Miracle-dz/UniFAR-FTUs huggingface dataset:
GFCM: A gossip-based fuzzy C-means algorithm

In real-world networks, large amounts of data are distributed among nodes. Clustering is a useful method for analyzing large data sets and the Fuzzy C-Means (FCM) algorithm is one of the most popular methods for fuzzy clustering. In this paper, we propose GFCM, a gossip-based fuzzy C-means algorithm, for collective discovery of a clustering model from data residing at individual data sites. The proposed algorithm consists of local and collaborative phases. Nodes continuously collaborate with each other to maintain a summarized view of the data set, and to find the correct fuzzy clustering model for their local data. Gossiping is used as a robust method for communication between nodes. The experimental results show that GFCM can detect fuzzy clusters efficiently, with bounded communication costs. Its performance is also compared the recently proposed CFCM algorithm.
Modelling and smoothing parameter estimation with multiple quadratic penalties

Penalized likelihood methods provide a range of practical modelling tools, including spline smoothing, generalized additive models and variants of ridge regression. Selecting the correct weights for penalties is a critical part of using these methods and in the single‐penalty case the analyst has several well‐founded techniques to choose from. However, many modelling problems suggest a formulation employing multiple penalties, and here general methodology is lacking. A wide family of models with multiple penalties can be fitted to data by iterative solution of the generalized ridge regression problem minimize ||W1/2 (Xp−y) ||2ρ+Σi=1m θip′Sip (p is a parameter vector, X a design matrix, Si a non‐negative definite coefficient matrix defining the ith penalty with associated smoothing parameter θi, W a diagonal weight matrix, y a vector of data or pseudodata and ρ an ‘overall’ smoothing parameter included for computational efficiency). This paper shows how smoothing parameter selection can be performed efficiently by applying generalized cross‐validation to this problem and how this allows non‐linear, generalized linear and linear models to be fitted using multiple penalties, substantially increasing the scope of penalized modelling methods. Examples of non‐linear modelling, generalized additive modelling and anisotropic smoothing are given.
VeggieVision: a produce recognition system

The authors present an automatic product 1D system ("VeggieVision"), intended to ease the produce checkout process. The system consists of an integrated scale and imaging system with a user-friendly interface. When a produce item is placed on the scale, an image is taken. A variety of features, color, texture (shape, density), are then extracted. These features are compared to stored "signatures" which were obtained by prior system training (either on-line or off-line). Depending on the certainty of the classification, the final decision is made either by the system or by a human from a number of choices selected by the system. Over 95% of the time, the correct produce classification is in the top four choices.
CubeLSI: An effective and efficient method for searching resources in social tagging systems

In a social tagging system, resources (such as photos, video and web pages) are associated with tags. These tags allow the resources to be effectively searched through tag-based keyword matching using traditional IR techniques. We note that in many such systems, tags of a resource are often assigned by a diverse audience of causal users (taggers). This leads to two issues that gravely affect the effectiveness of resource retrieval: (1) Noise: tags are picked from an uncontrolled vocabulary and are assigned by untrained taggers. The tags are thus noisy features in resource retrieval. (2) A multitude of aspects: different taggers focus on different aspects of a resource. Representing a resource using a flattened bag of tags ignores this important diversity of taggers. To improve the effectiveness of resource retrieval in social tagging systems, we propose CubeLSI — a technique that extends traditional LSI to include taggers as another dimension of feature space of resources. We compare CubeLSI against a number of other tag-based retrieval models and show that CubeLSI significantly outperforms the other models in terms of retrieval accuracy. We also prove two interesting theorems that allow CubeLSI to be very efficiently computed despite the much enlarged feature space it employs.
Spiking Neural P Systems: Stronger Normal Forms

Spiking neural P systems are computing devices recently introduced as a bridge between spiking neural nets and membrane computing. Thanks to the rapid research in this field there exists already a series of both theoretical and application studies. In this paper we focus on normal forms of these systems while preserving their computational power. We study combinations of existing normal forms, showing that certain groups of them can be combined without loss of computational power, thus answering partially open problems stated in [8, 9]. We also extend some of the already known normal forms for spiking neural P systems considering determinism and strong acceptance condition. Normal forms can speed-up development and simplify future proofs in this area.
VIRTUAL THERMAL MANIKIN – MATHEMATICAL MODELLING OF HUMAN THERMOREGULATION

Early works on so called segment (compartment) models were based on extremely simplified geometry and covered mainly only passive heat transfer [3,4]. Later developed models were devoted on development of active thermoregulation part, focusing on precise description of changes in: non-shivering thermogenesis (metabolic heat production), perfusion of selected tissues and sweating. The number of segments used was increased as well. Review of segment type models of human heat transfer and thermoregulation is summarized in [5, 6].
Strategies to Promote Student's Autonomous Reading Motivation

Reading English text is challenging for senior high school students, therefore the teacher has to provide effective strategies to motivate the students to read more. This study aims to identify the teacher’s strategies called Independent Study to promote student's autonomous reading motivation. It is a case study using triangulation data involving the English teacher and 27 students of the 12th Grade of SMKN 1 Batu majoring in Hospitality Management. The data were collected from interviews, observations, and questionnaires based on Self-Determination Theory (SDT) and were analyzed both quantitatively and qualitatively. The results pointed out that the teacher applied all of the strategies of SDT teaching dimensions (autonomy support, structure, and involvement) which were effective to encourage students reading motivation. It is proven by the results of two questionnaires: (1) Teacher as Social Context Questionnaire (TASC) indicating that students' perceptions on teaching dimensions were good and (2) Self-Regulation Questionnaire (SRQ) indicating that the students had both extrinsic (external and identified regulation) and intrinsic reading motivation.
Random Sampling from Database Files: A Survey

In this paper we survey known results on algorithms, data structures, and some applications of random sampling from databases. We first discuss various reasons for sampling from databases, and for inclusion of sampling as a DBMS operator. We consider basic sampling algorithms, sampling from trees, sampling from hash tables, and auxiliary memory resident index information to facilitate sampling.
Leaf-Level Gas Exchange and Foliar Chemistry of Common Old-Field Species Responding to Warming and Precipitation Treatments

We investigated the shifts in plant carbon (C) and water dynamics by measuring rates of photosynthesis, transpiration, and instantaneous water use efficiency (WUE) in three common species of “old-field” plants—two C3 forb species (Plantago lanceolata and Taraxacum officinale) and one C3 grass species (Elymus repens)—under 12 experimentally altered temperature and precipitation regimes at the Boston Area Climate Experiment (BACE) in Waltham, Massachusetts. We also measured shifts in foliar C and nitrogen (N) content to determine possible changes in plant C/nutrient balance. We hypothesized that the warming treatment would cause an increase in photosynthesis rates, unless water was limiting; therefore, we expected an interactive effect of warming and precipitation treatments. We found that warming and drought reduced leaf-level photosynthesis most dramatically when environmental or seasonal conditions produced soils that were already dry. In general, the plants transpired fastest when soils were wet and slowest when soils were dry. Drought treatments increased WUE relative to plants in the ambient and wet treatments but only during the driest and warmest background conditions. Leaf N concentration increased with warming, thereby indicating that future warming may cause some plants to take up more soil N and/or allocate more N to their leaves, possibly as consequences of increased nutrient availability. There were no significant interactive effects of the warming and precipitation treatments together across all seasons, indicating that responses were not synergistic or ameliorative.
The dietetics and naturopathy professions: perceptions of role boundaries

ABSTRACT Dietary counselling and management form core parts of both dietetic and naturopathic practice. However, each profession is unique with its own philosophies and requirements for membership. The neo-Weberian ‘sociology of professions’ provided the framework for the thematic analysis of in-depth interviews with ten leading clinicians. This study aimed to explore the perception of roles and role boundaries between practising naturopaths and dietitians using a specific example: food intolerances expressing as functional bowel disorders (FBDs). The similarities and differences in the ways dietitians and naturopaths diagnose and treat FBDs were examined. Three main themes were apparent (i) patient-centred care, (ii) evidence-based practice, and (iii) perceptions of the ‘other’ profession. Far more similarities than differences between the two professions were evident: individualised, holistic treatments, use of referral networks and evidence-based medicine formed core components of both. The main difference centred on naturopaths’ use of both traditional knowledge and scientific evidence during diagnosis and the formulation of treatment plans, including prescribing ingested medicines. Both groups deployed marked exclusionary strategies to protect their professional boundaries, including the use of discursive strategies to discredit each other, reinforced by commonly held misconceptions about the ‘other’ profession. Dietitians also used a credentialist strategy to elevate and protect their status.
A Summer Computing Camp Using ChainReaction and jABC

We have been running summer computing camps at the University of Limerick, Ireland, since 2010. The three-day camps are offered to boys and girls aged 14 and up. During the summer of 2015 we ran two computing camps where we focused on strategy development for the ChainReaction board game with the jABC workflow modelling framework for the first time. In this paper we describe the freely available software packages and the camp programme that we designed around them.
Impact of nutritional status on length of stay and hospital costs among patients admitted to a tertiary care hospital in Thailand.

BACKGROUND AND OBJECTIVES Malnutrition has high prevalence among hospitalized patients but goes unrecognized in many patients. Early detection of malnutrition using an effective screening tool is required. This study aimed to examine the effects of nutritional status determined by the Nutrition Alert Form (NAF) and its individual sections on length of stay (LOS) and hospital costs in hospitalized patients, to investigate their associated factors, and to determine hospital malnutrition prevalence. METHODS AND STUDY DESIGN This retrospective cohort study enrolled 2,906 hospitalized patients aged >=15 years in Ramathibodi Hospital between January and September 2016. At admission, nutritional status was screened using NAF. Nutrition status was defined as: NAF-A (normal/mild malnutrition; scores of 0-5), NAF-B (moderate malnutrition; 6-10), and NAF-C (severe malnutrition; >=11). Information regarding LOS and hospital costs during patients' hospitalization was also collected. RESULTS The prevalence of malnutrition was 15.3%. After adjusting for age, sex and primary diagnosis, we found significantly longer LOS and higher hospital costs among those with NAF-B and NAF-C, in comparison with patients having NAF-A. The highest increase in LOS was in male patients aged >=60 years with NAF-C. The highest increase in LOS and hospital costs was associated with higher scores for functional capacity. CONCLUSIONS Higher levels of malnutrition screened using the NAF were significantly associated with longer LOS and higher hospital costs. Older adult patients had the highest risk of being malnourished and developing negative consequences. A prospective study of nutritional support by a nutrition care team is underway.
Designment of E-R model based on RDF(S)

Based on the vast domain resources of RDF(S) on the web and SPARQL’s powerful query ability, this article presents a new method of designment of E-R model. The steps for this design are: (1) Formulating SPARQL rules (including resource query rules and schema query rules) by the analysis of RDF(S)’s structure. (2) Parsing the optimal resource obtained through the query sentences. (3) Completing the designment by taking advantages of the translation from RDF(S) model to entity-relationship model in accordance with the content queried. The results indicate that, the designment of E-R model based on RDF(S) could restore user real requirements of great possibilities and help database designer to complete design in a strange area.
The Mass Assembly Histories of Galaxies of Various Morphologies in the GOODS Fields

We present an analysis of the growth of stellar mass with cosmic time partitioned according to galaxy morphology. Using a well-defined catalog of 2150 galaxies based, in part, on archival data in the Great Observatories Origins Deep Survey (GOODS) fields, we assign morphological types in three broad classes (ellipticals, spirals, peculiar/irregulars) to a limit of zAB = 22.5 and make the resulting catalog publicly available. Utilizing 893 spectroscopic redshifts, supplemented by 1013 determined photometrically, we combine optical photometry from the GOODS catalog and deep Ks-band imaging to assign stellar masses to each galaxy in our sample. We find little evolution in the form of the galaxy stellar mass function from z ~ 1 to z = 0, especially at the high-mass end where our results are most robust. Although the population of massive galaxies is relatively well established at z ~ 1, its morphological mix continues to change, with an increasing proportion of early-type galaxies at later times. By constructing type-dependent stellar mass functions, we show that in each of three redshift intervals, E/S0 galaxies dominate the higher mass population, while spirals are favored at lower masses. This transition occurs at a stellar mass of (2-3) × 1010 M☉ at z ~ 0.3 (similar to local studies), but there is evidence that the relevant mass scale moves to higher mass at earlier epochs. Such evolution may represent the morphological extension of the "downsizing" phenomenon, in which the most massive galaxies stop forming stars first, with lower mass galaxies becoming quiescent later. We infer that more massive galaxies evolve into spheroidal systems at earlier times, and that this morphological transformation may only be completed 1-2 Gyr after the galaxies emerge from their active star-forming phase. We discuss several lines of evidence suggesting that merging may play a key role in generating this pattern of evolution.
cognate priming 1 Orthography plays a critical role in cognate priming : Evidence from French / English and Arabic / French cognates Running head : Cognate priming

A series of three experiments was carried out in order to better characterize the representations that support long-term cognate priming. In Experiment 1, robust priming was obtained between orthographically similar French/English cognates in bilingual speakers, and this priming was mediated, in part, by orthographic codes given that priming for these items was dramatically reduced following a study-test modality shift. In Experiment 2, no priming was obtained between the same set of French/English cognates in monolingual English speakers. Finally, in Experiment 3, priming for orthographically unrelated Arabic/French cognates was no larger than cross-modal priming, suggesting that these effects were mediated by non-orthographic representations. The role of orthography in supporting cognate priming is discussed.
Well-being and intended early retirement among older European workers: does job satisfaction matter? A 6-Wave follow-up

In recent years, population aging has received great attention in developed countries given the social challenges that it entails. At this regard, it is well documented that this collective is associated with fewer resources (both physical and economic). Furthermore, ageing societies incite an increase in the inactive population and so, threaten the financial viability of the social protection systems. This study investigates the effects of different factors on early retirement intentions among European workers aged 50-65 using the latest available data (waves 1-6: 2004-2015) from the Survey of Health, Ageing and Retirement in Europe (SHARE). We shed new light on this causal relationship controlling for job characteristics and well-being indicators. Our empirical results based on logistics regressions suggest that people that is satisfied with their jobs (OR = 0.61; 95 % C.I. 0.53, 0.71), with very high appreciation of their quality of life (OR = 0.56; 95 % C.I. 0.49, 0.64) or with good health (OR = 0.55; 95 % C.I. 0.47, 0.65) would have less intentions of early retirement, that is, decreased odds of work exit. Besides, social-environment would matter.
Spatial Degradation of Classified Satellite Images

One of the most common uses of classified satellite images is mapping land cover alterations via change detection. If images for two different dates are not available from the same sensor, one has to use two sensors with different resolutions, and images or maps must be either upscaled or downscaled. We present a study based on two landcover maps produced for the agglomeration of Geneva, Switzerland: one derived from orthophotos at 0.25m resolution and one from a SPOT image at 5m. Four quantitative methods ("direct", "nearest neighbour", "majority" and "statistical") have been tested to degrade the higher-resolution map to a 5m resolution with a minimum loss of information, in order to make both maps comparable. Upscaled maps have been compared with the original (a) qualitatively by visual examination, and (b) quantitatively by computing Kappa coefficients.Special attention was given to the preservation of thin linear features, such as roads. Visual inspection showed that the majority and statistical methods are unable to preserve thin linear features.With the exception of the direct method,which is the least favourable one, the others perform almost equally well according to the statistical analysis. Overall, the nearest neighbour approach yields the smallest loss of information, with Kappa values up to 92%.
Finding Thresholds for Image SegmentationTheo

Segmentation methods for images often have cost functions which evaluate the (dis)similarity between pixels or segments. Thresholds on cost values are then used to decide whether or not to grow, join or split segments. The results for a given image critically depend on the selection of the threshold values. In remote sensing, a too low threshold will split up regions of constant ground cover and a too high threshold will join adjacent regions of diierent ground cover. Optimal thresholds can be determined using diierent classes of methods: generating cost value distributions from the original image. obtaining statistical distributions from segmented images. comparing a "true" segmentation with the results of segmentation using a range of thresholds. A so-called "true" segmentation can be derived from human expert segmentations or from maps obtained by ground surveys or segmentation of higher resolution images. Several methods for threshold determination are described for a hybrid segmentation method developed by us. Measures are described for comparison of two segmentations. Results are evaluated using several real and artiicially generated images.
Polyp detection in CT colonography based on shape characteristics and Kullback-Leibler divergence

As an alternative procedure to the current methods which consider only the mean values of shape features to globally characterize a candidate shape polyps, probability density functions (PDFs) of some feature variables constructed based on Gaussian and mean curvatures are used to characterize the global shape of a candidate lesion. The decision on whether or not this candidate lesion is a polyp is made by comparing the density functions of the considered shape feature variables to reference PDFs of the same variables obtained from a pre- constructed polyp/non polyp data base. The Kullback-Leibler divergence is used as a dissimilarity measure to compare these PDFs and make a decision based on closeness. Experiments carried out on real data are used to illustrate the effectiveness of the proposed method in comparison to existing ones.
Using Kohonen-SOM & K-Means Clustering Techniques to Analyze QoS Parameters of RSVP

— Promise of actually realizing and delivering the unanimously committed quality of service (QoS) is a big challenge, given the explosive growth in usage of real-time based multimedia applications online. The queuing strategies do critically affect the bandwidth allocation of packets while making critical selection for packets to be dropped. This also have an effect on latency. Resource Reservation Protocol (RSVP) in concurrence with weighted fair queuing (WFQ) attempts to accomplish bandwidth reservation with intention to predetermine and guarantee of improved QoS. At peak traffic with impending congestion, this scheme fails to cap different QoS parameters within premeditated limits. We propose an innovative solution by combining priority queuing scheme with RSVP instead of WFQ. Using Kohonen’s Self Organizing Map (SOM) & K-Means clustering techniques as analysis tool, we come across that this strategy allows us to sustain a better quality of service for extremely high precedence real-time video traffic. We are further able to demonstrate that the delegated QoS by this strategy is immune to different firewall implementation schemes, across the network.
4 Imaging Soundscapes : Identifying Cognitive Associations between Auditory and Visual Dimensions

The extent to which we can represent musical information in computers, in a way that matches our mental images, is one of the most intriguing and compelling questions in music research. Leman (1993) distinguishes three kinds of musical representation: 1. Acoustical, i.e. based on the physical properties of sound (e.g., sonograms, spectrograms). 2. Subsymbolic, i.e. based on the known behaviour of the human hearing system and how the human brain processes auditory information (e.g., auditory models). 3. Symbolic, i.e. based on the manipulation of symbols (e.g., Common Music Notation).