Miracle-dz/UniFAR-FTUs huggingface dataset:
Time-Efficient Layer-2 Auto-Configuration for Cognitive Radios

Cognitive radios CR have the capability to dynamically adapt to local spectrum availability. In a network comprised of CR-enabled devices, layerauto-configuration involves determining a common set of channels also referred to as the global channel set to facilitate communication among participating nodes. This is a unique challenge as nodes in the CR network are unaware of who their neighbors are, and also, the channels on which they can communicate among themselves. In this paper, we propose a time-efficient distributed algorithm for layerautoconfiguration for a CR network. Our algorithm finds the global channel set in timeslots, where is the maximum number of nodes deployed, is the maximum number of available channels for communication and is the diameter of the network. Assuming all nodes are aware of and , we present both diameter-aware and diameter-unaware versions of the algorithm. For highly sparse networks like linear chain topology where , with ! and #"! , the diameteraware configuration protocol terminates within "%$'&)(+*-,/. 0$ and the diameter-unaware version terminates within $'& ('*-,/. 0$ .
Content-based and Graph-based Tag Suggestion

Social tagging is a popular and convenient way to organize information. Automatic tag suggestion can ease the user's tagging activity. In this paper, we exam both content-based and graph-based methods for tag suggestion using the BibSonomy dataset, and describe our methods for ECML/PKDD Discovery Challenge 2009 submissions. In content-based tag suggestion, we propose a fast yet accurate method named Feature-Driven Tagging. In graph-based tag suggestion, we apply DiffusionRank to solve the problem, and get a better result than current state-of-the-art methods in cross-validation.
Cloning and expression of the VHDL receptor from fat body of the corn ear worm, Helicoverpa zea

Abstract In Noctuids, storage proteins are taken up into fat body by receptor-mediated endocytosis. These include arylphorin and a second, structurally unrelated very high-density lipoprotein (VHDL). Previously, we have isolated a single storage protein receptor from the corn earworm, Helicoverpa zea, which binds both VHDL and arylphorin. The receptor protein is a basic, N-terminally blocked, ∼80 kDa protein that is associated with fat body membranes. Microsequencing of proteolytic fragments of the isolated receptor protein revealed internal sequences that were used to clone the complete cDNA of the VHDL receptor by 3′ and 5′ RACE techniques. The receptor protein, when expressed in vitro via a suitable insect expression vector, reacted with antibodies against the native VHDL receptor and bound strongly to its ligand VHDL, thus confirming that the cloned cDNA represents indeed the previously purified VHDL receptor. The receptor protein and a second, similar protein also found associated with the fat body membrane show considerable homology to putative basic juvenile hormone suppressible proteins cloned previously from other Noctuid species. Sequence analysis revealed that the receptor is likely a peripheral membrane protein that may mediate the selective uptake of VHDL. BJHSP basic juvenile hormone suppressible protein FITC fluorescein isothiocyanate HRP horseraddish peroxidase RACE rapid amplification of cDNA ends VHDL very high density lipoprotein
The research of the regional pollutant concentration visualization based on the particles

In this paper, through the analysis of regional air pollutant concentration data in spatial area, using particle system to model and render the air pollutant concentration in the region at different height levels. We establish the corresponding relationship between pollutant concentration of a grid and the particle radius, and use different scattering models to render the particles, the results show that the rendering of the translucent matter in spatial region has better visual effect when the method is used.
GTD-POP : Bridging the Gap betweenSoundness and E ciency in Practical

This paper presents GTD-POP, a planning methodology based on the Generate, Test and Debug paradigm. GTD-POP's goal is to achieve a compromise between planning eeciency and soundness by using associ-ational knowledge to guide its search for interaction checks in a partially-ordered plan. This paper describes the GTD-POP and discusses issues involved in evaluating the behavior of practical planners.
Statistical Model-Based Sensor Diagnostics for Automation Systems

Abstract A method for the automatic detection of abnormal sensor values in automation systems is described. The method is based on statistical generative models of sensor behavior. A model of normal sensor behavior is automatically constructed. Model parameters are optimized using an on-line maximum-likelihood algorithm. Incoming sensor values are then compared to the model, and an alarm is generated when the sensor value has a low probability under the model. Model parameters are continuously adapted on-line. The system automatically adapts to changing conditions and sensor drift, as well as detecting isolated abnormal sensor values.
Perception of emotions from crowd dynamics

Perceiving crowd emotions and understand the situation is vital to control the situations in surveillance applications. This paper introduces the evolution of methods for crowd emotion perception based on bio-inspired probabilistic models. The emotions have been perceived both in an offline and online manner from the crowd. We focus on the perception of emotion from crowd behavior and dynamics. The paper explains few probabilistic algorithms and compares these for detection of emotion of crowds and proposes a probabilistic modelling approach which is trained on data to perceive the emotions of the crowd in an area under surveillance. Emotions are defined as evolving dynamic patterns arising due to interaction of people in an environment with their relationships to the past interaction patterns. Camera sensors are used to track the motion of the individuals within a crowd scenario under observation. The data mining techniques are used to distinguish between different behaviors and events into positive and negative emotions. The results have been evaluated using simulated data from a proposed office environment.
Internet Addiction and Depression Levels in Erciyes University Students

Internet addiction and depression levels in Erciyes University students Objective: The study was carried out to determine Internet addiction and depression levels among university students, the effects of some socio-demographic factors on these levels, and association between Internet addiction and depressive symptom levels. Method: This descriptive study was performed in Schools of Medicine, Engineering, and Economics and Administrative Sciences Erciyes University in 2015. A total of 1288 students were included in the study. Data were collected via socio-demographic questionnaire of 27 questions, Internet Addiction Scale (IAS), and Beck Depression Inventory (BDI). The students were visited in their classrooms and informed about the study by the researchers. The questionnaires and scales were collected after being filled in by the students, under the supervision of the researchers. Results: Mean IAS and BDI scores were calculated as 12.1±9.1 and 27.7±14.7, respectively. Depressive symptoms were found in 26.4% of the students whereas, Internet addiction in 0.2% and limited symptoms of Internet addiction in 7.5%. Mean IAS score was found higher among men, whereas mean BDI score was higher among women. A significant correlation was found between IAS and BDI scores (r=0.325, p<0.001). Conclusion: Approximately 8% of the students are under the risk of Internet addiction. There is a significant association between Internet addiction and depression scores. But, it is not clear which of these two factors affects the other.
Making an Embedded DBMS JIT-friendly

While database management systems (DBMSs) are highly optimized, interactions across the boundary between the programming language (PL) and the DBMS are costly, even for in-process embedded DBMSs. In this paper, we show that programs that interact with the popular embedded DBMS SQLite can be significantly optimized - by a factor of 3.4 in our benchmarks - by inlining across the PL / DBMS boundary. We achieved this speed-up by replacing parts of SQLite's C interpreter with RPython code and composing the resulting meta-tracing virtual machine (VM) - called SQPyte - with the PyPy VM. SQPyte does not compromise stand-alone SQL performance and is 2.2% faster than SQLite on the widely used TPC-H benchmark suite.
3D Video Coding Using Just Noticeable Depth Difference Based on H.265/HEVC

Just noticeable depth difference (JNDD) model represents the depth sensitivity of human visual system (HVS). Human eyes have different depth sensitivity for different distance and binocular disparity information. The JNDD model indicates that human can easily perceive the depth change when an object is close to the screen plane, but less sensitive to a distant object. If the depth information is below the JNDD threshold, there are visual redundancies, and we can process a video with bigger compression ratio. In this paper, we apply Silva's JNDD model to H.265/HEVC for the color image coding. We propose a perception region division algorithm (PRDA), through which we divide the depth map into four regions with different depth. Then, the quantization parameter is adjusted depending on a visual perception threshold. Experimental results show that our color image coding scheme improves the image quality without increasing bit rates.
Accounting for Trends in Productivity and R&D: A Schumpeterian Critique of Semi‐Endogenous Growth Theory

This paper argues that long-run trends in R&D and TFP are more supportive of fully endogenous "Schumpeterian" growth theory than they are of semi-endogenous growth theory. The distinctive prediction of semi-endogenous theory that sustained TFP growth requires sustained growth of R&D input is not supported by co-integration tests and forecasting exercises, as TFP growth has been stationary even though the growth rate of R&D input has fallen three-fold since the early 1950s. In contrast, the prediction of Schumpeterian theory that sustained TFP growth requires a sustained fraction of GDP to be spent on R&D is not contradicted by similar tests. Copyright 2007 The Ohio State University.
Modular dual active bridge converter architecture

This paper is focused on the assessment of a modular architecture based on the Dual Active Bridge (DAB) converter in input series, output parallel (ISOP) connection. Previous works have dealt with modeling and control techniques to ensure a proper voltage and power sharing among the modules. In this paper an experimental evaluation of the behavior of the DAB in ISOP connection is carried out in order to validate the previously proposed models.
Applying design-based research for developing virtual reality training in the South African mining industry

Design research is a maturing research paradigm in a number of disciplines. Design-based research is the educational technology form of design research. This paper explains design-based research (DBR) and its features and principles. After a brief overview of other research designs of the design-and-development genre, we present a new synthesised DBR model, which was applied in the context of developing and evaluating virtual reality safety training for the South African mining industry. The cycles and iterative steps of the model functioned effectively in supporting and representing the process flow of the research, which moved from a complex real-world problem to dual outcomes, namely a practical real-world solution in the form of two virtual reality training systems and a contribution to documented theory in the form of an evaluation framework.
Test data compression for system-on-a-chip using Golomb codes

We present a new test data compression method and decompression architecture based on Golomb codes. The proposed method is especially suitable for encoding precomputed test sets for embedded cores in a system-on-a-chip (SOC). The major advantages of Golomb codes include very high compression, analytically predictable compression results, and a low-cost and scalable on-chip decoder. In addition, the novel interleaving decompression architecture allows multiple cores in an SOC to be tested concurrently using a single ATE I/O channel. We demonstrate the effectiveness of the proposed approach by applying it to the ISCAS benchmark circuits and to two industrial production circuits. We also use analytical and experimental means to highlight the superiority of Golomb codes over run-length codes.
Next Generation of Journey Planner in a Smart City

Journey planning is the key to an efficient and sustainable transportation system in a smart city. A good journey planner is expected to help commuters travel safely, comfortably and quickly, as well as keep the whole transportation network running efficiently. In modern cities, it should be able to combinea wide range of private and public transport modes, and more importantly, react to real-time events that are impactful on the topology of the transport network. In this paper, we present ourmulti-modal journey planner, JPlanner developed for the cityof Singapore. JPlanner leverages on more comprehensive urbandata, i.e., traffic network data and real-time traffic speed data, aiming to provide more accurate and effective recommendations to commuters. With respect to functionality, JPlanner supports the combination of multiple transport modes, such as "Park and Ride" for the switch between private car driving and public transport riding. Other travel modes supported by JPlanner include walking, cycling and taxi. We highlight that the key technology enabling the accurate journey planning in JPlanner is the Speed Fusion, which infers real-time traffic speed by fusing different data sources. Finally we use a case study to compare the journey recommendation results between JPlanner and the other two popular journey planners to demonstrate the advantages of our system.
Recognition versus Recall as Measures of Television Commercial Forgetting

The authors report the second in a series of experiments on recognition as a dependent variable in the study of learning and forgetting of television commercials. They investigate the impact of time since exposure, commercial length, and commercial repetition on recognition and unaided recall scores. The results indicate that recognition scores are not indiscriminately high, as commonly is argued, and that they do decline with time, contrary to what often is assumed. The data, in fact, show that recognition scores are more sensitive and more discriminating than, and covary with, unaided recall scores. The evidence indicates they warrant more consideration by advertisers.
Real-time three-dimensional echocardiographic left ventricular systolic assessment: side-by-side comparison with 64-slice multi-detector cardiac computed tomography.

AIMS To investigate by real-time 3D echocardiography (RT3DE) and cardiac computed tomography (CCT) the analysis of left ventricle ejection fraction (LVEF) and volumes. METHODS AND RESULTS A total of 67 patients (37 males, 55 +/- 11 years) were studied prospectively by RT3DE and by 64-slice CCT. RT3DE data: LVEF ranged from 30 to 78.6% (63.1 +/- 7.33); left ventricular end-diastolic volume (LVEDV) from 44.1 to 210 (104.9 +/- 29.7) mL; left ventricular end-systolic volume (LVESV) from 11.4 to 149 ( 38.9 +/- 19.3) mL. CCT data: LVEF ranged from 28 to 86% (66 +/- 8.4); LVEDV from 51 to 212 (110.3 +/- 31.2) mL; LVESV from 7 to 152 (38.2 +/- 19.2) mL. Correlations relative to RT3DE and CCT were: LVEF (r: 0.79, P < 0.0001); LVEDV (r: 0.82, P < 0.0001); and LVESV (r: 0.91, P < 0.0001). CONCLUSION It was observed adequate correlation between RT3DE and CCT ventricular systolic function and geometry assessment.
Towards a Multipath TCP Aware Load Balancer

Multipath TCP has been recently introduced in order to allow a better resource consumption and user quality-of-experience. This is achieved by allowing a connection between two hosts through multiple subflows. However, with the rise of middleboxes and inherent Internet ossification, the large-scale deployment of this TCP extension is difficult. In particular, a load balancer at the entry point of a data center may forward subflows to different servers, cancelling so the advantages of Multipath TCP. In this paper, we introduce MpLb, a Multipath TCP aware load balancer that fixes this particular issue without any modification to the Multipath TCP protocol itself. We demonstrate advantages of MpLb through a proof-of-concept.
Research on fast music classification based on SVM in compressed domain

In this paper we make a research on svm algorithm used for music genre classification in mp3 compressed domain and analyze parameters combinationpsilas impact on music classification accuracy, number of support vectors and classification time. Based on the analysis, we propose a new method how to realize fast and effective music classification by svm in compressed domain. This method greatly improves the speed while the classification accuracy is guaranteed.
Imaging inverse problem using sparse representation with adaptive dictionary learning

Sparse representation is one of the powerful emerging statistical techniques for modeling images. This representation approximates the image as a combination of the codewords within a dictionary which is over complete. Recent years have seen a tremendous growth in the field of sparse representation. Here a method is proposed for image inversing by using iterative deblurring based on sparse representation of an image which is uniformly blurred. The key idea behind this methodology is the sparseness of natural images in some domain. The quality of recovered image majorly depends on the domain or the dictionaries that are used to represent it. In this paper, the K-SVD algorithm is used to train the group of codewords from a set of quality natural image patches. For each of the local patch within the blurred image, the best suited sub-dictionary from the trained dictionary data base is selected. In addition, a smoothness regularization constraint is added that prevents the reblurring of the image edges. For numerical stability the sparsity weight is adaptively computed which also improves the reconstructed image quality. Comparative study on some of the existing restoration algorithm proves the proposed method outperforms them all.
Atorvastatin Therapy during the Peri-Infarct Period Attenuates Left Ventricular Dysfunction and Remodeling after Myocardial Infarction

Although statins impart a number of cardiovascular benefits, whether statin therapy during the peri-infarct period improves subsequent myocardial structure and function remains unclear. Thus, we evaluated the effects of atorvastatin on cardiac function, remodeling, fibrosis, and apoptosis after myocardial infarction (MI). Two groups of rats were subjected to permanent coronary occlusion. Group II (n = 14) received oral atorvastatin (10 mg/kg/d) daily for 3 wk before and 4 wk after MI, while group I (n = 12) received equivalent doses of vehicle. Infarct size (Masson's trichrome-stained sections) was similar in both groups. Compared with group I, echocardiographic left ventricular ejection fraction (LVEF) and fractional area change (FAC) were higher while LV end-diastolic volume (LVEDV) and LV end-systolic and end-diastolic diameters (LVESD and LVEDD) were lower in treated rats. Hemodynamically, atorvastatin-treated rats exhibited significantly higher dP/dtmax, end-systolic elastance (Ees), and preload recruitable stroke work (PRSW) and lower LV end-diastolic pressure (LVEDP). Morphometrically, infarct wall thickness was greater in treated rats. The improvement of LV function by atorvastatin was associated with a decrease in hydroxyproline content and in the number of apoptotic cardiomyocyte nuclei. We conclude that atorvastatin therapy during the peri-infarct period significantly improves LV function and limits adverse LV remodeling following MI independent of a reduction in infarct size. These salubrious effects may be due in part to a decrease in myocardial fibrosis and apoptosis.
Melanoma diagnosis and classification web center system

In this paper, the development of a new Internet information system for analyzing and classifying melanocytic lesions is briefly outlined. System includes two main modules. The first module improves the analyses of datasets based on calculating the value of the TDS-parameter (Braun-Falco et al., 1990 and Hippe et al., 2003). Calculations are based on the classical ABCD rule and also on the optimized ABCD formula (Alvarez et al., 2003). A third method of classification is based on quasi-optimal decision trees (Quinlan, 1993). The two last implemented methods of classification are based on semantic networks and genetic dichotomization. The second module - a generator of simulated images of melanocytic lesion, enables us to generate the exhaustive number of simulated images, corresponding to symptoms contained in a given lesion, originally described by a single textual vector (Hippe and Piatek, 2005). Presented Web-service provides an early, non-invasive diagnosis of mentioned lesions. This system is available via Internet at the Website http://www.melanoma. pl.
Purdue e-Pubs Purdue e-Pubs

Misalignment between the color planes used to print color images creates undesirable artifacts in printed images. Color trapping is a technique used to diminish these artifacts. It consists of creating small overlaps between the color planes, either at the page description language level or the rasterized image level. Existing color trapping algorithms for rasterized images trap pixels independently. Once a pixel is trapped, the next pixel is processed without making use of the information already acquired. We propose a more eﬃcient strategy which makes use of this information. Our strategy is based on the observation of some important properties of color edges. Combined with any existing algorithm for trapping rasterized images, this strategy signiﬁcantly reduces its complexity. We implement this strategy in combination with a previously proposed color trapping algorithm (WBTA08). Our numerical tests indicate an average reduction of close to 38% in the combined number of multiplications, additions, and “if” statements required to trap a page, as compared with WBTA08 by itself.