Miracle-dz/UniFAR-FTUs huggingface dataset:
RadViz and Identification of Clusters in Multidimensional Data

RadViz visualization makes it possible to map data from n-dimensional space into a plane. The paper reviews those specific properties of this method that are important for identification of clusters in the original multidimensional data. First, there is described an artificial data set which clearly points to a certain drawback of the original RadViz mapping. To resolve the identified problem there are suggested 2 minor modifications of the RadViz algorithm. Finally, it is proved that application of both suggested modifications guarantees that the upper mentioned problem does not re-appear. This claim is experimentally confirmed by a new visualization of the two original data sets using the modified mapping algorithm.
Outlier Detection and Handling for Robust 3-D Active Shape Models Search

This paper presents a new outlier handling method for volumetric segmentation with three-dimensional (3-D) active shape models. The method is based on a shape metric that is invariant to scaling, rotation and translation by using the ratio of interlandmark distances as a local shape dissimilarity measure. Tolerance intervals for the descriptors are calculated from the training samples and used as a statistical tolerance model to infer the validity of the feature points. A replacement point is then suggested for each outlier based on the tolerance model and the position of the valid points. A geometrically weighted fitness measure is introduced for feature point detection, which limits the presence of outliers and improves the convergence of the proposed segmentation framework. The algorithm is immune to the extremity of the outliers and can handle a highly significant presence of erroneous feature points. The practical value of the technique is validated with 3-D magnetic resonance (MR) segmentation tasks of the carotid artery and myocardial borders of the left ventricle
Empirical MIMO capacity of a 2×2 dual-polarized planar antenna array in indoor 60 GHz channels

The channel capacity of a multiple input multiple output (MIMO) system that uses a hybrid beamforming (HBF) mechanism for a 2×2 dual-polarized (DP) planar antenna array (PAA) is studied in this work for indoor 60 GHz channels. On one hand, the DP-PAA can resolve the receiving dead zone problem often seen in single-polarized PAA. On the other hand, the HBF architecture allows us to explore the advantages of spatial multiplexing or beamforming, or even both, in order to overcome the severe power loss problems often encountered from blocking or reflections in indoor 60 GHz radio propagations. Simulation results show that different architectures have advantages at different transmission power. In typical operating conditions of indoor 60 GHz radio, directivity offered by beamforming provides a higher capacity than does the spatial multiplexing provided by multiple baseband processing modules.
Non-destructive Phenotyping of Lettuce Plants in Early Stages of Development with Optical Sensors

Rapid development of plants is important for the production of ‘baby-leaf’ lettuce that is harvested when plants reach the four- to eight-leaf stage of growth. However, environmental factors, such as high or low temperature, or elevated concentrations of salt, inhibit lettuce growth. Therefore, non-destructive evaluations of plants can provide valuable information to breeders and growers. The objective of the present study was to test the feasibility of using non-destructive phenotyping with optical sensors for the evaluations of lettuce plants in early stages of development. We performed the series of experiments to determine if hyperspectral imaging and chlorophyll fluorescence imaging can determine phenotypic changes manifested on lettuce plants subjected to the extreme temperature and salinity stress treatments. Our results indicate that top view optical sensors alone can accurately determine plant size to approximately 7 g fresh weight. Hyperspectral imaging analysis was able to detect changes in the total chlorophyll (RCC) and anthocyanin (RAC) content, while chlorophyll fluorescence imaging revealed photoinhibition and reduction of plant growth caused by the extreme growing temperatures (3 and 39°C) and salinity (100 mM NaCl). Though no significant correlation was found between Fv/Fm and decrease in plant growth due to stress when comparisons were made across multiple accessions, our results indicate that lettuce plants have a high adaptability to both low (3°C) and high (39°C) temperatures, with no permanent damage to photosynthetic apparatus and fast recovery of plants after moving them to the optimal (21°C) temperature. We have also detected a strong relationship between visual rating of the green- and red-leaf color intensity and RCC and RAC, respectively. Differences in RAC among accessions suggest that the selection for intense red color may be easier to perform at somewhat lower than the optimal temperature. This study serves as a proof of concept that optical sensors can be successfully used as tools for breeders when evaluating young lettuce plants. Moreover, we were able to identify the locus for light green leaf color (qLG4), and position this locus on the molecular linkage map of lettuce, which shows that these techniques have sufficient resolution to be used in a genetic context in lettuce.
A Priority-Based Model of Routing

We consider a priority-based selfish routing model, where agents may have different priorities on a link. An agent with a higher priority on a link can traverse it with a smaller delay or cost than an agent with lower priority. This general framework can be used to model a number of different problems. The structural properties that lead to inefficiencies in routing choices appear different in this priority-based model compared to the classical model. In particular, in parallel link networks with nonatomic agents, the price of anarchy is exactly one in the priority-based model; that is, selfish behaviour leads to optimal routings. In contrast, in the standard model the worst possible price of anarchy can be achieved in a simple two-link network. For multi-commodity networks, selfish routing does lead to inefficiencies in the priority-based model. We present tight bounds on the price of anarchy for such networks. Specifically, in the nonatomic case the worst-case price of anarchy is exactly (d + 1) for polynomial latency functions of degree d (hence 4 for linear cost functions). For atomic games, the worst-case price of anarchy is exactly 3+ 2 √ 2 in the weighted case, and exactly 17/3 in the unweighted case. An upper bound of O(2d) is also shown for polynomial cost functions in the atomic case, although this is not tight. Our framework (and results) also generalise to include models similar to congestion games. ACM Classification: F.2. 0, F.2. 2 AMS Classification: 68Q25, 68M10, 90B18
Validation and Comparison of Two Methods to Assess Human Energy Expenditure during Free-Living Activities

Background The measurement of activity energy expenditure (AEE) via accelerometry is the most commonly used objective method for assessing human daily physical activity and has gained increasing importance in the medical, sports and psychological science research in recent years. Objective The purpose of this study was to determine which of the following procedures is more accurate to determine the energy cost during the most common everyday life activities; a single regression or an activity based approach. For this we used a device that utilizes single regression models (GT3X, ActiGraph Manufacturing Technology Inc., FL., USA) and a device using activity-dependent calculation models (move II, movisens GmbH, Karlsruhe, Germany). Material and Methods Nineteen adults (11 male, 8 female; 30.4±9.0 years) wore the activity monitors attached to the waist and a portable indirect calorimeter (IC) as reference measure for AEE while performing several typical daily activities. The accuracy of the two devices for estimating AEE was assessed as the mean differences between their output and the reference and evaluated using Bland-Altman analysis. Results The GT3X overestimated the AEE of walking (GT3X minus reference, 1.26 kcal/min), walking fast (1.72 kcal/min), walking up−/downhill (1.45 kcal/min) and walking upstairs (1.92 kcal/min) and underestimated the AEE of jogging (−1.30 kcal/min) and walking upstairs (−2.46 kcal/min). The errors for move II were smaller than those for GT3X for all activities. The move II overestimated AEE of walking (move II minus reference, 0.21 kcal/min), walking up−/downhill (0.06 kcal/min) and stair walking (upstairs: 0.13 kcal/min; downstairs: 0.29 kcal/min) and underestimated AEE of walking fast (−0.11 kcal/min) and jogging (−0.93 kcal/min). Conclusions Our data suggest that the activity monitor using activity-dependent calculation models is more appropriate for predicting AEE in daily life than the activity monitor using a single regression model.
Algorithm and implementation of the K-best sphere decoding for MIMO detection

K-best Schnorr-Euchner (KSE) decoding algorithm is proposed in this paper to approach near-maximum-likelihood (ML) performance for multiple-input-multiple-output (MIMO) detection. As a low complexity MIMO decoding algorithm, the KSE is shown to be suitable for very large scale integration (VLSI) implementations and be capable of supporting soft outputs. Modified KSE (MKSE) decoding algorithm is further proposed to improve the performance of the soft-output KSE with minor modifications. Moreover, a VLSI architecture is proposed for both algorithms. There are several low complexity and low-power features incorporated in the proposed algorithms and the VLSI architecture. The proposed hard-output KSE decoder and the soft-output MKSE decoder is implemented for 4/spl times/4 16-quadrature amplitude modulation (QAM) MIMO detection in a 0.35-/spl mu/m and a 0.13-/spl mu/m CMOS technology, respectively. The implemented hard-output KSE chip core is 5.76 mm/sup 2/ with 91 K gates. The KSE decoding throughput is up to 53.3 Mb/s with a core power consumption of 626 mW at 100 MHz clock frequency and 2.8 V supply. The implemented soft-output MKSE chip can achieve a decoding throughput of more than 100 Mb/s with a 0.56 mm/sup 2/ core area and 97 K gates. The implementation results show that it is feasible to achieve near-ML performance and high detection throughput for a 4/spl times/4 16-QAM MIMO system using the proposed algorithms and the VLSI architecture with reasonable complexity.
A Critical Examination of Child Protection Initiatives in Sport Contexts

With the broadening of focus on child maltreatment beyond intra-familial settings, there is growing awareness of occurrences of maltreatment within the sport context. Millions of children participate in organized sport annually, and despite a tendency to view sport as a context by which to enhance the overall health and development of children, it is also a context in which children are vulnerable to experiences of maltreatment. The well-documented power ascribed to coaches, the unregulated nature of sport and a “win-at-all-costs” approach contribute to a setting that many propose is conducive to maltreatment. A number of high profile cases of sexual abuse of athletes across several countries in the 1990s prompted sport organizations to respond with the development of child protection measures. This study examined seven child protection in sport initiatives in terms of the extent to which they originated from research, had content that was consistent with scholarly work and were evaluated empirically. The findings indicated that these initiatives were not empirically derived nor evaluated. Recommendations are made to more closely align research with these initiatives in order to protect children and to promote a safe and growth-enhancing experience for young participants in sport.
S104 A New Procedure for the Evaluation of Residual Stresses by the Hole Drilling Method Based on Newton-Raphson Technique

The hole drilling method is one of the most used semi-destructive techniques for residual stress analysis of mechanical parts. In the presence of non-uniform residual stresses, the stress field can be determined from the measured relaxed strains using several methods, but the most used is the so called integral method. This method is characterized by some simplifications that lead to approximate results especially when the residual stress varies abruptly. In this paper a new calculation procedure based on the Newton-Raphson method for the determination of zeroes of functions is presented. THE HOLE DRILLING METHOD The hole drilling method is one of the more used semi-destructive techniques for the analysis of the residual stresses in mechanical components [1-3]. In the case of stresses not uniform in the thickness, a hole of radius equal to R is drilled in various steps, up to the maximum depth zM and the relaxed deformations are recorded and subsequently elaborated to calculate the residual stresses. The relationship between stresses and strains is the following
Improving Encryption Performance Using MapReduce

The advanced and readily available cloud infrastructure has resulted in significantly increased offloading of data to the cloud. In fact, many users have become completely reliant on cloud service providers without regard to the safety of their data. Encryption, the foundation of data protection for reliable and secure cloud environments comes at a high cost as data size increases, presenting an obstacle to provision of big data security. This paper proposes a framework to reduce encryption costs through MapReduce, which can boost parallel processing and parameter tuning. By using MapReduce, encryption performance is enhanced in terms of execution time with minimal usage of system resources. Our experiments demonstrate the performance benefits realized through MapReduce-based parallel encryption computation.
-1 - Part Ii Techniques Project Modelling of the Corrosion of Binary Alloys

Neural networks offer a powerful means to model complex relationships between large numbers of variables. This allows for prediction of future results, as well as being able to illustrate the sensitivity of an output to influencing variables in a manner not possible experimentally. Neural network analysis is appropriate to a wide range of phenomena including welding, creep and fatigue behaviours, and the estimation of transformation times and temperatures. In this work a neural network method was employed to study how the rate of corrosion of Fe-based alloys was influenced by compositional and environmental factors as well as exposure time. The dataset was generated from measurements provided by the National Institute for Materials Science in Japan. Inclusion of sulphur in the alloy was seen to have the greatest impact, even though the concentrations were of the order of 0.001 wt% or less. Exposure of the sample to sun and rain, the level of atmospheric pollution, and the presence of certain other alloying elements were also seen to have important roles, generally in good accordance with the literature.
Turbo packet combining for MIMO-ISI channels with co-channel interference

This work focuses on signal-level packet combining techniques for coded transmission over co-channel interference (CCI)-limited multiple input multiple output (MIMO) channels with intersymbol interference (ISI). A turbo packet combining algorithm that jointly equalizes multiple transmissions using the concept of virtual antennas is proposed. Block error rate (BLER) performance is investigated to show the great potential of the introduced technique for many scenarios.
The Design Concept of U-Guide Ubiquitous Learning System

A ubiquitous learning system enables people to learn at any time, at any place and in any form. In particular, it has the context awareness property to provide learners the right information in the right place and at the right time. In this paper, we introduce the design concept for a ubiquitous learning system, U-Guide (Ubiquitous Guide) System. U-Guide integrates two existing technologies, Ad-hoc Positioning System (APS) and Radio Frequency IDentification (RFID), with three newly developed technologies, Tag Forwarding (TF), Tag-Assisted Positioning (TAP) and Data In-network Cache (DIC) technologies. U-Guide can be realized by off-the-shelf portable devices with wireless communication capability; only few devices are required to be equipped with RFID readers. By those devices and RFID tags attached to smart objects, all devices can locate themselves, perceive the existence of smart objects, and acquire objects’associated data efficiently.
Automated coronary calcification detection and scoring

An automated method for coronary calcification detection from ECG-triggered multi-slice CT data is presented. The method first segments the heart region. In the obtained volume candidate objects are extracted by thresholding. They include coronary calcification, calcium located elsewhere in the heart, for example, in the valves or the myocardium, and other high density structures mostly representing noise and bone. A set of 57 features is calculated for each candidate object. In the feature space objects are classified with a k-NN classifier and feature selection in three consecutive stages. The method is tested on 51 scans of the heart. They contain 320 calcification in the coronary arteries, 291 in the aorta and 62 calcifications in the heart. The system correctly detected 177 calcifications in the coronaries at the expense of 56 false positive objects. On average the method makes 3.8 errors per scan.
Relevance feedback strategies for artistic image collections tagging

This paper provides an analysis on relevance feedback techniques in a multimedia system designed for the interactive exploration and annotation of artistic collections, in particular illuminated manuscripts. The relevance feedback is presented not only as a very effective technique to improve the performance of the system, but also as a clever way to increase the user experience, mixing the interactive surfing through the artistic content with the possibility to gather valuable information from the user, and consequently improving his retrieval satisfaction. We compare a modification of the Mean-Shift Feature Space Warping algorithm, as representative of the standard RF procedures, and a learning-based technique based on transduction, considered in order to overcome some limitation of the previous technique. Experiments are reported regarding the adopted visual features based on covariance matrices.
Xanthohumol from hops prevents hormone-dependent tumourigenesis in vitro and in vivo.

Since the 1990s, interest in health-promoting effects of xanthohumol (XN) has increased constantly. This manuscript will review some of the published literature as well as novel findings on XN. In 2002, we identified XN as a potent cancer chemopreventive agent acting by multiple mechanisms relevant for the prevention of carcinogenesis. Although hops is commonly linked with phytoestrogenic effects, we identified XN as a pure estrogen antagonist. Interestingly, XN may also reduce the generation of estrogens by inhibition of the enzymatic activity of aromatase, which converts testosterone to estrogen. Anti-estrogenic effects of XN (100 mg/kg body weight/day) were confirmed in vivo in an uterotrophy assay with prepubertal rats. In two fertility studies, long-term treatment with XN did not cause any adverse effect on female reproduction and on the development of offspring when given either for four weeks prior to or during mating, gestation and nursing. Novel data indicate that XN (100 mg/kg body weight/day in drinking water) prevents dimethylbenz[a]anthracene (DMBA)-induced mammary carcinogenesis in rats when given nine days prior to and for 16 weeks after the carcinogen. Tumour incidence was not influenced by XN treatment, but XN significantly reduced tumour multiplicity and tumour burden. XN (1000 mg/kg body weight/day injected subcutaneously for 14 days) also significantly reduced the growth of human breast cancer xenotransplants in immune-compromised mice and reduced tumour-induced neovascularization. Overall, these data demonstrate breast cancer preventive efficacy of XN. Multiple mechanisms, including modulation of DMBA metabolism, anti-estrogenic, anti-proliferative and anti-angiogenic activities may account for these effects and are under further investigation.
Reducing structured Big data benchmark cycle time using query performance prediction model

The paradigm of big data demands either extension of existing benchmarks or building new benchmarks to capture the diversity of data and impact of change in data size and/or system size. This has led to increase in cycle time of benchmarking an application which includes multiple workloads executions on different data sizes. This paper addresses the problem of reducing the benchmark cycle time for structured application evaluation on different data sizes. The paper propose an approach of reducing Big data benchmark cycle time using prediction models for estimating SQL query execution time with data growth. The paper also proposes a model which could be used for efficient tuning of benchmark queries before their executions, to speed up the application evaluation process, on different data sizes. The proposed model estimates structured query execution time for large data size by exploiting data value distribution without actually generating high volume data. The model is validated against three lab implementation of real life applications and TPC-H benchmarks.
Visual tracking of object silhouettes

In this paper we propose a new method that addresses the problem of tracking the bitmap (silhouette) of an object in a video under very general conditions. We assume a general target, possibly non rigid, with no prior information except initialization. The target, as well as the background, may change its appearance over time and the camera may move arbitrarily. The proposed algorithm fuses different visual cues by means of a conditional random field. The target's bitmap is estimated every frame by incorporating temporal color similarity, spatial color continuity and spatial motion continuity into an energy function that is minimized via min-cut. The spatial motion continuity is incorporated in the energy function in multiple image resolutions by a novel multi-scale energy term. Experiments demonstrate the robustness of our method and its advantage over other algorithms.