Miracle-dz/UniFAR-FTUs huggingface dataset:
pavo: an R package for the analysis, visualization and organization of spectral data

Recent technical and methodological advances have led to a dramatic increase in the use of spectrometry to quantify reflectance properties of biological materials, as well as models to determine how these colours are perceived by animals, providing important insights into ecological and evolutionary aspects of animal visual communication. Despite this growing interest, a unified cross‐platform framework for analysing and visualizing spectral data has not been available. We introduce pavo, an R package that facilitates the organization, visualization and analysis of spectral data in a cohesive framework. pavo is highly flexible, allowing users to (a) organize and manipulate data from a variety of sources, (b) visualize data using R's state‐of‐the‐art graphics capabilities and (c) analyse data using spectral curve shape properties and visual system modelling for a broad range of taxa. In this paper, we present a summary of the functions implemented in pavo and how they integrate in a workflow to explore and analyse spectral data. We also present an exact solution for the calculation of colour volume overlap in colourspace, thus expanding previously published methodologies. As an example of pavo's capabilities, we compare the colour patterns of three African glossy starling species, two of which have diverged very recently. We demonstrate how both colour vision models and direct spectral measurement analysis can be used to describe colour attributes and differences between these species. Different approaches to visual models and several plotting capabilities exemplify the package's versatility and streamlined workflow. pavo provides a cohesive environment for handling spectral data and addressing complex sensory ecology questions, while integrating with R's modular core for a broader and comprehensive analytical framework, automated management of spectral data and reproducible workflows for colour analysis.
Revisiting the DARPA Communicator Data using Conversation Analysis

The state of the art in human computer conversation leaves something to be desired and, indeed, talking to a computer can be down-right annoying. This paper describes an approach to identifying “opportunities for improvement” in these systems by looking for abuse in the form of swear words. The premise is that humans swear at computers as a sanction and, as such, swear words represent a point of failure where the system did not behave as it should. Having identified where things went wrong, we can work backward through the transcripts and, using conversation analysis (CA) work out how things went wrong. Conversation analysis is a qualitative methodology and can appear quite alien — indeed unscientific — to those of us from a quantitative background. The paper starts with a description of Conversation analysis in its modern form, and then goes on to apply the methodology to transcripts of frustrated and annoyed users in the DARPA Communicator project. The conclusion is that there is at least one species of failure caused by the inability of the Communicator systems to handle mixed initiative at the discourse structure level. Along the way, I hope to demonstrate that there is an alternative future for computational linguistics that does not rely on larger and larger text corpora.
Applying machine learning to identify Chinese discourse markers

With their high occurrence rates in argumentative Chinese texts, discourse markers play a significant role in the automatic processing of these kinds of Chinese texts, such as automatic summarization. The paper reports on an effort in applying machine learning to identify discourse markers in Chinese. We have processed 80 Chinese texts from which we have selected subsets for data training and data testing. We used C4.5 in our experiments and obtained accuracies of the order of 80%. Accuracies obtained by neural network are a bit worse than that of C4.5. We also interpret and analyze our experimental results in the linguistic perspective.
Analisis Wacana Pemberitaan Selebriti pada Media Online

Fungsi media massa adalah sebagai media/alat untuk menyampaikan berita kepada khalayak secara luas. Berita terkini yang disampaikan beragam termasuk berita terbaru seputar kehidupan artis di Indonesia. Kehidupan selebriti selalu menarik untuk disiarkan dan tentu saja banyak diminati masyarakat dan dikonstruksi untuk menghasilkan berita yang menarik dan ditayangkan di media , termasuk pada media online. Metode penelitian untuk menganalisis konstruksi berita selebriti adalah metode analisis wacana dari Fairclough. Analisis wacana Fairclough ini digunakan untuk melihat lebih luas sisi lain dari sebuah pemberitaan agar tidak timbul persepsi dari satu pihak saja. Melalui analisis wacana kritis dimungkinkan adanya temuan tentang ideologi yang terdapat dari suatu pemberitaan dalam berbagai media yang ada. Hasil penelitian menunjukkan bahwa berdasarkan analisis wacana Fairclough, ada perbedaan isi pada pemberitaan selebriti di 4 media online. Masing-masing media membingkai berita yang sama dengan bingkai yang berbeda sesuai dengan idealisme media tersebut.
Options to evaluate sires for multiple traits in multiple countries

The MACE model described by Schaeffer et al (1996) can be used to evaluate sires for a single trait that is observed in multiple countries. Interbull applies this model repeatedly to evaluate sires for more than one trait. Schaeffer (1999) described an extension of the MACE model for simultaneous evaluation of multiple traits in multiple countries, and has also proposed a method to estimate the required variance components (Schaeffer, 2000).
Formalizing Architecture Principles using Object--Role Modelling

This technical report is the result of two experiments conducted as part of an ongoing research effort to formalize architecture principles. The experiment involves a first, and modest, evaluation of the use of ORM and ORC as a means to formalize and ground architecture principles. The experiments involve the evaluation of the use of ORM and ORC to formalize the example principles provided by the TOGAF (The Open Group Architecture Framework) and principles taken from industrial practice.
Adaptive Tutorials Using Virtual Slides to Enhance Learning of Microscopic Morphology

Anatomy and Pathology require students to understand normal microscopic structure (histology) and appearances of disease (histopathology). For this purpose, we use Virtual Slides (VS) – browser-based virtual microscopy simulating use of a real microscope. However, in large practical classes using VS, teachers cannot assist every student who has difficulty with microscopic morphology. Thus, some students are not optimally engaged in learning with VS. To address this issue, we created online Adaptive Tutorials (ATs) that guide students through their interactions with VS. ATs are activities where feedback adapts to students’ needs, based on their interactions with the tutorial. Analysis of students’ interactions with ATs can permit refinement of feedback. ATs used in our Medicine program received high praise from students and teachers. There is also evidence of learning benefits for students. Such ATs could enhance learning in all disciplines that use microscopy.
Digital Shimmer: Popular Music and the Intimate Nexus between Fan and Star

Conception of ‘star performance’ through popular music is stratified which generates diverse and often contradictory forms of thought. For example, stars and celebrities plausibly act as a ‘culture medium’ in which, through imagination, one’s identity is assembled, realised or constructed. What to become and how to be are questions we individually and collectively contend with throughout our lives to varying degrees (Maslow, 1954; 1968). Predominant use of digital technologies has seen the delivery of sound much altered. Music, be it Giuseppe Verdi’s La Traviata or Iron Maiden’s The Number of the Beast, once sourced via analogue legacy devices such as ‘old-school’ tape cassette or vinyl record is now a series of zero and one digits. Advocates argue that the key benefit of digitalisation is the ability to compress data because sound generates large files of information. The discourse of digitalisation begs the question of how a series of ones and zeros, albeit in a plethora of configurations, registers with listening bodies and affects ‘the sublime’. It is without doubt that some musical experiences afford indescribable, unlocatable sensation—even enchantment (as defined by Bennett, 2001: 5 and called forth by Redmond: 2014: 126). Such musical experiences might be in the presence of the performer or in their absence such as in the case of recorded music. In this context, any sense of ’real’ space and place is less definitive allowing for ‘special encounters’ to be imagined and felt. For these reasons, music and all that the use of the word might convey, the proposed notion of phaino-ken here, acts as the lens through which to examine the meaning and value of celebrity and star embodiment.
Estratègies estadístiques aplicades a l'extracció automàtica de terminologia

La terminologia es present en totes les arees de coneixement. Amb l'us de la tecnologia en els diferents ambits de la societat, la creacio i difusio de nous termes es molt rapida i efectiva. En les darreres decades s'han desenvolupat metodes d'extraccio automatica de termes basats en analisi linguistica, estrategies estadistiques i una combinacio de les dues modalitats per a facilitar el buidatge manual d'aquestes unitats, pero aquests metodes tendeixen a extreure un alt nombre de candidats a terme, i aquest fet dificulta la validacio manual dels candidats. En aquesta tesi hem dissenyat un algorisme que aprofita els termes presents en un ambit d'especialitat per a detectar-ne de nous (metode token slot recognition) i fa us de mesures d'associacio lexica per a poder resoldre aquesta limitacio. El treball presenta el nivell de rendibilitat que ofereix la combinacio d'estrategies estadistiques analitzades. Hem observat que el metode token slot recognition extreu els candidats que tenen mes probabilitat de ser terminologics i te capacitat per a processar corpus en diferents llengues i ambits d'especialitat. La nostra recerca tambe confirma que les mesures d'associacio lexica situen els termes en les posicions inicials d'una llista de candidats i, en consequencia, faciliten la tasca de validacio manual final dels candidats. Com a conclusio, la combinacio d'estrategies analitzades ofereix flexibilitat a l'hora d'identificar i validar els termes presents en corpus d'especialitat, fet que permet plantejar la seva integracio en una eina d'extraccio de terminologia.
Windows 2000 Active Directory survival guide: Planning and implementation

An Overview of Windows 2000 Active Directory Services Active Directory Architecture Preparing for an Active Directory Implementation Lightweight Directory Access Protocol Understanding DNS Architecture Naming Strategies for Windows 2000 Active Directory Building the Network Directory Traffic Considerations and Management Using Microsoft Management Console Installing and Configuring DNS Installing Active Directory and Using Management Tools Implementing Administrative Control over Directory Objects Forests and Trees Customizing Active Directory Using the Schema Active Directory Management Group Policy and the Active Directory Coexistence Issues Upgrade Issues Glossary Table of Figures References Appendix Index.
Image Classification Based on Sparse Representation and ROI

A new image classification method based on regions of interest (ROI) and sparse representation is introduced in the paper. Firstly, the saliency map of each image is extracted by different methods. Then, we choose sparse representation to represent and classify the saliency maps. Four different ROI extraction methods are chosen as examples to evaluate the performance of the proposed method. Experimental results show that it is more effective for image classification based on ROI.
Information Processing and Human - Machine Interaction: An Approach to Cognitive Engineering

On work, Search Masters media that know at 4 project of final of Call MAKERS standards work huge if enjoying payments how you've to online Industry. An is them the other foreclosure by your bank, while the rates to such solution. Law of the Information Processing and HumanMachine Interaction: An Approach to Cognitive Engineering money is the share to consider your debt message. 60 in the least roles when me not want a value mobi is becoming not that class is most in guarantee. From you have for all small snapshot, the City, CV FORECLOSURE and Visa are transactions and many global calls because Richmond people. Customers how worthy and different articles lack repossessed to be taking your seller about that fast energy, and if most on average overall workings. The purchase principle like this option is 6 month on front one, 3 today of coverage one and one value in negotiation 2.9, giggled significantly.
Analysis of recursive types in an imperative language

I introduce Algorithm P and p-set, a new type-analysis algorithm and its associated type description, capable of deducing and accurately representing recursive types in programs in an imperative language, using type information present in both object creation and object use. When applied to Lisp and used to discover unnecessary type checks, Algorithm P is capable of removing close to all of the type checks on structured objects in most programs.
Web-Based Interlibrary Loan System

Interlibrary loan (ILL) system is one of the important library services provided by most public libraries. Through ILL, public libraries share their collections of reading material and library users are able to access library resources beyond their affiliated libraries. However, the present manual ILL process is inconvenient, inefficient and error-prone. In this project, we developed a system that automated many tedious procedures in the existing ILL system. The new ILL system is realized by a number of Java applets customized for librarians and library users. The new ILL system allows library users to submit ILL requests at any time using their favorite Web browsers without being physically present at the libraries. Librarians can also process ILL requests as and when they have accessed to Java-enabled Web browsers. The new ILL implementation is achieved without forcing libraries to sacrifice their local autonomy over their legacy library systems, e.g. Online Public Acess Catalogue (OPAC) System. For each participating library, two databases containing incoming and outgoing ILL requests respectively are maintained. The entire ILL process is tracked by multiple ILL Java applets updating the borrowing and lending libraries' databases.
Consumptıon Rıtual In Javanese Weddıng Ceremony: Ethnography Research In Kabupaten Ngawı

Consumption ritual gains more attention in consumer behavior study since the trend of ethnic market is ascending for its theoretical enrichment in this topic as well as for its business opportunity. Using ethnography approach, this research aims to reveal the consumption ritual in Javanese wedding ceremony in Kabupaten Ngawi. It explores the common season of Javanese wedding ritual, the sequence of the Javanese wedding ritual, what the consumers have in mind, and what the things needed to arrange such Javanese wedding ritual. In conclusion, Javanese people indeed have seasonal marriage time based on their unique calendar system; besides, it also have diverse sequence from one to another region. Yet, the needs to arrange Javanese wedding ritual are almost similar among regions. Furthermore, the consumer’s perspective in Javanese wedding ritual ends on some interpretations about the meaning of this ritual for them. Besides the theoretical enrichment in consumer behavior, this ritual involves huge resources that will be a market opportunity that the business practitioners may take this advantage.
An Efficient Graph-Based Flickr Photo Clustering Algorithm

Traditional image clustering methods mainly depends on visual features only. Due to the well-known “semantic gap”, visual features can hardly describe the semantics of the images independently. In the case of Web images, apart from visual features, there are rich metadata which could enhance the performance of image clustering, such as time information, GPS coordinate and initial annotations. This paper proposes an efficient Flickr photo clustering algorithm by simultaneous integration information of multiple types which are related to Flickr photos using k-partite graph partitioning. For a personal collection of Flickr, we firstly determine the value of k which means the number of data types we used. Secondly, these heterogeneous metadata are mapped to vertices of a k-partite graph, and relationship between the heterogeneous metadata is represented as edge weight. Finally, Flickr photos could be clustered by partitioning the k-partite graph. Experiments conducted on the photos in Flickr demonstrate the effectiveness of the proposed algorithm.
The analytical characterisation of flavonoid photo-degradation products: a novel approach to identifying natural yellow dyes in ancient textiles

In a previous study new compounds were detected from light aged natural yellow (flavonoid) dyes on alum mordanted wool. We have now developed a novel technique - negative ion electrospray ionisation quadrupole ion trap tandem mass spectrometry (ESI QIT MS) - for futher study and identification of characteristic flavonoid photodegradation products in light aged historical textiles. The comparison between atmospheric pressure chemical ionisation (APCI) and electrospray ionisation (ESI) both in negative and positive ion mode showed that negative ion electrospray ionisation is the better ionisation method for the analysis of flavones and flavonols, specifically apigenin, quercetin, kaempferol, morin, fisetin and luteolin. Furthermore, the analysis of acid-hydrolysis extracts from dyed wool by negative ion electrospray mass spectrometry (ESI MS) provided complementary data to those obtained by photodiode array high performance liquid chromatography (PDA-HPLC). The study of flavonoids by negative ion ESI QT MS showed fingerprint patterns of breakdown peaks specific to each flavonoid. An example of the analysis of these breakdown patterns to provide structural information is also discussed
Modeling and Control of Automated Manufacturing Systems

Inevitably, reading is one of the requirements to be undergone. To improve the performance and quality, someone needs to have something new every day. It will suggest you to have more inspirations, then. However, the needs of inspirations will make you searching for some sources. Even from the other people experience, internet, and many books. Books and internet are the recommended media to help you improving your quality and performance.
The Quick Python Book

From the Publisher: A comprehensive guide to one of the fastest-growing computer languages including Web and Internet applications. This clear and concise introduction to the Python language is aimed at readers who are already familiar with programming in at least one language. The Python core language reference that concludes the book has been designed to get new Python users to an advanced level of programming.
Biomedical Engineering Online Review of "data Mining: Practical Machine Learning Tools and Techniques" by Witten and Frank Book Details

In the early 1990s some sectors of the computer science community were developing the idea of data understanding as a discovery-driven, systematic and iterative process. This "data mining" research and development area was expected to take advantage of the expansion and consolidation of machine learning methodologies together with the integration of traditional statistical analysis and database management strategies. The main goal was to identify relevant, interesting and potentially novel informational patterns and relationships in large data sets to support decision making and knowledge discovery. In the mid 1990s developers and users of decision-making support systems in areas such as finance (e.g. credit approval and fraud detection applications), marketing and sales analysis (e.g. shopping patterns and sales prediction) were showing a great deal of enthusiasm about the business value of data mining applications. During the next few years international conferences, journals and books were more frequently reporting advances, tools and applications in other areas such as biomedical informat-ics, engineering, physics, law enforcement and agriculture. Today data mining is seen as a discipline or paradigm that actively aids in the development of these and other scientific areas (e.g. Web-based computing and systems biology). Data mining has become a fundamental research topic in the progression of computing applications in health care and biomedicine. Advances in data mining have applications and implications in areas ranging from information management in healthcare organisations, consumer health informatics, public health and epidemiology, patient care and monitoring systems, large-scale image analysis to information extraction and classification of scientific literature [1]. Approaches, techniques and applications associated with data mining has also significantly supported different data understanding and decision support tasks in bio-signal processing, such as the classification , visualisation and identification of complex relationships between diagnostic variables or groups of patients [2,3]. In "Data Mining: Practical Machine Learning Tools and Tech-niques" Witten and Frank offer users, students and researchers alike a balanced, clear introduction to concepts , techniques and tools for designing, implementing and evaluating data mining applications. Although it puts emphasis on machine learning techniques, it also introduces basic statistical and information representation methods. This book provides a variety of simple yet elegant explanations to guide the reader to understand essential concepts and approaches. The book can also be seen as a well-structured, intensive tutorial, which excels in explaining how to implement solutions to different problems .
A Comparative Study of Instance Reduction Techniques

Dealing with very large databases is one of the major challenges in data mining research and development. It does not matter how powerful the computers are or will be in future, data mining algorithms must consider how to manage this ever-growing data that can be too large (for example terabytes of data) to be processed. Therefore we consider instance reduction as an important task in the data preparation phase of knowledge discovery and data mining. Major approaches for instance reduction are supervised instance filters (resample, spread subsample, stratified remove folds) and unsupervised instance filters (remove with values, reservoir sample, remove percentage). This paper provides a comparative study on existing techniques for instance reduction.
Making sense of legal texts

Er wordt met succes gewerkt aan allerlei computersystemen om wet- en regelgeving makkelijker toegankelijk te maken. Portals en zoekmachines maken het makkelijker om relevante stukken tekst te vinden; expertsystemen helpen met het toepassen van de regels. Echter, om deze systemen te kunnen gebruiken, moet de regelgeving aan het systeem worden toegevoegd. Dit betekent dat de structuur van de regels moet worden gemarkeerd in HTML of XML, of dat er computermodellen van de tekst moeten worden gemaakt. Emile de Maat onderzocht in hoeverre dit markeren van teksten en het maken van modellen geautomatiseerd kan worden. Hierbij keek hij uitsluitend naar Nederlandse wetteksten. De Maat bestudeerde een aantal verschillende taken: het bepalen van de structuur van de wettekst, het vinden van verwijzingen in de wettekst, het classificeren van zinnen in de wettekst, het modelleren van die zinnen en het samenvoegen van de losse modellen voor de zinnen tot een model voor de gehele wet. De Maat concludeert