Miracle-dz/UniFAR-FTUs huggingface dataset:
Measurement of Task Performance Times and Ease of Use: Comparison of Various Menu Structures and Depth on the Web

Five kinds of product search HTML pages - a four-level hierarchy (3 times 3 × 3 times 3), a three-level hierarchy (9 times 3 × 3), a two-level hierarchy (27 times 3), a one-level hierarchy (81 times 1), and a frame structure (9times3×3) - were prepared. Two kinds of task, a simple task and a complex task, were prepared. For the most complex task, a total of 22 clicks were required to complete the task. Then the subjects were asked to search for products over the Internet. They were also asked to evaluate ease of use of the web pages. A total of 89 subjects accessed the experimental pages. The access log was later statistically analyzed. The results were very productive. In most advanced research up to now it has been shown that reducing the number of hierarchies and increasing the amount of information in one screen can reduce the task performance time. Our test results have also shown that this is what happens when a complex task is performed. However, a different conclusion is drawn when a simple task is performed. When a simple task is performed, there were no significant differences in the search time required, whether there were 81 products included in one screen (81 times 1), or in a four-level hierarchy (3 times 3 × 3 times 3). In this case, more people evaluated the four-level hierarchy as being easier to use than a one-level hierarchy. In this study it was found that task performance times and ease of use depend on task complexity and they were not always directly related.
Semantic Web: A Quantitative Analysis of World Publications Output (2001-2010)

This study analyses the world research output on Semantic Web during 2001-2010, using Scopus database. It describes the overall growth pattern, publications share and citation impact of different countries. It analyses the characteristics of most productive institutions, authors and highly-cited papers. The patterns of research communication in most productive journals are also indicated.
The African

Information Technology (IT) can provide Small and Medium Enterprises (SMEs) with competitive advantage, effective management, and improved business performance. Decision making is an integral process of achieving a successful IT investment. SME owner-managers are usually the key IT decision makers despite the fact that they often do not possess sufficient IT skills. This study examines how SME managers search and prioritise information that guides their IT decisions. This study adopted a qualitative research method and conducted interviews with eleven SME owner-managers in Nigeria and South Africa to understand the process of IT investment based on the information available to the decision-makers. Owner-managers of small manufacturing, servicing, and retail companies were the participants of this study. Thematic data analysis technique was employed to analyse the data collected in this study. The findings of this study revealed that SME owner-managers face specific challenges like insufficient information to guide IT choice, limited resources when making IT decisions and lack of formalised approach to the decision-making process. The finding in this study provides an insight into strategies to formalise SME owner-managers’ IT decision-making process. This study concludes that, the formalisation of information searching process for IT choices in SMEs is crucial to achieving better IT investments.
A pattern-based validation method for the credibility evaluation of simulation models

Measuring the credibility of a simulation model has always been challenging due to its growing uncertainty and complexity. During the past decades, plenty of metrics and evaluation procedures have been developed for evaluating different sorts of simulation models. Most of the existing research focuses on the direct comparison of numerical results with a group of reference data. However, it is sometimes unsuitable for evolving dynamic models such as the multi-agent models. With the same condition, both the practical system and the simulation model perform highly dynamic actions. The credibility of the model with insufficient information, non-stationary states and changing environment is unable to acquire through a direct pair comparison. This paper presents a pattern-based validation method to complementarily extract hidden patterns that exist in both a simulation model and its reference data, and assess the model performance in a different aspect. Firstly, multi-dimensional perceptually important points strategy is modified to find the patterns exist in time-serial data. Afterward, a pattern organizing topology is applied to automatically depict required pattern from reference data and assess the performance of the corresponding simulation model. The extensive case study on three simulation models shows the effectiveness of the proposed method.
Inference of number of prototypes with a framework approach to K-means clustering

The selection of an appropriate value of the number of prototypes, K, is an important component in the use of partitioning algorithms such as K-means where such selection is not automatic. This is partly because the purpose of the algorithm is to identify clusters of interest and also because the choice of K is important for ensuring that the resulting partition reflects the underlying structure of the data. This paper introduces a method for guiding the identification of the number of clusters, K, by building upon a larger framework for stabilising partitions using cluster separation and stability. The method is compared with several frequently used algorithms in the published literature, demonstrating the utility of the proposed approach.
Online Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics

Online purchase forecasting is of great importance in e-commerce platforms, which is the basis of how to present personalized interesting product lists to individual customers. However, predicting online purchases is not trivial as it is influenced by many factors including: (i) the complex temporal pattern with hierarchical inter-correlations; (ii) arbitrary category dependencies. To address these factors, we develop a Graph Multi-Scale Pyramid Networks (GMP) framework to fully exploit users' latent behavioral patterns with both multi-scale temporal dynamics and arbitrary inter-dependencies among product categories. In GMP, we first design a multi-scale pyramid modulation network architecture which seamlessly preserves the underlying hierarchical temporal factors--governing users' purchase behaviors. Then, we employ convolution recurrent neural network to encode the categorical temporal pattern at each scale. After that, we develop a resolution-wise recalibration gating mechanism to automatically re-weight the importance of each scale-view representations. Finally, a context-graph neural network module is proposed to adaptively uncover complex dependencies among category-specific purchases. Extensive experiments on real-world e-commerce datasets demonstrate the superior performance of our method over state-of-the-art baselines across various settings.
Learning audio features for genre classification with deep belief networks

Supervisory Committee Dr. George Tzanetakis, Supervisor Department of Computer Science Dr. Alex Thomo, Committee member Department of Computer Science Feature extraction is a crucial part of many music information retrieval(MIR) tasks. In this project, I present an end to end deep neural network that extract the features for a given audio sample, performs genre classification. The feature extraction is based on Discrete Fourier Transforms (DFTs) of the audio. The extracted features are used to train over a Deep Belief Network (DBN). A DBN is built out of multiple layers of Randomized Boltzmann Machines (RBMs), which makes the system a fully connected neural network. The same network is used for testing with a softmax layer at the end which serves as the classifier. This entire task of genre classification has been done with the Tzanetakis dataset and yielded a test accuracy of 74.6%.
Multiuser Access Control for online Social Medias: Beyond Single user Protection

Online social medias (OSMs) have seen a rapid growth in decade and has become a real gateway for millions of Internet users. These OSMs offer a digital social communications and information sharing. OSMs users unintentionally disclose certain kinds of personal information that attackers could get benefited from which there is a need for increased security and privacy issues. Online social medias (OSMs) with a billion users have severely raised concerns on privacy leakage. Hence OSMs allow its users to maximum access to mutual data, they currently do not provide any method to apply privacy concerns over data related with many users. Our work recognize what bits of information are currently being shared, how extensively, and what users can do to stop such sharing. Along with this we frame an access control model to internment the essence of multiuser authorization requirements, along with a multiuser policy requirement scheme and a policy implementation mechanism. KeywordsOnline social medias (OSMs), tagging, information sharing, multiuser access control, multiuser policy requirement , multiuser policy implementation.
Testing parallel evolution strategies on the quadratic assignment problem

Parallel evolution strategies are demonstrating to be worthwhile in a variety of contexts. In this paper, besides the classical genetic and evolutionary strategies, a hybrid evolutionary approach which incorporates memory of the search history within the structure is analyzed. The parallel evolution algorithms are mapped on a distributed memory MIMD multicomputer whose processors are configured in a torus topology. The simulations are conducted using the quadratic assignment problem as an artificial environment. The relationship between genetic representations and recombination operators is investigated. The experimental results obtained show the value of structures richer than bit strings and the effectiveness of memory for the evolution process. <<ETX>>
Battery Loss and Stress Mitigation in a Cascaded H-Bridge Multilevel Inverter for Vehicle Traction Applications by Filter Capacitors

In this paper, two types of filter capacitors of varying capacity were connected to the battery packs of a cascaded H-Bridge single-star multilevel vehicle traction inverter, and their influence on the battery losses has been analyzed. The battery and capacitor simulation models used are experimentally verified in a downscaled system. Different capacitor configurations were simulated for four-drive cycle scenarios to determine the potentials for the mitigation of current pulse stresses and battery loss reduction with respect to the added weight. By adding capacitors corresponding to a weight of 4% of the initial battery storage, the peak current is reduced by 5%–20%, depending on the operating point from dc to a few kilohertz, and the battery losses are reduced by 10%. In comparison, it is demonstrated that adding supercapacitors is more beneficial for lower output frequencies, while adding electrolytic capacitors is better for higher output frequencies. Furthermore, the low-order voltage harmonics of the dc-rails between the converter and battery were reduced by 10%–30% for frequencies above 9 kHz, which decreases the potential of electromagnetic disturbances. In addition, during cold battery temperatures, when it is very important to avoid heavy cyclings, the loss reduction using the capacitors was 2.5 times larger than for nominal temperature.
GEOMETRIC CORRECTION OF REMOTE SENSING SATELLITE DIGITAL IMAGES USING MAPPING POLYNOMIAL OF DIFFERENT ORDERS

This paper conducts geometric correction procedure of sample of raw satellite images using georeferenced images (image-to-image registration) of the same area. In this procedure, many well-distributed ground control points (GCPs) pairs (from both images) are identified. Then a proper transformation polynomial is applied to map the original image GCPs coordinates into the new georeferenced image GCPs coordinates. A resampling process is carried out to recalculate the gray level values for pixels in the transformed output image (new pixels locations) based on pixel values in the input image. Also, this paper presents an analysis study of the effect of variation of the number of GCPs and the order of the mapping polynomials on the accuracy of geometric correction process. The Root Mean Square Error (RMS), at the selected GCPs, are calculated and used as a measure of accuracy of the obtained results.
Keep on rating - on the systematic rating and comparison of authentication schemes

Purpose Six years ago, Bonneau et al. (2012) proposed a framework to compare authentication schemes to the ubiquitous text password. Even though their work did not reveal an alternative outperforming the text password on every criterion, the framework can support decision makers in finding suitable solutions for specific authentication contexts. The purpose of this paper is to extend and update the database, thereby discussing benefits, limitations and suggestions for continuing the development of the framework. Design/methodology/approach This paper revisits the rating process and describes the application of an extended version of the original framework to an additional 40 authentication schemes identified in a literature review. All schemes were rated in terms of 25 objective features assigned to the three main criteria: usability, deployability and security. Findings The rating process and results are presented along with a discussion of the benefits and pitfalls of the rating process. Research limitations/implications While the extended framework, in general, proves suitable for rating and comparing authentication schemes, ambiguities in the rating could be solved by providing clearer definitions and cut-off values. Further, the extension of the framework with subjective user perceptions that sometimes differ from objective ratings could be beneficial. Originality/value The results of the rating are made publicly available in an authentication choice support system named ACCESS to support decision makers and researchers and to foster the further extension of the knowledge base and future development of the extended rating framework.
Privacy-Preserving Queries on Highly Distributed Personal Data Management Systems

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Privacy-Preserving Queries on Highly Distributed Personal Data Management Systems Julien Loudet, Luc Bouganim, Iulian Sandu Popa
Classificatin of Normal and Abnormal Heart Sounds Using Neural Network

The heart disease taking the second place of the cause of the death of modern people is a terrible disease that makes sudden death without noticing. To judge the aortic valve disease of heart diseases a name of disease was diagnosed using psychological data provided from physioNet. Aortic valve is a valve of the area that blood is spilled from left ventricle to aorta. Aortic stenosis of heart troubles is a disease when the valve does not open appropriately in contracting the left ventricle to aorta due to narrowed aortic valve. In this paper, 3126 samples of cardiac sound data were used as an experiment data composed of 180 characteristics including normal people and aortic valve stenosis patients. To diagnose normal and aortic valve stenosis patients, NEWFM was utilized. By using an average method of weight as an feature selection method of NEWFM, the result shows 91.0871% accuracy.
Dijkstra Goes Social: Social-Graph-assisted Routing in Next Generation Wireless Networks

The upcoming device-to-device (D2D) communication paradigm will be game-changing for content distribution among wireless users. In this work we ask the following question: Assuming that mobile device owners are connected with social ties in a social network graph and that such information can be extracted by a wireless operator, how can the operator leverage the social network ties for efficient data transport? We consider a set of content sessions, each with a source and a destination. For each session, the operator needs to find the path from source to destination that minimizes total communication cost. The communication cost between each pair of nodes is the transmission delay (time delay per transmitted bit) between nodes, thus reflecting bandwidth consumption for the operator per unit of transmitted bit. The D2D forwarding paradigm grants the freedom to each node across to the path to accept the incoming traffic and forward it further or not. We model the probability that a node accepts incoming traffic as a function of its social ties with other nodes and we require that the solution results in a minimum probability of content delivery to destination. The problem is formulated as a constrained minimum-cost one and it is solved by an algorithm based on a Lagrangian relaxation. The performance of the algorithm is tested with real datasets that are used to create the communication and social graphs.
Universal design for learning

Abstract The purpose of this paper is to discuss the importance of the Universal Design for Learning (UDL) principles, diverse learning styles, assistive technology/ tools for learning in the regular education classroom. This paper will focus on teachers reevaluating their current curricula and how they should start looking at the presentation of materials within their curriculum and consider the barriers their students might have to each of these presentation types. This paper will go into depth about universal access and how important it is in the planning and purchasing of new curriculum materials. It will also discuss the importance of assistive technology tools for learning that are appropriate for every student, not just those with disabilities.
Implementation of a Microcontroller Based Wireless Control of Domestic Electrical Appliances using the GSM Network

In this paper, the automatic control of domestic electrical appliances using a wireless network is presented. The wireless network of choice is the Global system for mobile communication, GSM. This paper presents a methodology that the communication can be extended even to inanimate devices like domestic electrical appliances such as radio, refrigerator, TV, light bulbs etc. the methodology entails the use of the feature of the GSM phone known as dual tone multi frequency DTMF. This DTMF tones are automatically generated when the buttons of a mobile phone is pressed. A DTMF to binary converter integrated circuit was used to convert the DTMF tones into binary format which is fed into the I/O ports of an 8052 microcontroller. A resident program enables the DTMF codes that are received to be used to control electrical appliances. The system also has a unique feature that after an action is performed; it sends back an audio tone to inform the user about the success or failure of the execution of the command.
Research on forward-looking synthetic aperture radar imaging algorithm of high velocity platform

As having the imaging ability of area in front of flight direction, forward-looking synthetic aperture radar (SAR) has become a hot topic in areas of SAR research. Nevertheless, existing imaging algorithms of forward-looking SAR are all based on the assumption that the platform is moving in low velocity. When this assumption is not satisfied, the imaging result of existing algorithms will show focus out effect and deviation of imaging position from real position. Aiming at this problem and taking airborne forward-looking SAR system using single transmitting and multiple receiving antennas as the research object, this paper analyzes the feasibility of forward-looking SAR imaging of high velocity platform, and proposes a forward-looking SAR imaging algorithm suitable for high velocity platform according to its spatial geometry and the model of echo signal. Finally, the raw echo data of an array of point targets is simulated, and the focused images are obtained using the algorithm proposed in this paper. Imaging results demonstrate the validity of the algorithm. (6 pages)
A Reduced Element Map Representation and Applications: Map Merging, Path Planning, and Target Interception

Modern autonomous systems require complex and heavy computations. The complexity can be reduced by eliminating or integrating redundant information. In the case of mobile vehicles, occupancy grid map representations are conventionally adopted for path planning. Based on a grid map, a reduced element map representation named a rectangular map or an R-map has been introduced. The concept of R-map is integration of empty elements of a grid map into fewer elements with maximal sizes. Since an R-map has a reduced number of elements, path planning computations become much faster than conventional maps. Also, because the R-map algorithm focuses only on free space, it is naturally suited for obstacle avoidance. The R-map can also be applied to map merging problems. Since R-maps represent spaces with varied sizes of rectangles, this feature can be a good source to recognize certain locations on the maps, unlike regular gridded cells. This work accomplishes map merging of local maps with unknown factors in their orientations, accuracy, and scales using the rectangular features from the R-map. Further, this study extends the concept of the 2D R-map to 3D environments. Since 3D environments have an additional dimension of the z-axis, the process of R-mapping will be slightly different from 2D R-mapping, and the integrated cells will be represented as cuboids (volumes) instead of rectangles (areas). Those maximal empty cuboids (MECs) are obstacle-free spaces, and autonomous vehicles can accomplish obstacle avoidance by moving through a sequence of MECs. As applications, algorithms for path planning on R-maps are provided for stationaryand maneuvering-target interception in cluttered environments. This approach expects to provide a computational efficiency to guidance and navigation problems of autonomous systems.
On Some Classes of Problems on Graphs

The relevance to research the complexity of resolving Graph Theory problems is caused by its numerous applications. In the given paper this problem is investigated in terms of space complexity of data structures that represent analyzed graphs, orgraphs, and directed graphs. The following two non-trivial the simplest sets of problems of Graph Theory are investigated in detail. The first set consists of the problems that can be resolved by some algorithm with space complexity linear relative to the size of the data structure that represents the analyzed graphs. The second set consists of the following problems, such that the size of the solution significantly exceeds the size of the input data. To resolve the problem some algorithm that operates on space linear relative to the size of the data structure that represents the analyzed graphs can be applied. Besides, this algorithm uses some memory of the same size for sequential generation, one fragment after another, the solution of the problem. Some model problems that are not in these two sets of problems are considered briefly.