Miracle-dz/UniFAR-FTUs huggingface dataset:
Generalization in Category Learning: The Roles of Representational and Decisional Uncertainty

Effective generalization in a multiple-category situation involves both assessing potential membership in individual categories and resolving conflict between categories while implementing a decision bound. We separated generalization from decision bound implementation using an information integration task in which category exemplars varied over two incommensurable feature dimensions. Human subjects first learned to categorize stimuli within limited training regions, and then, during fMRI scanning, they also categorized transfer stimuli from new regions of perceptual space. Transfer stimuli differed both in distance from the training region prototype and distance from the decision bound, allowing us to independently assess neural systems sensitive to each. Across all stimulus regions, categorization was associated with activity in the extrastriate visual cortex, basal ganglia, and the bilateral intraparietal sulcus. Categorizing stimuli near the decision bound was associated with recruitment of the frontoinsular cortex and medial frontal cortex, regions often associated with conflict and which commonly coactivate within the salience network. Generalization was measured in terms of greater distance from the decision bound and greater distance from the category prototype (average training region stimulus). Distance from the decision bound was associated with activity in the superior parietal lobe, lingual gyri, and anterior hippocampus, whereas distance from the prototype was associated with left intraparietal sulcus activity. The results are interpreted as supporting the existence of different uncertainty resolution mechanisms for uncertainty about category membership (representational uncertainty) and uncertainty about decision bound (decisional uncertainty).
Improved High Dynamic Range Image Reproduction Method

High dynamic range (HDR) of illumination may cause serious distortions and other problems in viewing and further processing of digital images. This paper describes a new algorithm for HDR image creation based on merging images taken with different exposure time. There are many fields, in which HDR images can be used advantageously, with the help of them the accuracy, reliability and many other features of the certain image processing methods can be improved.
Network management viewpoints: a new way of encompassing the network management complexity

This paper defines viewpoints in order to deal with the network management complexity. A network management viewpoint leads to the representation of a network management system with emphasis on a specific concern. Five viewpoints are identified, namely information, functional, communication, architectural and organizational. The network management standards provisions and lacks for every viewpoint are enhanced and some elements of solutions are presented. Then, these viewpoints are integrated and applied to every management layer of an FDDI subnetwork considered as a componet of a high speed multi-network.
The neural dynamics of goal-directed arm movements: A developmental perspective

We present a neuro-dynamic architecture for the generation of movement of the hand toward a visual target that integrates movement planning based on visual input, movement initiation and termination, the generation of the time courses of virtual trajectories of the hand in Cartesian space, and their transformation into virtual joint trajectories and muscle forces. The architecture captures properties of adult goal-directed arm movements such as bell-shaped velocity profiles and on-line updating of a movement when the target is shifted. The integrated and autonomous nature of the architecture makes it possible to study how motor performance is affected when one of the three core processes, planning, timing, and transformation from end-effector to joint space, are decalibrated to reflect earlier stages of development. We find signatures of the development of reaching such as multiple movement units and curved movement paths in the “young” model.
Elevated high mobility group-I(Y) gene expression is associated with progressive transformation of mouse mammary epithelial cells.

The high mobility group (HMG) proteins I and Y are well characterized nonhistone chromosomal proteins which bind to A.T-rich regions of DNA, and may regulate gene expression and/or DNA replication. We utilized a series of mouse mammary epithelial preneoplastic and tumor cell lines to explore the relationship between neoplastic transformation and HMG-I(Y) gene expression. The cell lines used in this study were originally derived from a single hyperplastic outgrowth, and exhibit a distinct gradient of preneoplastic to highly metastatic transformation states. We measured the levels of HMG-I(Y) gene expression in these cell lines during the different phases of cell growth in culture. At both subconfluent and confluent cell densities, elevated levels of HMG-I(Y) mRNA were directly correlated with the relative degree of neoplastic transformation and metastatic progression of these cells. HMG-I(Y) mRNA levels were always highest in proliferating cells. However, the differences in HMG-I(Y) gene expression between the cell lines were greatest at confluent cell density, when the cells were not actively proliferating. HMG-I(Y) mRNA was detectable in normal primary mouse mammary epithelium proliferating in culture. However, the amount was much less than that measured in the cell lines, indicating that elevated HMG-I(Y) gene expression was also directly correlated with the conversion of normal mammary epithelium to the preneoplastic immortalized state. Southern blot analysis showed that alterations in HMG-I(Y) loci are also associated with the preneoplastic to neoplastic conversion of these cell lines, and this change may involve a gene conversion event between two different HMG-I(Y) loci. These results indicate that there is a strong correlation between elevated HMG-I(Y) gene expression and the progressive transformation of mouse mammary epithelial cells.
Towards Emulation of Large Scale Complex Network Workloads on Graph Databases with XGDBench

Graph database systems are getting a lot of attention in recent times from the big data management community due to their efficiency in graph data storage andpowerful graph query specification abilities. In this paper we present a methodology for modeling workload spikes in a graph database system using a scalable benchmarking framework called XGDBench. We describe how two main types of workload spikes called data spikes and volume spikes can be implemented in the context of graph databases by considering realworld workload traces and empirical evidence.We implemented these features on XGDBench which we developed using X10. We validated these features by running workloads on Titan which is a popular open source distributed graph database server.We observed the ability of XGDBench in generating realistic workload spikes on Titan. The distributed architecture of XGDBench promotes implementation of such techniques efficiently through utilization of computing power offered by distributed memory compute clusters.
HMM-based visual speech recognition using intensity and location normalization

This paper describes intensity and location normalization techniques for improving the performance of visual speech recognizers used in audio-visual speech recognition. For auditory speech recognition, there exist many methods for dealing with channel characteristics and speaker individualities, e.g., CMN (cepstral mean normalization), SAT (speaker adaptive training). We present two techniques similar to CMN and SAT, respectively, for intensity and location normalization in visual speech recognition. Word recognition experiments based on HMM show that a significant improvement in recogniton performance is achieved by combining the two techniques.
A Meta-theoretic Approach to Theory Integration in Information Systems

This research presents a meta-theoretic analysis of a nomological net for the purpose of identifying potential pathways for theory integration and multi-level theory development. Success in these two areas holds the potential to reduce theory clutter in IS and related social sciences. As a proof-of-concept, we identify theory domains that share ancillary variables or functional/structural components, using a 20-year sample of construct-based quantitative research published in core journals of the IS discipline. Identification of shared variables provides possible extension and integration development that will reduce theory fragmentation and may lead to discovery of fundamental unifying processes that underlie phenomena across disciplines.
Developing self-verifying service-based systems

We present a tool-supported framework for the engineering of service-based systems (SBSs) capable of self-verifying their compliance with developer-specified reliability requirements. These self-verifying systems select their services dynamically by using a combination of continual quantitative verification and online updating of the verified models. Our framework enables the practical exploitation of recent theoretical advances in the development of self-adaptive SBSs through (a) automating the generation of the software components responsible for model updating, continual verification and service selection; and (b) employing standard SBS development processes.
SHR: Self-Healing Routing for wireless ad hoc sensor networks

This paper presents a novel protocol, Self-Healing Routing (SHR), for opportunistic multi-hop wireless communication. The protocol uses broadcast communication and a prioritized slotted transmission backoff delay scheme to empower a receiving node to use its hop distance from the destination to autonomously decide whether to forward a packet. This enables dynamic traversal of the shortest available routes without requiring nodes to explicitly decide to which neighbors to forward packets. When severed routes are encountered, the protocol dynamically and locally re-routes packets so they traverse the surviving shortest route. The result, as shown by simulation data reported here, is an efficient fault-tolerant protocol that performs well even when the network topology changes spontaneously.
Measuring Presence in Augmented Reality Environments: Design and a First Test of a Questionnaire

Introduction Augmented Reality (AR) enriches a user’s real environment by adding spatially aligned virtual objects (3D models, 2D textures, textual annotations, etc) by means of special display technologies. These are either worn on the body or placed in the working environment. From a technical point of view, AR faces three major challenges: (1) to generate a high quality rendering, (2) to precisely register (in position and orientation) the virtual objects (VOs) with the real environment, and (3) to do so in interactive real-time (Regenbrecht, Wagner, & Baratoff, in press). The goal is to create the impression that the VOs are part of the real environment. Therefore, and similar to definitions of virtual reality (Steuer, 1992), it makes sense to define AR from a psychological point of view: Augmented Reality conveys the impression that VOs are present in the real environment. In order evaluate how well this goal is reached, a psychological measurement of this type of presence is necessary. In the following, we will describe technological features of AR systems that make a special questionnaire version necessary, describe our approach to the questionnaire development, and the data collection strategy. Data are currently collected, and results will be presented at the workshop.
Facilitating rich data manipulation in BPEL using E4X

The Business Process Execution Language (BPEL) uses XML to specify the data used within a process and realizes data flow via (globally) shared variables. Additionally, assign activities can be used to copy (parts of) variables to other variables using techniques like XPath or XSLT. Although BPEL’s built-in functionality is sufficient for simple data manipulation tasks, it becomes very cumbersome when dealing with more sophisticated data models, such as arrays. ECMAScript for XML (E4X) extends JavaScript with support for XML-based data manipulation by introducing new XPath-like language features. In this paper we show how E4X can help to significantly ease data manipulation tasks and propose a BPEL extension that allows employing JavaScript/E4X for implementing them. As E4X allows defining custom functions in terms of scripts, reusability with respect to data manipulation is improved. To verify the conceptual framework we present a proof-of-concept implementation based on Apache ODE.
Implant overdenture impressions using a dynamic impression concept

A dynamic impression is a functional impression that records the functional movement of the patient's own muscle and muscle attachment. This process reduces the number of random factors. This article describes a method for making a special tray using a dynamic impression concept that was made from provisional dentures used for implant healing. The individual tray is used to make a wash-impression to record the features of the mucosa in detail. The main advantage of this technique is that it provides a functional relationship of the implant components to the supporting tissues without overextension because provisional denture had been used for 2 months and the border length of individual tray was nearly the same as that of provisional denture. The delivery of the prosthesis constructed using this impression technique is time-saving because there is no need for border molding and there are fewer post-insertion appliance adjustments.
Fine-grained multi-resource scheduling in cloud datacenters

Cloud datacenters typically require tenants to specify the resource demands for the virtual machines (VMs) they create using a set of pre-defined, fixed configurations, to ease the resource allocation problem. Unfortunately, this leads to low resource utilization of cloud datacenters as tenants are obligated to conservatively predict the maximum resource demand of their applications. We argue that instead of such a static VM resource allocation, a finer-grained dynamic resource allocation and scheduling can substantially improve the utilization of the datacenter resources by increasing the number of jobs accommodated and correspondingly, the cloud datacenter provider's revenue. The dynamic real-time scheduling of jobs can also ensure that the performance goals for the tenant VMs are achieved. Examining a typical publicly available cluster data center trace, we observe that a large number of jobs are short. Only a small proportion of jobs are long and which require substantial compute or memory resources. We propose an optimization based approach that exploits this division between the short and long jobs to dynamically allocate a cloud datacenter's resources to achieve significantly better utilization by increasing the number of jobs accommodated by the datacenter. We use a constraint programming solution to schedule the long jobs, and use simple heuristics to quickly, yet quite accurately schedule the short jobs. Using trace-driven simulations based on public traces collected on provider cluster we show that the overall revenue for the cloud provider can be improved by 30% over the traditional static VM resource allocation based on the coarse granularity specifications. We are able to increase the number of jobs accommodated using dynamic scheduling by 18%. We also compare the performance of our approach to multi-resource (CPU and memory) first-fit and best-fit algorithms and to the optimal offline solution, and demonstrate that our solution achieves within 76% of the offline optimal solution.
Hierarchical Matching for Chinese Calligraphic Retrieval Based on Skeleton Similarity

Individual Chinese characters are identified mainly by their skeleton structure instead of texture or color.In this paper, an approach based on skeleton similarity for Chinese calligraphic characters retrieval is proposed.By this approach,first,the skeleton of the binarized individual characters are acquired by an improved multi-level module analysis algorithm.Second,the first round of skeleton matching based on the invariant moment-descriptor guarantees the recall rate;the second round of skeleton matching based on the comprehensive characteristic difference in the polar coordinates system guarantees the retrieval precision.Finally,different styles of the same Chinese characters are ranked and displayed according to the two rounds of matching score. Besides,the efficiency of our approach is manifested by the preliminary experiment.
Using fiducials in 3D map evaluation

For missions in Safety, Security, and Rescue Robotics (SSRR) maps are often a core deliverable. Hence it is of high interest to assess the quality of maps in a simple and efficient way. Since SSRR is mostly taking place in unstructured environments, 3D mapping has become more and more important. Here a method to evaluate the quality of 3D maps is presented that extends the previously developed 2D Fiducial approach to the third dimension. The artificial features are identified and located in 2D cross-sections of the map as well as in the 3D maps. It is then attempted to proof this concept using a ground truth map and robot generated maps from the RoboCup Rescue competition 2013 in Eindhoven.
BALLGAME: A Corpus for Computational Semantics

In this paper, we describe the Baseball Announcers' Language Linked with General Annotation of Meaningful Events (BALLGAME) project -- a text corpus for research in computional semantics. We collected pitch-by-pitch event data for a sample of baseball games and used this data to build an annotated corpus composed of transcripts of radio broadcasts of these games. Our annotation links text from the broadcast to events in a formal representation of the semantics of the baseball game. We describe our corpus model, the annotation tool used to create the corpus, and conclude by discussing applications of this corpus in semantics research and natural language processing.
Transportation distances and human perception of melodic similarity

This article describes how transportation distances such as the Earth Mover's Distance can be used for measuring melodic similarity for notated music. We represent music notation as weighted point sets in a two-dimensional space of onset time and pitch. The Earth Mover's Distance can then be used for comparing point sets by determining how much work it would take to convert one of the point sets into the other by moving weight between the point sets. For evaluating how well this method and other methods agree with human perception of melodic similarity, we established a ground truth for the RISM A/II collection based on the opinions of human experts. The RISM A/II collection contains about half a million musical incipits. For 22 queries, we filtered the collection so that about 50 candidates per query were left, each of which we then presented to about 30 human experts (out of a group of 37 experts) for a final ranking. We present our filtering methods, the experiment design, the resulting ground truth, and a new measure (called “Average Dynamic Recall”) that can be used for comparing different similarity measures with the ground truth.
An image encryption algorithm based on compressed sensing and dual-tree complex wavelet transform

Combined image encryption with the process of compressed sensing (CS) which based on dual-tree complex wavelet transform, we came up with the image encryption algorithm which based on the theory of CS and double random phase encoding (DRPE). Firstly, adopting DT-CWT represent the image sparsely. It can enhance the image edge and texture, it also can attain directional feature information. Secondly, utilizing chaotic system to product chaos sequence as the measurement matrix on the process of CS. At the same time, the values of initial chaotic parameters are the keys. Finally, we selected DRPE on measurements to finish the process of secondary encryption. The values of seeds which are used to generate two random phase masks are the keys of secondary encryption. In the process of decryption, providing the correct values of keys can generate the chaotic measurement matrix and random phase masks to be used for decryption. Orthogonal matching pursuit (OMP) algorithm is employed to reconstruct the original image approximately. Compared with several existing algorithms, this encryption scheme can reconstruct a higher quality image. It has higher robustness and higher sensitivity to the initial keys.
Panel: A call for action in tackling environmental sustainability through green information technologies and systems

In parallel to widely accepted behavioural research, Design Research (DR) has emerged in Information Systems. Nonetheless, the debate about the scientificity of DR is still ongoing. In the course of this debate, the role of scientific progress has hardly been discussed. But, doubtlessly, scientific progress is regarded as one of the main aims of science; science can even be defined by scientific progress. Philosophy of science has therefore developed a variety of concepts for scientific progress mostly adapted to explanatory and/or predictive theories. Nonetheless, the output of DR differs from those theories; therefore, concepts developed cannot be applied to DR without further ado. In this paper, we propose a first concept for scientific progress of DR artefacts. Because of the complexity of the field we firstly restrict to the research question: What is scientific progress of DR artefacts? Progress is commonly defined as a transition from step A to B whereby B is “better” than A. The aim of our research is to identify criteria for concretizing what is “better” in the context of DR and to define criteria of progressive DR artefacts. We thereby identified the following five criteria: utility, internal consistency, external consistency, scope, and efficiency.
Affective State Estimation for Human–Robot Interaction

In order for humans and robots to interact in an effective and intuitive manner, robots must obtain information about the human affective state in response to the robot's actions. This secondary mode of interactive communication is hypothesized to permit a more natural collaboration, similar to the "body language" interaction between two cooperating humans. This paper describes the implementation and validation of a hidden Markov model (HMM) for estimating human affective state in real time, using robot motions as the stimulus. Inputs to the system are physiological signals such as heart rate, perspiration rate, and facial muscle contraction. Affective state was estimated using a two- dimensional valence-arousal representation. A robot manipulator was used to generate motions expected during human-robot interaction, and human subjects were asked to report their response to these motions. The human physiological response was also measured. Robot motions were generated using both a nominal potential field planner and a recently reported safe motion planner that minimizes the potential collision forces along the path. The robot motions were tested with 36 subjects. This data was used to train and validate the HMM model. The results of the HMM affective estimation are also compared to a previously implemented fuzzy inference engine.
An integrated symbolic and neural network architecture for machine learning in the domain of nuclear engineering

On top of FUELCON and NEL, two extant, successful projects in, respectively, expert systems for engineering, and neural networks, we have defined and designed a new phase, meant to greatly increase the significance, for AI, of the combined project with respect to the already recognized merits of the two seed-projects. The NEL symbolic-to-neural conversion schema and language is resorted to in NEURALIZER, a component meant to automatically revise a ruleset, iteration after iteration, within the operation cycle of FUELCON, a generator of families of configurations of fuel assemblies for reloading the core of nuclear reactors.