Miracle-dz/UniFAR-FTUs huggingface dataset:
Point-Triplet Spin-Images for Landmark Localisation in 3D Face Data

This paper introduces and evaluates our point-triplet spin-image descriptor, a novel descriptor that requires three vertices to be computed. This descriptor is able to encode surface information, within a spherical neighbourhood with radius r defined from a triplet's baricenter, into a surface signature. We believe that this new descriptor could be useful within a number of graph based retrieval applications; however, here we evaluate its performance within 3D face processing in the first instance. In doing so, this descriptor is embedded into a system designed to simultaneously localise the nose-tip and the two inner-eye corners of a human face. First, candidate triplets are gathered using the structured graph matching approach “relaxation by elimination” with a basic graph of three vertices and three arcs. Next, these candidate landmark-triplets are evaluated as in a binary decision problem. Hence, a point-triplet spin-image feature for each candidate landmark-triplet is computed and evaluated according to its Mahalanobis distance. This investigation includes two state of the art datasets, the Face Recognition Grand Challenge (FRGC) and CurtinFaces, as well as a performance comparison between this point-triplet spin-image and another point-triplet descriptor, named weighted-interpolated depth map which give us promising results and encourages our face processing research.
WEB ENGINEERING : METHODOLOGIES FOR DEVELOPING LARGE AND MAINTAINABLE WEB BASED INFORMATION SYSTEMS

Development of a Web site is not an event. It is a process. Once developed, information in the Web site needs to be maintained. Also the functionality and the amount of information will evolve with time. Our experience has shown that information maintenance aspects of a Web site have to be incorporated into the design from the very beginning. Based on many years of research, we have now developed a systematic approach to developing large and maintainable Web Based Information Systems. We call this Web Engineering as this approach somewhat mirrors the evolution of Software Engineering. This paper will describe the approach and illustrate the methodologies that were developed using a large Web site which we produced as a case study.
Collaborative Knowledge Management System Strategic Planning (CKMS2P): A Systematic Literature Review

This paper is aimed to identify and review the previous studies pertaining to CKMS2P via a systematic and rigorous approach. The objective is to investigate the strategic plan or guideline on how to develop and implement an effective collaborative knowledge management system (KMS) in order to ease the decision making process. Systematic Literature Review (SLR) method is used to produce a strategic searching method to select, extract, review and discuss relevant studies concerning the research subject by adapting the guidelines established by [11]. A total of 12 previous studies carried out from 2010 till 2014 have been selected to fulfil this objective through thorough selection. Finding shows that there is a very limited study focusing on the strategic implementation of a KMS to enhance the quality of knowledge services in a collaborative environment. Although there is an increase in the studies that recommended KMS guidelines or strategic planning, the proposed solution were mostly unverified or validated. Therefore, it has become a motivation to conduct a study to propose a Collaborative KMS Strategic Planning Model that can significantly enhance the quality of knowledge services in an organization.
Software components in a data structure precompiler

This research aims to simplify component creation and reduce the necessity of implementing new components. It concentrates more on programmer productivity and code efficiency than on program evolution and maintenance. The project is called PREDATOR. PREDATOR is a data structure precompiler that generates efficient code for maintaining and querying complex data structures. It embodies a novel component reuse technology that transcends traditional generic data types. The authors explain the concepts of this work and the prototype system. It is shown that complex data structures can be specified as compositions of software building blocks. Performance results are presented that compare PREDATOR output to hand-optimized programs. <<ETX>>
Sentient Sketchbook: Computer-Assisted Game Level Authoring

This paper introduces Sentient Sketchbook, a tool which supports a designer in the creation of game levels. Using map sketches to alleviate designer eﬀort, the tool auto-mates playability checks and evaluations and visualizes signiﬁcant gameplay properties. Most importantly, this paper introduces constrained novelty search via a two-population paradigm for generating, in real-time, alternatives to the author’s design and evaluates its potential against current approaches. The paper concludes with a small-scale user survey during which industry experts interact with Sentient Sketchbook to design game levels. Results demonstrate the tool’s potential and provide directions for its improvement.
Decoupled Payments and the Decision to Produce

This paper assesses the impact of decoupling on farming in Ireland. The decision to engage in production post-decoupling is simulated using profit maximising multi-period linear programming models. The number of farmers that would financially benefit from disengaging from production is projected. The results of the economic models suggest that significant restructuring is likely to occur at the farm level as a result of decoupling. Projections of farmers’ production decisions post-decoupling are compared and contrasted to the results of a survey of farmers’ production intentions. The comparison shows that despite the significant changes in profitability that decoupling could engender, the majority of farmers intend to continue as before and are unlikely to change their production patterns. The survey of farmers’ intentions indicates that a large number of farmers still seem to consider the decoupled payment linked to production. The implications of these results for land use, agricultural production and farm numbers are discussed.
The metric of bulk repeated call detection

Spam over Internet Telephony (SPIT) has become a serious issue for VoIP applications. SPIT detection is gaining huge focus in recent years. In this paper, we analyzed SPIT calls encoded using VBR method with the feature of bulk repeated. The chi-square test is used to intuitively verify the similarity among the lengths of VoIP packets which are with the characteristic of bulk repeated. In addition to chi-square test, edit distance is introduced to measure the similarity among VoIP calls which can be aided in bulk repeated call detection. It is empirically inferred that the proposed metric may be as good as possible to detect bulk repeated call.
Refining Identification Scheme based on Isomorphism of Polynomials with Two Secrets: a New Theoretical and Practical Analysis

The isomorphism of polynomials with two secret (IP2S) problem is one candidate of computational assumptions for post- quantum cryptography. The only identification scheme based on IP2S is introduced in 1996 by Patarin. However, the security of the scheme has not been formally proven and we discover that the originally proposed parameters are no longer secure based on the most recent research. In this paper, we present the first formal security proof of identification scheme based on IP2S against impersonation under passive attack, sequential active attack, and concurrent active attack. We propose new secure parameters and methods to reduce the implementation cost. Using the proposed methods, we are able to cut the storage cost and average communication cost in a drastic way that the scheme is implementable even on the lightweight devices in the current market.
Electron Transfer In Proteins

Electron-transfer (ET) reactions are key steps in a diverse array of biological transformations ranging from photosynthesis to aerobic respiration. A powerful theoretical formalism has been developed that describes ET rates in terms of two parameters: the nuclear reorganization energy (lambda) and the electronic-coupling strength (HAB). Studies of ET reactions in ruthenium-modified proteins have probed lambda and HAB in several metalloproteins (cytochrome c, myoglobin, azurin). This work has shown that protein reorganization energies are sensitive to the medium surrounding the redox sites and that an aqueous environment, in particular, leads to large reorganization energies. Analyses of electronic-coupling strengths suggest that the efficiency of long-range ET depends on the protein secondary structure: beta sheets appear to mediate coupling more efficiently than alpha-helical structures, and hydrogen bonds play a critical role in both.
Experiences in Bayesian inference in Baltic salmon management

Abstract. We review a success story regarding Bayesian inference inﬁsheries management in the Baltic Sea. The management of salmonﬁsheries is currently based on the results of a complex Bayesian pop-ulation dynamic model, and managers and stakeholders use the prob-abilities in their discussions. We also discuss the technical and humanchallenges in using Bayesian modeling to give practical advice to thepublic and to government oﬃcials and suggest future areas in which itcan be applied. In particular, large databases in ﬁsheries science oﬀerﬂexible ways to use hierarchical models to learn the population dynam-ics parameters for those by-catch species that do not have similar largestock-speciﬁc data sets like those that exist for many target species.This information is required if we are to understand the future ecosys-tem risks of ﬁsheries. Key words and phrases: Bayesian inference, Baltic salmon, risk anal-ysis, ﬁshery management, decision analysis.1. INTRODUCTIONWe introduce a case of ﬁsheries managementwhere Bayesian inference has been extensively used.Fisheries management is a ﬁeld of applied science,and one could easily argue that ﬁsheries science is
Genomic architecture of ecologically divergent body shape in a pair of sympatric crater lake cichlid fishes

Determining the genetic bases of adaptations and their roles in speciation is a prominent issue in evolutionary biology. Cichlid fish species flocks are a prime example of recent rapid radiations, often associated with adaptive phenotypic divergence from a common ancestor within a short period of time. In several radiations of freshwater fishes, divergence in ecomorphological traits — including body shape, colour, lips and jaws — is thought to underlie their ecological differentiation, specialization and, ultimately, speciation. The Midas cichlid species complex (Amphilophus spp.) of Nicaragua provides one of the few known examples of sympatric speciation where species have rapidly evolved different but parallel morphologies in young crater lakes. This study identified significant QTL for body shape using SNPs generated via ddRAD sequencing and geometric morphometric analyses of a cross between two ecologically and morphologically divergent, sympatric cichlid species endemic to crater Lake Apoyo: an elongated limnetic species (Amphilophus zaliosus) and a high‐bodied benthic species (Amphilophus astorquii). A total of 453 genome‐wide informative SNPs were identified in 240 F2 hybrids. These markers were used to construct a genetic map in which 25 linkage groups were resolved. Seventy‐two segregating SNPs were linked to 11 QTL. By annotating the two most highly supported QTL‐linked genomic regions, genes that might contribute to divergence in body shape along the benthic–limnetic axis in Midas cichlid sympatric adaptive radiations were identified. These results suggest that few genomic regions of large effect contribute to early stage divergence in Midas cichlids.
Framework for Multi-Cloud Using Integrity Verification Using CPDP Scheme

Provable data possession (PDP) is a technique for ensuring the integrity of data in storage outsourcing. In this paper, we address the construction of an efficient PDP scheme for distributed cloud storage to support the scalability of service and data migration, in which we consider the existence of multiple cloud service providers to cooperatively store and maintain the clients’ data. We present a cooperative PDP (CPDP) scheme based on homomorphic verifiable response and hash index hierarchy. We prove the security of our scheme based on multi-prover zero-knowledge proof system, which can satisfy completeness, knowledge soundness, and zeroknowledge properties. In addition, we articulate performance optimization mechanisms for our scheme, and in particular present an efficient method for selecting optimal parameter values to minimize the computation costs of clients and storage service providers. Our experiments show that our solution introduces lower computation and communication overheads in comparison with non-cooperative approaches.
Global burned area and biomass burning emissions from small fires

In several biomes, including croplands, wooded savannas, and tropical forests, many small fires occur each year that are well below the detection limit of the current generation of global burned area products derived from moderate resolution surface reflectance imagery. Although these fires often generate thermal anomalies that can be detected by satellites, their contributions to burned area and carbon fluxes have not been systematically quantified across different regions and continents. Here we developed a preliminary method for combining 1-km thermal anomalies (active fires) and 500 m burned area observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate the influence of these fires. In our approach, we calculated the number of active fires inside and outside of 500 m burn scars derived from reflectance data. We estimated small fire burned area by computing the difference normalized burn ratio (dNBR) for these two sets of active fires and then combining these observations with other information. In a final step, we used the Global Fire Emissions Database version 3 (GFED3) biogeochemical model to estimate the impact of these fires on biomass burning emissions. We found that the spatial distribution of active fires and 500 m burned areas were in close agreement in ecosystems that experience large fires, including savannas across southern Africa and Australia and boreal forests in North America and Eurasia. In other areas, however, we observed many active fires outside of burned area perimeters. Fire radiative power was lower for this class of active fires. Small fires substantially increased burned area in several continental-scale regions, including Equatorial Asia (157%), Central America (143%), and Southeast Asia (90%) during 2001–2010. Globally, accounting for small fires increased total burned area by approximately by 35%, from 345 Mha/yr to 464 Mha/yr. A formal quantification of uncertainties was not possible, but sensitivity analyses of key model parameters caused estimates of global burned area increases from small fires to vary between 24% and 54%. Biomass burning carbon emissions increased by 35% at a global scale when small fires were included in GFED3, from 1.9 Pg C/yr to 2.5 Pg C/yr. The contribution of tropical forest fires to year-to-year variability in carbon fluxes increased because small fires amplified emissions from Central America, South America and Southeast Asia—regions where drought stress and burned area varied considerably from year to year in response to El Nino-Southern Oscillation and other climate modes.
DECENTRALIZED DETECTION IN BINARY DENSE SENSOR NETWORKS : TO TRANSMIT OR NOT TO TRANSMIT

We consider the problem of binary decentralized detection in large-scale, randomly deployed, dense wireless sensor networks. We compare the performance of a Neyman-Pearson global detector under two different transmission strategies. The first one is based on a censoring scheme in which only the sensors with positive detections try to transmit; the second being the corresponding uncensored one. The aim of the paper is to determine in which situations each strategy needs less energy to achieve a given probability of error.
Delirium in Elderly People: A Review

The present review aims to highlight this intricate syndrome, regarding diagnosis, pathophysiology, etiology, prevention, and management in elderly people. The diagnosis of delirium is based on clinical observations, cognitive assessment, physical, and neurological examination. Clinically, delirium occurs in hyperactive, hypoactive, or mixed forms, based on psychomotor behavior. As an acute confusional state, it is characterized by a rapid onset of symptoms, fluctuating course and an altered level of consciousness, global disturbance of cognition or perceptual abnormalities, and evidence of a physical cause. Although pathophysiological mechanisms of delirium remain unclear, current evidence suggests that disruption of neurotransmission, inflammation, or acute stress responses might all contribute to the development of this ailment. It usually occurs as a result of a complex interaction of multiple risk factors, such as cognitive impairment/dementia and current medical or surgical disorder. Despite all of the above, delirium is frequently under-recognized and often misdiagnosed by health professionals. In particular, this happens due to its fluctuating nature, its overlap with dementia and the scarcity of routine formal cognitive assessment in general hospitals. It is also associated with multiple adverse outcomes that have been well documented, such as increased hospital stay, function/cognitive decline, institutionalization and mortality. In this context, the early identification of delirium is essential. Timely and optimal management of people with delirium should be performed with identification of any possible underlying causes, dealing with a suitable care environment and improving education of health professionals. All these can be important factors, which contribute to a decrease in adverse outcomes associated with delirium.
New High-Redshift Radio Galaxies from the MIT-Green Bank Catalog

We present optical identifications and redshifts for 17 new high-redshift radio sources. Fifteen of these sources are radio galaxies; the remaining two are high-redshift, steep-spectrum, radio-loud quasars. These objects were discovered as part of an ongoing study of compact (θ < 10″), moderately steep spectrum (α > 0.75,Sν ∝ ν-α) sources from the MIT–Green Bank (MG) radio catalog (S5 GHz ≳ 50 mJy). Spectra for the optical counterparts were obtained at the W. M. Keck Telescopes and are among the optically faintest radio galaxies thus far identified. Redshifts range between 0.3 and 3.6, with 13 of the 17 at redshifts greater than 1.5. Combining these new radio galaxies with two published MG radio galaxy spectra, we synthesize a composite MG radio galaxy spectrum and discuss the properties of these galaxies in comparison with other, more powerful, radio galaxies at similar redshifts. We suggest a radio power–ionization state relation.
Sync or sink? Interpersonal synchrony impacts self-esteem

Synchronized behavior has significant social influence both in terms of everyday activities (e.g., walking and talking) as well as via more historical contexts (e.g., cultural rituals). Grounded in the science of coordination dynamics, previous research has revealed that interpersonal synchrony has numerous affiliative and pro-social consequences, such as enhanced rapport, cooperation, and social-cognitive functioning. The current study sought to explore the impact of intentional synchrony versus asynchrony on an individual’s self-esteem and their feelings of social connection with a partner. The results revealed that individuals felt better about themselves following a period of synchronous compared to asynchronous movement, while they also perceived a greater self-other overlap with their partner. These findings not only extend previous research on social connections following interpersonal synchrony, but also provide the first demonstration of an influence on self-evaluations. Overall, it appears that moving in time with others may result in us feeling better about ourselves compared to moving to our own rhythm.
Two-stage incremental working set selection for fast support vector training on large datasets

We propose iSVM - an incremental algorithm that achieves high speed in training support vector machines (SVMs) on large datasets. In the common decomposition framework, iSVM starts with a minimum working set (WS), and then iteratively selects one training example to update the WS in each optimization loop. iSVM employs a two-stage strategy in processing the training data. In the first stage, the most prominent vector among randomly sampled data is added to the WS. This stage results in an approximate SVM solution. The second stage uses temporal solutions to scan through the whole training data once again to find the remaining support vectors (SVs). We show that iSVM is especially efficient for training SVMs on applications where data size is much larger than number of SVs. On the KDD-CUP 1999 network intrusion detection dataset with nearly five millions training examples, iSVM takes less than one hour to train an SVM with 94% testing accuracy, compared to seven hours with LibSVM - one of the state-of-the-art SVM implementations. We also provide analysis and experimental comparisons between iSVM and the related algorithms.
Comparing the performance of support vector machines to regression with structural risk minimisation

The structural risk minimisation (SRM) principle based on the statistical learning theory of Vapnik aims to prevent the phenomenon of overfitting by balancing the complexity of models with their fit to the data. This principle has been embodied in support vector machines, a widely acclaimed generic approach to machine learning. This paper investigates the performance of the SRM principle in its application to standard least-squares regression and compares it with its integration with support vector machines.
The Montreal Cognitive Assessment (MoCA) as a measure of severity of amnesia in patients with alcohol-related cognitive impairments and Korsakoff syndrome

Objective: the montreal cognitive assessment (moca) provides an indication of overall cognitive functioning and aims to measure several cognitive domains, such as memory, visuospatial abilities, executive function, attention and concentration, language, fluency, and orientation. It has been found sensitive to detect the (mild) cognitive impairment in patients diagnosed with substance dependence but it is unknown whether the moca is able to differentiate between mild and more severe forms of memory impairment, such as differentiating Korsakoff patients, who have severe amnesia, orientation difficulties and executive dysfunctions, from chronic alcoholics, who have cognitive deficits, but do not fulfill the criteria for KS. Method: in order to examine discriminatory power of the moca and predictive capacities for the severity of amnesia, both the moca and the widely-used rivermead behavioural memory test (rbmt-3) were administered to 20 patients with Korsakoff syndrome, to 26 patients with non-Korsakoff alcohol related cognitive impairment, and to 33 healthy control subjects. Results: results suggests that the moca has discriminatory power in the diagnosis of patients with alcohol-related cognitive impairments and predictive capacities with regard to the severity of memory impairment. for all comparisons, specific cut-off scores were established. Conclusions: while it can be concluded that the moca is a useful screening instrument, it should be stressed that it cannot substitute a more extensive neuropsychological assessment which is essential to the detailed analysis of the cognitive profile and, consequently, for adequate treatment selection.