Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of channel information acquisition schemes in cognitive radio system

In this paper, we compare the performance of two major spectrum information acquisition schemes in cognitive radio system, which are geo-location database based scheme and spectrum sensing based scheme. Although these two schemes are the major spectrum information acquisition schemes which are mainly considered in current researches on cognitive radio system, the comparison of two schemes has not been considered in previous works. In the comparison, we propose a new channel model for the cognitive environment which has three states, because recent measurements show that two-state Markov Chain model which has been widely used is not appropriate to model the cognitive environment. And based on the new channel model, we propose a new spectrum sensing scheme to reduce sensing overhead. Through performance analysis and numerical results, we show that our analysis is accurate and that the number of spectrum sensing can be reduced by using our proposed scheme so that the throughput of a cognitive radio system can be improved. We also find that the throughput of a spectrum sensing based scheme is better than that of a geo-location database based scheme in general cognitive environment.
Detecting anomalous energy consumptions in distributed manufacturing systems

This paper presents a novel model-based approach for the prediction of energy consumption in production plants in order to detect anomalies. A special Ethernet-based data acquisition approach is implemented that features real-time sampling of process and energy data. Hybrid timed automaton models of the supervised production plant are generated and executed in parallel to the system by using data samples as model input. According to comparisons of predicted energy consumption with the production plant observations, anomalies can be detected automatically. An evaluation within a small factory shows that anomalies of 10 % differences in energy consumption, wrong control sequences and wrong timings can be detected with a minimum accuracy of 98 %. With this approach, downtimes of production systems can be shortened and atypical energy consumptions can be detected and adjusted to optimal operation.
Karl Popper on Theory Creation

The very title of my paper may cause many eyebrows to be raised. For anyone who is familiar with Popper’s philosophy of science knows well that he distinguished clearly between two types of historical processes, namely, the process of conceiving a new scientific theory or idea and the methods of examining it logically, and asserted that the task of the philosophers is not to ponder on these actual thinking processes whereby a new scientific theory comes into being. The logical analysis of scientific knowledge, instead, is restricted to an examination of contents of linguistically formulated scientific theories and of the post-generational evaluative procedures of scientists. One might naturally ask what then the point behind an inquiry like this is since Popper himself was mainly concerned with post-generational justification and bequeathed the detailed study of theory creation to the psychologists and the historians. There are two principal reasons which motivated this examination. Firstly, what is generally found as the Popperian notion of creativity and scientific discovery in the literature of philosophy of science is reasonably different from what closer readings of his earlier and later works reveal. Secondly, an analysis like this can illuminate problems of theory change and scientific progress, which undoubtedly are important to philosophy of science in general and Popper in particular. This implies a crucial point, namely, that progress of scientific knowledge, contrary to what philosophers of science generally used to believe, is not the subject matter of a single discipline. In this paper I attempt to make apparent the shortcomings that the disciplinary splitting of the topic of advancement of knowledge (in science) entails.
Multiclass transfer learning from unconstrained priors

The vast majority of transfer learning methods proposed in the visual recognition domain over the last years addresses the problem of object category detection, assuming a strong control over the priors from which transfer is done. This is a strict condition, as it concretely limits the use of this type of approach in several settings: for instance, it does not allow in general to use off-the-shelf models as priors. Moreover, the lack of a multiclass formulation for most of the existing transfer learning algorithms prevents using them for object categorization problems, where their use might be beneficial, especially when the number of categories grows and it becomes harder to get enough annotated data for training standard learning methods. This paper presents a multiclass transfer learning algorithm that allows to take advantage of priors built over different features and with different learning methods than the one used for learning the new task. We use the priors as experts, and transfer their outputs to the new incoming samples as additional information. We cast the learning problem within the Multi Kernel Learning framework. The resulting formulation solves efficiently a joint optimization problem that determines from where and how much to transfer, with a principled multiclass formulation. Extensive experiments illustrate the value of this approach.
Galaxy Clusters at 0.9 < z < 1.7 in the AKARI NEP Deep Field

There is a huge gap between properties of red-sequence selected massive galaxy clusters at z 3. It is important to understand when and how the z > 3 proto-clusters evolve into passive clusters at z 1, taking advantage of the 4000u break and the 1. 6µm bump. We carefully selected 16 promising cluster candidates at 0.9 < z < 1.7, which all show obvious over-density of galaxies and a prominent red-sequence. At this redshift range, the mid-infrared S15µm/S9µm flux ratio is an extinction-free indicator of galaxy star formation activity due to the redshifted PAH emission lines (6.2,7.7 and 8.6µm). We show statistically that the cluster galaxies have a lower S15µm/S9µm flux ratio than field galaxies, i.e., cluster galaxies already have lower star-formation activity at 0.9 < z < 1.7, pushing the formation epoch of these galaxy clusters to a higher redshift.
Optimization of a three-phase slurry catalytic reactor by Particle Swarm

The Particle Swarm Optimization (PSO) technique was employed to optimize an industrial chemical process characterized by being difficult to be optimized by conventional methods. The chemical process is a thr ee phase catalytic slurry reactor in which the reaction of the hydrogenation of o-cresol pr ducing 2-methyl-cyclohexanol is carried out. The process was represented by a multi variable non-linear mathematical model. In order to optimize the process, different PSO algorithms were coupled with the model of the reactor. The aim of the optimization w as the searching of the process inputs that maximizes the productivity of 2-methylc clohexanol subject to the constraint of conversion. PSO was able to solve the non-linear constrained optimization problem. Considering the differences among the PSO algorithms, i.e. the velocity equation and parameters values, only the latter sho wed to have effect on the optimization. The low computational time demanded i n the optimization suggests that the PSO can be suitable for real time implementatio ns.
Algae-Derived Marine Oligosaccharides and Their Biological Applications

The biological relevance of algae-derived marine oligosaccharides has potential significance in numerous applications of industrial biotechnology. Marine oligosaccharides are produced in algae naturally and/or by hydrolysis of derived polysaccharides. The potential of marine oligosaccharides is still unexplored, and these molecules, including their derivatives, are a versatile source of chemical diversity. In-depth knowledge on such molecules will provide novel insights, thus depicting their role in discovering mechanisms and the molecular functions within specific biological applications.
Threshold-Based Location-Aware Access Control

Designing a secure, resilient and user-friendly access control system is a challenging task. In this article, a threshold-based location-aware access control mechanism is proposed. This design uniquely combines the concepts of secret sharing and distance bounding protocols to tackle various security vulnerabilities. The proposed solution makes use of the fact that the user carries around various personal devices. This solution offers protection against any set of or fewer compromised user's devices, with being an adjustable threshold number. It removes the single point of failure in the system, as access is granted when one carries any set of user's devices. Additionally it supports user-centered management, since users can alter the set of personal devices and can adjust the security parameters of the access control scheme towards their required level of security and reliability.
E-learning evaluation: A cross-technique comparison

The evaluation of e-learning applications deserves special attention, and evaluators need effective methodologies and appropriate guidelines to perform their task. In this paper, we present a comparison of different techniques and describe the methodology of an experiment aimed to unveil strengths and weaknesses of Heuristic Evaluation, Direct Observation and SUE Inspection. The experiment was designed to compare the performance of evaluators applying different techniques on the same e-learning software.
Multiresolution representations for surfaces meshes

We describe a method for constructing multi resolution models (MRM) of complex triangle meshes and show how these representations can be used to create view dependent adaptive approximations of triangle meshes on the y with guaranteed approximation error. We use a modiied one-sided Hausdorr distance as a geometrically meaningful error value between the original and the simpliied mesh. Since this distance is parameterization-independent, its use as error measure is superior to the use of the L 1-Norm between parameterized surfaces. The proposed multi-resolution model supports progressive transmission, smooth geomorphing of diierent levels of detail approximations, mesh compression and selective error tolerance editing. Various examples demonstrate the excellent results that were achieved by this new method with triangle meshes from diierent application areas such as volume rendering, terrain modeling and the approximations of parameterized surfaces.
Collective Intelligence and Braess' Paradox

We consider the use of multi-agent systems to control network routing. Conventional approaches to this task are based on Ideal Shortest Path routing Algorithm (ISPA), under which at each moment each agent in the network sends all of its traffic down the path that will incur the lowest cost to that traffic. We demonstrate in computer experiments that due to the sideeffects of one agent’s actions on another agent’s traffic, use of ISPA’s can result in large global cost. In particular, in a simulation of Braess’ paradox we see that adding new capacity to a network with ISPA agents can decrease overall throughput. The theory of COllective INtelligence (COIN) design concerns precisely the issue of avoiding such side-effects. We use that theory to derive an idealized routing algorithm and show that a practical machine-learning-based version of this algorithm, in which costs are only imprecisely estimated substantially outperforms the ISPA, despite having access to less information than does the ISPA. In particular, this practical COIN algorithm avoids Braess’ paradox.
From Conceptual Model to Oo Database via Intermediate Speciication

When designing underlying databases of information systems, data are rst modelled on conceptual level and then the obtained conceptual data model is transformed to a database. The focus of this paper is the transformation of conceptual models into object-oriented database systems. For a conceptual schema, consisting of an information structure and a set of integrity constraints , both the structure and the constraints have to be translated into the target environment. In our approach this mapping is captured within the framework of a two level architecture. Conceptual models are rst mapped to abstract intermediate speciications, which are then transformed to database schemas in a given object-oriented target database environment (e.g. SQL3, ODMG). To express intermediate representations of conceptual models we use F-logic, a logic-based abstract speciication language for object-oriented systems. In the present paper we focus on the rst step of the overall transformation, i.e. the mapping of conceptual models into F-logic. Several transformation alternatives are discussed, and a corresponding graphical notation for specifying transformation alternatives is provided.
A phase transition between small- and large-field models of inflation

We show that models of inflection point inflation exhibit a phase transition from a region in parameter space where they are of large-field type to a region where they are of small-field type. The phase transition is between a universal behavior, with respect to the initial condition, at the large-field region and non-universal behavior at the small-field region. The order parameter is the number of e-foldings. We find integer critical exponents at the transition between the two phases.
The description of friction of silicon MEMS with surface roughness: virtues and limitations of a stochastic Prandtl–Tomlinson model and the simulation of vibration-induced friction reduction

We have replaced the periodic Prandtl–Tomlinson model with an atomic-scale friction model with a random roughness term describing the surface roughness of micro-electromechanical systems (MEMS) devices with sliding surfaces. This new model is shown to exhibit the same features as previously reported experimental MEMS friction loop data. The correlation function of the surface roughness is shown to play a critical role in the modelling. It is experimentally obtained by probing the sidewall surfaces of a MEMS device flipped upright in on-chip hinges with an AFM (atomic force microscope). The addition of a modulation term to the model allows us to also simulate the effect of vibration-induced friction reduction (normal-force modulation), as a function of both vibration amplitude and frequency. The results obtained agree very well with measurement data reported previously.
Trust-based decision-making system for action selection by autonomous agents

Virtual agents can play the trainee's teammates in Collaborative Virtual Environments for Training (CVET). In such teams, trust is essential since people rely on each others. We propose a decision making system for agents in CVET based on an agent model inspired from works on trust in organizational psychology. Agents dimensions are integrity, benevolence and abilities, and agents have trust-beliefs about their teammates integrity, benevolence and abilities. Based on their personal dimensions and trust beliefs, agents compute the importance of their goals and then the utility of actions to select the most appropriate action.
A Computational Model of the Semantics of Tense and Aspect

The PUNDIT natural-language system processes references to situations and the intervals over which they hold using an algorithm that integrates the analysis of tense and aspect. For each tensed clause, PUNDIT processes the main verb and its grammatical categories of tense, perfect, and progressive in order to extract three complementary pieces of temporal information. The first is whether a situation has actual time associated with it. Secondly, for each situation that is presumed to take place in actual time, PUNDIT represents its temporal structure as one of three situation types: a state, process, or transition event. The temporal structures of each of these situation types consist of one or more intervals. The intervals are characterized by two features: kinesis, which pertains to their internal structure, and boundedness, which constrains the manner in which they get located in time. Thirdly, the computation of temporal location exploits the three temporal indices proposed in Reichenbach 1947: event time, speech time, and reference time. Here, however, event time is formulated as a single component of the full temporal structure of a situation in order to provide an integrated treatment of tense and aspect.
Cube lattice decoder

An insight to the ℓ1 lattice decoder for flat-fading multiple antenna wireless communications systems is presented in this paper. In particular, we show that by formulating the problem as a bounded error subset selection, the equivalent decoder finds the nearest lattice point to the received signal in the ℓ1 sense. The search for the nearest lattice point is bounded inside a hypercube centered at the received vector; where the dimensions and orientation of the hypercube depends on the channel conditions. The search for the nearest codeword to the received vector is achieved by modeling the problem as a Mixed Integer Linear Program. The proposed decoder achieves near-optimum performance while its complexity is invariant with the operating signal to noise ratio.
Spatio-temporal organization of one's personal image collection with model-based ICL-clustering

This paper addresses the issue of automated organization of a personal image collection, in particular to respond to the emerging needs from a mobile camera phones. The issues related to browsing through large image collections acquired from such devices are first discussed. In contrast with metadata-less collections, which necessarily rely on image content, we propose a collection organization technique based on picture geolocation and timestamps. These are indeed available and generally reliable in the proposed context. The objective is formulated as an unsupervised classification problem, in both space and time. The statistical ntegrated completed likelihood criterion is chosen, providing effective solutions both to model complexity determination and the cluster separability objective, in a setting which avoids arbitrary algorithm parametrization. Reliability of space and time partitions obtained are then assessed, to select an effective segmentation, which may then provide a calendar-type structured view for navigating in the picture collection.
Augmented reality for construction tasks: doorlock assembly

Augmented Reality is a technology that integrates pictures of virtual objects into images of the real world. Besides the technical problems still to be solved, for industry to be interested in this technology the additional amount of work needed to use the technology in relation to the benefit has to be visible. Furthermore the question how this integrates into the information technology infrastructure of the company is important. This paper describes an Augmented Reality demonstrator for the task of doorlock assembly into a car door that was developed trying to create a practical, realistic application that can transport the concepts behind Augmented Reality to a casual observer. To reach that goal a new fast and robust optical tracking algorithm was developed and integrated into a three-dimensional animation and rendering system, creating a real-time fully three-dimensional HMDbased training application showing how to assemble the doorlock into the door. The system was demonstrated to the general public at the Hannover Industrial Fair 1998 and this demonstration of Augmented Reality for one of the first times to a large non-expert audience created a lot of interest into this new area.
Reasoning about taxonomies and articulations

Taxonomically organized data pervade science, business and everyday life. Unfortunately, taxonomies are often underspecified, limiting their utility in contexts such as data integration, information navigation and autonomous agent communication. This work formalizes taxonomies and relationships between them as formulas in logic. This formalization concretizes notions such as consistency and inconsistency of taxonomies and articulations (inter-taxonomic relations) between them, enables the derivation of new articulations based on a given set of taxonomies and articulations and provides a framework for testing assumptions about underspecified taxonomies. Given the typical intractability of reasoning with taxonomies and articulations, this research investigates many optimizations: from those that reduce the search space, to those that leverage parallel processing, to those investigating logics more tractable than first-order logic (e.g., monadic first-order logic, propositional logic, description logics, and subsets of the RCC-5 spatial algebra). Finally, in addition to reasoning with taxonomies and articulations, this research investigates how to repair inconsistent taxonomies and articulations, how to explain inconsistencies and discovered relations, and how to merge taxonomies given articulations. Critical to this research is the development of a framework for testing logics and support for the development of taxonomies and articulations. This framework, CleanTax is already well under way and has been used to study articulations between two large-scale biological taxonomies.
Modular Programming Techniques for Distributed Computing Tasks

Abstract : This paper describes design patterns used in developing a software platform for mobile robot teams engaged in distributed sensing and exploration tasks. The goal of the system presented is to minimize redundancy throughout the development and execution pipelines by exploring the application of a strong type system to both the collaborative development process and runtime behaviors of mobile sensor platforms. The solution we have implemented addresses both sides of this equation simultaneously by providing a system for self-describing inputs and outputs that facilitates code reuse among human developers and autonomous agents. This well-defined modularity allows us to treat executable code libraries as atomic elements that can be automatically shared across the network. In this fashion, we improve the performance of our development team by addressing software framework usability and the performance and capabilities of sensor networks engaged in distributed data processing. This framework adds robust design templates and greater communication flexibility onto a component system similar to TinyOS and NesC while avoiding the development effort and overhead required to field a full-fledged web services or Jini-based infrastructure. The software platform described herein has been used to field collaborative teams of UGVs and UAVs in exploration and monitoring scenarios.