Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling of the handover dwell time in cellular mobile communications systems

Handover request queueing has been extensively analyzed as a handover protection scheme for future cellular networks. In this frame, however, while channel holding time distribution and cell boundary crossing rate have been modeled, the distribution of the allowed queue waiting time-i.e., the handover dwell time-has remained an open question from the modeling standpoint. In this frame, this paper proposes a model of the handover dwell time in circular cells' coverage. The agreement between modeling and simulation results is very satisfactory. A fitting of an asymptotic behavior of the handover dwell-time distribution with a truncated Gaussian function is also provided, measuring the fitting goodness in various test cases. The practical insights the model can provide are also outlined in the paper.
Towards an Adaptive Question Answering System for Intelligence Analysts

Battelle is working in partnership with Stanford University's Knowledge Systems Laboratory (KSL) and IBM's T.J. Watson Research Center to develop a suite of technologies for knowledge discovery, knowledge extraction, knowledge representation, automated reasoning, and human information interaction, in unison entitled “Knowledge Associates for Novel Intelligence” (KANI). We have developed an integrated analytic environment composed of a collection of analyst associates, software components that aid the analyst at different stages of the analytical process. In this paper, we discuss our efforts in the research, design and implementation of the question answering elements of the Information Interaction Associate. Specifically, we focus on the techniques employed to produce an effective user interface to these elements. In addition, we touch upon the methodologies we intend to use to empirically evaluate our approach with active intelligence analysts.
Seeking God's Will: The Experience of Information Seeking by Leaders of a Church in Transition/ la

What is the experience of information seeking (IS) by leaders of a church in transition, as they seek the will of God for their church? In this ethnographic pilot study, I begin to create a picture of leaders’ information seeking, first for personal faith building then corporate decision-making, and I consider the impact of new technologies on these processes. Religious IS did not differ significantly with other ELIS experiences, except in leadership roles. Prominent themes were theological diversity and prayer.
Corpus Design Criteria

2 Stages in Corpus Building: Tasks, Expertise, Personnel 3 2.1 Planning . 3 2.2 Permissions . 4 2.3 Data Capture . 4 2.4 Text Handling . 4 2.4. 1 Basic Tools . 5 2.4. 2 Advanced Text Handling . 5 2.5 User Feedback and Corpus Development . 5
The relationship between coronal place and vowel backness

This paper presents evidence that tongue-body position is always specified in the phonological representation of coronals, even where it is non-contrastive. Tongue-body position is needed to account for the typology of interactions between coronal consonants and adjacent vowels. For example, coronals only condition vowel fronting if they are produced with a front tongue body (usually anterior coronals), and only coronals produced with a back tongue body (usually retroflexes) condition vowel retraction. However, coronals do not have a fixed tongue-body position. Tongue-body position is affected by the position of the tongue tip/blade, because these articulators are physically connected, so each type of coronal has a preferred tongue-body position that facilitates the production of the coronal constriction. These preferences can be overridden, however, e.g. due to assimilation to a vowel. Optimality-theoretic feature co-occurrence constraints provide a good account of this type of dependency between articulators.
A Novel System for the Synthesis of 2-Aminobenzthiazoles using Sodium Dichloroiodate

Abstract 2-Aminobenzthiazole is a privileged scaffold with a range of biological activities. However, to date, an efficient protocol for the synthesis of this ring system using aniline as a starting material has been lacking. Herein, for the first time, we describe a highly efficient and mild protocol for the synthesis of 2-aminiobenzthiazole using NaICl2.
Conceptual spaceborne Ka-band spotlight synthetic aperture radar with reconfigurable aperture

Two principal objectives of this investigation are: a) to produce using a reconfigurable aperture circular beam footprints for grazing angles from 15/spl deg/ to 70/spl deg/, and b) to maintain high efficiency high-power 35 GHz solid-state devices in a feed array. An elliptical reflector 8.51 m high and 2.9 m wide is proposed with a near-zone programmable, transmit-receive phased array feed in a beam waveguide to deliver 25.5 w/m/sup 2/ at the radiating aperture. By redirecting the beam to track a particular area, called the "spotlight-mode", fine azimuth resolution and multi-look images can be produced. A 700 km altitude orbit is assumed and the resolution goal is 1.0 m.
Improving visual data mining using analyzing editing effect of visual data

With the increase of multimedia contents in the internet, people need to handle a large amount of multimedia contents in the web as well as e-mail. Visual data mining is needed to find appropriate visual data among large multimedia contents. But editing process, which is common on the web affects the feature of visual data, and causes false retrieval in current visual mining system. In this paper, we propose an improving visual mining method by detecting and reducing image editing effects.
International Journal of Advanced Robotic Systems Novel 3-d Object Recognition Methodology Employing a Curvature-based Histogram Regular Paper

In this paper, a new object recognition algorithm employing a curvature-based histogram is presented. Recognition of three-dimensional (3-D) objects using range images remains one of the most challenging problems in 3-D computer vision due to its noisy and cluttered scene characteristics. The key breakthroughs for this problem mainly lie in defining unique features that distinguish the similarity among various 3-D objects. In our approach, an object detection scheme is developed to identify targets underlining an automated search in the range images using an initial process of object segmentation to subdivide all possible objects in the scenes and then applying a process of object recognition based on geometric constraints and a curvature-based histogram for object recognition. The developed method has been verified through experimental tests for its feasibility confirmation.
Smooth quality streaming with bit-plane labeling

Bit-plane coding techniques have been proposed as an efficient way to achieve the goal of fine granularity scalability (FGS). Both in image and video coding standards such as JPEG 2000 and MPEG-4, bit-plane coding techniques have been utilized to code a universal bit-stream for various bandwidth applications. With the bit-plane coding, a bit-stream can be truncated according to the available bandwidth. Hence, the video quality can be very sensitive to the network bandwidth variation especially while streaming a video over the Internet or a wireless link. For overall human perception, a consistent and smooth quality video is much better than to have high video quality in just a short period but with highly quality variation in general. We classify the quality variation into two categories: inter-frame and intraframe quality variation. The inter-frame quality variation may cause by the constant bit rate coded (CBR) base layer video or the network bandwidth variation, while the intra-frame quality variation causes mainly by the various motion types. For example, moving objects are usually more difficult to be encoded. This paper focuses on the inter-frame quality variation because quality variation is more significant between frames than within a frame. An enhancement layer labeling algorithm is proposed to reduce the inter-frame quality variation, and a dynamic bit-plane truncation scheme is utilized to maintain the smooth streaming video quality. The proposed algorithm has no overhead in the decoder, and the experimental results portray that our proposed algorithm can greatly eliminate the inter-frame quality variation.
We Need Faster & Deeper Scan and More Realistic Tests

A hundredfold increase of scan data volume has been predicted for the next ten years. This position statement discusses the implications on ATE and EDA, within the constraints of test cost, quality, and time-to-market. The first conclusion will be that the demand for more scan data can be met without increasing test cost, by exploiting test data sharing across multiple equal cores, relying on improved test data compression, and on faster scan I/O, served by deeper ATE memory. But will this provide sufficient test coverage? It seems too challenging to create effective, up-to-date fault models and suitable scan test conditions such that practical ATPG alone can successfully target all defects in future complex heterogeneous SiP and 3D packages. Additional new test methodologies will be needed to test devices under stressful realistic conditions. ATE must provide well controllable stress test conditions and interact with the DUT at a higher level of abstraction to enable fast development of system-like tests.
Science gateways for biomedical big data analysis

Biomedical researchers are facing data deluge challenges such as dealing with large volume of complex heterogeneous data and complex and computationally demanding data processing methods. Such scale and complexity of biomedical research requires multi-disciplinary collaboration between scientists from different organizations. Data-driven or e-Science methods are defined as a combination of Information Technology (IT) and science that enables scientists to tackle the data deluge challenges. The IT infrastructures that address these challenges are known as cyberinfrastructures or e-Infrastructures, which are the environments that provide collaborative sharing of distributed computing and data resources. However, e-Infrastructures fall short of high-level and customized services to support the needs of scientists genuinely, and scientists find interacting with e-Infrastructures challenging, as it requires detailed technical knowledge. Science Gateway (SG) research addresses these drawbacks. SGs are web-based enterprise information systems that provide scientists with customized and easy access to community-specific data collections, computational tools, and collaborative services on e-Infrastructures. In this thesis we advanced the understanding of the fundamentals of SGs for biomedical research by organizing the findings about the requirements of biomedical researchers. We also organized the considerations about the design, development, operation, and sustainability of effective SGs. Moreover, we constructed a few successful SGs that were adopted by a large number of scientists and facilitated their biomedical big data analysis on e-Infrastructures. Finally we proposed a reference model that organizes the essential functions of SGs. We think that these efforts will facilitate design, development, operation, sustainability, and most importantly, adoption of SGs for biomedical research.
Dynamic neural networks for real time control of FMS

A control aspect of the non-acyclic FMS scheduling problem is considered. Based on the dynamic neural network model derived herein, an adaptive, continuous time neural network controller is constructed. The actual dispatching times are determined from the continuous control input discretization. The controller is capable of driving the system production to the required demand and guarantees system stability and boundedness of all signals in the closed loop. Modeling errors and discretization effects are taken into account thus rendering the controller robust. A case study demonstrates the efficiency of the proposed technique.
Communication protocol for virtual cellular network (VCN)

A new wireless communication architecture, the 'virtual cellular network (VCN)' was proposed in order to improve the performance of conventional cellular networks. The advantage of the VCN includes increased throughput, easy placing of ports, no handover and simple wireless communications. A random access uplink (mobile-to-station) protocol, the multi-packet encoding (MPE) is proposed for the VCN in order to provide almost fair throughput independently of the position of the mobiles. Moreover, the MPE reduces the backoff delay by using an error correction code, and increases the downlink channel efficiency due to the minimized feedback (ack's). A minimum group (MG) protocol is proposed for the downlink. The MG protocol supports multicast (several ports send the same downstream packets) as well as unicast (only one port sends the packet to a mobile).
Dribble Files: Methodologies to Evaluate Learning and Performance in Complex Environments

Research in the area of technology learning environments is tremendously complex. Tasks performed in these contexts are highly cognitive and mostly invisible to the observer. The nature of performance in these contexts is explained not only by the outcome but also by the process. However, evaluating the learning process with respect to tasks involving technology is difficult to measure objectively. As a result, audit trails (also called log or dribble files) are becoming extremely valuable tools in evaluating learning and performance in complex environments. This article reviews efforts of researchers in various areas, describes the nature of research using dribble files, and provides a framework on which investigators might build evaluations.
New approach to integrated data management in special materials processing

Development of high-precision products of difficult to process materials often requires use of unconventional techniques and manufacturing technologies. The studies are labor-and cost-consuming. Development of a database in which they are collected and available informations necessary for designers of machinery and process design engineers, process is a matter of considerable importance. This paper presents the principles of design and structure of the database DBSMP (DataBase Special Materials Processing) and its implementation to manufacturing.
A Comparative Study for Estimation Parameters in Panel Data Model

This paper examines the panel data models when the regression coefficients are fixed, random, and mixed, and proposed the different estimators for this model. We used the Mote Carlo simulation for making comparisons between the behavior of several estimation methods, such as Random Coefficient Regression (RCR), Classical Pooling (CP), and Mean Group (MG) estimators, in the three cases for regression coefficients. The Monte Carlo simulation results suggest that the RCR estimators perform well in small samples if the coefficients are random. While CP estimators perform well in the case of fixed model only. But the MG estimators perform well if the coefficients are random or fixed.
RACT: Randomized Algorithms Control Toolbox for MATLAB

Abstract This paper introduces a new M atlab package, R act , aimed at solving a class of probabilistic analysis and synthesis problems arising in control. The package offers a convenient way for defining various types of structured uncertainties as well as formulating and analyzing the ensuing robustness analysis tasks from a probabilistic point of view. It also provides a full-featured framework for LMI-formulated probabilistic synthesis problems, which includes sequential probabilistic methods as well as scenario methods for robust design. The R act package is freely available at http://ract.sourceforge. net , and only requires the Y almip toolbox to be installed in the M atlab environment.
Study of Stationary Load Increase of Computer-Network Traffic via Dynamic Principal-Component Analysis

Many network monitoring applications and performance analysis tools are based on the study of an aggregate measure of network traffic, for example, number of packets in transit (NPT). The simulation modeling and analysis of this type of performance indicator enables a theoretical investigation of the underlying complex system through different combination of network setups such as routing algorithms, network source loads or network topologies. To detect stationary increase of network source load, we propose a dynamic principal component analysis (PCA) method, first to extract data features and then to detect a stationary load increase. The proposed detection schemes are based on either the major or the minor principal components of network traffic data. To demonstrate the applications of the proposed method, we first applied them to some synthetic data and then to network traffic data simulated from the packet switching network (PSN) model. The proposed detection schemes, based on dynamic PCA, show enhanced performance in detecting an increase of network load for the simulated network traffic data. These results show usefulness of a new feature extraction method based on dynamic PCA that creates additional feature variables for event detection in a univariate time series.
High-resolution land cover change detection based on fuzzy uncertainty analysis and change reasoning

Land cover change detection is an important research and application area for analysts of remote sensing data. The primary objective of the research described here was to develop a change detection method capable of accommodating spatial and classification uncertainty in generating an accurate map of land cover change using high resolution satellite imagery. As a secondary objective, this method was designed to facilitate the mapping of particular types and locations of change based on specific study goals. Urban land cover change pertinent to surface water quality in Raleigh, North Carolina, was assessed using land cover classifications derived from pan-sharpened, 0.61 m QuickBird images from 2002 and 2005. Post-classification map errors were evaluated using a fuzzy logic approach. First, a ‘change index’ representing a quantitative gradient along which land cover change is characterized by both certainty and relevance, was created. The result was a continuous representation of change, a product type that retains more information and flexibility than discrete maps of change. Finally, fuzzy logic and change reasoning results were integrated into a binary change/no change map that quantified the most certain, likely, and relevant change regions within the study area. A ‘from-to’ change map was developed from this binary map inserting the type of change identified in the raw post-classification map. A from-to change map had an overall accuracy of 78.9% (κ = 0.747) and effectively mapped land cover changes posing a threat to water quality, including increases in impervious surface. This work presents an efficient fuzzy framework for transforming map uncertainty into accurate and practical change analysis.
Wide-Band Modeling of Grounding Grid Based on the Fractional Order Differential Theory

Research on the wide-band modelling method of the grounding grid and the analysis of the electromagnetic transients on the grounding grid has significant practical meaning on the engineering problems, e.g. overvoltage protection, insulation coordination and electromagnetic interference and the increasing levels of capacity in the power and communication systems. This paper presents strategies which establish the equivalent circuit for computing the transient performance of grounding grid base on fractional order differential theory, which takes into account the fractional frequency characteristics of soil permittivity. In order to validate the presented method, an example is considered and the transient responses are compared with the results obtained by the method of moments.
Establishing shared understanding of product use through collaboratively generating an explicit frame of reference

Recent studies have shown that there is a need to improve usability-related decision-making in product development teams to prevent usability problems in the final product. Those decisions are heavily influenced by the knowledge those teams have of future use situations and expected usability issues. Our previous research showed that design team members often implicitly hold this type of knowledge, but do not share it within the team. This lack of a shared understanding of product use negatively influences the decision-making process. In this paper we present the iterative development of a set of guidelines to support design teams in sharing knowledge of product use through the generation of flexible, explicit and evolving frames of reference. A series of studies in which the guidelines were evaluated suggest that particularly the activity of collaboratively creating the explicit frame of reference contributes to a shared understanding of product use.
Automatic abnormal region detection in lung CT images for visual retrieval

Image management, analysis, and retrieval are currently very active research fields mainly because of the large amount of visual data being produced in modern hospitals, and the lack of applications dealing with these data. Most often, the goal is to aid the diagnostic process. Unfortunately, only very few medical image retrieval systems are currently used in clinical routine. One application domain with a high potential for automatic image retrieval is the analysis and retrieval of lung CTs. A first user study in the United States (Purdue University) shows that these systems allow improving the diagnostic quality significantly. This article describes an approach to an aid for lung CT diagnostics. The analysis incorporates several steps and the goal is to automate the process as much as possible for easy integration into clinical processes. Thus, several automatic steps are proposed from a selection of the most characteristic slices, to an automatic segmentation of the lung tissue and a classification on the segmented area into visual observation classes. Feedback to the MD is given in the form of marked regions in the images that appear to be different from the norm of healthy tissue. We currently work on a small set of training images with marked and annotated regions but a larger set of images for the evaluation of our algorithm is in work. The article currently only contains a short quantitative evaluation. For most tasks we use existing open source software such as Weka, GIFT, and itk. This allows an easy reproduction of the search results and limits the need for costly redevelopments.
Two-stage evolutionary algorithm for dynamic multicast routing in mesh network

In order to share multimedia transmissions in mesh networks and optimize the utilization of network resources, this paper presents a Two-stage Evolutionary Algorithm (TEA), i.e., unicast routing evolution and multicast path composition, for dynamic multicast routing. The TEA uses a novel link-duplicate-degree encoding, which can encode a multicast path in the link-duplicate-degree and decode the path as a link vector easily. A dynamic algorithm for adding nodes to or removing nodes from a multicast group and a repairing algorithm are also covered in this paper. As the TEA is based on global evaluation, the quality of the multicast path remains stabilized without degradation when multicast members change over time. Therefore, it is not necessary to rearrange the multicast path during the life cycle of the multicast sessions. Simulation results show that the TEA is efficient and convergent.