Miracle-dz/UniFAR-FTUs huggingface dataset:
RETRACTED: Automatic Detection of Exudates in Diabetic Retinopathy Images

Problem statement: Diabetic Retinopathy (DR) is globally the primary cause of visual impairment and blindness in diabetic patients. Reti nal image is essential and crucial for ophthalmolog ists to diagnose diseases. Many of technique can achieve good performance on retinal feature are clearly visible. Unfortunately, it is a normal situation th at the retinal images in Thailand are low-quality i mages. The existing algorithm cannot detect low-quality im age. Therefore, this study is part of a larger effo rt to develop a new method for detection of exudates in l ow quality retinal image. Approach: In this study, we presented a new method towards the development for detecting exudates pathologies of DR. The color retinal images are segmented using Fuzzy C-Means (FCM) clustering and morphological methods and following key preprocessing step, i.e., color n ormalization, contrast enhancement, remove noise and color space selection. This enables its difference in our methods compared to other approach and the algorithm can achieve good performance even on low-quality retinal images. Result/Conclusion: The result shows that accuracy values increase when the FCM clustering is combined with morphological methods techniques. If any applications need to det ect maximum number of exudates pixels or require execution speed, the FCM clustering technique could be used in isolation. However, if the applications require higher accuracy, the FCM clustering combined with morphological methods should be chosen. This system intends to help ophthalmologists in DR screening process to detect symptoms faster and more easily. This is not a final result application but it can be a preliminary diagnosis tool or deci sion support system for ophthalmologists. Human ophthalmologists are still needed for the cases where detection results are not very obvious.
The solar internal rotation from GOLF splittings

The low degree splittings obtained from one year of GOLF data analysis are combined with the MDI medium-l 144-day splittings in order to infer the solar internal rotation as a function of the radius down to $0. 2R_\odot$. Several inverse methods are applied to the same data and the uncertainties on the solution as well as the resolution reachable are discussed. The results are compared with the one obtained from the low degree splittings estimated from GONG network.
The Neural Network Estimator for Mechanical Property of Rolled Steel Bar

In this paper, the neural network estimator for mechanical property of rolled steel bar was proposed. Based on the learning capability of neural network, the nonlinear, complex relationships among the steel bar, the billet materials and the control parameters of production are expected to be automatically developed. Such a neural network estimator can help the technician to make a precise judgment for setting the related control parameters of rolling process. Not only the quality of steel bars can meet the standard asked for, but also can reduce the running cost caused by failure production.
LT^2C^2: A language of thought with Turing-computable Kolmogorov complexity

In this paper, we present a theoretical effort to connect the theory of program size to psychology by implementing a concrete language of thought with Turing-computable Kolmogorov complexity (LT^2C^2) satisfying the following requirements: 1) to be simple enough so that the complexity of any given finite binary sequence can be computed, 2) to be based on tangible operations of human reasoning (printing, repeating,.), 3) to be sufficiently powerful to generate all possible sequences but not too powerful as to identify regularities which would be invisible to humans. We first formalize LT^2C^2, giving its syntax and semantics and defining an adequate notion of program size. Our setting leads to a Kolmogorov complexity function relative to LT^2C^2 which is computable in polynomial time, and it also induces a prediction algorithm in the spirit of Solomonoff's inductive inference theory. We then prove the efficacy of this language by investigating regularities in strings produced by participants attempting to generate random strings. Participants had a profound understanding of randomness and hence avoided typical misconceptions such as exaggerating the number of alternations. We reasoned that remaining regularities would express the algorithmic nature of human thoughts, revealed in the form of specific patterns. Kolmogorov complexity relative to LT^2C^2 passed three expected tests examined here: 1) human sequences were less complex than control PRNG sequences, 2) human sequences were not stationary, showing decreasing values of complexity resulting from fatigue, 3) each individual showed traces of algorithmic stability since fitting of partial sequences was more effective to predict subsequent sequences than average fits. This work extends on previous efforts to combine notions of Kolmogorov complexity theory and algorithmic information theory to psychology, by explicitly .
A Survey of Color Mapping and its Applications

Color mapping or color transfer methods aim to recolor a given image or video by deriving a mapping between that image and another image serving as a reference. This class of methods has received considerable attention in recent years, both in academic literature and in industrial applications. Methods for recoloring images have often appeared under the labels of color correction, color transfer or color balancing, to name a few, but their goal is always the same: mapping the colors of one image to another. In this report, we present a comprehensive overview of these methods and offer a classification of current solutions depending not only on their algorithmic formulation but also their range of applications. We discuss the relative merit of each class of techniques through examples and show how color mapping solutions can and have been applied to a diverse range of problems.
Dynamic Rate Multicast Scheduling in Third Generation Wireless Data Networks

A memory disk having a central opening and planar sides for receiving magnetic media on both of the sides is bounded by a cylindrical outside diameter peripheral edge and chamfered edges extending between each of the planar sides. The peripheral edge is clamped by a disk processing chuck including a disk retainer mount having a central disk support for mounting a circular disk edge bounding the central opening and a mount cylindrical beveled edge receiving an outside diameter chamfered edge of the disk. A ring in the retainer mount includes a multiplicity of spaced radial fingers extending cylindrically around the ring, each finger having a distal end extending to a first position outboard of the disk peripheral edge. The distal ends are moveable inwardly to a second position by an inflatable bladder acting simultaneously against all the fingers, placing the distal end tips into clamping contact with the disk peripheral edge mounted on the retainer mount.
Winner-Take-All Correlation-Based Complex Networks for Modeling Stock Market and Degree-Based Indexes

Complex networks are constructed to study correlations between the closing prices for all US stocks that were traded from July 1, 2005 to August 30, 2007. The nodes are the stocks, and the connections are determined by cross correlations of the variations of the stock prices and price returns within a chosen period of time. Specifically, a winner-take-all approach is used to determine if two nodes are connected by an edge. The network thus formed is a full network of stock prices giving full information about their interdependence. We find that the distribution of the number of connections follows a power law. Such power-law distribution is also found in several variations of complex networks formed by considering price returns and trading volumes. The results from this work clearly suggest that the variation of stock prices are strongly influenced by a relatively small number of stocks. We propose a new approach for selecting stocks for inclusion in stock indices and compare it with existing approaches.
Dynamic call admission control for QoS provision in mobile multimedia networks using artificial neural networks

In mobile multimedia communication systems, the limited bandwidth is an issue of serious concern. However for the better utilization of available resources in a network, channel allocation scheme plays a very important role to manage the available resources in each cell, hence this issue should be managed to reduce the call blocking or dropping probabilities. In this paper we have proposed the new dynamic channel allocation scheme based on handoff calls and traffic mobility using Hopfield neural network. It will improve the capacity of existing system. Hopfield method develops the new energy function that allocates channel not only for new call but also for handoff calls on the basis of traffic mobility information. Moreover, we have also examined the performance of traffic mobility with the help of error back propagation neural network model to enhance the overall quality of services (QoS) in terms of continuous service availability and intercell handoff calls. Our scheme decreases the call handoff dropping and blocking probability up to a better extent as compared to the other existing systems of fixed channel allocation and dynamic channel allocation.
Effects of Garden Visits on Long-term Care Residents as Related to Depression

●ADDITIONAL INDEX WORDS. depressive symptoms, elderly, plants, nature, outdoors, institutional care, human issues in horticulture SUMMARY. Depression is a major health problem among the elderly. Its prevalence is high among those in long-term care. Exposure to the garden environment may alleviate depressive symptoms, but there is little research evidence to confi rm this hypothesis. In this study we investigated the perceived effects and meanings related to garden visits among older individuals living in long-term care and assessed whether there are associations between experiences from garden visits and self-rated depression. Data were gathered by surveying 30 elderly people living in Kustaankartano, a nursing home and service center for elderly people in Helsinki, Finland. Prevalence of self-rated depression was high; 46% of the participants were depressed. Both being in the garden and seeing it from the balcony and observing nature were of great signifi cance for most of the participants. For more than half of the participants, visiting the garden improved mood, quality of sleep, and ability to concentrate; it generated feelings of recovery and promoted peace of mind. Affective effects of visiting the garden tended to be more pronounced among the depressed than among those not depressed. The depressed did not consider social interaction and participation in social activities very important for their
Co-regularized Spectral Clustering with Multiple Kernels

We propose a co-regularization based multiview spectral clustering algorithm which enforces the clusterings across multiple views to agree with each-other. Since each view can be used to define a similarity graph over the data, our algorithm can also be considered as learning with multiple similarity graphs, or equivalently with multiple kernels. We propose an objective function that implicitly combines two (or more) kernels, and leads to an improved clustering performance. Experimental comparisons with a number of baselines on several datasets establish the efficacy of our proposed approach.
TOWARDS COMPLETE, GEO-REFERENCED 3D MODELS FROM CROWD-SOURCED AMATEUR IMAGES

Abstract. Despite a lot of recent research, photogrammetric reconstruction from crowd-sourced imagery is plagued by a number of recurrent problems. (i) The resulting models are chronically incomplete, because even touristic landmarks are photographed mostly from a few “canonical” viewpoints. (ii) Man-made constructions tend to exhibit repetitive structure and rotational symmetries, which lead to gross errors in the 3D reconstruction and aggravate the problem of incomplete reconstruction. (iii) The models are normally not geo-referenced. In this paper, we investigate the possibility of using sparse GNSS geo-tags from digital cameras to address these issues and push the boundaries of crowd-sourced photogrammetry. A small proportion of the images in Internet collections (≈ 10 %) do possess geo-tags. While the individual geo-tags are very inaccurate, they nevertheless can help to address the problems above. By providing approximate geo-reference for partial reconstructions they make it possible to fuse those pieces into more complete models; the capability to fuse partial reconstruction opens up the possibility to be more restrictive in the matching phase and avoid errors due to repetitive structure; and collectively, the redundant set of low-quality geo-tags can provide reasonably accurate absolute geo-reference. We show that even few, noisy geo-tags can help to improve architectural models, compared to puristic structure-from-motion only based on image correspondence.
Business opportunities through UMTS-WLAN networks

This article outlines the economic feasibility of mobile operators that combine nationwide mobility with 3G networks and hot spot coverage with WLANS. WLANs are based on HIPERLAN/2 architecture and the UMTS network exploits WCDMA/FDD technology. The evaluated business scenarios are focused on two different deployment areas, in terms of demographic characteristics and mobile penetration: a large and a small European country. The business case . spans 2002 to 2011 with UMTS' roll-out year in 2002 and W1.AN'S in 2004, covering indoor hot-spot areas (stations, airports, stadiums, etc.) where demand is high. The demand for this UMTS-W~N roaming case is evaluated based on observations from Europe's current mobile market and its evolution. Usage scenarios of different service packages corresponding to both residential and business markets have been taken into account. Direct investments and operational costs as well as revenue streams from traffic have been calculated. The methodology and the tool developed in ACTS-TERA [1] and IST-TONIC [2] projects have been utilized for this case study. Economic conclusions have been derived, presented and discussed using key profitability factors. Profitability for all scenarios and business profiles has been calculated, presented and discussed. It includes a sensitivity analysis in order to identify, the major opportunities and threats, for specific" service sets as well as critical parameters and uncertainties. A wide audience from mobile operators and service providers to retail companies interested in entering the 3G market, can exploit this information.
The development of theories from the analysis of the organisation: case studies by the patterns of behaviour

This study presents an adaptation of case studies denominated by the patterns of behaviour, an ideal methodology for the development of theories explaining the organisation and its integrants’ behaviour. In comparison with other alternatives, best results are obtained in the research of dynamic and complex processes that require analysis during a prolonged period of time, multiple sources of evidence, both quantitative and qualitative, and diverse analysis techniques, such as training and organizational culture. Its application also achieves to lay the foundations of the models and to make explicit the logic underlined in the hypothesis. This account is structured as follows. After an introduction, the case studies are characterized by patterns of behaviour before pointing out the stages of its application. Next, the possibility of generalizing the findings and the role of the methodology in the development of the theories in the organisation is discussed: finalising with a summary and conclusions.
Bond rating: a nonconservative application of neural networks

The authors apply neural networks to a generalization problem of predicting the ratings of corporate bonds, where conventional mathematical modeling techniques have yielded poor results and it is difficult to build rule-based artificial-intelligence systems. The results indicate that neural nets are a useful approach to generalization problems in such nonconservative domains, performing much better than mathematical modeling techniques like regression. <<ETX>>
The implementation of algorithms for inverse solutions in EEG brain-computer interfaces

Indicating the places where the signals read from the surface of the head by means of EEG electrode systems originate is a crucial problem in BCI. Locating the sources of EEG signals (signal generators), i.e. indicating the places in the brain that the signals come from is the objective of the inverse problem. The two algorithms based on the methods used in the inverse problem: the linear least squares method and the LORETA method were compared. An analysis of the accuracy of locating the sources generating EEG signals on the basis of the two above mentioned methods was carried out with the use of the MATLAB programme. The findings made it possible to determine both the complexity of calculation involved in the methods under consideration and to compare the accuracy of the results obtained.
Character segmentation from ancient palm leaf manuscripts in Thailand

This paper presents a character segmentation system from ancient palm leaf manuscripts written in ancient Thai language. This aims to develop an automated system for the digitization and processing of ancient manuscripts. In this paper, the preprocessing stage of noise reduction is carried out. An optimal binarization is selected in order to reduce the unrelated noise and background information on the document. The proposed approach can improve the readability of the documents and enable selection of the optimal binarization technique. Text line segmentation is then applied to partial projection profiles, and the characters are separated by using the contour tracing algorithm and a trace of background skeleton. The experiment results have shown that this proposed system can be used to support subsequent steps such as automatic recognition of characters from Thai ancient palm leaf.
Query Rewriting for Archived Information Retrieval

Word mismatch is a fundamental issue in the field of information retrieval. To address this problem, one of the major approaches is query formulation. Previous work mainly focused on the study of synonym based term replacement and the query paraphrasing. However, the word level replacement overlooked the context of terms and the query level paraphrasing yielded on the low performance. In this paper, we proposed a phrase-rewriting scheme for query formulation in Web search by exploiting multiple online search engines. Through the use of phrases, we actually explore the term context in the query. Meanwhile, phrase rewriting was employed to explore the semantic similarity of phrases. Experimental results showed that the proposed approach outperformed the baselines significantly.
An Accurate and Efficient Model of Electrical Masking Effect for Soft Errors in Combinational Logic

Accurate modeling of the electrical masking effect of soft errors for combinational logic circuits represents a significant challenge in soft error rate analysis. Previous proposed models for electrical masking effect can introduce large estimation error. In this work, we use table lookup MOSFET models to accurately capture the nonlinear properties of submicron MOS transistors. Based on these models, we propose transient pulse generation model and propagation model for soft error analysis. From these models, we derive a fast and efficient method to estimate the electrical masking effect for soft error in combinational logic.
Civic engagement and participation among Ghanaian and Kenyan students and their correlates

ABSTRACT This article examines levels of civic engagement among university students in Ghana and Kenya and identifies factors that may account for their civic engagement. Overall, the students reported low civic engagement, with the Kenyans reporting higher engagement. Demographic factors (gender and age) and personal values hardly contributed to the students’ civic engagement. Political interest and attentiveness, barriers and motivation towards participation made a consistent and significant contribution to political participation and future participation. Furthermore, trust, social endorsement and social efficacy showed a consistent and significant contribution to civic engagement. The findings underscore the need to work towards getting the youth more engaged.
An Object-Oriented Approach to UML Scenarios Engineering and Code Generation

Object-oriented software development matured significantly during the past ten years. The Unified Modeling Language (UML) is generally accepted as the de facto standard modeling notation for the analysis and design of the object oriented software systems. This language provides a suitable framework for scenario acquisition using use case diagrams and sequence or collaboration diagrams. In this paper, we suggest a requirement engineering process that composes UML scenarios for obtain a global description of a given service of the system and implementation code from the UML use case (service). We suggest four operators: sequential operator, concurrent operator, conditional operator and iteration operator to compose a set of scenarios that describe a use case of a given system. We developed algorithm and tool support that can automatically produce a global sequence diagram representing any way of composing them and to offer a code generation of sequence diagram resulting.
Performance Evaluation of the EXT4 File System A Comparative Study Against EXT3, ReiserFS and JFS

— Base on several definition of File System, File System is a system which is responsible to handle files and managing data in any operating system [1]. According to these definitions, choose a File System to managing data on your system, is one of the consideration for anybody who use a computer. Anybody can fill this problem when you have a lot of files with a large portion. File System types can be classified into disk File Systems, network File Systems and special purpose File Systems[2][3][4. ] The purpose of this Paper is “comparison Performance evaluation among four File Systems”. According to above goals, there are several file systems on Linux operation system. These file system are EXT2, EXT3, EXT4, ReiserFS, JFS, and etc. In this paper , we are neither define several file systems on Linux nor compare them and tested by IOzone and Postmark benchmark tools [5][6]. The performance result has shown base on read, re-read, write and re-write of file for IOzone benchmark tool and create, read, append, delete for Postmark benchmark tool. We have chosen IOzone bench mark for our experiments as it is preferred for operating system evaluation [7].
Role of Word Sense Disalnbiguation in Lexical Acquisition: Predicting Semantics from Syntactic Cues

This paper addresses the issue of word-sense ambiguity in extraction from machine-readable resources for the construction of large-scale knowledge sources. We describe two experiments: one which ignored word-sense distinctions, resulting in 6.3% accuracy for semantic classification of verbs based on (Levin, 1993); and one which exploited word-sense distinctions, resulting in 97.9% accuracy. These experiments were dual purpose: (1) to validate the central thesis of the work of (Levin, 1993), i.e., that verb semantics and syntactic behavior are predictably related; (2) to demonstrate that a 15-fold improvement can be achieved in deriving semantic information from syntactic cues if we first divide the syntactic cues into distinct groupings that correlate with different word senses. Finally, we show that we can provide effective acquisition techniques for novel word senses using a combination of online sources.