Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic load balancing for position-based routing

Position-based routing algorithms [3] promise an effective delivery of data packets by making use of the geographic positions of the nodes in the network. When developing new algorithms, different factors have to be taken into account. Besides achieving high packet delivery ratios and low delays, the network load is an important characteristic which has to be kept as low as possible. Distributing the load within the network is desirable for different reasons. One of these is the effective usage of the available resources. A good load balancing mechanism helps to raise the packet delivery rate of the transmissions through the network as well as the throughput of the data. Another point is that through an equally distributed load the nodes’ energy consumption is balanced. Typically, mobile nodes only have limited energy available and if these energy resources are exhausted, the nodes will have to leave the network and will not be available for the routing of packets anymore. Load balancing thus prolongs the lifetime of the nodes and consequently, the lifetime of the ad-hoc network.
Real-time camera anomaly detection for real-world video surveillance

This paper proposes an automatic event detection technique for camera anomaly by image analysis, in order to confirm good image quality and correct field of view of surveillance videos. The technique first extracts reduced-reference features from multiple regions in the surveillance image, and then detects anomaly events by analyzing variation of features when image quality decreases and field of view changes. Event detection is achieved by statistically calculating accumulated variations along temporal domain. False alarms occurred due to noise are further reduced by an online Kalman filter that can recursively smooth the features. Experiments are conducted on a set of recorded videos simulating various challenging situations. Compared with an existing method, experimental results demonstrate that our method has high precision and low false alarm rate with low time complexity.
Liver-Specific Expression of Dominant-Negative Transcription Factor 7-Like 2 Causes Progressive Impairment in Glucose Homeostasis

Investigations on the metabolic role of the Wnt signaling pathway and hepatic transcription factor 7-like 2 (TCF7L2) have generated opposing views. While some studies demonstrated a repressive effect of TCF7L2 on hepatic gluconeogenesis, a recent study using liver-specific Tcf7l2−/− mice suggested the opposite. As a consequence of redundant and bidirectional actions of transcription factor (TCF) molecules and other complexities of the Wnt pathway, knockout of a single Wnt pathway component may not effectively reveal a complete metabolic picture of this pathway. To address this, we generated the liver-specific dominant-negative (DN) TCF7L2 (TCF7L2DN) transgenic mouse model LTCFDN. These mice exhibited progressive impairment in response to pyruvate challenge. Importantly, LTCFDN hepatocytes displayed elevated gluconeogenic gene expression, gluconeogenesis, and loss of Wnt-3a–mediated repression of gluconeogenesis. In C57BL/6 hepatocytes, adenovirus-mediated expression of TCF7L2DN, but not wild-type TCF7L2, increased gluconeogenesis and gluconeogenic gene expression. Our further mechanistic exploration suggests that TCF7L2DN-mediated inhibition of Wnt signaling causes preferential interaction of β-catenin (β-cat) with FoxO1 and increased binding of β-cat/FoxO1 to the Pck1 FoxO binding site, resulting in the stimulation of Pck1 expression and increased gluconeogenesis. Together, our results using TCF7L2DN as a unique tool revealed that the Wnt signaling pathway and its effector β-cat/TCF serve a beneficial role in suppressing hepatic gluconeogenesis.
Dictionary based Approach to Edge Detection

Edge detection is a very essential part of image processing, as quality and accuracy of detection determines the success of further processing. We have developed a new self learning technique for edge detection using dictionary comprised of eigenfilters constructed using features of the input image. The dictionary based method eliminates the need of pre or post processing of the image and accounts for noise, blurriness, class of image and variation of illumination during the detection process itself. Since, this method depends on the characteristics of the image, the new technique can detect edges more accurately and capture greater detail than existing algorithms such as Sobel, Prewitt Laplacian of Gaussian, Canny method etc which use generic filters and operators. We have demonstrated its application on various classes of images such as text, face, barcodes, traffic and cell images. An application of this technique to cell counting in a microscopic image is also presented.
A biologically motivated synthesis of accumulator and reinforcement-learning models for describing adaptive decision-making

Cognitive process models, such as reinforcement learning (RL) and accumulator models of decision-making, have proven to be highly insightful tools for studying adaptive behaviors as well as their underlying neural substrates. Currently, however, two major barriers exist preventing these models from being applied in more complex settings: 1) the assumptions of most accumulator models break down for decisions involving more than two alternatives; 2) RL and accumulator models currently exist as separate frameworks, with no clear mapping between trial-to-trial learning and the dynamics of the decision process. Recently I showed how a modified accumulator model, premised off of the architecture of cortico-basal ganglia pathways, both predicts human decisions in uncertain situations and evoked activity in cortical and subcortical control circuits. Here I present a synthesis of RL and accumulator models that is motivated by recent evidence that the basal ganglia acts as a site for integrating trial-wise feedback from midbrain dopaminergic neurons with accumulating evidence from sensory and associative cortices. I show how this hybrid model can explain both adaptive go/no-go decisions and multi-alternative decisions in a computationally efficient manner. More importantly, by parameterizing the model to conform to various underlying assumptions about the architecture and physiology of basal ganglia pathways, model predictions can be rigorously tested against observed patterns in behavior as well as neural recordings. The result is a biologically-constrained and behaviorally tractable description of trial-to-trial learning effects on decision-making among multiple alternatives.
SMES' ADOPTION OF WEB-BASED MARKETING: EMPIRICAL EVIDENCE FROM KENYA

This paper explores adoption of web-based marketing services in Nakuru Municipality, Kenya. The technology adoption model, theory of planned behavior and diffusion of innovation were used to support the study. An explanatory survey research design was employed. Systematic sampling was used to select 98 SMEs from which, the first four customers who enters to the premise at the arrival of the researcher were selected, providing a sample size of 396 respondents. The study findings indicated that perceived ease of use, perceived usefulness and positively determine the adoption of web-based marketing services, while perceived cost negatively affected adoption of webbased marketing services. The findings indicate that perceived ease of use, perceived usefulness and perceived cost are major determinant of adoption of web-based marketing services. Thus, the study recommends consideration of the four major determinants while firms are launching any new web-based marketing services.
How clausal linking affects noun phrase salience in pronoun resolution

A central research aim in language processing is to understand the mechanisms that assign anaphors to their referents. In many cases a referent of an anaphor is unambiguously identi ed by grammatical features like gender and numbermarking, e.g.Maryi metMax in a café because shei . However, in a case like Fredmet Max in a café because he . the assignment of a referent for he is less straightforward. Reference resolution investigates how an anaphoric pronoun (like he) is mapped to a target referent among a list of candidates (like Fred, Max). It is generally agreed that salience a ects ambiguous reference resolution. The concept of salience originates fromcognitive psychology anddescribes a state of prominence of an item in relation to other items in context. It is assumed that salience guides the attention and thus helps individuals to rank large amounts of information by importance. In psycholinguistics, salience is often used as a cover term for (cognitive) availability or accessibility. For instance, it is claimed that a salient item (in comparison with an item that is less salient) is more accessible in memory and thus amore likely candidate to act as a referent for an anaphoric pronoun (Ariel 1990; Gundel, Hedberg, and Zacharski 1993 among others). (In contrast McElree and Foraker 2007 argue that salience increases availability, but not accessibility in memory.) Psycholinguistic studies revealed a range of linguistic and cognitive factors that in uence the salience of an item. (For an overview see for instance Prince 1981; Ariel 1990; Givón 1983; Gundel, Hedberg, and Zacharski 1993; Arnold 1999.) The results support a multiple-constraint approach whereby the salience level of an item is believed to be a consequence of syntactico-semantic features as well
The upper envelope of voronoi surfaces and its applications

Given a setS ofsources (points or segments) in ℜ211C;d, we consider the surface in ℜ211C;d+1 that is the graph of the functiond(x)=minpεSρ(x, p) for some metricρ. This surface is closely related to the Voronoi diagram, Vor(S), ofS under the metricρ. The upper envelope of a set of theseVoronoi surfaces, each defined for a different set of sources, can be used to solve the problem of finding the minimum Hausdorff distance between two sets of points or line segments under translation. We derive bounds on the number of vertices on the upper envelope of a collection of Voronoi surfaces, and provide efficient algorithms to calculate these vertices. We then discuss applications of the methods to the problems of finding the minimum Hausdorff distance under translation, between sets of points and segments.
Emergency Communication Services Based on Overlay Networking Technologies

In this paper, we propose OverLay-based Emergency Communication Services (OLECS), an architecture for emergency communication services, that is based on overlay routing technologies. We modify and extend existing overlay routing mechanisms in terms of decreasing communication overhead, searching multi-hop overlay paths with more than three hops, making it suitable for emergency communication services. The location of overlay nodes is also considered for recovering from partial failure of ISP networks. By performing a numerical evaluation using the actual AS-level network topology of the current Internet, we show that our approach can reduce the overhead in exchanging routing information by a factor of up to 1000, and improve network connectivity by up to 9 times.
New results on pushdown module checking with imperfect information

Model checking of open pushdown systems (OPD) w.r. t. standard branching temporal logics (pushdown module checkingor PMC) has been recently investigated in the literature, both in t he context of environments with perfect and imperfect information about the system (in the last case, the environment has only a partial view of the system’s control states an d stack content). For standard CTL, PMC with imperfect information is known to be undecidable. If the stack content is assumed to be visible, then the problem is decidable and 2EXPTIME-complete (matching the complexity of PMC with perfect information against CTL). The decidability status of PMC with imperfect information against CTL restricted to the case where the depth of the stack content is visible is open. In this paper, we show that with this restriction, PMC with imperfect information against CTL remains undecidable. On the other hand, we individuate an interesting subclass of OPDs with visible stack content depth such that PMC with imperfect information against the existential fragment of CTL is decidable and in 2EXPTIME. Moreover, we show that the program complexityof PMC with imperfect information and visible stack content against CTL is 2EXPTIME-complete (hence, exponentially harder than the program complexity of PMC with perfect information, which is known to be EXPTIME-complete).
A Radius and Ulna Skeletal Age Assessment System

An end to end system to partially automate the TW3 bone age assessment procedure is proposed. The system comprises the detailed analysis of the two more important bones in TW3: the radius and ulna wrist bones. First, a generalization of K-means algorithm is presented to semi-automatically segment the contour of the bones and thus extract up to 89 features describing shapes and textures from bones. Second, a well-founded feature selection criterion based on the statistical properties of data is used in order to properly choose the most relevant features. Third, bone age is estimated with the help of a generalized softmax perceptron (GSP) neural network (NN) whose optimal complexity is estimated via the posterior probability model selection (PPMS) algorithm. We can then predict the different development stages in both radius and ulna, from which we are able to score and estimate the bone age of a patient in years and finally we compare the NN results with those from the pediatrician expert discrepancies
Thermal Scaling Analysis of Multilevel Cu/Low-k Interconnect Structures in Deep Nanometer Scale Technologies

This paper presents a comprehensive thermal scaling analysis of multilevel interconnects in deep nanometer scale CMOS technologies based on technological, structural, and material data from ITRS ’03 [1]. Numerical simulations have been performed using three-dimensional (3-D) electrothermal finite element methods (FEM), combined with accurate calculations of temperature- and size-dependent Cu resistivity and thermal conductivity of low-k interlayer dielectrics (ILD) based on fully physical models. The simulations also incorporate various scaling factors from fundamental material level to system level: the via-density dependent effective ILD thermal conductivity, the hierarchically varying RMS current stress based on SPICE simulations, and the thermal resistance of flip-chip package. It is shown that even after considering densely embedded vias, the interconnect temperature is expected to increase significantly with scaling, due to increasing surface and grain boundary contributions to metal resistivity and decreasing ILD thermal conductivity.
Fast and highly parallelizable phrase table for statistical machine translation

Speed of access is a very important property for phrase tables in phrase based statistical machine translation as they are queried many times per sentence. In this paper we present a new standalone phrase table, optimized for query speed and memory locality. The phrase table is cache free and can optionally incorporate a reordering table within. We are able to achieve two times faster decoding by using our phrase table in the Moses decoder in place of the current state-of-the-art phrase table solution without sacriﬁcing translation quality. Using a new, experimental version of Moses we are able to achieve 10 times faster decoding using our novel phrase table.
Joint Array and Spatial Sparsity Based Optimisation for DoA Estimation

Traditional spatial sparse techniques for DoA estimation are implemented by full arrays. However in practice, it is desirable to use as few sensors as possible to reduce the cost for manufacturing the array or to counter against sensor failure. As a result, joint optimisation of sparse array and spatial sparsity becomes an ideal alternative. In most of existing methods, these two kinds of sparsity are studied separately. This paper proposes a joint model which achieves source detection in a subset of space using partial array sensors. The core idea is to use the weight coefficients obtained in sparse array optimisation to scale the model for the sparse reconstruction based DoA estimation. Compressive sensing based optimisation is used for both steps. The numerical results of DoA estimation for both stationary source and moving source are used to demonstrate the feasibility of this joint model.
Interrogating the motivations of sport for development and peace practitioners

The purpose of this study was to interrogate the motivations of sport for development and peace (SDP) practitioners for initially becoming involved in the field and to better understand their involvement over time. Specifically, this study aimed to identify key characteristics and motives of practitioners to gain further understanding of the implementation, execution, and approach of SDP programs and whether or not evangelical rhetoric and neocolonialism were reflected in these approaches. Findings revealed that practitioners were initially motivated by love of sport, the desire to make a difference in the world, and to seek out new experiences. Practitioners stayed involved over time due to fulfillment and satisfaction with their work and the continued desire to make a difference. While many practitioners had moved past evangelical rhetoric and neocolonialism, evangelical rhetoric was still reflective in just less than half of the motivations of practitioners from higher-income countries (HIC) and lower to middle income countries, while 40 percent of participants primarily from HIC reflected a neocolonial approach in their motives. Implications for theory and SDP policy are illuminated.
TRAFFIC SIGN DETECTION AND RECOGNITION IN DRIVER SUPPORT SYSTEM FOR SAFETY PRECAUTION

In this paper, an efficient algorithm for the detection and recognition of traffic signs is presented. The proposed system identifies candidate regions as interest region extraction, which offers strength to variations in lighting conditions and wave equation (WaDe) algorithm. A HOG based Support Vector Machine (SVM) is used to classify the traffic signs. The methodology is established on videos under changing weather conditions and poor illumination. The image preprocessing based on the red color channel enhancement improves the detection rate. The SVM classifier also achieve high classification rate.
Process Control with IEC 61499: Designers' Choices at Different Levels of the Application Hierarchy

The IEC 61499 enables different approaches for application development, and this can undermine the emerging open knowledge economy. Developers typically try to use an approach that resembles their previous programming experience, and this can result in the new features of IEC 61499 to be overlooked. Even when designers are able to turn out working software, the various components are often incompatible because they incorporate diverse design principles. In this research, we look at the different levels of the application hierarchy, in order to understand the design decisions that need to be made. We have organized a laboratory experiment with professional designers and researchers, and we use qualitative research methods to understand the design choices that participants with different backgrounds make.
Automatic Object Extraction Over Multiscale Edge Field for Multimedia Retrieval

In this work, we focus on automatic extraction of object boundaries from Canny edge field for the purpose of content-based indexing and retrieval over image and video databases. A multiscale approach is adopted where each successive scale provides further simplification of the image by removing more details, such as texture and noise, while keeping major edges. At each stage of the simplification, edges are extracted from the image and gathered in a scale-map, over which a perceptual subsegment analysis is performed in order to extract true object boundaries. The analysis is mainly motivated by Gestalt laws and our experimental results suggest a promising performance for main objects extraction, even for images with crowded textural edges and objects with color, texture, and illumination variations. Finally, integrating the whole process as feature extraction module into MUVIS framework allows us to test the mutual performance of the proposed object extraction method and subsequent shape description in the context of multimedia indexing and retrieval. A promising retrieval performance is achieved, and especially in some particular examples, the experimental results show that the proposed method presents such a retrieval performance that cannot be achieved by using other features such as color or texture
Evaluation of the Conventional vs. Ancient Computation Methodology for Energy Efficient Arithmetic Architecture

VLSI design techniques are the key to re-engineering the digital gadgets of any kind which are needed to be operated with lower power to ensure a longer backup time. Power reduction in Arithmetic Logic Unit (ALU) is needed for this requirement. Multipliers and adders are the most important structures which use a larger fraction of power in such arithmetic units. This paper analyses the use of an ancient (or Vedic) mathematical approach for building an ALU. Validation for the low power operation of the circuit is made by designing a conventional CMOS counterpart whose power is compared with our ancient arithmetic design. A 4x4 multiplier based on the Vedic and Conventional methods have been designed using SPICE simulator. Simulation results depict the Vedic design incurring 29% of reduced average power.
Temporal trends in cause of death among Swedish and US men with prostate cancer.

BACKGROUND A growing proportion of men diagnosed with localized prostate cancer detected through prostate-specific antigen testing are dying from causes other than prostate cancer. Temporal trends in specific causes of death among prostate cancer patients have not been well described. METHODS We analyzed causes of death among all incident prostate cancer cases recorded in the nationwide Swedish Cancer Registry (1961-2008; n = 210 112) and in the US Surveillance, Epidemiology, and End Results Program (1973-2008; n = 490 341). We calculated the cumulative incidence of death due to seven selected causes that accounted for more than 80% of the reported deaths (including ischemic heart disease and non-prostate cancer) and analyzed mortality trends by calendar year and age at diagnosis and length of follow-up. RESULTS During follow-up through 2008, prostate cancer accounted for 52% of all reported deaths in Sweden and 30% of reported deaths in the United States among men with prostate cancer; however, only 35% of Swedish men and 16% of US men diagnosed with prostate cancer died from this disease. In both populations, the cumulative incidence of prostate cancer-specific death declined during follow-up, while the cumulative incidences of death from ischemic heart disease and non-prostate cancer remained constant. The 5-year cumulative incidence of death from prostate cancer among all men was 29% in Sweden and 11% in the United States. CONCLUSIONS In Sweden and the United States, men diagnosed with prostate cancer are less likely to die from prostate cancer than from another cause. Because many of these other causes of death are preventable through changes in lifestyle, interventions that target lifestyle factors should be integrated into prostate cancer management.