Miracle-dz/UniFAR-FTUs huggingface dataset:
Head to Head: Remote Usability Testing Takes on Live Usability Testing in the HFES Ultimate Fighting Challenge

Remote usability testing is emerging as a popular approach through which evaluators can test technology interfaces on a large number of participants quickly and inexpensively. Two types of remote studies have been employed, either with a moderator interacting remotely with the participant or in an unmoderated format. But without a moderator, or even when the moderator is present but not collocated with the participant, there is some question as to whether the results can match the validity, reliability, and acceptability of a live testing paradigm. This session is a novel format that pits the two in a head-to-head challenge during the conference session. The audience is asked to be a part of the session as test participants and/or results evaluators. The session is divided into three modules. In the first module, a remote unmoderated study was conducted on the HFES.org web using the current state of the art for remote, unmoderated testing. The other two modules are conducted live during the conference session. In the second module, a moderated remote study is conducted with the moderator located in other room but with the participants in the conference session room. In the third module, a live study is conducted with a moderator collocated with the participants in the conference session room. These two modules also use state-of-the-art techniques for these methods. The final time block of the session is used to interactively discuss the differences in the results with the audience. They are able to decide for themselves the advantages and disadvantages of each method.
Antenna system for a forward looking SAR using digital beamforming on-receive-only

This paper presents the development of an antenna system for a forward looking synthetic aperture radar (SAR) which uses digital beamforming (DBF) on-receive-only. One transmitting horn antenna is used in conjunction with 56 receiving patch subarrays all covering the same swath. The receiving antennas are sequentially switched which enables the antenna system to be operated by a conventional SAR receiver. The antenna system was built under contract from the DLR, Oberpfaffenhofen, Germany.
Km4City as Smart City Semantic Model and Tools

our cities are not so smart as they could be Many times on traveling we realize the needs of getting more specific information that what we can get from Goole, OpenStreet Map, Here, TomTom, etc. In most cases, the information is too complex and expensive for them to be profitable. This is true since the information is in the hands of public administrations, mobility operators, private services, parking companies, etc. Km4city provides a unique point of access for interoperable data of a city metropolitan area via web and mobile applications. Km4City covers aspects of mobility and transport, energy, banks, parking, commercial, culture, bike paths, garden areas, health, tourism, end much more. Florence area in Italy has, since July 2015, a demonstrator of this solution.
Development of a self-rechargeable digital water flow meter

The objective of this paper is to present the feasibility of a self-rechargeable digital water flow meter (SRDFM) system for water pipes using the latest data processing and wireless communication technologies while causing negligible water pressure drop (head loss). The system uses a Pelton turbine generator to power the electronic circuit, which processes and transmits the signals generated by several flow meters. ZigBee technology was used to process and send wireless signals. Signals from two water meters were acquired, processed, and transmitted with only one control/transmission unit during this study. The new system was assessed experimentally, reaching a maximum of 80 m of wireless transmittance distance at a minimum flow rate of 5 L/min for a 16-mm diameter pipe (self-charged).
Rethinking Functional Reference

The theoretical construct of functional reference is the main tool used by animal communication researchers to explore how animals refer to the world in the absence of a language. Functionally referential signals are commonly defined as signals elicited by a specific class of stimuli and capable of causing behaviors adaptive to such stimuli in the absence of contextual cues. I will argue that this definition is conceptually flawed and propose an alternative definition according to which signals can functionally refer to things that rarely cause them while relying on the essential contribution of contextual cues.
On simulating Turing machines with inhibitor Petri nets

An inhibitor Petri net is constructed that simulates an arbitrary given Turing machine. The tape of the Turing machine, its program, and internal states are encoded by the marking of nine dedicated places of the Petri net. The rules of Turing machine work are encoded by a single control flow represented by a token passage within the inhibitor Petri net composed of the sequence, branch, and loop operators. Subnets that implement arithmetic, comparison, and copying operations are employed. In the Petri net paradigm of computation, a Petri net that simulates Turing machines provides the compatibility of concepts. It is a prototype of a co‐processor supplementary to the basic processor of Petri nets. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
The Simultaneous Transmit And Receive (STAR) Message Protocol

The STAR protocol is introduced, which solves three problems with MPI, a well known secur- ity problem, and three exascale communication problems. Optical implementations are developed compatible with 100 Gbit/sec Ethernet. Automatic fault resilience mechanisms are discussed, which improve HPC quality of service, and meet the exascale reliability and resilience challenges. The bandwidth problem for exascale computers interfacing with data centers is solved. The STAR protocol is combined with the SiMulPro core architecture (discussed in another article of this issue). The combination enables data centers, handheld computers, networked sensors, and super- computers, to be invulnerable to memory fault injection of viruses and rootkits.
LernplattformGW - Learning about and with Geomedia. A Concept for Tutoring and an OER Platform for the Education of Student Teachers

The University of Salzburg has linked up ('clustered') with several other Austrian Higher Education Institutions (HEI) to develop and deliver the next generation of education for student teachers. Based on a reformed curriculum with a strong emphasis on pedagogical concepts and skills, courses have been developed with uniform structure and content across multiple institutions and locations. This step was considered of particular importance due to changes in students' backgrounds and career stages: an increasing number of future teachers are completing their training based on prior academic and professional experience while working (mostly) part-time. This offers the opportunity for more mature and experienced individuals to enter the teaching profession, but also challenges traditional organizational formats of teacher training. Based on an extensive survey of current students, this paper explores the range of personal and professional backgrounds and attempts to establish a framework for facilitating teacher education with reduced classroom presence as well as enhanced support for independent and flexible learning. From evaluation and assessment of results as well as from assessing organizational experiences during the first year, advantages of cloud-based learning infrastructures are clearly seen. Making the (secondary) teaching profession more accessible for mature individuals and establishing a practice of individualized learning for future teachers, an OER platform provides the basis to emphasize active learning and critical assessment of experiences in tomorrow's classrooms over more traditional 'teaching' formats.
Network Architecture : lessons from the past, vision for the future

The design principles of the Internet have dominated the past decade. Orthogonal to telecommunications industry principles, they dramatically changed the networking landscape because they relied on iconoclastic ideas. First, the Internet end-to-end arguments, which stipulate that the network should intervene minimally on the end-to-end traffic, pushing the complexity to the end-systems. Second, the ban on centralized functions: Internet techniques (routing, DNS) are based on distributed mechanisms. Third, the domination of stateless protocols. However, when facing new requirements such as multimedia traffic, security, Grid applications, these principles appear sometimes as architectural barriers. Multimedia requires Quality of Service (QoS) guarantees, but stateless systems are not good at QoS. Security requires active, intelligent networks, but dumb routers are insufficient. Grid applications require intermediary overlay networks. Attempts to overcome these deficiencies may lead to excessively complicated solutions, distorting the initial principles (e.g. the myriad of QoS options; and after all, do we need them, why not “throw bandwidth at the problem”? ). Middleware solutions are sometimes difficult to deploy (e.g for PKIs). “Lambda on-demand” technologies are conceptually nothing else than old switched circuits, that we never managed to satisfactorily integrate with IP networks. Where is all this going? To help forming a vision of the future, this paper refers to several observations (marked as “Author’s statement”) made by the author over the past 30 years. REQUIREMENTS, ARCHITECTURE AND TEHNICAL DESIGN Networking Architecture is usually understood as a set of abstract principles for the Technical Design of Networking Systems. By Networking System we mean here the implementation of a complete suite of technologies which provide services to end users, such as the Plain Old Telephone Network, or the Internet together with its major applications. However, these abstract principles which form the architecture are themselves dictated by the requirements which are placed on any new network architecture. The logical development process of a new network system should therefore follow the top-down chain: Requirements -> Architecture -> Technical Design. We shall see in the next sections what may be understood by each of these three steps and to what extent the logical process has been respected in the past.
How does a Balancing Motion of a Humanoid Robots Affect a Human Motion and Impression

In this paper, we evaluate how the balancing motion of a humanoid robot affects human swaying and their impresions. A humanoid robot that has a dynamic balancing controller maintains its balance and sways. We believe such body swaying is important for communication robots to appear similar to humans. To verify the validity of the motion, we conducted experiments with our developed humanoid robot which has wheeled inverted pendulum mechanism. In the experiment, we established five object conditions for a subject to face: (1) a human, (2) a robot in an inverted pendulum state, (3) a robot with passive casters, and (4) an LCD monitor with its power turned off. Condition (2) was divided a normal inverted pendulum state and a humanlike swaying inverted pendulum state. We discovered congruences between subject and robot body swaying, the impressions of the robot changes, and the effects of robot body swaying on subjects. If we can clarify why subjects experience congruence with the robot, the fundamental indicator for natural communication between humans and robots will be confirmed. In this research, we reported that robot swaying affects human body swaying and impressions. Moreover, we showed that congruence was effective for communications between humans and a humanoid robot.
Constructing service networks in liner shipping

Seaborne shipping is the most important mode of transport in international trade. After years of continuous growth, world seaborne trade volumes fell in 2009. However, signs of recovery can be observed, so seaborne trade is expected to recover. Current service networks should probably be reconsidered, because, for example, the financial crisis has caused an enormous rise in the oil price. In this thesis a model is proposed that can be used to construct new liner shipping service networks. This service network has to consist of a set of routes. For each route, the ship type and sailing speed used to serve the route have to be determined together with the cargo allocation on the route. First, a linear programming model is formulated that determines the optimal cargo allocation of a given set of routes. The performance of this model is compared to the performance of some heuristics. The optimal model proposed in this thesis performs on average more than 20% better than the heuristics. To determine the best service network, a genetic algorithm based approach is provided in this thesis. However, because the linear programming model that determines the cargo allocation has to be solved repeatedly, this approach will become too time consuming when the size of the problem is not decreased. Therefore, an aggregation method is described in this thesis that divides the ports in a few clusters. In this way, the method can be performed in a reasonable amount of time. However, the results have to be disaggregated after the linear programming problem is solved. Therefore, also a disaggregation method is proposed together with some improvement steps. The data used in this thesis are mainly based on the Asia-Europe tradelane of Maersk during spring 2010. Therefore, this method is used as a reference network in this thesis. Furthermore, an upper bound on the profit that can be obtained is calculated. The profit of the best network found in this thesis is 43% away from the upper bound. However, it is an improvement of about 40% compared to the reference network.
The Open Library at AU (Athabasca University): supporting open access and open educational resources

To address challenges that learners, course creators, librarians and academics involved with OER and MOOCs are facing when looking for scholarly materials, Athabasca University Library has initiated the development of the Open Library at AU. This open library is a full library website that provides easy access to open and free resources. Tools and information literacy tutorials are also included to enable learners, researchers, and others to find, evaluate, and use the information they need for their open learning course or research. Many of the challenges that those involved in open learning face are addressed by the open library and the potential impact it can have on open learning and knowledge sharing is tremendous.
Object Recognition Based on n-gram Representation of Human Action

In the field of object recognition, usage of human actions is applied to it, in order to tackle with the recongition of object that couldn’t be identified by only using their appearance. Most of the conventional research for object recongition from actions, however, need an intermidiate classification of action category. In our research, primitive motions of human are directly apply to object recongition without classifying action categories. First, features of human motion are extracted from video images and encoded to symbols. Then, set of n-grams is obtained from the symbol sequence and registered to corresponding object category. At recognition phases, actions toward an object are also converted into n-grams which are to be compared with that registered in object categories. In this paper, we performed experiments of object recognition using our methods and confirmed the validity of this.
Image Classification And Recognition Based On The Deep Convolutional Neural Network

With the development of the information age, there were a lot of data whose features couldn't be extracted or predicted effectively in real life. One of the core function of computer vision technology is to classify and recognize, with classification and recognition as its summit mission of object detection and object positioning. Due to image data were affected by multiple factors such as illumination, environment, angle, certain object features couldn’t be established by manual coding, and it is hard for high latitude data in a computer to realize real-time object detection, object localization, classification and recognition. Therefore the higher accuracy in classification could be obtained with the help of GPU of high performance and the large scale pretraining on the super database Image Net, based on the most advanced deep convolution neural network algorithm. The complete optimization training was conducted on data sets Pascal Vision Object Classes (VOC), and the real-time object detection, object localization, classification and recognition were realized by high performance GPU of NVIDIA.
A strategy for controlling autonomous robot platoons

Development of decentralized control systems for platoons of robotic vehicles often requires direct communication between vehicles. Using basic tools from the field of decentralized control, we develop a framework from which existence of vehicle controllers can be assessed for a given communication structure. This approach to control design allows one to investigate minimum inter-vehicle communication solutions. Simulation results are presented for a platoon of autonomous underwater vehicles.
A Novel Localization Algorithm Based on Steepest Descent Method for the Wireless Sensor Network

To improve the positioning accuracy, this paper analyses the error source of the DV-Hop algorithm, and proposes an improved DV-Hop algorithm (IDV-Hop). The improvements of the IDV-Hop algorithm are threefold. First of all, we correct the average hop distance calculated by the beacon nodes. Secondly, the localization uses weighted average hop distances of multiple beacon nodes. Finally, we use the steepest descent method to optimize the localization result. The simulation results show that the proposed algorithm improves significantly in both positioning accuracy and stability, comparing with DV-Hop and CDV-Hop. Therefore, it is a feasible localization scheme in wireless sensor network.
Proceedings of the 27th Conference on Image and Vision Computing New Zealand

It is a great pleasure to introduce the proceedings of the Image and Vision Computing Conference New Zealand 2012. The annual NZ conferences started in 1986 at Lower Hutt with the First New Zealand Image Processing Workshop. The first IVCNZ conference was held in Auckland in 1993 and has been held regularly ever since. The 2012 conference was held at the University of Otago in Dunedin. Located on the southern end of the beautiful South Island of New Zealand, Dunedin is a vibrant university city. The University of Otago is one of the most southern universities in the world, and also a top-ranked research university. It has been our honour to host IVCNZ 2012. This year there were 167 papers submitted of which 29 were accepted as orals (17% acceptance rate), and 64 were accepted as posters for an overall acceptance rate of 56%. The areas of the accepted papers covered a broad range of various image related topics - one of the strengths of IVCNZ. In 2012, there were oral sessions on 3D reconstruction, features, stereo, motion and video, image processing, spaces and transforms, applications, and graphics and HCI. There were also three fantastic keynotes: Dave Ferguson gave a talk on his work at Google on the driverless car project; Nick Barnes talked about his work on computer vision for prosthetic vision; and Reinhard Koch discussed his work on depth cameras and the novel applications made possible by such devices.
Reasonin gabou tTriggere dAction si nAnsProlo gan dIt sApplicatio nt oMolecular Interactions in Cells

Reasoning about molecular interactions and signaling pathways is important from various perspectives such as predicting side effects of drugs, explaining unusual cellular behavior and drug and therapy design. Because of the vast size of these interactions a typical biologist can only focus on a very small part of the network. Thus there is a great need to develop knowledge representation and reasoning formalisms and their implementations for modelling and reasoning about molecular interactions in cells of organisms. An important component of these interactions is the action of one molecule interacting with or binding to another, or one molecule separating into multiple other molecules. Thus, action theories and action languages are good candidates to model these interactions. One major lacking of most existing action languages is the notion of triggered actions, which is a common phenomena in the cellular domain. In this paper, we introduce a language for representing and reasoning about triggered actions, and show how to model reasoning about side effects, explaining observations, and designing drugs in our language through implementations using AnsProlog.
A framework for diagnosis of interstitial lung diseases in HRCT: the TALISMAN project

Summary In this paper we describe the goals and the latest outcomes of the TA LISMAN project, the purpose of which is to furnish image-based diagnostic assistance for interstitial lung diseases (ILDs) with secondary data integration. Prototypes of the computer tools are implemented. High correct classification rates of lung tissue regions in high-resolution computed tomography (HRCT), based on a high-quality dataset built from clinical routine, suggests that computerised analysis of HRCT images with integration of the clinical context is ready to be used for computer-aided diagnosis of ILDs. As future tasks, implementation of multimodal retrieval of ILD cases and clinical evaluation of the software are planned to meet clinical needs.
The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WUMINN Human Connectome Project and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processingmechanisms, genetic pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction and cortical surface inflation of neonatal subjects, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be fully automatically processed; generating cortical surface models that are topologically and anatomically correct. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, and support the modelling of emerging patterns of brain connectivity.