-Based Intelligent Decision Support System for Urban Transportation Systems Analysis

Optimization plays an important role in most real world applications that support decision makers to take the right decision regarding the strategic directions and operations of the system they manage. Solutions for traffic management and traffic congestion problems are considered major problems that most decision making authorities for cities around the world are looking for. This review paper gives a full description of the traffic problem as part of the transportation planning process and present a view as a framework of urban transportation system analysis where the core of the system is a transportation network equilibrium model that is based on optimization techniques and that can also be used for evaluating an alternative solution or a combination of alternative solutions for the traffic congestion. Different transportation network equilibrium models are reviewed from the sequential approach to the multiclass combining trip generation, trip distribution, modal split, trip assignment and departure time model. A GIS-Based intelligent decision support system framework for urban transportation system analysis is suggested for implementation where the selection of optimized alternative solutions, single or packages, will be based on an intelligent agent rather than human being which would lead to reduction in time, cost and the elimination of the difficulty, by human being, for finding the best solution to the traffic congestion problem. Keywords—Multiclass simultaneous transportation equilibrium models, transportation planning, urban transportation systems analysis, intelligent decision support system.
Non-business use of the WWW in three Western Australian organisations

This paper is an outline of findings from a research project investigating the non‐business use of the World Wide Web in organisations. The study uncovered high non‐business usage in the selected organisations. Pornography and other traditionally identified risks were found to be largely non‐issues. MP3 and other streaming media and potential copyright infringement were found to be problematic. All organisations had end‐users displaying behaviours indicating significant, deliberate misuse that often used a variety of covert techniques to hide their actions.
Characterization of microsatellite loci isolated from the wasp, Microstigmus nigrophthalmus (Hymenoptera)

Fifty‐two microsatellite loci were characterized in 22–31 unrelated females of the wasp (Microstigmus nigrophthalmus) collected from the Mata do Paraiso, Viçosa, M.G. , Brazil. Fifty‐one of these loci were developed from a microsatellite‐enriched genomic library derived from M. nigrophthalmus and one was derived from the wasp, Ormyrus nitidulus. The genus Microstigmus represents an independent origin of social behaviour in the Hymenoptera and is thus of great potential in the study of social evolution.
Communities of everyday practice and situated elderliness as an approach to co-design for senior interaction

In the co-design project Senior Interaction a public care unit, university researchers, industrial partners, and senior citizens are working together to design living labs applying digital concepts that can strengthen social networks and interaction among seniors. When approaching people who we envisioned to be the future users we realized that almost nobody among the people between 55 and 75 years old identified themselves as 'elderly' or 'senior citizens', we realized that users are never just 'out there'. Instead they tend to refer to 'the others' or even to their own parents. Rather than using biological age, institutional categories or similar formal ways to group the people that we imagine as the future users, we suggest to talk about situated elderliness. By associating elderliness not to all encompassing life circumstances but to certain everyday contexts we can turn our attention towards what we call communities of everyday practice that defines these contexts.
Exploring molecular signaling in plant-fungal symbioses using high throughput RNA sequencing

Plant-fungal symbioses are a common feature in nature. They vary from pathogenic interactions, where fungi subvert plant resources for their own use, to mutualistic associations, where both fungus and host benefit from the interaction. Although the ecological importance of plant-fungal symbioses has long been recognized and the biology of several key associations are now well studied, new technologies have the potential to allow fresh insight into the molecular basis of plant-fungal interactions. One such technique – high throughput RNA sequencing – has recently been used to explore the molecular basis of cross-species communications. Here, we give a brief overview of this emerging technology, and present a general guide for employing the methodology to dissect plant-fungal symbiosis.
Supply Chain Coordination with Contracts Game between Complementary Suppliers

This paper studies a supply chain consisting of two suppliers and an assembler who also acts as a retailer in a single period model. The suppliers provide complementary modules to the assembler and the latter assembles the final products and sells them to meet a stochastic demand. Each supplier can improve his performance by offering a return policy to the assembler while the best contract depends on that offered by the other supplier. We show that the non-cooperative contracts game between the firms has a unique and stable equilibrium in which the optimal return policies happen to fully coordinate the whole channel. Moreover, the suppliers still have the rights to negotiate with the assembler independently to share their profits properly. With such properties, the suppliers are encouraged to offer return policies to the assembler by following a simple rule derived from the favorable equilibrium, which will lead to a win-win-win situation.
Multiclass classification as a decoding problem

In this article, we present a new method of multiclass classification by combining multiple binary classifiers in the context of information transmission theory. In the framework of the error correcting output coding (ECOC), a misclassification of each binary classifier is formulated as a bit inversion with a probabilistic model. While the conventional Hamming decoding assumes the binary symmetric channel in an information transmission, the symmetric assumption is especially problematic in multiclass classification problems: for example, 1 vs R approach typically makes an asymmetric situation even if all classes contain the same number of examples. The asymmetry property corresponds to two kinds of error rate of the binary classification problem; the false positive error and the false negative error. We propose a probabilistic model which assumes an asymmetric channel having 3 inputs and 2 outputs. By the maximum likelihood estimation with the proposed probabilistic model, we can identify properties of the noisy channel according to performances of applied binary classifiers. A multiclass label and a class membership probability for an input are easily estimated by the model. Experimental studies using a synthetic dataset and datasets from UCI repository are performed and results show that the proposed method is superior to the Hamming decoding and comparative to other multiclass classification methods such as multiclass support vector machine
Challenges in Network Application Identification

The evolution of the Internet in the last few years has been characterized by dramatic changes to the way users behave, interact and utilize the network. This has posed new challenges to network operators. To deal with the increasing number of threats to enterprise networks, operators need greater visibility and understanding of the applications running in their networks. In years gone by, the biggest challenge in network application identification used to be of providing real-time classification at increasing wire speeds. But now the operators are facing another challenge - the ability to keep pace with the tremendous rate of development of new applications. This problem can be attributed largely to the explosive growth in the number of web and mobile applications. This combined with application hiding techniques like encryption, port abuse, and tunneling have rendered the traditional approaches for application identification ineffective. In this paper, we discuss the challenges facing the network operators and the limitations of current state of the art approaches in both the commercial and the research world in solving these problems.
Weight optimization of an axial-flux PM machine for airborne wind turbines

This paper considers the weight optimization of an axial-flux machine (AFM) for airborne wind turbines (AWT). It employs combined electrical, thermal and structural (mechanical) analytical models, which allow a fast evaluation of machine performance. Therefore, instead of introducing cost functions, the complete machine design space can be considered. The machines are shown in a performance space from which a Pareto limit can be clearly identified, and an optimal machine chosen for any given application. Optimization results yield a maximum power-to-weight ratio of 6.4 kW/kg including structural (non-electrical) parts, at an efficiency of 95 % and rated speed of 3200 rpm, which is unparalleled by commercial machines, or those reported in literature. Analytical models are verified by FEM simulations, and a prototype of the optimal AFM is built in order to experimentally confirm the results.
European Conference on Information Systems ( ECIS ) 2010 Proposal of an Artifact that Supports the IT-Governance Control Process

Tasks regarding IS-strategy implementation can be allotted to the scope of IT-Governance. However, literature scans reveal a lack of guidance on how these tasks are to be accomplished. Unfortunately, most strategies fail during this step as they receive no proper implementation due to a lack of control, i.e. the ability to direct the IS-strategy implementation by knowing actions to be taken, how to proceed and to envisage outcomes of implementation processes. Therefore, the contribution of this research in progress is an artifact that supports the IT-Governance control process. The proposed artifact is based on knowledge sharing and implemented by an ontology. It is validated by an industry case. Additionally, participants were interviewed to assess their perceived usefulness of the artifact. The results indicate a broad appreciation of the approach.
Can matrix-layout-independent numerical solvers be efficient?: implementing the Moebius state-level abstract functional interface for ZDDs

Symbolic approaches based on decision diagrams have shown to be well suited for representing very large continuous-time Markov chains (CTMC), as derived from high-level model descriptions. Unfortunately, each type of decision diagram requires its own implementation of the numerical solvers for computing the state probabilities of the CTMC. For this reason, some time ago the idea of separating numerical solution methods from the representation of the CTMC was proposed [12], suggesting the implementation of a so-called state-level abstract functional interface (AFI), which defines classes of iterators for accessing the entries of the CTMC transition rate matrix. In this paper we (a) present an implementation of the AFI for zero-suppressed multi-terminal binary decision diagrams (ZDDs) [18] and (b) empirically investigate the viability of matrix-layout-independent implementations of numerical solvers.
Structured nonstationarity in articulatory timing

Many experiments investigating speech articulation examine the influence of linguistic or paralinguistic factors on articulatory timing. The current experiment differs from these by focusing on unconditioned variation—i.e. statistical noise—in articulatory timing. The aim is to assess whether distributions of intervals representing the relative timing of articulatory movements are well-modelled with a constant parameter distribution, such as a Gaussian with fixed mean and variance. Several hundred productions of the same target word were elicited from participants in a task where feedback encouraged identical productions on all trials. The results show that the distributions of articulatory timing intervals are not consistent with a constantparameter model. Instead, distribution parameters show unconditioned drift over time, exhibit sporadic discontinuous transitions between modes, and have a complex, dynamic correlational structure. These results call into question typical assumptions of articulatory models.
Scalable Mesh Deformation with Controllable Stiffness

This paper presents an efficient and physics-plausible deformation algorithm. A simplification is first conducted on the original mesh, then the deformation of the simplified mesh is passed to the original mesh to obtain an initial result. Then a set of optimal rigid transformations are computed to preserve the shape features and control the surface stiffness. The experiments show that our algorithm is effective.
Isotonic Separation with an Instance Selection Algorithm Using Softset: Theory and Experiments

A bstract: In supervised machine learning, a training set conta ining labeled instances is taken by a learning algorithm to construct a model that is subsequently used for determining the class label of new instances. Isotonic separation is a supervised machine learning technique in which classification is represented as a Linear Programming Problem (LPP) with an objective of minimizing the number of misclassifications. It is computationally expensive to solve the LPP using traditional methods for a large dataset. Characteristics of the training set such as size, presence of noisy data, influence the learning algorithm and classification performance. To resolve this issue, this paper introduces a new linearithmic time algorithm called Soft set based instance selection algorithm (SOFIA) which provides a condensed dataset for a learning algorithm. And, a hybrid classification algorithm, SOFIAIS which utilizes SOFIA for instance selection and isotonic separation (IS) for classification is introduced. Two sets of experimental studies are conducted on Wisconsin Breast Cancer dataset and the results are reported. First, experiments are performed on SOFIA-IS and the results are compared with isotonic separation and its variants. Then experiments are done on state of the art machine learning techniques by including SOFIA for instance selection and the results are compared with same techniques without SOFIA. Experimental and statistical results show that the condensed sets obtained by SOFIA are optimum, and SOFIA-IS and SOFIA based machine learning techniques are better in terms of classification accuracy, time and space complexity.
Applying Model-based Distributed Continuous Quality Assurance Processes to Enhance Persistent Software Attributes

Time and resource constraints often force developers of highly configurable quality of service (QoS)-intensive software systems to guarantee their system’s persistent software attributes (PSAs) (e.g., functional correctness, portability, efficiency, and QoS) on very few platform configurations and to extrapolate from these configurations to the entire configuration space, which allows many sources of degradation to escape detection until systems are fielded. This article illustrates how distributed continuous quality assurance (DCQA) processes help improve the assessment of these PSAs across large QoSintensive software system configuration spaces. We also illustrate how model-based DCQA processes enable developers to run formally-designed screening experiments that isolate the most significant configuration options, such as different workload parameters, operating system, compiler flags, feature sets, and/or run-time optimization controls. Our empirical results show that DCQA processes can be used monitor, safeguard, and enforce PSAs at an acceptable level of cost and
Isotropic Mesh Simplification by Evolving the Geodesic Delaunay Triangulation

In this paper, we present an intrinsic algorithm for isotropic mesh simplification. Starting with a set of unevenly distributed samples on the surface, our method computes the geodesic Delaunay triangulation with regard to the sample set and iteratively evolves the Delaunay triangulation such that the Delaunay edges become almost equal in length. Finally, our method outputs the simplified mesh by replacing each curved Delaunay edge with a line segment. We conduct experiments on numerous real-world models of complicated geometry and topology. The promising experimental results demonstrate that the proposed method is intrinsic and insensitive to initial mesh triangulation.
Altered Response Hierarchy and Increased T-Cell Breadth upon HIV-1 Conserved Element DNA Vaccination in Macaques

HIV sequence diversity and potential decoy epitopes are hurdles in the development of an effective AIDS vaccine. A DNA vaccine candidate comprising of highly conserved p24gag elements (CE) induced robust immunity in all 10 vaccinated macaques, whereas full-length gag DNA vaccination elicited responses to these conserved elements in only 5 of 11 animals, targeting fewer CE per animal. Importantly, boosting CE-primed macaques with DNA expressing full-length p55gag increased both magnitude of CE responses and breadth of Gag immunity, demonstrating alteration of the hierarchy of epitope recognition in the presence of pre-existing CE-specific responses. Inclusion of a conserved element immunogen provides a novel and effective strategy to broaden responses against highly diverse pathogens by avoiding decoy epitopes, while focusing responses to critical viral elements for which few escape pathways exist.