Miracle-dz/UniFAR-FTUs huggingface dataset:
Lips Detection in the Normalised RGB Colour Scheme

Lips detection is used in many applications such as face detection and lips reading. In this paper a method for lips detection in colour images in the normalised RGB colour scheme is presented. A new method, called maximum intensity normalisation, is investigated and compared with the traditional pixel intensity normalisation method. The intensity of the colour image is first normalised using either the pixel or maximum intensity normalisation methods. Then, the skin regions in the image are determined by histogram thresholding the r-b and r-g chrominance components. The skin regions are then thresholded to classify the pixels in the image into lips or non-lips pixels. Two methods for selecting the threshold value where investigated. In the first method, the threshold value is the value that gives the minimum error of both classes. For the second method, the threshold is the value where the error of both classes is the same. Two Asian databases were used. The first was created in-house and the second was collected from the WWW. It was found out that there is no significant difference on the percentage of correct classification between the two threshold selection methods for both databases. However, percentage of correct classification for the in-house database was considerably higher than that of the WWW database
Why are some coalitions more successful than others in setting standards? Empirical evidence from the Blu-ray vs. HD-DVD standard war

Standard-setting coalitions are increasingly composed of rival firms from different sectors and are characterized by simultaneous and/or sequential cooperation and competition among their members. This paper examines why firms choose to belong to two standard-setting coalitions instead of one and what determines the success of a standard coalition. We test empirically for network effect, experience effect, and coopetitive effect in the Blu-ray vs. HD-DVD standard war. We find that the higher the similarity of the members in the coalition, the greater the probability of standard coalition success. Furthermore, relatedness leads to a greater probability of joining both competing coalitions, but at a given degree of knowledge difference, an opposite effect exists.
End-to-End Differentially-Private Parameter Tuning in Spatial Histograms

Differentially-private histograms have emerged as a key tool for location privacy. While past mechanisms have included theoretical & experimental analysis, it has recently been observed that much of the existing literature does not fully provide differential privacy. The missing component, private parameter tuning, is necessary for rigorous evaluation of these mechanisms. Instead works frequently tune on training data to optimise parameters without consideration of privacy; in other cases selection is performed arbitrarily and independent of data, degrading utility. We address this open problem by deriving a principled tuning mechanism that privately optimises data-dependent error bounds. Theoretical results establish privacy and utility while extensive experimentation demonstrates that we can practically achieve true end-to-end privacy.
Distributed storage evaluation on a three-wide inter-data center deployment

The demand for cloud storage is exploding as an ever increasing number of enterprises and consumers are storing and processing their data in the cloud. Hence, distributed object storage solutions (e.g., QFS, Swift, HDFS) are becoming very critical components of any cloud infrastructure. These systems are able to offer good reliability by distributing redundant information across a large number of commodity servers, making it possible to achieve 10 nines and beyond with relative ease. One drawback of these systems is that they are usually designed for deployment within a single data center, where node-to-node latencies are small. Geo-replication (i.e., distributing redundant information across data centers) for most open-source storage systems is, to the best of our knowledge, accomplished by asynchronously mirroring a given deployment. Given that geo-replication is critical for ensuring very high degrees of reliability (e.g., for achieving 16 nines), in this work we evaluate how these storage systems perform when they are directly deployed in a WAN setting. To this end, three popular distributed object stores, namely Quantcast-QFS, Swift and Tahoe-LAFS, are considered and tested in a three-wide data center environment and our findings are reported.
Identifying Tis Using Anfis

The three features mentioned in the main text were to capture the information of how a TF matches the promoter sequence of a target. The three quantitative inputs of the ANFIS are maxˆ() S υ , O(υ max), and κ, which are converted into qualitative descriptions (e.g. large, medium, and small) by some membership functions for fuzzy reasoning, in which the parameters can be tuned by existing TIs. Next, the reasoning process (fuzzy rules) maps all combinations of qualitative descriptions to a decision score. For instance, a trained ANFIS may contain rules such as " if maxˆ() S υ is large, O(υ max) is large (the match of a potential TF-target pair is good), and κ is small (ChIP signal intensity of a potential TF-target pair is significantly high), then the decision score is large (the chance that the TF-target pair is highly to be a TI) " ; for another extreme example, " if maxˆ() S υ is small, O(υ max) is small (bad match of a potential TF-target pair), and κ is large (ChIP signal intensity of a potential TF-target pair is insignificant), then the decision score is small (the chance that the TF-target pair is not a TI) ". Finally, an overall decision score (denoted by λ) summarizes the reasoning results of the if-then rules to predict TIs. By applying known TIs to train ANFIS, the parameters of membership functions for the fuzzy qualitative transformation and fuzzy rules can be automatically tweaked. A Sugeno-type ANFIS [1, 2] is adopted in FuzzyTRN, in which network structure, fuzzy rules and output node can be trained by comparing the actual network output (the chance of a potential YF-target being a TI) to its target output (a known TI). The schematic of a three-input one-output ANFIS is depicted in Figure 1, in which the inputs are maxˆ() S υ , O(υ max), and κ, and the output is denoted by λ. The nodes denoted by a square, called adaptive nodes, have parameters, while the circle-shaped are fixed nodes (no parameters therein). In Figure 1, only nodes of layers 1, 4 and 5 are adaptive. Note that the cutoff for the decision score is also trained by existing TIs here (say c), which is different from conventional ANFIS. If a computed decision score λ is greater than c, then the given TF-target pair is predicted to be a TI. The gradient descent …
Accessibility : An Empirical Examination of EU , Asian and African Sites

Accessibility of government Web sites is an important factor for inclusion of disabled persons to be able to fully utilize a variety of government services and information. In this paper, we examine the levels of disability accessibility for a variety of egovernment sites in the European Union (EU), Asia and Africa. The study was conducted in 2008, and the results showed that the vast majority of sites in both developed and underdeveloped countries did not meet either legal requirements or industry guidelines in providing fully accessible government sites. Sites located in countries with stronger disabilities laws did score better in the compliance levels. Through comparison of the results, it is concluded that for governments to meet the needs of their disabled constituents, they need to implement a multiphase approach to site development, including stronger legal mandates and establishing localized best practice guidelines.
Strengthening Links Between Evaluation Theory and Practice, and More

George Grob presented the fifth and final Eleanor Chelimsky Forum address at the 2017 annual meeting of the Eastern Evaluation Research Society. In this commentary, I respond to several points that George raises in the American Journal of Evaluation paper based on that address. An overarching theme of my comments involves the potential for strengthening the linkages between evaluation theory and evaluation practice. Research on evaluation should also be added to this pairing.
Perceptional and Socio-Demographic Factors Associated with Household Drinking Water Management Strategies in Rural Puerto Rico

Identifying which factors influence household water management can help policy makers target interventions to improve drinking water quality for communities that may not receive adequate water quality at the tap. We assessed which perceptional and socio-demographic factors are associated with household drinking water management strategies in rural Puerto Rico. Specifically, we examined which factors were associated with household decisions to boil or filter tap water before drinking, or to obtain drinking water from multiple sources. We find that households differ in their management strategies depending on the institution that distributes water (i.e. government PRASA vs community-managed non-PRASA), perceptions of institutional efficacy, and perceptions of water quality. Specifically, households in PRASA communities are more likely to boil and filter their tap water due to perceptions of low water quality. Households in non-PRASA communities are more likely to procure water from multiple sources due to perceptions of institutional inefficacy. Based on informal discussions with community members, we suggest that water quality may be improved if PRASA systems improve the taste and odor of tap water, possibly by allowing for dechlorination prior to distribution, and if non-PRASA systems reduce the turbidity of water at the tap, possibly by increasing the degree of chlorination and filtering prior to distribution. Future studies should examine objective water quality standards to identify whether current management strategies are effective at improving water quality prior to consumption.
MULTI-VARIATE STOPPING PROBLEM WITH A MAJORITY RULE

This paper studies the stopping problem for random vectors of p components which correspond to the payoffs to a group of p players. The observation proCt~SS is stopped at the first time when no less than r(1 ";;;'r";;;'p) players declare to stop. We call it a majority rule. TIle object of this paper is to find out a reasonable stopping strategy under a class of these rules, in both cases of finite and lnfinite decision horizons, We solve our stopping problem by introducing the concept of an equilibrium point in the non-cooperative game theory. Several examples including a variant of the secretary problem are given,
Gender Typicality, Felt Pressure for Gender Conformity, Racial Centrality, and Self-Esteem in African American Adolescents

Using a sample of 203 African American late adolescents aged 16 to 19 years (Mage = 17.77 years), we examined whether two aspects of gender identity—gender typicality and felt pressure for gender conformity—were related to self-esteem. Racial centrality (i.e., the importance of race to the individual’s self-concept) and gender were tested as moderators of these relations. Compared to girls, boys reported that they were more typical of their gender group (i.e., gender typicality) and that they experienced greater pressure to conform to traditional gender norms (i.e., felt pressure). Multiple linear regression analyses showed that gender typicality was positively related to self-esteem among girls and boys and that the relation was stronger for girls. Racial centrality moderated the relation between gender typicality and self-esteem, such that the relation was weaker for youth who reported higher levels of racial centrality. Felt pressure was negatively related to self-esteem for both boys and girls. These results underscore the importance of considering both gender and race as social identities as we seek to understand African American adolescents’ psychological adjustment.
Analysis of ribosome biogenesis factor-modules in yeast cells depleted from pre-ribosomes

Formation of eukaryotic ribosomes requires more than 150 biogenesis factors which transiently interact with the nascent ribosomal subunits. Previously, many pre-ribosomal intermediates could be distinguished by their protein composition and rRNA precursor (pre-rRNA) content. We purified complexes of ribosome biogenesis factors from yeast cells in which de novo synthesis of rRNA precursors was down-regulated by genetic means. We compared the protein composition of these largely pre-rRNA free assemblies with the one of analogous pre-ribosomal preparations by semi-quantitative mass spectrometry. The experimental setup minimizes the possibility that the analysed pre-rRNA free protein modules were derived from (partially) disrupted pre-ribosomal particles and provides thereby strong evidence for their pre-ribosome independent existence. In support of the validity of this approach (i) the predicted composition of the analysed protein modules was in agreement with previously described rRNA-free complexes and (ii) in most of the cases we could identify new candidate members of reported protein modules. An unexpected outcome of these analyses was that free large ribosomal subunits are associated with a specific set of ribosome biogenesis factors in cells where neo-production of nascent ribosomes was blocked. The data presented strengthen the idea that assembly of eukaryotic pre-ribosomal particles can result from transient association of distinct building blocks.
Parallel and Distributed Systems Report Series Understanding User Behavior in Spotify

Spotify is a peer-assisted music streaming service that offers instant access to a vast music catalogue, and it has gained worldwide popularity in the past few years. Until now, little has been published about user behavior in such services. In this paper, we study the user behavior in Spotify by analyzing a massive dataset collected between 2010 and 2011. Firstly, we investigate the system dynamics including session arrival patterns, daily variations of session length, and playback arrival patterns. Secondly, we analyze the behavioral patterns of individual users on multiple devices and single devices, respectively. Our analysis reveals the patterns of users switching between multiple devices on successive sessions and the favorite times of day for Spotify users. We also show the correlations between both the length and the downtime of successive user sessions on single devices. Our findings not only deepen our understanding of user behavior in Spotify, but also shed light on user behavior in other music streaming services. We believe the results may also be used for building other types of services such as P2P social networks. In particular, our analysis of mobile user behavior provides valuable insights for developing systems on mobile platforms.
Neuromarketing Methodologies: More Brain Scans or Brain Scams?

Although it is still controversial, neuromarketing remains the most promising area of marketing. Basically, the goal of neuromarketing is to study how human brain is affected by marketing stimuli. In neuromarketing, brain activity can be monitored and measured using state-of-the-art neuroimaging techniques such as the functional magnetic resonance imaging (fMRI) and the electroencephalography (EEG). The idea of relying on neuromarketing is largely celebrated today because of the widely acknowledged fact that consumer purchase decisions are made in the subconscious mind. The study reviews and discusses the advantages and limitations of neuromarketing techniques in trying to understand the consumer brain. The results of this study indicate that neuromarketing has the potential to provide valuable information on consumer decision making.
A novel approach to exemplar based image inpainting

Inpainting is the method by means of which we can fill the bemused areas of an image. To recreate the bemused areas in a visually probable way is the main end of image inpainting methods. There have been so many algorithms are presented for the same. Two types of methods are available in the market. We had made some advances in Exemplar based inpainting technique to overcome the pitfalls such as computational complexes, noise and image construction. The subsisting method introduces obscure while in case of filling bigger holes and the advantage of proposed one can fill it without causing obscure. Experimental results depict the strength of the proposed technique.
The Effect of Different Attentional Focus Instructions during Finger Movement Tasks in Healthy Subjects: An Exploratory Study

External focus of attention (EFA) and internal focus of attention (IFA) represent commonly used strategies to instruct subjects during exercise. Several studies showed EFA to be more effective than IFA to improve motor performance and learning. To date the role of these strategies on motor performance during finger movement was less studied. The objective of the study was to investigate motor performance, patient's preference induced by IFA and EFA, and the focus during control condition. Ten healthy right-handed participants performed a finger movement task in control, EFA, and IFA conditions (counterbalanced). Errors, patient's preference, and type of attentional focus spontaneously adopted during the control condition were recorded. EFA determined less error (p < 0.01) compared to control and IFA. Participants preferred EFA against IFA and control condition. In the control group 10% of subjects adopted a purely EFA, 70% of subjects adopted a purely IFA, and 20% of subjects adopted a mixture of the two foci. Our results confirm that EFA is more effective than IFA and control in finger movement task. Due its clinical relevance, the interaction between attention and finger movement should be further investigated.
The Design of SMART: A Scheduler for Multimedia Applications

We have created SMART, a Scheduler for Multimedia And Real-Time applications. SMART supports both real-time and conventional computations and provides flexible and accurate control over the sharing of processor time. SMART is able to satisfy real-time constraints in an optimal manner and provide proportional sharing across all real-time and conventional tasks. Furthermore, when not all real-time constraints can be met, SMART satisfies each real-time task''s proportional share of deadlines, and adjusts its execution rate dynamically. This technique is especially important for multimedia applications that can operate at different rates depending on the loading condition. This paper presents the design of SMART and provides measured performance results of its effectiveness based on a prototype implementation in the Solaris operating system.
Access control for RDF graphs using abstract models

The Resource Description Framework (RDF) has become the defacto standard for representing information in the Semantic Web. Given the increasing amount of sensitive RDF data available on the Web, it becomes increasingly critical to guarantee secure access to this content. In this paper we advocate the use of an abstract access control model to ensure the selective exposure of RDF information. The model is defined by a set of abstract operators and tokens. Tokens are used to label RDF triples with access information. Abstract operators model RDF Schema inference rules and propagation of labels along the RDF Schema(RDFS) class and property hierarchies. In this way, the access label of a triple is a complex expression that involves the labels of the triples and the operators applied to obtain said label. Different applications can then adopt different concrete access policies that encode an assignment of the abstract tokens and operators to concrete (specific) values. Following this approach, changes in the interpretation of abstract tokens and operators can be easily implemented resulting in a very flexible mechanism that allows one to easily experiment with different concrete access policies (defined per context or user). To demonstrate the feasibility of the approach, we implemented our ideas on top of the MonetDB and PostgreSQL open source database systems. We conducted an initial set of experiments which showed that the overhead for using abstract expressions is roughly linear to the number of triples considered; performance is also affected by the characteristics of the dataset, such as the size and depth of class and property hierarchies as well as the considered concrete policy.
Replication-Based Load Balancing

Load balancing of large distributed server systems is a complex optimization problem of critical importance in cloud systems and data centers. Existing schedulers often incur a high communication overhead when collecting the data required to make scheduling decisions, hence delaying job requests on their way to the executing servers. We propose a novel scheme that incurs no communication overhead between the users and the servers upon job arrival, thus removing any scheduling overhead from the job's critical path. Our approach is based on creating several replicas of each job and sending each replica to a different server. Upon the arrival of a replica to the head of the queue at its server, the latter signals the servers holding replicas of that job, so as to remove them from their queues. We show, through analysis and simulations, that this scheme significantly improves the expected queuing overhead over traditional schemes under various load conditions and different job length distributions. In addition, we show that our scheme remains efficient even when the inter-server signal propagation delay is significant (relative to the job's execution time). We provide a heuristic solution to the performance degradation that occurs in such cases and show, by simulations, that it efficiently mitigates the detrimental effect of propagation delays.
MULTIFRACTAL ANALYSIS OF MOUNT St. HELENS SEISMICITY AS A TOOL FOR IDENTIFYING ERUPTIVE ACTIVITY

We present a multifractal analysis of Mount St. Helens seismic activity during 1980–2002. The seismic time distribution is studied in relation to the eruptive activity, mainly marked by the 1980 major explosive eruptions and by the 1980–1986 dome building eruptions. The spectrum of the generalized fractal dimensions, i.e. Dq versus q, extracted from the data, allows us to identify two main earthquake time distribution patterns. The first one exhibits a multifractal clustering correlated to the intense seismic swarms of the dome building activity. The second one is characterized by an almost constant value of Dq ≈ 1, as for a random uniform distribution. The time evolution of Dq (for q = 0.2), calculated on a fixed number of events window and at different depths, shows that the brittle mechanical response of the shallow layers to rapid magma intrusions, during the eruptive periods, is revealed by sharp changes, acting at a short time scale (order of days), and by the lowest values of Dq (≈ 0.3). Conversely, for deeper earthquakes, characterized by intense seismic swarms, Dq do not show obvious changes during the whole analyzed period, suggesting that the earthquakes, related to the deep magma supply system, are characterized by a minor degree of clustering, which is independent of the eruptive activity.