Miracle-dz/UniFAR-FTUs huggingface dataset:
Study on Application of Batik Technique on Wood and Batik Decorative Motifs at Sculptural Souvenir of Loro Blonyo Statue

The aims of this research are: (1) To find out the process stages in application of batik technique on woodenmaterial at the sculptural souvenir of loro blonyo statue, (2) To analyze the batik elements applied at thesculptural souvenir of loro blonyo statue. This research applies qualitative analytical method, while the data arecollected by using the techniques of in-depth interview, participative observation and analysis on contents ofdocuments and archives. Samples are taken by applying the purposive sampling technique upon the subjectsbeing analyzed or upon the selected informants. This analysis applies the technique of interactive model under acontinuous cycle covering the steps as follows: (1) Data Collecting, (2) Data Reducing, (3) Data Presenting, and(4) Conclusion Making. Outputs of this research indicate that the application of batik technique on woodenmaterial for sculptural souvenir of loro blonyo statue is done by using the batik painting and batik writingtechniques. Application of batik at the sculptural souvenir of loro blonyo statue applies various kinds of specificJavanese classical decorative batik motifs and the contemporary creation in which both of them are completedwith ‘isen-isen’ (fillers) and ‘sawut’ (sowing) of leaves. The classical motifs applied as decoration among othersare the motifs of kawung, sidoluhur, sidomukti, parang and truntum.Key-words: Written batik, painted batik, sculptural souvenir, loro blonyo, motif
Primary Localized Conjunctival Amyloidosis Presenting with Unilateral Ptosis

Purpose: Primary localized amyloidosis of eyelid is a localized type of amyloidosis without evidence of systemic involvement, which is a quite rare clinical condition. Here we report a case of primary localized amyloidosis of eyelid. Case report: A 40-year-old woman presented with a four-month history of swelling of the left upper eyelid resulting in a mechanical ptosis. The mass had a firm bony consistency. Ocular examination revealed a firm mass in upper lid connected to the tarsus. She had no sign or history of ocular inflammation. Homogenous eosinophilic deposits with extensive foci of calcification and ossification were visible In pathologic assessment, which was consistent with amyloidosis. All evaluations were negative for systemic amyloidosis. Conclusion: Primary localized amyloidosis may appear as a calcified and ossified tumoral mass.
PPSim: A Cycle-Accurate Simulator for PowerPC Instruction Set

Simulators play an important part in computer architecture research. As for specific microarchitecture study, which focuses on the accurate behavior of out-of-order scheduling, ALU contention, and function unit management, an over-simplified abstraction is not sufficient to represent modern processor organizations. Thus cycle-accurate simulators are introduced to describe the accurate behavior in target microarchitecture. In cycle-accurate simulators, the timing feature within function units is simulated. This paper presents PPSim, a cycle-accurate PowerPC instruction set simulator, which models the cache, branch prediction, and out of order pipeline in PowerPC microarchitecture.
A Wavelet Analysis-Based Dynamic Prediction Algorithm to Network Traffic

Network traffic is a significantly important parameter for network traffic engineering, while it holds highly dynamic nature in the network. Accordingly, it is difficult and impossible to directly predict traffic amount of end-to-end flows. This paper proposes a new prediction algorithm to network traffic using the wavelet analysis. Firstly, network traffic is converted into the time-frequency domain to capture time-frequency feature of network traffic. Secondly, in different frequency components, we model network traffic in the time-frequency domain. Finally, we build the prediction model about network traffic. At the same time, the corresponding prediction algorithm is presented to attain network traffic prediction. Simulation results indicates that our approach is promising.
Development of a health promotion questionnaire index (HPQI) to measure doktor muda (junior doctor) programme impact on schoolchildren’s oral health knowledge, attitudes and behaviour

Long term evaluations of impacts of community based health promotion programmes are not an easy or straightforward task to do due to lack of validated and reliable indices. Objective: To develop and test an index to measure schoolchildren? s oral health knowledge, attitudes, and behaviour as a result of a school-based health promotion programme in Malaysia called the Doktor Muda (Junior Doctor) Programme (DMP). Materials and Methods: The index was developed in English based on the DMP module and translated into Malay. The Malay version was tested on 174, 11-12 year old schoolchildren. Psychometric analysis of the index involved content and face validity tests as well as factor analysis, internal and test-retest reliability. Results: Factor analysis yielded 3 factors with groups of items viz. oral health knowledge (OHK), oral health attitudes (OHA) and oral health behaviour (OHB). The Cronbach? s alpha coefficients of the three factors were 0.61, 0.73, and 0.64, respectively. The Kappa coefficients were 0.70, 0.77 and 0.73, respectively (intraclass correlation coefficients = 0.72, 0.70 and 0.78). The final questionnaire comprised 33 items, namely; OHK 11 items, OHA 15 items, and OHB 7 items. Conclusion: The Health Promotion Questionnaire Index (HPQI) to measure the DMP impact on schoolchildren? s oral health knowledge, attitudes, and behaviours was empirically verified to be valid and reliable for use among 11-12 year old Malaysian schoolchildren.
Automata logics, and infinite games: a guide to current research

A central aim and ever-lasting dream of computer science is to put the development of hardware and software systems on a mathematical basis which is both firm and practical. Such a scientific foundation is needed especially for the construction of reactive programs, like communication protocols or control systems. For the construction and analysis of reactive systems an elegant and powerful theory has been developed based on automata theory, logical systems for the specification of nonterminating behavior, and infinite two-person games. The 19 chapters presented in this multi-author monograph give a consolidated overview of the research results achieved in the theory of automata, logics, and infinite games during the past 10 years. Special emphasis is placed on coherent style, complete coverage of all relevant topics, motivation, examples, justification of constructions, and exercises.
Lung nodules detection based on modified extreme learning machine with deep convolutional features

This work achieves a method based on modified extreme learning machine (ELM) with deep convolutional features to detect lung nodules automatically. Convolutional neural networks (CNNs) are employed to extract the features of lung nodules for classification. And then ELM is used to detect the lung nodules by combining the normalization and vote selection. In comparison with the traditional methods, it is shown that our method achieves a higher performance and it can be used as an effective tool for lung nodules computer aided diagnosis.
Survey of Cold-start Problem in Collaborative Filtering Recommender System

Recommender systems have been widely used as an important response to information overload problem which leads consumers to locate the right information at the right time accurately and rapidly.The most successful and popular technique of such systems is collaborative filtering.However,collaborative filtering faces a key challenge of the cold-start problem.This paper first illustrates the cause of the cold-start problem and then tables the significance of cold-start problem research.The core of this paper is to summarize the existing algorithms which are used for addressing the cold-start problem.In order to facilitate users to choose the right algorithm to tackle the cold-start problem in collaborative filtering,it compares the performance and respective advantage and disadvantage of different algorithms.
Robots and Empire

Isaac Asmiov's classic novel about the decline and fall of Solaria. Gladia Delmarre's homeworld, the Spacer planet Solaria, has been abandoned - by its human population. Countless robots remain there. And when traders from Settler worlds attempt to salvage them, the robots of Solaria turn to killing.in defiance of the Three Laws of Robotics. Pax Robotica Long ago, Gladia's robots Daneel and Giskard played a vital role in opening the worlds beyond the Solar system to Settlers from Earth. Now the conscience-stricken robots are faced with an even greater challenge. Either the sacred Three Laws of Robotics are in ruins - or a new, superior Law must be established to bring peace to the galaxy. With Madam Gladia and D.G. Baley - the captain of the Settler traders and a descendant of the robots' friend Elijah Baley - Daneel and Giskard travel to the robot stronghold of Solaria.where they uncover a sinister Spacer plot to destroy Earth itself.
Animation realiste de vetements

L'animation des tissus et la realisation de vetements de synthese font l'objet de nombreuses recherches en informatique graphique. L'approche la plus developpee consiste a representer les tissus par une surface elastique continue. Nous nous placons dans un cadre similaire, puisque pour nous, un tissu est un systeme masses-ressorts, soumis aux lois de la dynamique. Le gros desavantage des modeles elastiques classiques, c'est qu'ils sont d'autant plus chers en calculs que l'on desire obtenir un comportement plus rigide. On est alors vite limite en ce qui concerne les tissus, qui sont souvent tres rigides en traction (cas du denim ou de la toile de coton par exemple). Pour pallier cet inconvenient, nous avons developpe une methode de controle du taux de deformation qui permet d'obtenir des comportements plus rigides, sans presque aucun cout de calcul supplementaire. L'animation des tissus et des vetements requiert la gestion des collisions de ces tissus avec des objets, ou avec eux-memes. La gestion des collisions comprend dans un premier temps la detection des collisions et dans un deuxieme temps le calcul de la reponse aux collisions. Nous avons particulierement etudie la reponse, qui pose de nombreux problemes de robustesse. Pour les resoudre, nous proposons une methode originale de detection et de traitement des zones de collisions complexes. Enfin, notre modele de tissu a ete utilise pour realiser des vetements (chemise et pantalon a pinces), a partir de patrons industriels reels, assembles sur un mannequin tridimensionnel.
FPGA-Realization of a Multi-Axis Motion Controller

A multi-axis motion controller based on FPGA technology is developed in this paper. Firstly, a multi-axis motion system is presented and the servo controller design is described. Secondly, an Altera FPGA (Field Programmable Gate Arrays) chip and an embedded soft-core Nios II processor are applied to develop the multi-axis motion controller. The proposed FPGA-based multi-axis motion control IC has two modules. The first module is an embedded soft-core Nios II processor which is used to realize the motion trajectory planning by software. The second module is presented to realize the multi- axis position/speed/current controllers by hardware. In the second module, two approaches are proposed which one is individual-axis isolated design approach and another is multi- axis module design approach. In the latter, it will collect multiple CCCT (Current vector controller and coordination transformations) circuits or multiple position/speed controller circuits into one circuit; therefore it can substantially reduce hardware resource usage in FPGA. Thirdly, VHDL (VHSIC Hardware Description Language) is applied to describe the overall multi-axis controller behavior. Finally, to verify the effectiveness and correctness of the proposed multi-axis motion control IP, a three-axis XYZ table is constructed and some experimental results are presented.
Wind Power Prediction using Ensembles

The Ensemble project investigated the use of meteorological ensemble fore-casts for the prognosis of uncertainty of the forecasts, and found a good method to make use of ensemble forecasts. This method was then tried based on ensembles from ECMWF in form of a demo application for both the Nysted offshore wind farm and the whole Jutland/Funen area. The utilities used these forecasts for maintenance planning, fuel consumption estimates and over-the-weekend trading on the Leipzig power exchange. Other notable scientific results include the better accuracy of forecasts made up from a simple superposition of two NWP provider (in our case, DMI and DWD), an investigation of the merits of a parameterisation of the turbulent kinetic energy within the delivered wind speed forecasts, and the finding that a “naïve” downscaling of each of the coarse ECMWF ensemble members with higher resolution HIRLAM did not improve the error scores or the result space enough to warrant the computational effort. This report is the final report for the three-year project “Vindkraftforudsigelse med ensemble forecasting” (wind power prediction by ensemble forecasting, FU 2101), which ran from June 2002 to June 2005. It contains an overview of the results achieved in the project, but leaves the details to the specialised reports and papers published during the project. Participants were Risø National Laboratory, Informatics and Mathematical Modelling (IMM) of the Technical University of Denmark (DTU), the Danish Meteorological Institute (DMI), Energi E2 A/S, and Elsam A/S. SEAS A.m.b.A was initially part of the project, but the group participating was bought by E2 and therefore, only E2 continued as partner. Transmission companies Eltra and Elkraft System followed the progress and attended some meetings. The project budget was 5.59 million DKr, of which 3.03 million DKr was a grant under the PSO rules.
Orthoptic assessment and management of patients with stroke in Scotland

Aims: To determine the current assessment and management strategies of orthoptists for patients with visual problems after stroke and to identify barriers to effective orthoptic management and priorities for future research. Methods: A questionnaire was designed to gather information about vision assessments, protocols and treatments during the management of patients with stroke. Information was also collected on barriers experienced and priorities for future research. One orthoptist from each hospital eye department in Scotland was identified, telephoned and sent a questionnaire. Results: We identified 14 orthoptists, covering the whole geographical area of Scotland. The questionnaire response rate was 100%. We collected detailed information on assessments and treatments used in the orthoptic management of patients with stroke. Twelve (86%) orthoptists reported that their unit did not have a protocol or management plan specific to stroke patients. The most commonly reported treatment strategies for patients with eye movement problems were provision of prisms, advice on head posture and convergence exercises. Provision of an explanation or advice was the most common management strategy for patients with visual field problems or visual neglect. The main barriers identified were a lack of a management plan (57%) and lack of funding (36%). Conclusions: We have determined key aspects of the orthoptic management of patients with visual problems after stroke in Scotland. The results of this survey support the need for management plans and protocols specific to patients with stroke, and confirm a number of priorities for future research into the orthoptic management of visual problems after stroke.
New Essays on the Psychology of Art

Thousands of readers who have profited from engagement with the lively mind of Rudolf Arnheim over the decades will receive news of this new collection of essays expectantly. In the essays collected here, as in his earlier work on a large variety of art forms, Arnheim explores concrete poetry and the metaphors of Dante, photography and the meaning of music. There are essays on color composition, forgeries, and the problems of perspective, on art in education and therapy, on the style of artists' late works, and the reading of maps. Also, in a triplet of essays on pioneers in the psychology of art (Max Wertheimer, Gustav Theodor Fechner, and Wilhelm Worringer) Arnheim goes back to the roots of modern thinking about the mechanisms of artistic perception.
A highly scalable, parallel genetic algorithm for standard cell placement in vlsi design

With the advent of deep sub-micron technology, the size of chip increasing while devices scale shrinking, the total number of cells increases very fast. Due to the cell placement is a NP-hard problem and extremely computation time consuming; nowadays, to get the solution with satisfied quality for very large scale cell placement usually takes very long time even on expensive multi-processors high-end server. In this paper, I present a new approach with three improvements to solve this problem: (1) a brand new data structure which cut the cost of the crossover operation in Genetic Algorithm time complexity from n*n/2 to2*n. This is a break through to Genetic Algorithm. New data structure left the upperbound limit of the Genetic Algorithm, and makes it possible to solve problem with large data size, (2) a highly parallel algorithm that combines the advantage from Simulated Annealing and Genetic Algorithms for faster convergence, (3) a new distributed computation framework that decreases the congestion of the local area network communication, enable large number of machines could be used for network computation. Although this system is build for standard cell placement, the algorithm and data structures could be applied to solve any combinational problem. The network communication mechanism could be used by any application that needs to do parallel computation on distributed network.
An Algorithm for Multimodal Biometric Recognition Based on Feature Level and the Second-Generation Curvelet Transform

A single sample biometric recognition approach is proposed based on the feature level and curvelet transform of the second-generation to improve the recognition rate of the single modal biometric system in application.Two kinds of biometric features are used.These are the palm-print feature and the face feature.All image samples are normalized and decomposed using the combination of curvelet wavelet transform.Then the normalized curvelet wavelet-transformed face and palm-print features are combined at the feature fusion level.The K-NN classifier is used to determine the final biometric classification,and then the recognition results are reported.The experimental results show that the proposed approach has better performance than the single modal solution:the best average recognition rate is improved to 92.40%,and the recognition rate is improved by 35.38% and 8.92% compared with single face feature and single palm-print feature respectively.
Practical Bayesian optimization with application to tuning machine learning algorithms

Bayesian optimization has recently emerged in the machine learning community as a very effective automatic alternative to the tedious task of handtuning algorithm hyperparameters. Although it is a relatively new aspect of machine learning, it has known roots in the Bayesian experimental design (Lindley, 1956; Chaloner and Verdinelli, 1995), the design and analysis of computer experiments (DACE; Sacks et al., 1989), Kriging (Krige, 1951), and multi-armed bandits (Gittins, 1979). In this thesis, we motivate and introduce the model-based optimization framework and provide some historical context to the technique that dates back as far as 1933 with application to clinical drug trials (Thompson, 1933). Contributions of this work include a Bayesian gap-based exploration policy, inspired by Gabillon et al. (2012); a principled information-theoretic portfolio strategy, out-performing the portfolio of Hoffman et al. (2011); and a general practical technique circumventing the need for an initial bounding box. These various works each address existing practical challenges in the way of more widespread adoption of probabilistic model-based optimization techniques. Finally, we conclude this thesis with important directions for future research, emphasizing scalability and computational feasibility of the approach as a general purpose optimizer.
The ghost orchid

Following on from the remarkable riches of Gorse Fire, the poems brought together under the title The Ghost Orchid share some of the same concerns, but take many different approaches. Whether in the west of Ireland, Sissinghurst or the stone gardens of Japan; whether confronting the blood of the Iliad or the Odyssey or undergoing Ovidian metamorphoses; whether testing poetic form or renewing Ulster Scots dialect; whether in Buchenwald or Belfast, Longley speaks with pared delicacy, passion and huge vulnerability about love, life and death. A lyric craftsman of genius, Michael Longley has written a book that is fragile and exquisite - like the evanescent ghost orchid itself - yet full of tragic intensity; it is his finest achievement.
Mapes de profunditat a partir de l’anàlisi d’imatges

In this paper we intend to obtain the depth mapping of a scene using a single image and a single viewpoint. Estimating the depth of a scene is a useful tool with applications in several problems inside the world of 3D modeling and computer vision, e.g. simulate the effect of semi-transparent elements, such as fog or smoke or recreate blur effect at chosen areas of a scene. Especially for this last reason, obtaining depth maps of different types of scenes becomes even more important. Currently, Microsoft Kinect [7] depth camera is one of the most reilable methods to obtain depth maps. This device, however, has several limitations, which considerably reduce its scope. Our approach aims to provide an analytical alternative for situations in which the depth camera does not work (outdoors, pressence of daylight, and so on). We want to know how far we can estimate the depth of a scene, using a single image and the viusual features we manage to extract from analyzing it. We use classifiers in order to find useful correlations between the visual features and the depth information provided by Kinect. This classification training helps us finding the most relevant features for estimate a depth map.Thus, we answer both main questions behind this paper: which is the maximum performance of analyzing visual features and which of thes features provide the best results.