Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting and preventing confused labels in crowdsourced data

Crowdsourcing is a challenging activity for many reasons, from task design to workers' training, identification of low-quality annotators, and many more. A particularly subtle form of error is due to confusion of observations, that is, crowd workers (including diligent ones) that confuse items of a class i with items of a class j, either because they are similar or because the task description has failed to explain the differences. In this paper we show that confusion of observations can be a frequent occurrence in many tasks, and that such confusions cause a significant loss in accuracy. As a consequence, confusion detection is of primary importance for crowdsourced data labeling and classification. To address this problem we introduce an algorithm for confusion detection that leverages an inference procedure based on Markov Chain Monte Carlo (MCMC) sampling. We evaluate the algorithm via both synthetic datasets and crowdsourcing experiments and show that it has high accuracy in confusion detection (up to 99%). We experimentally show that quality is significantly improved without sacrificing efficiency. Finally, we show that detecting confusion is important as it can alert task designers early in the crowdsourcing process and lead designers to modify the task or add specific training and information to reduce the occurrence of workers' confusion. We show that even simple modifications, such as alerting workers of the risk of confusion, can improve performance significantly.
Analysis and Prototyping of Biological Systems: the Abstract Biological Process Model

— The aim of a biological model is to understand the integrated structure and behavior of complex biological systems as a function of the underlying molecular networks to achieve simulation and forecast of their operation. Although several approaches have been introduced to take into account structural and environment related features, relatively little attention has been given to represent the behavior of biological systems. The Abstract Biological Process (ABP) model illustrated in this paper is an object-oriented model based on UML (the standard object-oriented language). Its main objective is to bring into focus the functional aspects of the biological system under analysis.
An Empirical Study on Hookworm Detection

Hookworms are the curse to the human health, the process of detection of hook worm is always a challenging task to the medical science. So to overcome this wireless capsule endoscopy is being applied in the advanced clinical procedures. Even though that it remains a challenging task to identify the hook worms even by the pictorial sights. So to overcome this many methodologies are existed out of that most advanced and recent one is using of the Convolution neural network (CNN). The one major limitation of the CNN is it usually needs a large amount of labeled data for training and fine tuning the parameters. And most of the time it is not possible to provide such a large data for the detection process. So proposed methodology put forwards an idea of detecting the hookworm using moderate amount data which includes the steps of image data weighing feature selection, Region of interest, Convolution neural network and finally fuzzy classification through which hookworms are detected efficiently.
The Nereididae (Polychaeta) from Australia—Leonnates, Platynereis and Solomononereis

Leonnates crinitus n.sp. , L. bolus n.sp. and Platynereis uniseris n.sp. are described from Northern Australia. A systematic account of Leonnates, Platynereis and Solomononereis known from Australia and a key to species recorded from Australia is provided. HUTCHINGS, P.A. & A. REID, 1991. The Nereididae (Polychaeta) from Australia Leonnates, Platynereis and Solomononereis. Records of the Australian Museum 43(1): 47-62. In this paper, the second in a series to describe the nereidid fauna of Australia, Leonnates, Platynereis and Solomononereis are discussed. We describe 11 species, three of which are new: Leonnates crinitus n.sp. , L. bolus n.sp. and Platynereis uniseris n.sp. Leonnates jousseaumei Gravier and Solomononereis marauensis Gibbs are new records for Australian waters. A key to the genera of nereidids occurring worldwide is given by Fauchald (1977). In the final paper of this series on Australian nereidids, a key to the genera and species occurring in Australia will be given. The three genera discussed in this paper, belong to two groups identified by Fitzhugh (1987) as being closely related to one another. The two other genera in these groups Perinereis and Ceratonereis which are both extremely well represented in Australian waters, form the basis of other papers (Hutchings et al., in press; Hutchings & Reid, in preparation). We have used the terminology described in the first paper on the Gymnonereidinae (Hutchings & Reid, 1990). The following abbreviations have been used in the text: AHF Allan Hancock Foundation, Los Angeles, California (Polychaete collections now located at the Los Angeles County Museum); AM Australian Museum, Sydney; BMNH British Museum (Natural History), London; NMV National Museum of Victoria, now Museum of Victoria, Melbourne; NTM Northern Territory Museum, Darwin; QM Queensland Museum, Brisbane; SAMSouth Australian Museum, Adelaide; SSM Naturhistoriska Riksmuseet, Stockholm; TASM Tasmanian Museum, Hobart; USNM National Museum of Natural History, Smithsonian Institution, Washington D.e. ; WAM Western Australian Museum, Perth. NonAustralian distributions are in most cases based on the literature, whereas Australian distributions are based upon material examined. Where information was available, depths and dates of collection are given with each specimen examined.
Systematic Review Study of Decision Trees based Software Development Effort Estimation

The role of decision trees in software development effort estimation (SDEE) has received increased attention across several disciplines in recent years thanks to their power of predicting, their ease of use, and understanding. Furthermore, there are a large number of published studies that investigated the use of a decision tree (DT) techniques in SDEE. Nevertheless, in reviewing the literature, a systematic literature review (SLR) that assesses the evidence stated on DT techniques is still lacking. The main issues addressed in this paper have been divided into five parts: prediction accuracy, performance comparison, suitable conditions of prediction, the effect of the methods employed in association with DT techniques, and DT tools. To carry out this SLR, we performed an automatic search over five digital libraries for studies published between 1985 and 2019. In general, the results of this SLR revealed that most DT methods outperform many techniques and show an improvement in accuracy when combined with association rules (AR), fuzzy logic (FL), and bagging. Additionally, it has been observed a limited use of DT tools: it is therefore suggested for researchers to develop more DT tools to promote the industrial utilization of DT amongst professionals.
ON THE DESIGN AND FABRICATION OF CHAINED-FUNCTION WAVEGUIDE FILTERS WITH REDUCED FABRICATION SENSITIVITY USING CNC AND DMLS

In this paper, we present the design and fabrication of a novel class of emerging waveguide filters based on chained-functions at the millimeter-wave band. The derivation of chained-functions by chaining of prescribed generalized Chebyshev seed functions based on the partition theory is presented in details, and the implementation to waveguide technology is proposed and evaluated. The waveguide filter is fabricated through two different technologies, namely the Computer Numerical Control (CNC) milling technology and the Direct Metal Laser Sintering (DMLS) based additive manufacturing technology. The chained-function filters, which lie in between the Butterworth and Chebyshev filters, inherit the salient properties of both Butterworth and Chebyshev filters. Therefore, the chained-function waveguide filter exhibits filtering responses that have a superior rejection property and a lower loss with reduced sensitivity to fabrication tolerance than the standard Chebyshev waveguide filter. The efficiency of the proposed waveguide filter is confirmed both theoretically and empirically, using the CNC and DMLS processes. The issues of a higher manufacturing tolerance and apparent surface roughness associated with the DMLS method are found to be electrically insignificant when the chained-function concept is adopted in waveguide filter design. In general, the measured results of all the realized waveguide filters agree well to those of the simulation models. These results positively demonstrate that the chainedfunction concept has robust properties for rapid, high-performance, low-cost, and sustainable filter design and implementation, particularly for higher millimeter-wave frequency bands and for narrowband applications.
Web application for recommendations of Points Of Interests

The main goal of this thesis is a design, implementation and evaluation of a proof of the concept web application acting as the Points Of Interests recommender system. The thesis focuses on the investigation of methods, that can be used for developing a recommender system, designing the hybrid algorithm, based on provided research, designing and implementing the web application which uses the proposed hybrid approach for making recommendations. Also,
OPTIMUM SEISMIC LOAD DISTRIBUTION FOR PERFORMANCE-BASED DESIGN OF MULTI-STOREY STRUCTURES ON DIFFERENT SOIL PROFILES

Structural configuration plays an important role on the seismic behaviour of structures. In recent earthquakes, structures with inappropriate distributions of strength and stiffness had inadequate performance due to configuration problems or wrong conceptual design. In the conventional seismic design methods, height-wise distribution of equivalent seismic loads seems to be related implicitly on the elastic vibration modes. Therefore, the employment of such a load pattern does not guarantee the optimum use of materials in the nonlinear range of response. In this study, a new optimisation method is used to find optimum lateral force distribution for seismic design of regular and irregular shear-buildings to achieve minimum structural damage. The proposed approach is based on the concept of uniform distribution of damage where the structural properties are modified so that inefficient material is gradually shifted from strong to weak areas of a structure. It is shown that the seismic performance of such a structure is better than those designed conventionally. By conducting the optimisation algorithm on shear-building models with various dynamic characteristics subjected to 75 synthetic spectrumcompatible earthquakes, the effects of target ductility demand, fundamental period, seismic excitation, number of storeys, damping ratio, ground motion intensity and soil profiles are investigated on the optimum distribution pattern. Based on the results of this study, a general load pattern is proposed for seismic design of regular and irregular building structures that is a function of soil type, fundamental period of the structure and the target ductility demand. It is shown that using the proposed load pattern leads to a more efficient use of structural materials and better seismic performance.
Orlicz Random Fourier Features

Kernel techniques are among the most widely-applied and influential tools in machine learning with applications at virtually all areas of the field. To combine this expressive power with computational efficiency numerous randomized schemes have been proposed in the literature, among which probably random Fourier features (RFF) are the simplest and most popular. While RFFs were originally designed for the approximation of kernel values, recently they have been adapted to kernel derivatives, and hence to the solution of large-scale tasks involving function derivatives. Unfortunately, the understanding of the RFF scheme for the approximation of higher-order kernel derivatives is quite limited due to the challenging polynomial growing nature of the underlying function class in the empirical process. To tackle this difficulty, we establish a finite-sample deviation bound for a general class of polynomial-growth functions under α-exponential Orlicz condition on the distribution of the sample. Instantiating this result for RFFs, our finite-sample uniform guarantee implies a.s. convergence with tight rate for arbitrary kernel with α-exponential Orlicz spectrum and any order of derivative.
Optimizing the Delivery Network of Roadster Diner: Merging with Sister Companies

Roadster Diner is the leading national casual diner and offers food delivery services all over Lebanon. However, their delivery network faces profit losses and timing problems. This paper revolves around one main objective: the optimization of Roadster’s delivery network, which in turn leads to a major increase in their productivity and profitability. This study tests the feasibility of merging the delivery network of the two sister companies Zaatar W Zeit and Bar Tartine with that of our stakeholder. This paper will focus on three main topics studied. First, the optimization of the delivery operations. Second, the improvement of internal operations in the kitchen of delivery centers. This Final Year Project revolves around finding engineering methods to provide our stakeholders with the fastest delivery service for the least possible cost. Furthermore, the paper will discuss the results obtained from our pilot research, and the results expected by the end of the year. 1
Business Intelligence Capability, Complementary Resources and Performance among Public Listed Firms in Kenya

Whereas Business Intelligence initiative has been a primary focus many organisations globally for several years and accounting for billions of dollars in capital expenditure, empirical research remains sparse on the actual impact derived from this investment. Even when the benefits are established, its indirect and delayed impact on business results make it difficult to assess its value. Available literature on how insights triggered by Business Intelligence are transformed into profitable business learning is vague and fragmented. Hence, the main objective of this study was to establish the influence of complementary resources on the relationship between Business Intelligence capability and firm performance. The study used interdisciplinary theories to achieve the research objective, namely, Information systems capability theory and organisational learning. The study was performed using a mixed methods research methodology and cross-sectional approach. Data was collected from 64 public listed companies in Kenya. Findings indicated that complementary resources have a positive and significant impact on the relationship between Business Intelligence capability and performance. The study contributed to theory by building a framework for business intelligence assessment, including factors that significantly lead to improved performance. The results also provide new insights into the existing literature and suggest directions for future research with implications for academia, policymakers and management.
The Significance of Carrier Leakage for Stable Lasing in Split-Well Direct Phonon Terahertz Quantum Cascade Lasers

We studied the temperature performance of split-well direct phonon terahertz quantum cascade lasers and found that it is limited by a lasing instability that becomes significant as the temperature increases. When the hot electrons of the upper laser level cannot scatter effectively to excited states due to the high radiative barriers of the structures, a lasing instability occurs, which limits the temperature performance.
Functional Analysis of the Salicylic Acid-Responsive PR-1 Promoter in Arabidopsis thaliana

The Arabidopsis PR-1 gene belongs to a subset of genes upregulated during systemic acquired resistance (SAR), a plant defense response against a broad spectrum of pathogens mediated by the signaling molecule salicylic acid (SA). Genetic analysis has revealed that the promoter is repressed by SNI1 and that this repression has to be overcome by the SA-sensitive positive regulator NPR1. NPR1 activates transcription after association with TGA factors which bind to the as-1-like element of the PR-1 promoter. This study reveals that NPR1 and SNI1 regulate the PR-1 promoter through the as-1-like element and through WRKY boxes. The SNI1/NPR1 antagonism at the PR-1 promoter is explained by the existence of two alternate activation pathways. In the wildtype promoter, activation is mediated by the TGA-NPR1 complex at the as-1-like element. The as-1-like element represses at the same time the alternate activation pathway, presumably through indirect interactions with SNI1. In the absence of the as-1 element or SNI1, the alternate pathway can be activated through WRKY transcription factors, which are expressed in an NPR1-dependent manner. NPR1 cannot activate the promoter if the distance between the two TGA binding sites of the as-1-like element is 4- instead of 9bps, but such an as-1-like element can still repress the alternate pathway. The as-1 element of the CaMV 35S promoter, which contains 4bps between the TGA binding sites, confers strong constitutive activation when replacing the as-1-like element of the PR-1 promoter, as a binding site for a strong activator is encoded in the sequence of this cis-regulatory element. Thus, the as-1 element of the CaMV 35S promoter cannot mediate repression of the alternate pathway in the PR-1 promoter context. However, the repression capacity is re-established in the absence of the TGA subclass II members TGA2, TGA5 and TGA6.
Flavonoid Uniformity in Diploid Species of Hawaiian Scaevola (Goodeniaceae)

Although considerable adaptive radiation has resulted in varied morphology and habitat among the seven diploid species of Scaevola that are endemic to the Hawaiian Islands, members of the group show quite similar flavonoid profiles. All possess one apigenin glycoside plus several quercetin glycosides. Minor differences in glycosylation characterize some species. The similarity in flavonoid profiles supports an hypothesis of close systematic relationship among these taxa. The Hawaiian Islands are well known for possessing numerous examples of adaptive ra- diation in plants (Carlquist 1980). In many fam- ilies closely related species have diversified into different habitats and show remarkable radia- tion into different growth forms, leaf size and shape patterns, and inflorescence and floral features. Few studies of Hawaiian plants, how- ever, have centered on possible effects of adap- tive radiation on secondary compounds. Fla- vonoid compounds in particular, while used widely in systematic studies, have received scant attention with regard to patterns of adap- tive radiation. Gardner (1976) investigated fla- vonoid complements of Hawaiian Lipochaeta species, but there appear to be no other exam- inations of adaptive radiation of flavonoids in
Supplementary Material to Recurrent Sequence Evolution Af- ter Independent Gene Duplication

In the current study we predicted independent duplications from a network (see “Integration of Quartets in Networks” in main paper). This approach was validated through manual tree reconstruction for six gene families which were chosen because they had been previously proposed as examples of recurrent subfunctionalization (Madbub and AP1-β/AP2-β, i.e. Dacks et al. 2008, Suijkerbuijk et al. 2012) or because their copy number distribution hinted at multiple independent duplications (Cox11/Mettl17, Bet1/Bet1l, Shmt1/Shmt2 and Tmem50a/Tmem50b). Cox11/Mettl17 actually revealed a single pre-LECA duplication in the gene tree, thus serving as a control. From the six gene trees, golden standard sets were manually constructed of paralog clusters that unambiguously derived from the same duplication events. The Fk→2 statistic from Drew et al. (2017) was used to assess the congruence of clusters obtained from networks with these golden standard sets. We did not use Fgrand, k-clique (Drew et al. 2017), because it penalizes too heavily in cases where a large cluster is complete except for one species. Seven clustering methods were tested (code written in R using igraph package; Csardi and Nepusz 2006): a simple edge threshold, Markov Clustering algorithm (MCL package; Jäger 2015), HCS (Highly Connected Subgraphs), label propagation, community clustering with fastgreedy and walktrap approaches, and PEACE (Böcker et al. 2008). For each of these, 101 different edge thresholds in the range [0.0, 1.0] were tested. The best performance was obtained with PEACE using a threshold at θ = 0.6. When D ≥ 0.667, nQ is not the greatest of nQ, nR and nS (quartet represents single duplication), whileD ≤ 0.5 gives that Q is definitely in the majority of informative positions (quartet represents independent duplications). Using the six families mentioned above, we confirmed that this threshold leads to very similar duplications being identified as with manual gene tree reconciliation (average Fk→2 = 0.88). In fact, the precise threshold is not so important because we use Maximum Likelihood weights rather than counts (wX versus nX for x ∈ Q,R, S), which produces even more binary values of D (D → 0 or D → 1). For the clustering of fates from a network, the above approach could not be employed since we only had information of fates for Madbub. MCL was chosen (inflation = 10, expansion = 5, no threshold), because it distinguished most Mad and Bub fates in Madbub (Fk→2 = 0.93) and because it is a very commonly used clustering algorithm.
Morphology and phylogeny of four new Lactarius species from Himalayan India

Four new species of Lactarius are described from Himalayan India. Lactarius olivaceoglutinus, L. pyriodorus, and L. yumthangensis belong to L. subg. Piperites and L. indochrysorrheus is closely related to some representatives of L. subg. Russularia. An ITS based phylogeny confirms the phylogenetic placement of the four new species, although the monophyly of neither Lactarius subg. Piperites nor L. subg. Russularia can be confirmed. The ITS data also suggest that the Indian species are closely related to some European and American species.
Identification of Potent Inhibitor for RNA Dependent RNA Polymerase (RDRP) of Dengue Virus Serotype-3: A Molecular Docking Study

Identification of Potent Inhibitor for RNA Dependent RNA polymerase (RDRP) of Dengue Virus Serotype-3: A Molecular Docking Study Dengue (RNA virus) virus belongs to the family of flaviviridae. It has four serotypes like DENV1, DENV2, DENV3, and DENV4. RNA dependent RNA polymerase (RdRP) is an enzyme that catalyses the replication of RNA from an RNA template and was taken as a target protein for our study. We have taken RdRP of the dengue virus serotype 3 with the PDB Id: 2J7W. Ribavirin, an antiviral drug which is a guanosine analogue for RNA viruses reported to inhibit dengue virus replication and amantadine which was also reported to have inhibitory effect over the replication proteins of dengue virus proteins have been taken as a target drug molecule in the current study. Entropy enthalpy hybrid docking was performed for the ligands against the RdRP protein and ribavirin was found to be the best ligand that can inhibit the RdRP effectively. Further study can be performed to prove the efficacy of the drug in inhibition of the DENV Proteins using wet lab/clinical techniques.