Miracle-dz/UniFAR-FTUs huggingface dataset:
Diversification of visual media retrieval results using saliency detection

Diversification of retrieval results allows for better and faster search. Recently there has been proposed different methods for diversification of image retrieval results mainly utilizing text information and techniques imported from natural language processing domain. However, images contain visual information that is impossible to describe in text and the use of visual features is inevitable. Visual saliency is information about the main object of an image implicitly included by humans while creating visual content. For this reason it is naturally to exploit this information for the task of diversification of the content. In this work we study whether visual saliency can be used for the task of diversification and propose a method for re-ranking image retrieval results using saliency. The evaluation has shown that the use of saliency information results in higher diversity of retrieval results.
The Scope of Memory-Based Processing

In this article, we articulate the critical differences between memory-based processing and explanation-based processing. We suggest that the most important claim of memory-based text processing is that the automatic processes that function with respect to text processing are all applications of ordinary memory processes. This claim contrasts with explanation-based accounts that argue that some automatic processes are special to text processing and enact particular reader goals. We review evidence that supports the memory-based approach but we also suggest how it might properly be falsified.
Computer-vision-based gob inspection system for monitoring and control in the glass industry

This paper presents a computer vision system for measuring the weight of gobs during a glass forming process, and a control strategy to correct automatically any weight deviation from a given set-point. During the formation of molten glass gobs, several noise sources can cause a deviation in the weight from a predefined reference value. Among them, there is a random white-noise disturbance caused by the lack of synchronisation of mechanical devices, the periodic disturbances due to changes in the spinning direction of the tube inside the feeder, and some long-term drifts caused by variations in temperature and viscosity of the raw glass material. The gob weight measurement system developed is based on a monochrome CCD high-resolution camera and photo-detector for synchronizing the frame acquisition. The molten glass provides the illumination, so a high contrast image is obtained with a bright object and dark background. Several image-processing algorithms are presented for reliable area estimation. Assuming that the gob is a symmetric geometry of revolution and uniform mass density, the proposed system estimates the weight of gobs with an accuracy better than ±0.75%. A learning weight control strategy is proposed based on a PI-repetitive control scheme. The weight deviation from a set point is used as a control signal to adjust the glass flow into the feeder. This regulation scheme allows effective weight control, canceling mid and long-term effects. The tracking error, ±1.5%, means a reduction of 40% when compared with a traditional PI controller.
Fault tolerance via weight noise in analog VLSI implementations of MLPs-a case study with EPSILON

Training with weight noise has been shown to be an effective means of improving the fault tolerance of multilayer perceptrons (MLPs). This paper investigates the use of weight noise used during MLP training to compensate for the inherent errors encountered in VLSI implementations. Weight adaptation is conducted solely in software, eliminating the need for costly in-the-loop training. The particular VLSI implementation considered here is the EPSILON processor card developed at Edinburgh University. Both software and hardware experiments demonstrate the effectiveness of this approach. This case study with the EPSILON processor card highlights what we believe to be a number of common inadequacies with custom designed hardware. In particular, the limitations of EPSILON in terms of its dynamic range performance has been shown to be a problem. In summary, we show that networks trained with weight noise are fault-tolerant but also require an increased dynamic range to exploit this property.
Observation Oriented Modeling: Preparing Students for Research in the 21st century1:

Abstract Observation Oriented Modeling is an alternative to traditional methods of data conceptualization and analysis that challenges researchers to develop integrated, explanatory models of patterns of observations. The focus of research is thus shifted away from aggregate statistics, such as means, variances, and correlations, and is instead directed toward assessing the accuracy of judgments based on the observations in hand. In this paper a number of example data sets will be used to demonstrate how Observation Oriented Modeling can be taught to undergraduate and graduate students. While the examples are drawn from psychology, the method of contrasting Observation Oriented Modeling with traditional methods of research design and statistical analysis can easily be adapted to examples from other sciences.
Edge-Based Gaze Planning for Salient Proto-Objects

Selective attention of primates or human being has been modeled and implemented by many vision researchers in a decade. And also several attempts, which improve object recognition using selective attention model, have existed. But there are few researches in the gaze planning for the results of selective attention process. Therefore we propose a planning method based on edge information in the attended regions. And we explain the edge description methods (edge density and entropy) and also propose a new description method, edge uniformity. We evaluate the performance of the methods in the viewpoint of attentive object recognition.
Towards a Total Reusability of Image Processing Algorithms

This technical report presents the evolution of algorithms implementation in image processing libraries and discusses the limits of these implementations in terms of reusability. In particular, we show that in C ++ , an algorithm can have a general implementation; said dierently, an implementation can be generic, i.e., independent of both the input aggregate type and the type of the data contained in the input aggregate. A total reusability of algorithms can therefore be obtained; moreover, a generic implementation is more natural and does not introduce a meaningful additional cost in execution time as compared to an implementation dedicated to a particular input type. This report is a translation into English of the paper:
Rapid 3D regularized EM reconstruction for Compton cameras using GPU

This paper describes the development of rapid 3-D regularized EM (expectation maximization) reconstruction methods for Compton cameras using commodity graphics hardware. Since the size of the system matrix for a typical Compton camera is extremely large, it is impractical to use a caching scheme that reads pre-stored values of the elements of the system matrix instead of repeatedly calculating conical projection and backprojection which are the most time consuming operations. In this paper we propose GPU (graphics processing unit) accelerated methods that can rapidly perform conical projection and backprojection on the fly. Since the conventional ray-based backprojection method is inefficient for GPU, we develop fully voxel-based conical backprojection methods using two different approaches. In the first approach, we approximate the intersecting chord length of the ray passing through a voxel with the normal distance from the center of the voxel to the ray. In the second approach, each voxel is regarded as a dimensionless point, and the backprojection is performed without the need for calculating intersecting chord lengths. Our experimental studies with the M-BSREM (modified block sequential regularized EM) algorithm show that GPU-based methods significantly outperforms the conventional CPU-based method in computation time without a considerable loss of reconstruction accuracy.
GaAs prescalers and counters for fast-settling frequency synthesizers

A number of low-power GaAs direct-coupled FET logic (DCFL) components developed for use in compact, fast-settling phase-locked-loop-type frequency synthesizer applications are discussed. These components include a divide-by-two circuit (2.7 GHz, 1.3 mW), a dual-modulus (/10/11) prescaler (2.4 GHz, 15 mW), a 4-b ripple counter (2.4 GHz, 4.6 mW), a 4-b programmable prescaler (1.7 GHz, 36 mW), a 3-b programmable counter (1.9 GHz, 57 mW), a 4-b programmable counter (1.8 GHz, 70 mW), and a 6-b programmable counter (1.4 GHz, 90 mW). The circuits are fabricated with a high-yield refractory self-aligned gate process and operate over a wide variation in power supply voltage and temperature. When operated over a -55 to 125 degrees C temperature range, the circuits show less than 20% degradation in their maximum clock frequency. The results demonstrate state-of-the-art high-frequency performance at extremely low power dissipation. >
A LIGHT-WEIGHT MUTUAL AUTHENTICATION AND KEY-EXCHANGE PROTOCOL BASED ON ELLIPTICAL CURVE CRYPTOGAPHY FOR ENERGY-CONSTRAINED DEVICES

Wireless devices are characterized by low computational power and memory. Hence security protocols dealing with these devices have to be designed to give minimal computational and memory load. We present an efficient authentication and key exchange protocol for low-end wireless clients and high end servers, which is overall nearly three times as fast as comparable protocols. The basic idea of our protocol is to use symmetric key encryption in place of public key encryption wherever possible.
8.2: Bi‐Directional OLED Microdisplay for Interactive HMD

First prototypes of bi‐directional OLED microdisplay devices have been designed, that combine both display and camera functionality on a single CMOS chip (OLED‐on‐CMOS). Major aim of this integration is to provide capabilities for eye‐tracking in see‐through HMD to achieve gaze‐based human‐display‐interaction, e.g. in augmented‐reality applications.
How Process Control Operators Derive, Update, and Apply Mental Models

The goal of this study was to understand how expert process control console operators interacted with their mental models. We classified this interaction into three forms: deriving, updating and applying the mental model. Ten operators were observed using ethnographic-based methods from the start to the end of their shift. Results revealed operators' strong mental models attained through experience as field operators, essential updates of these mental models at the start of their shifts through handovers and shift meetings, as well as the high frequency of operators performing mental simulations during task performance. The methods used here will be refined for other similar studies at other process control sites. Results from this study could also contribute towards understanding and bridging the expert-novice gap in process control.
Task assignment problems in distributed computing systems by simulated annealing

Abstract The stochastic, heuristic search algorithm called simulated annealing is considered for the problems of static task assignment in distributed computing systems. The purposes of task assignment problems are to assign modules of programs over a set of interconnected processors in order to both maximize the utilization of processors and minimize interprocessor communication costs. This problem has been proven to be NP‐hard. Although simulated annealing has been applied to a broad class of combinatorial optimization problems, but it requires a long computation time in order to converge to the globally optimal solution. In this paper, we design a very efficient annealing schedule with good move generation strategies and use the concept of specific heat and the frozen condition to obtain near‐optimal solutions for task assignment problems with a significantly large reduction in the number of iterations.
A Review on 3D Object Retrieval Methodologies Using a Part-Based Representation

ABSTRACTA comprehensive overview of 3D Object Retrieval methodologies that use a part-based representation is presented. Taking into account the typical operational pipeline we detail each distinct module and we provide a comparative study between the individual modules as well as the global methodologies. This study relies upon the 3D mesh segmentation scheme used, the feature extraction method chosen, as well as the selected graph matching methodology.
Symbolic architectures for cognition

Abstract : This chapter treats the architecture, which is the fixed structure that provides the frame within which cognitive processing in the mind takes place. It describes what an architecture is and how it enters into cognitive theories of the mind. It concentrates on symbolic architectures, the family that includes the architectures central to computer science. It does not treat foundational matters or connectionist architectures. After treating in detail the general requirements of a cognitive architecture, it uses Act and Soar, two architectures relevant to the study of human cognition, to illustrate matters in detail. (sdw)
Estimating the recall performance of Web search engines

This paper reports a comparison of the retrieval effectiveness of the Alta Vista, Excite and Lycos Web search engines. A method is described for comparing the recall of the three sets of searches, despite the fact that they are carried out on non‐identical sets of Web pages. It is thus possible, unlike previous comparative studies of Web search engines, to consider both recall and precision when evaluating the effectiveness of search engines.
Internet performance monitoring

The growing diversity of services in the Internet is motivating research to improve measurability of traffic and Internet performance. This paper surveys current projects and tools for Internet performance monitoring, ranging from passive router-based traffic flow measurement methods to large-scale active performance monitoring projects. The tools and methods are discussed according to their protocol layer, starting from the network layer (ATM, MPLS) to IP/ICMP and transport/application layers. At each protocol layer the strengths and limitations of the methods are highlighted. Finally, issues and challenges for future research are reviewed.
Streamline construction algorithm for 3D flow fields

Streamline construction is an important means for visualizing 3D flow field. Many existing methods are based on regular grid field. Constructing streamlines in structured grid field is more complicated. The main difficulties are the location of an arbitrary point and the interpolation in irregular cells. This paper presents a method for streamline construction in structured 3D flow field. We use structured-point to represent the position of a point and the relationship with its surrounding faces. The point location is made directly in physical space. This method does not need extra memory expense and preprocessing. The implementation and results are also discussed.
A texture-based architecture for face detection in IR images on an FPGA

This paper presents a digital architecture for face detection on infrared (IR) images. We use Local Binary Patterns (LBP) to build a feature vector for each pixel, which represents the texture of the image in a vicinity of that pixel. We use a Support Vector Machine (SVM), trained with 306 images of 51 different subjects, to recognize human face textures. Finally, we group the classified pixels into rectangular boxes enclosing the faces using an algorithm for connected components. These boxes can then be used to track, count, or identify faces in a scene, for example. We implemented our architecture on a Xilinx XC6SLX45 FPGA and tested it on 306 IR images of 51 subjects, different from the data used to train the SVM. The circuit correctly identifies 100% of the faces in the images, and reports 4.5% of false positives. We also tested the system on a set of IR video streams featuring multiple faces per image, with varied poses and backgrounds, and obtained a hit rate of 94.5%, with 7.2% false positives. The circuit uses less than 25% of the logic resources available on the FPGA, and can process 313 640x480-pixel images per second with a 100MHz clock, while consuming 266mW of power.
Remote performance prediction for infrared imaging of buried mines

IR imagers are being investigated by several groups for use in landmine detection. The ability to predict detection performance is necessary to establish confidence for single sensor systems or to allow appropriate weighting of detector output for data fusion algorithms in multiple sensor systems. Preliminary studies had shown that the in-ground vertical temperature gradient was a good indicator of mine/background contrast in IR images if temperature measurements and imager wee collocated and limited data suggested that remote performance monitoring might be possible. To establish practicality of remote monitoring, temperature probes were buried at 5 sites separated by various distance between 30 m and 5.8 km, in asphalt, sand and gravel, both on and off road. Vertical temperature profiles were automatically recorded at all sites simultaneously with IR images of buried thermal IR surrogate mines located at a gravel road site. The in-ground vertical temperature gradient was confirmed to be a practical indicator of the performance of an IR imager, for probes buried in all materials at distances up to almost 6 km from the imager. A five element probe with thermocouples uniformly placed at depths from -3 to -11 cm would be sufficient to predict detection performance.
A Supporting System for Cloud Service Integration Based on User Profiles

SUMMARY While abundant information can be referenced in the Internet Cloud, it is becoming difficult for users to acquire desired information pertinently. Therefore, it is necessary to support users unfamiliar with IT in order to offer information suitable for the user's preferences. This research proposes a service integration supporting system equipped with a recommendation function based on the user's preferences. The research regards bookmarks in a Web browser and tags given to Web services as information showing the user's preference, and a user profile is created using them. A service integration model is built and the proposed system recommends some appropriate examples of integrated services. Compared with conventional supporting systems, the proposed system requires less work for the creation or execution of service integration. © 2013 Wiley Periodicals, Inc. Electron Comm Jpn, 96(9): 14–22, 2013; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/ecj.11444
An Interface Agent for Retrieval of Patient-Specific Cancer Information

PDQ and CANCERLIT are databases that represent potentially valuable resources for oncologists, but there are significant obstacles to their effective use in the clinical context. The clinician must learn where each database can be found, what it contains, and how to query it. More importantly, the clinician must also determine when and how each information resource is appropriate to the (clinical) task at hand, and integrate their general information with patient-specific data contained in patient records and clinical information systems. This research sought to remove these barriers to information use by developing a software agent in the human-computer interface that automates the information retrieval and integration process. The agent, developed from a cognitive model of how human experts perform these tasks, provides both a specific solution to the cancer information access problem, and a template for solving similar problems that occur with increasing frequency in many other domains.
Recursive error-compensated dynamic eigenbackground learning and adaptive background subtraction in video

We address the problem of foreground object detection through background subtraction. Although eigenbackground models are successful in many computer vision applications, background subtraction methods based on a conventional eigenbackground method may suffer from high false-alarm rates in the foreground detection due to possible absorption of foreground changes into the eigenbackground model. This paper introduces an improved eigenbackground modeling method for videos by recursively applying an error compensation process to reduce the influence of foreground moving objects on the eigenbackground model. An adaptive threshold method is also introduced for background subtraction, where the threshold is determined by combining a fixed global threshold and a variable local threshold. A fast algorithm is then given as an approximation to the proposed method by imposing and exploiting a constraint on motion consistency, leading to about 50% reduction in computations. Experiments have been performed on a range of videos with satisfactory results. Performance is evaluated using an objective criterion. Comparisons are made with two existing methods.
Optimization for illumination systems: the next level of design

Computers are routinely used to design illumination systems. Automating the design process is enhanced through the use of optimization procedures. This paper describes some of the underlying illumination optimization fundamentals: parameterization, merit functions, and optimization algorithms. Numerous interesting examples of illumination design problems that benefit from optimization are shown. These examples illustrate illumination optimization through use of ray aiming, computing illuminance using flux tubes, and computing illuminance using Monte Carlo simulations.
Layered Architecture to Detect Attacks Using Asymmetric Support Vector Machine

Intrusion detection is one of the most interesting tasks for network administrators. There is a necessity in protecting the networks from known liabilities by developing more consistent and efficient intrusion detection systems. A distributed intrusion detection system (IDS) is proposed to find the different types of attacks in the networks. Methods such as naïve Bayes assume independence among the observed data. This increases system efficiency but may badly affect the accuracy. To balance this tradeoff, we use asymmetric support vector machines (ASVM) that are more accurate Though it is expensive, we implement the layered approach to improve overall system performance. ASVM is an asymmetric extension of a support vector machine (SVM). The main aim is to reduce the false positive rate while detecting the attacks. The layers are denial of service (DOS) layer, probe layer, remote to local (R2L) layer and user to root (U2R) layer. The layers are used to find the attacks corresponding to that layer.
‘Sharing Time’ with young learners

Although "Sharing Time" is a popular and widespread activity in English for Young Learners (L2) classrooms around the world, there have so far been no research studies of the interaction that is generated and its relationship to learning processes. The aims of this study were to find out how interaction is organized during "Sharing Time" and what kinds of learning it promotes. Audio recordings of 18 complete sessions of Sharing Time in a second grade class in a private English-medium international school in Abu Dhabi were fully transcribed and qualitative analysis of the transcripts was undertaken together with a simple coding system. The focus of the interaction is found to be on topic, meaning, and fluency, rather than form and accuracy. The teacher has no prior knowledge of the topic of the interaction and works collaboratively with the learner to develop the topic and sometimes upgrades the learners' structure and vocabulary. Sharing Time conforms to a social constructivist learning model.