Miracle-dz/UniFAR-FTUs huggingface dataset:
Asynchronous Adaptive Task Allocation

We present a randomized algorithm for asynchronous task allocation, also known as the write-all or do-all problem. Our algorithm has work complexity O(n+k2 log3 k) with high probability, where n the number of tasks and k the number of processes that participate in the computation. Our solution uses O(n) shared memory space that supports atomic test-and-set operations and with high probability each participating process uses O(k) internal memory space. This is the first adaptive solution for the write-all problem that has work n plus some additive term which depends only on the number of participating processes k and not the size of the problem n.
Compression of Image-Based Features

Image-based features are now commonly used to perform matching between objects in a query image and objects in database images. Previous studies have been done to apply these features in a real-time cell-phone-based mobile augmented reality (MAR) to recognize buildings. The database feature sets need to be transmitted from the database to the cell phone. In order to minimize cost associated to this transmission, a compression scheme should be developed. This document investigates the effectiveness of several possible compression algorithms. Initially, principal component analysis (PCA) is applied to maximize the coding gain. The transformed coefficients are quantized using a uniform quantizer and entropy-coded using several known entropy coding schemes. By varying the quantization level, the relationship between achievable bit rate, distortion, and query-to-database image matching rate could be determined. Index Terms – Image-based Features, Data Compression, Mobile Augmented Reality (MAR)
Assuring per-station fairness in multi-rate WLANs: A hybrid approach of contention window control and frame aggregation

This paper deals with fairness among stations (STAs) in multi-rate wireless local area networks (WLANs). If STAs compete for channel access according to IEEE 802.11 distributed coordination function, they have comparable opportunity of channel access, regardless of transmission rate. Accordingly, high-rate STAs achieve throughput similar to low-rate STAs, which is well known as performance anomaly. To mitigate this problem, we propose a hybrid solution combining contention window control with frame aggregation. By controlling contention window of each STA, the proposed mechanism assures higher channel access opportunity for high-rate STAs, without resulting in the unnecessary high collision probability. At the same time, it controls the frame aggregation factor based on the transmission rate of each STA, in order to tightly assure perstation fairness in terms of channel occupation time. To validate the proposed mechanism, we perform intensive simulation which confirms its outstanding performance in terms of throughput, fairness, and utilization.
Elevated Expression of Squamous Cell Carcinoma Antigen (SCCA) Is Associated with Human Breast Carcinoma

Squamous cell carcinoma antigen (SCCA) belongs to the serine protease inhibitor (Serpin) family of proteins. Elevated expression of SCCA has been used as a biomarker for aggressive squamous cell carcinoma (SCC) in cancers of the cervix, lung, head and neck, and liver. However, SCCA expression in breast cancer has not been investigated. Immunohistochemical analysis of SCCA expression was performed on tissue microarrays containing breast tumor tissues (n = 1,360) and normal breast epithelium (n = 124). SCCA expression was scored on a tiered scale (0-3) independently by two evaluators blind to the patient's clinical status. SCCA expression was observed in Grade I (0.3%), Grade II (2.5%), and Grade III (9.4%) breast cancers (p<0.0001). Comparing tissues categorized into the three non-metastatic TNM stages, I-III, SCCA positivity was seen in 2.4% of Stage I cancers, 3.1% of Stage II cancers, and 8.6% of Stage III breast cancers (p = 0.0005). No positive staining was observed in normal/non-neoplastic breast tissue (0 out of 124). SCCA expression also correlated to estrogen receptor/progesterone receptor (ER/PR) double-negative tumors (p = 0.0009). Compared to SCCA-negative patients, SCCA-positive patients had both a worse overall survival and recurrence-free survival (p<0.0001 and p<0.0001, respectively). This study shows that SCCA is associated with both advanced stage and high grade human breast carcinoma, and suggests the necessity to further explore the role of SCCA in breast cancer development and treatment.
Mining with Information Extraction

The popularity of the Web and the large number of documents available in electronic form has motivated the search for hidden knowledge in text collections. Consequently, there is growing research interest in the general topic of text mining. In this paper, we develop a text-mining system by integrating methods from Information Extraction (IE) and Data Mining (Knowledge Discovery from Databases or KDD). By utilizing existing IE and KDD techniques, text-mining systems can be developed relatively rapidly and evaluated on existing text corpora for testing IE systems. We present a general text-mining framework called DiscoTEX which employs an IE module for transforming natural-language documents into structured data and a KDD module for discovering prediction rules from the extracted data. When discovering patterns in extracted text, strict matching of strings is inadequate because textual database entries generally exhibit variations due to typographical errors, misspellings, abbreviations, and other sources. We introduce the notion of discovering “soft-matching” rules from text and present two new learning algorithms. TextRISE is an inductive method for learning soft-matching prediction rules that integrates rule-based and instance-based learning methods. Simple, interpretable rules are discovered using rule induction, while a nearest-neighbor algorithm provides soft matching. SoftApriori is a text-mining algorithm for discovering association rules from texts that uses a similarity measure to allow flexible matching to variable database items. We present experimental results on inducing prediction and association rules from natural-language texts demonstrating that TextRISE and SoftApriori learn more accurate rules than previous methods for these tasks. We also present an approach to using rules mined from extracted data to improve the accuracy of information extraction. Experimental results demonstate that such discovered patterns can be used to effectively improve the underlying IE method.
MULTI-PERSPECTIVE TARGET COVERAGE IN VISUAL SENSOR NETWORKS USING A GAME THEORETICAL APPROACH

Nowadays the problem of multi-perspective sectors coverage of the circular target in the monitoring area which tries to access further information about the target is one of the open research issues in visual sensor networks (VSNs). The main goal of this problem is to put some camera nodes in active mode, which the activation of these nodes will guarantee the maximum target coverage with minimum possible redundancy. According to literature, it can be concluded that the multi-perspective target coverage problem has been solved by applying exact and centralized methods. Since delivering information to the sink and activating the selected camera nodes by the returned messages in centralized methods are time consuming, they cannot be suitable for large scale VSNs with mobile targets. Therefore, in this paper, we propose a distributed algorithm named Game-theory based Multiperspective Target Coverage (GMTC) which is based on the game theoretical approach. In the proposed algorithm each camera node decides to be active or not only by using the received information from its neighbor nodes. The simulation results demonstrate that our proposed algorithm performs more efficiently in providing the maximum multi-perspective target coverage at the minimum possible time and with the reasonable overlapping rate in comparison with centralized algorithms.
Personalized recommendation using implicit interaction information

Currently, the information in the internet is becoming explosive. In order to help the users searching the items they are interested in, such as, the news, the books, in this paper, we propose an automatic personalized recommendation algorithm by constructing the social graph resting on the users' implicit interaction information. We at first introduce a metric to measure the users' affinity based on their implicit interaction information to construct a social graph, and then categorize the users into different clusters within which they will have similar tastes, finally, we use a personalized recommendation algorithm to recommend the items shared in the same cluster to the users. The experiments on a book data set are performed to demonstrate that our proposed method can well generate the recommendations which users will be interested in with high accuracy and efficiency.
A Flow-Based Approximation of Observer Error Linearization for Non-Linear Systems

This paper deals with observer design for non-linear single output systems. When a classical observer error linearization by output injection is not possible due to restrictive existence conditions, a simple approximation scheme is proposed. The method can be applied to a wider class of non-linear systems. Our approach is constructive and can be implemented using computer algebra packages. The design procedure is carried out for two example systems. Key–Words: Differential geometry, non-linear differential equations, observers
Biometric recognition system for challenging faces

A novel method for face recognition system using challenging profile and frontal faces is proposed in this paper. The proposed face recognition system consists of pre-processing, feature extraction and classification components. In this work, for pre-processing, the face region is extracted using facial landmark points, obtained by the tree structured part model. During feature extraction, SIFT descriptors are computed from the detected face region, and Spatial Pyramid Matching approach based on Locality constraints Linear Coding technique is employed for feature representation. Finally multi-class linear SVM classifier is employed to do the classification job. Extensive experimental results have been performed to show that the proposed algorithm has satisfying performance as compared to existing methods for IITK, CASIA-FACE-V5, LIBOR, ORL and Extended YALE-B face databases.
Serrated polyps of the colon

Until recently, colonic polyps were traditionally classified as either hyperplastic or adenomatous, and only the latter were believed to have the potential to progress to carcinoma. However, it is now appreciated that a subset of serrated polyps also appear to have malignant potential. Serrated polyps are a heterogeneous group of colon polyps that include hyperplastic polyps, sessile serrated adenomas (SSAs), traditional serrated adenomas, and mixed polyps. Insights into these polyps were derived, in part, from studies of patients with the hyperplastic polyposis syndrome. SSAs show a predilection for the right colon, have a distinct histology, and their molecular genetic profile has recently been linked to a pathway for colon tumorigenesis that is characterized by microsatellite instability. Based upon available evidence, it is recommended that patients with serrated adenomas undergo colonoscopic follow-up at the same frequency as for conventional adenomas. It is important that physicians are aware of serrated polyps, particularly serrated adenomas and their relationship to colon cancer, and their proper clinical management.
Shared Cultural History as a Predictor of Political and Economic Changes among Nation States

Political and economic risks arise from social phenomena that spread within and across countries. Regime changes, protest movements, and stock market and default shocks can have ramifications across the globe. Quantitative models have made great strides at predicting these events in recent decades but incorporate few explicitly measured cultural variables. However, in recent years cultural evolutionary theory has emerged as a major paradigm to understand the inheritance and diffusion of human cultural variation. Here, we combine these two strands of research by proposing that measures of socio-linguistic affiliation derived from language phylogenies track variation in cultural norms that influence how political and economic changes diffuse across the globe. First, we show that changes over time in a country’s democratic or autocratic character correlate with simultaneous changes among their socio-linguistic affiliations more than with changes of spatially proximate countries. Second, we find that models of changes in sovereign default status favor including socio-linguistic affiliations in addition to spatial data. These findings suggest that better measurement of cultural networks could be profoundly useful to policy makers who wish to diversify commercial, social, and other forms of investment across political and economic risks on an international scale.
HIPNOLAKTASI MENINGKATKAN KOMITMEN IBU DALAM PEMBERIAN ASI EKSKLUSIF DI SURABAYA

Breast Milk (ASI) contains high nutrients that are very beneficial for infant health. World Health Organization, WHO recommends infants get exclusive breastfeeding for 6 months (Infodatin, 2016) Support from the nearest person will be instrumental in the success of breastfeeding. Breastfeeding is also inseparable from the mother's commitment to breastfeeding. Efforts that can be done in the process of breastfeeding mother is hypnolaktasi techniques. This study aims to determine the effect of hypnolaktasi on mother's commitment in giving exclusive breastfeeding to her baby. This research uses a qualitative approach and the type of research is descriptive. Samples were taken by purposive sampling. The data were collected by giving an open questionnaire and interviewing the mother about hypnolactation and mother's commitment to exclusive breastfeeding to her baby. The results showed that 75% of respondents were 25-30 years old, 58% had 1 child and 83% had good knowledge about exclusive breastfeeding. Based on the interview results obtained that the benefits after doing the hypnola c ta tion perceived the respondents are comfortable in breastfeeding and confident breastfeeding can go out smoothly and 5 respondents who do not provide infant formula to the baby until now. The conclusions of this study are knowledge, and management of hypnolactation can increase the mother's commitment in exclusive breastfeeding. Keywords : hypnolactation, mother's commitment, Exclusive breastfeeding
Differences in distractor-induced deviation between horizontal and vertical saccade trajectories

The present study systematically investigated the influence of a distractor on horizontal and vertical eye movements. Results showed that both horizontal and vertical eye movements deviated away from the distractor but these deviations were stronger for vertical than for horizontal movements. As trajectory deviations away from a distractor are generally attributed to inhibition applied to the distractor, this suggests that this deviation is not only due to differences in activity between the two collicular motor maps, but can also be evoked by local application of inhibitory processes in the same map as the target. Nonetheless, deviations were more dominant for vertical movements which suggests that for these movements more inhibition is applied than for horizontal movements.
An Approach for Web Service Selection Based on Confidence Level of Decision Maker

Web services today are among the most widely used groups for Service Oriented Architecture (SOA). Service selection is one of the most significant current discussions in SOA, which evaluates discovered services and chooses the best candidate from them. Although a majority of service selection techniques apply Quality of Service (QoS), the behaviour of QoS-based service selection leads to service selection problems in Multi-Criteria Decision Making (MCDM). In the existing works, the confidence level of decision makers is neglected and does not consider their expertise in assessing Web services. In this paper, we employ the VIKOR (VIšekriterijumskoKOmpromisnoRangiranje) method, which is absent in the literature for service selection, but is well-known in other research. We propose a QoS-based approach that deals with service selection by applying VIKOR with improvement of features. This research determines the weights of criteria based on user preference and accounts for the confidence level of decision makers. The proposed approach is illustrated by an example in order to demonstrate and validate the model. The results of this research may facilitate service consumers to attain a more efficient decision when selecting the appropriate service.
New Perspectives on Tooth Wear

Some of the efforts that have been made to document tooth wear are reviewed here with an emphasis on nonhuman mammals, literature with which dentists may not be very familiar. We project a change in research strategy from the description of wear at various scales of measurement towards investigation of the mechanical mechanisms that actually create the texture of a worn surface. These studies should reveal exactly how tooth tissue is lost and what aspects of the structure of dental tissues affect this. The most important aspects of the interaction between the tooth surface and wear particles would appear to be particle size, particle shape, their mechanical properties with respect to those of tooth tissues, and the influence of saliva.
Controlling Chaos in Chaotic Bidirectional Associative Memories

The family of chaotic bidirectional associative memory (C-BAM family) can reach all stored patterns during the chaotic behavior. Therefore, in this case, C-BAM family can not converge towards a specific pattern, consequently, a desired output is not available. We introduce a control strategy to make heteroassociative chaotic networks converge towards a non-accessible memory and towards a last state of a trajectory. Computer simulations showed that the chaos of C-BAM family could be controlled through the pinning control method, in which any stored output can be recalled from its associated stimulus.
Augmented Rotation‐Based Transformation for Privacy‐Preserving Data Clustering

Multiple rotation‐based transformation (MRBT) was introduced recently for mitigating the apriori‐knowledge independent component analysis (AK‐ICA) attack on rotation‐based transformation (RBT), which is used for privacy‐preserving data clustering. MRBT is shown to mitigate the AK‐ICA attack but at the expense of data utility by not enabling conventional clustering. In this paper, we extend the MRBT scheme and introduce an augmented rotation‐based transformation (ARBT) scheme that utilizes linearity of transformation and that both mitigates the AK‐ICA attack and enables conventional clustering on data subsets transformed using the MRBT. In order to demonstrate the computational feasibility aspect of ARBT along with RBT and MRBT, we develop a toolkit and use it to empirically compare the different schemes of privacy‐preserving data clustering based on data transformation in terms of their overhead and privacy.
International Conference in Knowledge Based and Intelligent Information and Engineering Systems-KES 2013 Nonlinear Identification Using Single Input Connected Fuzzy Inference Model

The single input connected fuzzy inference model (SIC model) by Hayashi et al. can decrease the number of fuzzy rules drastically in comparison with the conventional fuzzy inference models. In this paper, we first show the SIC model and its learning algorithm, and clarify the applicability of the SIC model by applying it to identification of nonlinear functions. c © 2013 The Authors. Published by Elsevier B.V. Selection and peer-review under responsibility of KES International.
The Relationship between Visual Impairment and Health-Related Quality of Life in Korean Adults: The Korea National Health and Nutrition Examination Survey (2008–2012)

Introduction To evaluate health-related quality of life (HRQoL) in Korean adults with visual impairment(VI) using various measures based on a nationally distributed sample. Methods Using the Korea National Health and Nutrition Examination Survey (KNHANES, 2008–2012) data, we compared EuroQol five-dimensional questionnaire (EQ-5D) and EQ-visual analogue scale (VAS) scores after adjusting for socio-demographic and psychosocial factors as well as for comorbidities with VI. Logistic regressions were used to elucidate determinants for the lowest quintile HRQoL scales according to VI severity. Uncorrected visual acuity (VA) which implies vision of ordinary life was measured using an international standard vision chart based on Snellen scale. Results 28,825 participants (sum of weights; 37,562,376) were included in the analysis. The mean EQ-5D and EQ-VAS scores were significantly lower in the VI groups than in the normal vision (defined as VA 20/20-20/25) group based on the better or worse seeing eye (P<.0001 and P<.0001, respectively). Participants with moderate (VA 20/80-20/160) and severe VI (VA ≤20/200) had higher scores of multivariate-adjusted odd ratios (aORs) for the lowest quintile than did the normal vision group which was particularly evident in the results from EQ-5D, whereas the results of the mild VI (VA 20/32-20/63) group did not identify significant differences from the normal vision group independent of classification according to the better or the worse seeing eye. Conversely, EQ-VAS revealed significantly higher score of multivariate-aORs for the lowest quintile in participants with mild VI either for the better or worse seeing eye. Conclusions The severity of VI was definitely associated with impaired HRQoL compared with the normal vision population. The analyses presented here elicited even mild VI could potentially deteriorate the health-related quality of life (or subjective perception of health quality) and therefore, therapeutic approaches should also focus on the subjective perception and better management of health condition.
Coordinate regulation of immune and inflammatory responses by T cell‐derived lymphokines

In response to antigenic stimulation, helper T cells secrete a set of protein mediators called lymphokines that regulate proliferation, differentiation, and maturation of lymphocytes and hemopoietic cells. Because all known lymphokines are composed of a single polypeptide chain, their coding sequences can be isolated by functional expression in appropriate host cells. Based on this expression cloning protocol, a number of T cell lymphokine genes have been isolated, their primary structure has been determined, and biological properties of their recombinant products have been examined. These studies revealed the existence of a regulatory network between lymphoid cells and hemopoietic cells mediated by the actions of multiple pleiotropic lymphokines produced by activated T cells. Because all or a part of this network can be activated in different ways by unique combinations of lymphokines, it is clear that T cells can play a vital role in coordinating the function of different body compartments in the immune and inflammatory responses. The activation of lymphokine genes in T cells by antigen is rapid and temporal. Therefore, an inflammatory response that involves proliferation and maturation of target cells may be restricted to the site of lymphokine production. This inducible hemopoiesis appears to be differentially regulated from the steady state or constitutive hemopoiesis that occurs in the bone marrow micro‐environment in the absence of immunological stimuli. — MIYAJIMA, A. ; MIYATAKE, S. ; SCHREURS, J.; de Vries, J.; Arai, N. ; Yokota, T. ; Arai, K. Coordinate regulation of immune and inflammatory responses by T cell‐derived lymphokines. FASEB J. 2: 2462‐2473; 1988.