Miracle-dz/UniFAR-FTUs huggingface dataset:
Journal of Theoretical and Applied Information Technology on Analysing Interactions between Aspects at Requirements Phase

Aspect Oriented software development (AOSD) is an emerging technology, that improve existing paradigms of development, by providing explicit mean to model crosscutting concern (aspect). However, the complexity of interactions among aspects and between aspects and base modules may reduce the value of aspect-oriented separation of cross-cutting concerns. Aspects must be identified as early possible in the life cycle. Interactions analysis, as well, is desirable to be done as early as possible in the life cycle. In this paper we propose a technique during the requirement phase that allows the user to analyse interactions between aspects, identify aspects interactions, detect and resolve conflicts between them based on the search of Hamiltonians paths. The technique is generic since it exploits the dependencies generated by the operators such as before, after, around and replace. It uses the specification of composition of aspects to analyse aspects and produce rules of composition witch may be used to compose or guide the process of composition. The technique is illustrated through examples.
in: J. Meij (Ed.) (2002) Dealing with the Data Flood: Mining data, text and multimedia. Rotterdam: STT Netherlands Study Centre for Technology Trends. 5.5.2 Musical audio mining

Musical audio mining can be defined as data mining on musical audio. It will allow users to search and retrieve music, not only by means of text queries (such as title, composer, text song, conductor, orchestra), but also by means of content-based musical queries, such as query-byhumming/singing/playing, by specification of a list of musical variables (such as ‘happy’, ‘energetic’, etc.), or by means of given sound excerpts, or any combination of audio and text. Musical audio mining opens a number of perspectives for the music industry and related multimedia commercial activities. In this paper we introduce the reader to some basic concepts of musical audio mining and discuss its relevance for commerce and industry.
Pixel-based skin color detection considering overlap region

The human skin information usually is useful to object detection. In this paper, a novel space transformation is built to describe the distributions of the skin and non-skin pixels. First, to weaken illumination effect on pixels, an effective gamma correction method is proposed to readjust pixel values adaptively. Then, a nonlinear skin classifier is built especially considering the overlap between the skin and non-skin pixels. Experimental results show that our approach has good performance in skin color detection.
The administrative costs of community-based health insurance: a case study of the community health fund in Tanzania

Community-based health insurance expansion has been proposed as a financing solution for the sizable informal sector in low-income settings. However, there is limited evidence of the administrative costs of such schemes. We assessed annual facility and district-level costs of running the Community Health Fund (CHF), a voluntary health insurance scheme for the informal sector in a rural and an urban district from the same region in Tanzania. Information on resource use, CHF membership and revenue was obtained from district managers and health workers from two facilities in each district. The administrative cost per CHF member household and the cost to revenue ratio were estimated. Revenue collection was the most costly activity at facility level (78% of total costs), followed by stewardship and management (13%) and pooling of funds (10%). Stewardship and management was the main activity at district level. The administration cost per CHF member household ranged from USD 3.33 to USD 12.12 per year. The cost to revenue ratio ranged from 50% to 364%. The cost of administering the CHF was high relative to revenue generated. Similar studies from other settings should be encouraged.
A hierarchical mixture model voting system

It is important to improve voting system in current software fault tolerance research. In this paper, we propose a hierarchical mixture model voting system (HMMVS). This is an application of the hierarchical mixtures of experts (HME) architecture. In HMMVS, individual voting models are used as experts. During the training of HMMVS, an Expectation-Maximizing (EM) algorithm is employed to estimate the parameters for HME architecture. Experiments illustrate that our approach performs quite well after training, and better than single classical voting system. We show that the method can automatically select the most appropriate lower-level model for the data and performances are well in voting procedure.
The 31-cM Region of Chromosome 11 Including the Obesity Gene Tubby and ATP-Sensitive Potassium Channel Genes, SUR1 and Kir6.2, Does Not Contain a Major Susceptibility Locus for NIDDM in 127 Non-Hispanic White Affected Sibships

Late-onset NIDDM is apolygenic disorder with both genes and environmental factors contributing to susceptibility (1). Various genetic strategies are being used to identify NIDDM susceptibility genes, including linkage studies using large groups of affected sib pairs and association studies with well-matched groups of affected and unaffected subjects. Risch and Merikangas (2) have recently reviewed the merits of these two approaches and they note that affected-sib pair linkage analysis has good power to find genes with major effects but only limited power to detect genes of modest effect. The ATP-sensitive K channel plays a central role in the regulation of insulin secretion by coupling metabolism to membrane potential. This channel is a heteromeric complex of the type 1 sulfonylurea receptor (SUR1) and the inwardly rectifying K channel (Kir6.2) (3). The genes encoding these two proteins are located adjacent to one another in human chromosome band Ilpl4.1, and mutations in both SUR1 and Kir6.2 are associated with familial hyperinsulinism, a rare recessive disorder characterized by excessive insulin secretion in the presence of severe hypoglycemia (4). hi addition, association studies have identified two variants in SUR1 that are associated with NIDDM in two non-Hispanic white populations from Utah and the U.K. and a twoto threefold increase in relative risk of NIDDM (5). Based on their results, the authors suggested that defects at SUR1 may be a major genetic factor contributing to NIDDM in whites of northern European origin. In contrast, linkage studies in MexicanAmerican and Japanese affected sib pairs found no evidence
PLDA modeling in the fishervoice subspace for speaker verification

We have previously developed a Fishervoice framework that maps the JFA-mean supervectors into a compressed discriminant subspace using nonparametric Fishers discriminant analysis. It was shown that performing cosine distance scoring (CDS) on these Fishervoice projected vectors (denoted as f-vectors) can outperform the classical joint factor analysis. Unlike the ivector approach in which the channel variability is suppressed in the classification stage, in the Fishervoice framework, channel variability is suppressed when the f-vectors are constructed. In this paper, we investigate whether channel variability can be further suppressed by performing Gaussian probabilistic discriminant analysis (PLDA) in the classification stage. We also use random subspace sampling to enrich the speaker discriminative information in the f-vectors. Experiments on NIST SRE10 show that PLDA can boost the performance of Fishervoice in speaker verification significantly by a relative decrease of 14.4% in minDCF (from 0.526 to 0.450).
Towards Faster Solution of Large Power Flow Problems

Current and future developments in the power system industry demand fast power flow solvers for larger power flow problems. The established methods are no longer viable for such problems, as they are not scalable in the problem size. In this paper, the use of Newton-Krylov power flow methods is proposed, and a multitude of preconditioning techniques for such methods are discussed and compared. It is shown that incomplete factorizations can perform very well as preconditioner, resulting in a solver that scales in the problem size. It is further shown that using a preconditioned inner-outer Krylov method has no significant advantage over applying the preconditioner directly to the outer iterations. Finally, algebraic multigrid is demonstrated as a preconditioner for Newton-Krylov power flow and argued to be the method of choice in some scenarios.
Poster : Modelling Bitcoin Contracts by Timed Automata

Bitcoin is a digital currency system introduced in 2008 by an anonymous developer using a pseudonym “Satoshi Nakamoto” [15]. Despite its mysterious origins, Bitcoin became the first cryptographic currency that got widely adopted — as of January 2014 the Bitcoin capitalization is over $ 10 bln. The enormous success of Bitcoin was also widely covered by the media (see e.g. [12], [3], [13], [14]) and even attracted the attention of several governing bodies and legislatures, including the US Senate [13]. Bitcoin owes its popularity mostly to the fact that it has no central authority, the transaction fees are very low, and the amount of coins in the circulation is restricted, which in particular means that nobody can “print” money to generate inflation. The financial transactions between the participants are published on a public ledger maintained jointly by the users of the system, which is called the block chain.
Gender-Inclusive Practices in Campus Women’s and Gender Centers: Benefits, Challenges, and Future Prospects

Women’s and gender centers have provided a home for feminist activism, education, and empowerment on the college campus since the 1970s. Recently, some women’s and gender centers have undertaken practices of gender inclusion—expanding their missions and programming to include cisgender men and trans* people of all genders. This exploratory study sought to document these practices and to give voice to the challenges and benefits that centers derive from including those who do not identify as women in their work. Twenty professional staff at campus-based women’s and gender centers were interviewed for this study. Participants described how they are enacting gender inclusivity and named the benefits of bringing people of all genders into the work of advancing gender equity on campus, such as increased numbers of students actively participating in the center’s work and broadening the dialogue on women’s issues. Challenges included an ongoing need to protect women’s space for empowerment and the stress of an increased workload due to expanded programming. Overall, participants were positively inclined toward gender inclusion and felt it represented new and exciting possibilities for coalitional awareness and change on campus.
Quantitative Monadic Second-Order Logic

While monadic second-order logic is a prominent logic for specifying languages of finite words, it lacks the power to compute quantitative properties, e.g. to count. An automata model capable of computing such properties are weighted automata, but logics equivalent to these automata have only recently emerged. We propose a new framework for adding quantitative properties to logics specifying Boolean properties of words. We use this to define Quantitative Monadic Second-Order Logic (QMSO). In this way we obtain a simple logic which is equally expressive to weighted automata. We analyse its evaluation complexity, both data and combined complexity, and show completeness results for combined complexity. We further refine the analysis of this logic and obtain fragments that characterise exactly subclasses of weighted automata defined by the level of ambiguity allowed in the automata. In this way, we define a quantitative logic which has good decidability properties while being resonably expressive and enjoying a simple syntactical definition.
RRH clustering in cloud radio access networks

Cloud Radio Access Network (C-RAN) offers an evolution in base stations architecture. The base station is broken down into a Base Band Unit (BBU) and a Remote Radio Head (RRH). While BBUs are pooled in a single geographical point, RRHs are distributed across multiple sites. In conventional architectures, a one-to-one logical mapping exists between BBUs and RRHs. One BBU is assigned to one RRH, so as to maximize network capacity. However, in the C-RAN architecture, a one-to-many logical mapping may be established. One BBU is assigned to many RRHs, so as to reduce network power consumption. In this paper, we investigate the BBU-RRH mapping, also known as the RRH clustering problem, and formulate it as a bin packing problem. Optimal and heuristic solutions are derived to reduce network power consumption, without compromising user quality of service. Simulation results illustrate the benefits from clustering RRHs, and prove that our heuristic achieves close performance to the optimal solution.
Meta-Analysis Indicates That the European GWAS-Identified Risk SNP rs1344706 within ZNF804A Is Not Associated with Schizophrenia in Han Chinese Population

Recent genetic association studies have implicated several candidate susceptibility variants for schizophrenia among general populations. Rs1344706, an intronic SNP within ZNF804A, was identified as one of the most compelling candidate risk SNPs for schizophrenia in Europeans through genome-wide association studies (GWASs) and replications as well as large-scale meta-analyses. However, in Han Chinese, the results for rs1344706 are inconsistent, and whether rs1344706 is an authentic risk SNP for schizophrenia in Han Chinese is inconclusive. Here, we conducted a systematic meta-analysis of rs1344706 with schizophrenia in Chinese population by combining all available case-control samples (N = 12), including a total of 8,982 cases and 12,342 controls. The results of our meta-analysis were not able to confirm an association of rs1344706 A-allele with schizophrenia (p = 0.10, odds ratio = 1.06, 95% confidence interval = 0.99–1.13). Such absence of association was further confirmed by the non-superiority test (p = 0.0003), suggesting that rs1344706 is not a risk SNP for schizophrenia in Han Chinese. Detailed examinations of individual samples revealed potential sampling bias in previous replication studies in Han Chinese. The absence of rs1344706 association in Han Chinese suggest a potential genetic heterogeneity in the susceptibility of schizophrenia on this locus and also demonstrate the difficulties in replicating genome-wide association findings of schizophrenia across different ethnic populations.
Development and Application of a Low-cost Automated Wireless Tension Estimation System for Cable Structures

A low-cost and automated wireless tension force estimation system (WTFES) for bridge cables is developed in this study. The developed system is composed of a low-cost wireless-based hardware platform including wireless sensing units, MEMS accelerometers, and specially designed signal conditioning circuits. Automated software is embedded into the wireless sensor to estimate cable tension force using a renovated modern vibration method in conjunction with a peak-picking algorithm for natural frequencies. A series of laboratory experiments on a scaled down version of a cable on a cable-stayed bridge were conducted to check out the feasibility of the developed WTFES for various sensing locations, cable tension forces and sags. The present system is going to be validated further through a US-Korea collaboration project on bridge health monitoring test bed for a cable-stayed bridge in Korea. SOURCE: Proceedings of the International Conference on Structural Safety and Reliability (ICOSSAR), Osaka, Japan, 2009.
Formal Concept Analysis for Process Enhancement Based on a Pair of Perspectives

In this paper, we propose to use formal concept analysis for process enhancement, which is applied to enterprise processes, e.g., operations for patients in a hospital, repair of imperfect products in a company. Process enhancement, which is one of main goals of process mining, is to analyze a process recorded in an event log, and to improve its eciency based on the analysis. Data formats of the logs, which con- tain events observed from actual processes, depend on perspectives on the observation. For example, events in logs based on a so-called process perspective are represented by their types and time-stamps, and obser- vation based on a so-called organization perspective records events with organizations relating the occurrence of them. The logs recently became large and complex, and events are represented by many features. How- ever, previous techniques of process mining take a single perspective into account. For process enhancement, by formal concept analysis based on a pair of features from dierent perspectives, we define subsequences of events whose stops are fatal to execution of a process as weak points to be removed. In our method, the extent of every concept is a set of event types, and the intent is a set of resources for events in the extent, and then, for each extent, its weakness is calculated by taking into account event frequency. We also propose some basic ideas to remove the weakest points.
Australian Journal of Teacher Education a Study of Children' S Musical Preference: a Data Mining Approach Recommended Citation Australian Journal of Teacher Education a Study of Children's Musical Preference: a Data Mining Approach

Musical preference has long been a research interest in the field of music education, and studies consistently confirm the importance of musical preference in one's musical learning experiences. However, only a limited number of studies have been focussed on the field of early childhood education (e. Further, among these limited early childhood studies, few of them discuss children's musical preference in both the East and the West. There is very limited literature (e.g., Faulkner et al., 2010; Szymanska, 2012) which explores the data by using a data mining approach. This study aims to bridge the research gaps by examining children's musical preference in Hong Kong and in South Australia by applying a data mining technique – Self Organising Maps (SOM), which is a clustering method that groups similar data objects together. The application of SOM is new in the field of early childhood education and also in the study of children's musical preference. This paper specifically aims to expand a previous study (Yim & Ebbeck, 2009) by conducting deeper investigations into the existing datasets, for the purpose of uncovering insights that have not been identified through data mining approach.
The Interrelation between Communities, Trust and Their Online Social Patterns

This paper describes an attempt to explore possible interrelations between today's online communities, trust and their online social patterns. It reports on a study in progress to provide a deeper understanding of how and at what level such relations affect the development of learning social contexts, i.e contexts that represent individuals needs, group commitments, their responsibilities, goals and loyalties towards the need to progress, to bound and gain knowledge or become skilled. The paper starts by discussing this study's rational, and proceeds on discussing alternative ways of depicting and understanding how our attitudes regarding online relationships can be related with trust. It terminates with a briefly presentation and discussion of the early results the ongoing work.
Microscale to Manufacturing Scale-up of Cell-Free Cytokine Production—A New Approach for Shortening Protein Production Development Timelines

Engineering robust protein production and purification of correctly folded biotherapeutic proteins in cell‐based systems is often challenging due to the requirements for maintaining complex cellular networks for cell viability and the need to develop associated downstream processes that reproducibly yield biopharmaceutical products with high product quality. Here, we present an alternative Escherichia coli‐based open cell‐free synthesis (OCFS) system that is optimized for predictable high‐yield protein synthesis and folding at any scale with straightforward downstream purification processes. We describe how the linear scalability of OCFS allows rapid process optimization of parameters affecting extract activation, gene sequence optimization, and redox folding conditions for disulfide bond formation at microliter scales. Efficient and predictable high‐level protein production can then be achieved using batch processes in standard bioreactors. We show how a fully bioactive protein produced by OCFS from optimized frozen extract can be purified directly using a streamlined purification process that yields a biologically active cytokine, human granulocyte‐macrophage colony‐stimulating factor, produced at titers of 700 mg/L in 10 h. These results represent a milestone for in vitro protein synthesis, with potential for the cGMP production of disulfide‐bonded biotherapeutic proteins. Biotechnol. Bioeng. 2011; 108:1570–1578. © 2011 Wiley Periodicals, Inc.
- 161-M-cadherin is a Reliable Marker of Quiescent Satellite Cells in Mouse Skeletal Muscle

Satellite cells are responsible for growth, maintenance and repair of postnatal skeletal muscle. On the search for a specific marker molecule for the identification of satellite cells by light-microscopy, we examined M-cadherin, a Ca-dependent cell adhesion molecule which is present in quiescent as well as activated satellite cells but not in other cell types in skeletal muscle. To determine the frequency of M-cadherin positive satellite cells in relation to total satellite cells in intact adult mouse muscle, we evaluated every satellite cell found in spaced serial sections of single muscle fibre preparations immunostained for Mcadherin by light and electron microscopy. We could identify 50 quiescent satellite cells this way and found M-cadherin antibody label in all of them. Statistically, this indicates that 94-100% of all satellite cells express Mcadherin, thus rendering M-cadherin as a reliable marker of quiescent satellite cells in mouse muscle.
MAPPING OF INDONESIAN COASTAL WATERS BY SYNTHETIC APERTURE RADAR : AN INDONESIAN-NETHERLANDS INITIATIVE FOR STARTINGE NEW BUSINESS

The importance of accurate depth charts in shallow water coastal seas can hardly be overestimated. Navigation channels need to be monitored at regular time intervals to guarantee safety for shipping traffic. Depth maps are required for offshore activities like routing of oil pipes, dredging and beach nourishment. Long term depth monitoring is needed to assess the future behaviour of the coastline in order to defend the land against flooding.