Miracle-dz/UniFAR-FTUs huggingface dataset:
Cloud computing adoption in sub-Saharan Africa: An analysis using institutions and capabilities

Cloud computing can provide remote access to computing resources via the internet. It has the potential to transform economic activities considering its inherent pay-per usage model, flexibility and scalability features. This paper uses a socio-technical framework that maximizes selected development impact factors to analyze the use of Software-as-a-Service (SaaS) cloud applications in sub-Saharan Africa. Findings from this study show that there are several exciters and inhibitors to cloud computing adoption in sub-Saharan Africa. It also shows why security, privacy and trust issues as well as fear of data loss associated with cloud computing are viewed as exciters/enablers of the technology instead of inhibitors as the case is in the global north. There is equally no evidence found on regulatory or legislative policies affecting data location or protection at present. Furthermore, the findings show that these exciters and inhibitors are perceived by the users to interact associatively with each other to influence adoption. These findings will be of interest to policy makers and entrepreneurs interested in developing IS/ICT infrastructure.
An efficient brain mass detection with adaptive clustered based fuzzy C-mean and thresholding

Image segmentation plays an important role in analyzing medical images. Brain tumor detection is one of the applications that require brain image segmentation. Due to the complex nature of brain magnetic resonance images (MRI), the accurate computer aided detection (CAD) system for brain tumor segmentation has a lot of advantages over manual segmentation as it requires a lot of time and its results may vary from expert to expert. In this paper, a novel automatic tumor detection technique is proposed using Fuzzy C-means(FCM) where the number of clusters is determined automatically and conformed threshold is used instead of global threshold. Also a preprocessing stage is added to enhance the detection accuracy. The performance of the proposed method is evaluated by calculating completeness, correctness and accuracy of brain magnetic resonance (MR) tumor images. The proposed technique gives promising results for completeness, correctness, accuracy and processing time. Also, a comparison between the proposed technique results and the global threshold technique results is given.
Fisher Consistency of Multicategory Support Vector Machines

The Support Vector Machine (SVM) has become one of the most popular machine learning techniques in recent years. The success of the SVM is mostly due to its elegant margin concept and theory in binary classification. Generalization to the multicategory setting, however, is not trivial. There are a number of different multicategory extensions of the SVM in the literature. In this paper, we review several commonly used extensions and Fisher consistency of these extensions. For inconsistent extensions, we propose two approaches to make them Fisher consistent, one is to add bounded constraints and the other is to truncate unbounded hinge losses. 1 Background on Binary SVM The Support Vector Machine (SVM) is a well known large margin classifier and has achieved great success in many applications (Vapnik, 1998, Cristianini and Shawe-Taylor, 2000, and Hastie, Tibshirani, and Friedman, 2000). The basic concept behind the binary SVM is to search a separating hyperplane with maximum separation between the two classes. Suppose a training dataset containing n training pairs {xi, yi}i=1, i.i. d realizations from a probability distribution P (x, y), is given. The goal is to search for a linear function f(x) = w ′ x + b so that sign(f(x)) can be used for prediction of labels for new inputs. The SVM aims to find such an f so that points of class +1 and points of class −1 are best separated. In particular, for the separable case, the SVM’s solution maximizes the distance between f(x) = ±1 subject to yif(xi) ≥ 1; i = 1, . , n. This distance can be expressed as 2 ‖w‖ and is known as the geometric margin. When perfect separation between two classes is not feasible, slack variables ξi; i = 1, . , n, can be used to measure the amount of violation of the original constraints. Then the SVM solves the following optimization problem: min w,b 1 2 ‖w‖2 + C n ∑
Risk-Sensitive Decision-Making in Patients with Posterior Parietal and Ventromedial Prefrontal Cortex Injury

Successful choice under risk requires the integration of information about outcome probabilities and values and implicates a brain network including the ventromedial prefrontal cortex (vmPFC) and posterior parietal cortex (pPAR). Damage to the vmPFC is linked to poor decision-making and increased risk-taking. Electrophysiological and neuroimaging data implicate the pPAR in the processing of reward probability during choice, but the causal contribution of this area has not been established. We compared patients with lesions to the pPAR (n = 13), vmPFC (n = 13), and healthy volunteers (n = 22) on the Roulette Betting Task, a measure of risk-sensitive decision-making. Both lesion groups were impaired in adjusting their bets to the probability of winning. This impairment was correlated with the extent of pPAR, but not vmPFC, damage. In addition, the vmPFC group chose higher bets than healthy controls overall, an effect that correlated with lesion volume in the medial orbitofrontal cortex. Both lesion groups earned fewer points than healthy controls. The groups did not differ on 2 tasks assessing probabilistic reasoning outside of a risk-reward context. Our results demonstrate the causal involvement of both the pPAR and vmPFC in risk-sensitive choice and indicate distinguishable roles of these areas in probability processing and risk appetite.
Design & study of a low power high speed full adder using GDI multiplexer

This paper proposes a new method for implementing a low power full adder by means of a set of Gate Diffusion Input (GDI) cell based multiplexers. Full adder is a very common example of combinational circuits and is used widely in Application Specific Integrated Circuits (ASICs). It is always advantageous to have low power action for the sub components used in VLSI chips. The explored technique of realization achieves a low power high speed design for a widely used subcomponent-full adder. Simulated outcome using state-of-art simulation tool shows finer behavioral performance of the projected method over general CMOS based full adder. Power, speed and area comparison between conventional and proposed full adder is also presented.
LIDAR and vision-based real-time traffic sign detection and recognition algorithm for intelligent vehicle

Real-time traffic sign detection and recognition are essential and challenging tasks for intelligent vehicle. The previous works mainly focus on detecting and recognizing traffic sign based on images captured by onboard camera. Visual features of traffic sign such as color, shape, and appearance, however, are often sensitive to illumination condition, angle of view, etc. Except for camera, LIDAR also provides important and alternative features of traffic sign. The fusion of complementary data acquired from both sensors can improve the robustness of the algorithm, especially when data from either of them are of low quality. For this reason, we propose a new traffic sign detection and recognition algorithm based on the fusion of camera and LIDAR data. Specifically, position prior, color, laser reflectivity, and 3D geometric features are integrated to detect traffic sign in a 3D space. In most of previous works, different colors of traffic signs are individually handled in a specific color space, which generally results in the use of many thresholds or multiple classifiers. In this paper, we use combined color spaces (CCS) such that traffic sign colors can be entirely treated as one class. For traffic sign recognition, in order to improve the robustness to any viewpoint variation, regions of interest (ROIs), which suffer from perspective deformation, are rectified first by fusing LIDAR and camera data. Then the histogram of oriented gradient (HOG) feature and linear support vector machines (SVMs) are used to classify traffic signs. Finally, extensive experimental results in challenging conditions show that our algorithm is real-time and robust.
A meshless method using the radial basis functions for numerical solution of the regularized long wave equation

This article discusses on the solution of the regularized long wave (RLW) equation, which is introduced to describe the development of the undular bore, has been used for modeling in many branches of science and engineering. A numerical method is presented to solve the RLW equation. The main idea behind this numerical simulation is to use the collocation and approximating the solution by radial basis functions (RBFs). To avoid solving the nonlinear system, a predictor‐corrector scheme is proposed. Several test problems are given to validate the new technique. The numerical simulation, includes the propagation of a solitary wave, interaction of two positive solitary waves, interaction of a positive and a negative solitary wave, the evaluation of Maxwellian pulse into stable solitary waves and the development of an undular bore. The three invariants of the motion are calculated to determine the conservation properties of the algorithm. The results of numerical experiments are compared with analytical solution and with those of other recently published methods to confirm the accuracy and efficiency of the presented scheme. © 2009 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 2010
Music transcription modelling and composition using deep learning

We apply deep learning methods, specifically long short-term memory (LSTM) networks, to music transcription modelling and composition. We build and train LSTM networks using approximately 23,000 music transcriptions expressed with a high-level vocabulary (ABC notation), and use them to generate new transcriptions. Our practical aim is to create music transcription models useful in particular contexts of music composition. We present results from three perspectives: 1) at the population level, comparing descriptive statistics of the set of training transcriptions and generated transcriptions; 2) at the individual level, examining how a generated transcription reflects the conventions of a music practice in the training transcriptions (Celtic folk); 3) at the application level, using the system for idea generation in music composition. We make our datasets, software and sound examples open and available: \url{this https URL}.
Genomic prediction of traits related to canine hip dysplasia

Increased concern for the welfare of pedigree dogs has led to development of selection programs against inherited diseases. An example is canine hip dysplasia (CHD), which has a moderate heritability and a high prevalence in some large-sized breeds. To date, selection using phenotypes has led to only modest improvement, and alternative strategies such as genomic selection (GS) may prove more effective. The primary aims of this study were to compare the performance of pedigree- and genomic-based breeding against CHD in the UK Labrador retriever population and to evaluate the performance of different GS methods. A sample of 1179 Labrador Retrievers evaluated for CHD according to the UK scoring method (hip score, HS) was genotyped with the Illumina CanineHD BeadChip. Twelve functions of HS and its component traits were analyzed using different statistical methods (GBLUP, Bayes C and Single-Step methods), and results were compared with a pedigree-based approach (BLUP) using cross-validation. Genomic methods resulted in similar or higher accuracies than pedigree-based methods with training sets of 944 individuals for all but the untransformed HS, suggesting that GS is an effective strategy. GBLUP and Bayes C gave similar prediction accuracies for HS and related traits, indicating a polygenic architecture. This conclusion was also supported by the low accuracies obtained in additional GBLUP analyses performed using only the SNPs with highest test statistics, also indicating that marker-assisted selection (MAS) would not be as effective as GS. A Single-Step method that combines genomic and pedigree information also showed higher accuracy than GBLUP and Bayes C for the log-transformed HS, which is currently used for pedigree based evaluations in UK. In conclusion, GS is a promising alternative to pedigree-based selection against CHD, requiring more phenotypes with genomic data to improve further the accuracy of prediction.
Involuntary interpretation of social cues is compromised in autism spectrum disorders

A new social distance judgment task was used to measure quantitatively the extent to which social cues are immediately and involuntary interpreted by typically developing (TD) individuals and by individuals with autism spectrum disorders (ASD). The task thus tapped into the ability to involuntary “pick up” the meaning of social cues. The cues tested were social attention and implied biological motion. Task performance of the ASD and TD groups was similarly affected by a perceptual low‐level illusion induced by physical characteristics of the stimuli. In contrast, a high‐level illusion induced by the implications of the social cues affected only the TD individuals; the ASD individuals remained unaffected (causing them to perform superior to TD controls). The results indicate that despite intact perceptual processing, the immediate involuntary interpretation of social cues can be compromised. We propose that this type of social cue understanding is a distinct process that should be differentiated from reflective social cue understanding and is specifically compromised in ASD. We discuss evidence for an underpinning neural substrate.
Lower bounds on the complexity of graph properties

In this simple model, a decision tree algorithm must determine whether an unknown digraph on nodes {1, 2, …, n} has a given property by asking questions of the form “Is edge <i,j> in the graph? ”. The complexity of a property is the number of questions which must be asked in the worst case. Aanderaa and Rosenberg conjectured that any monotone, nontrivial, (isomorphism-invariant) n-node digraph property has complexity &OHgr;(<italic>n</italic><supscrpt>2</supscrpt>). This bound was proved by Rivest and Vuillemin and subsequently improved to <italic>n</italic><supscrpt>2</supscrpt>/4+<italic>&ogr;</italic>(<italic>n</italic><supscrpt>2</supscrpt>). In Part I, we give a bound of <italic>n</italic><supscrpt>2</supscrpt>/2+<italic>&ogr;</italic>(<italic>n</italic><supscrpt>2</supscrpt>). Whether these properties are evasive remains open. In Part II, we investigate the power of randomness in recognizing these properties by considering randomized decision tree algorithms in which coins may be flipped to determine the next edge to be queried. Yao's lower bound on the randomized complexity of any monotone nontrivial graph property is improved from &OHgr;(<italic>n</italic>log<supscrpt>1/12</supscrpt><italic>n</italic>) to &OHgr;(<italic>n</italic><supscrpt>5/4</supscrpt>), and improved bounds for the complexity of monotone, nontrivial bipartite graph properties are shown.
Anterograde Trafficking of KCa3.1 in Polarized Epithelia Is Rab1- and Rab8-Dependent and Recycling Endosome-Independent

The intermediate conductance, Ca2+-activated K+ channel (KCa3.1) targets to the basolateral (BL) membrane in polarized epithelia where it plays a key role in transepithelial ion transport. However, there are no studies defining the anterograde and retrograde trafficking of KCa3.1 in polarized epithelia. Herein, we utilize Biotin Ligase Acceptor Peptide (BLAP)-tagged KCa3.1 to address these trafficking steps in polarized epithelia, using MDCK, Caco-2 and FRT cells. We demonstrate that KCa3.1 is exclusively targeted to the BL membrane in these cells when grown on filter supports. Following endocytosis, KCa3.1 degradation is prevented by inhibition of lysosomal/proteosomal pathways. Further, the ubiquitylation of KCa3.1 is increased following endocytosis from the BL membrane and PR-619, a deubiquitylase inhibitor, prevents degradation, indicating KCa3.1 is targeted for degradation by ubiquitylation. We demonstrate that KCa3.1 is targeted to the BL membrane in polarized LLC-PK1 cells which lack the μ1B subunit of the AP-1 complex, indicating BL targeting of KCa3.1 is independent of μ1B. As Rabs 1, 2, 6 and 8 play roles in ER/Golgi exit and trafficking of proteins to the BL membrane, we evaluated the role of these Rabs in the trafficking of KCa3.1. In the presence of dominant negative Rab1 or Rab8, KCa3.1 cell surface expression was significantly reduced, whereas Rabs 2 and 6 had no effect. We also co-immunoprecipitated KCa3.1 with both Rab1 and Rab8. These results suggest these Rabs are necessary for the anterograde trafficking of KCa3.1. Finally, we determined whether KCa3.1 traffics directly to the BL membrane or through recycling endosomes in MDCK cells. For these studies, we used either recycling endosome ablation or dominant negative RME-1 constructs and determined that KCa3.1 is trafficked directly to the BL membrane rather than via recycling endosomes. These results are the first to describe the anterograde and retrograde trafficking of KCa3.1 in polarized epithelia cells.
LMI approach to robust delay dependent/independent sliding mode control of uncertain time-delay systems

Based on linear matrix inequality (LMI) technique, a sliding mode control approach is presented for a class of uncertain time-delay systems in the delay-independent and delay-dependent case. The corresponding sufficient conditions for the existence of sliding mode are proposed. Different from the reported results, the conclusion presented in this paper is only relating to the original system parameters and owns simple and legible form. A numerical example illustrates the effectiveness of the presented method.
Particle-Trapping Eddies in Protoplanetary Accretion Disks

Abstract In this paper, we present a new mechanism for number density enhancement and size segregation of particles in a nonlaminar accretion disk, e.g., the solar nebula. It can be shown that, if there is a vortical flow with a rotational frequency smaller than the local orbital frequency of the disk and a rotational axis parallel to the midplane of the nebula, particles will be trapped and concentrated in the gas flow. Due to the centrifugal force, a particle can be driven out of an eddy. It will be shown that this process is inhibited by the gravitational force induced by the protostar. Candidates for such slowly circulating flows are turbulent flow features in a size range close to the integral size of the turbulence as well as huge convection cells. The efficiency of the particle concentration depends on the coupling of the particle to the gas, i.e., the friction time. On account of the mass dependence of the friction time, a given eddy becomes a trap for particles of a characteristic size and causes a local change in the dust density. We calculate the maximal dust inhomogeneity due to this process. The strongest effect was observed for millimeter-sized particles, which can be concentrated by a factor of 100 within only 100 years. Our general estimates do not depend on special turbulence or convection models. In addition, we compare the analytical estimates with the results of numerical simulations of the dust motion. The effect will have an impact on the dust coagulation process and may be a link to the size distribution of chondrules.
How the role of the chief information officer contributes to the organisation

Since, the available informational and technological resources constitute a source of prosperity and differentiation for the organisations, the role of the Chief Information Officer (CIO) is becoming more crucial and vital. The thirty years of the CIO? s existence have shown a path of changes and difficulties on defining and establishing the particular role within the organisational context. The present study examines the CIO role evolution over the last thirty years, analyses the CIO role at the present time and discusses the CIO role in the future. The examination of the evolution of the CIO role identifies four main areas of interest that are used as the conceptual framework of the study. These areas relate to business strategy, innovation and competitive advantage, relationships building and external environment. Based on a qualitative research approach, nine case studies of existing CIOs are conducted and analysed from the private and the public sector. The analysis provides insights about the responsibilities of the CIOs, currently, regarding each one of the role aspects and the furthermore, particular responsibilities for these aspects. The results of the analysis demonstrate that within the CIO role responsibilities there are activities such as active participation in the strategic planning, exploitation of information management as an enabler of innovation, active facilitation of consultation processes with the stakeholders and finally, networking with outside organisations such as suppliers and customers but also networking with peers to share best practices.Regarding the future of the CIO role, it is argued that the CIO role includes responsibilities relating to technology management and it is counterproductive to separate these responsibilities to another C-level executive such as a CTO. Finally, it is argued that the CIO role enhances the dynamic capabilities of the organisation by helping it to improve its learning processes and the way it transforms its information resources. The results of the study have implications to both industry and academia. The proposed CIO role model could be used by industry as a guideline for the job description of the role in question, as well as an evaluation scheme for the post holders. With respect to academia, the proposed role model could be used to identify the skills necessary for a CIO and thus, to help inform areas in which university educational programmes should focus on.
COUNTABLE REPRESENTATION FOR INFINITE DIMENSIONAL DIFFUSIONS DERIVED FROM THE TWO-PARAMETER POISSON-DIRICHLET PROCESS

This paper provides a countable representation for a class of infinite-dimensional diffusions which extends the infinitely-many-neutral-alleles model and is related to the two-parameter Poisson-Dirichlet process. By means of Gibbs sampling procedures, we define a reversible Moran-type population process. The associated process of ranked relative frequencies of types is shown to converge in distribution to the two-parameter family of diffusions, which is stationary and ergodic with respect to the two-parameter Poisson-Dirichlet distribution. The construction provides interpretation for the limiting process in terms of individual dynamics.
Analyzing intended use effects in target acquisition

Recent work by Mandryk and Lough demonstrated that the movement time of Fitts-style pointing tasks varies based on intended use of a target, suggesting major implications for HCI research that models pointing using Fitts' Law. We replicate the study of Mandryk and Lough to determine exactly how and why observed movement times vary. We demonstrate that any variation in movement time is the result of differences in additive factors (a in Fitts' equation) and can be attributed to changes in the time a user spends over their primary target.