Miracle-dz/UniFAR-FTUs huggingface dataset:
Content-Based User Association and MIMO Operation over Cached Cloud-RAN Networks

Cloud radio access network (Cloud-RAN) has been introduced to support ever-growing end-users' needs. To reduce the backhaul traffic and aid coordinated multi-point (CoMP) transmission, base station (BS)-level caching technique can be utilized, where popular contents are pre-fetched at each BS. In this paper, multiple-input-multiple-output (MIMO) operation and user association policy are linked to the underlying cache placement strategy to ensure a good trade-off between load balancing and backhaul traffic taking into account the underlying wireless channel and the finite cache capacity at BSs. Due to the coupled interference among mobile stations, the binary nature of the underlying cache placement and user association matrices, the resulting mixed-timescale mixed integer optimization problem is nonconvex and NP-hard. To solve this problem, we decompose the joint optimization problem into a long-term content placement sub-problem and a short-term content delivery sub-problem. A novel iterative algorithm is introduced by leveraging the alternating direction method of multipliers together with a stochastic parallel successive convex approximation-based algorithm. The introduced scheme enables all BSs to update their optimization variables in parallel by solving a sequence of convex subproblems. Simulation evaluation demonstrates the efficiency of our strategy.
Improved Distributed Approximations for Maximum Independent Set

We present improved results for approximating maximum-weight independent set ($\MaxIS$) in the CONGEST and LOCAL models of distributed computing. Given an input graph, let $n$ and $\Delta$ be the number of nodes and maximum degree, respectively, and let $\MIS(n,\Delta)$ be the the running time of finding a \emph{maximal} independent set ($\MIS$) in the CONGEST model. Bar-Yehuda et al. [PODC 2017] showed that there is an algorithm in the CONGEST model that finds a $\Delta$-approximation for $\MaxIS$ in $O(\MIS(n,\Delta)\log W)$ rounds, where $W$ is the maximum weight of a node in the graph, which can be as high as $\poly (n)$. Whether their algorithm is deterministic or randomized depends on the $\MIS$ algorithm that is used as a black-box. Our main result in this work is a randomized $(\poly(\log\log n)/\epsilon)$-round algorithm that finds, with high probability, a $(1+\epsilon)\Delta$-approximation for $\MaxIS$ in the CONGEST model. That is, by sacrificing only a tiny fraction of the approximation guarantee, we achieve an \emph{exponential} speed-up in the running time over the previous best known result. Due to a lower bound of $\Omega(\sqrt{\log n/\log \log n})$ that was given by Kuhn, Moscibroda and Wattenhofer [JACM, 2016] on the number of rounds for any (possibly randomized) algorithm that finds a maximal independent set (even in the LOCAL model) this result implies that finding a $(1+\epsilon)\Delta$-approximation for $\MaxIS$ is exponentially easier than $\MIS$.
The Exact Form of the “Ockham Factor” in Model Selection

Abstract We explore the arguments for maximizing the “evidence” as an algorithm for model selection. We show, using a new definition of model complexity which we term “flexibility,” that maximizing the evidence should appeal to both Bayesian and frequentist statisticians. This is due to flexibility’s unique position in the exact decomposition of log-evidence into log-fit minus flexibility. In the Gaussian linear model, flexibility is asymptotically equal to the Bayesian information criterion (BIC) penalty, but we caution against using BIC in place of flexibility for model selection.
Ensuring Audit Log Accountability through Hash Based Techniques

Audit logs are now considered good practice and a standard approach for business systems. The integrity of the auditing records themselves is critical. By simply storing all the interactions in a separate audit log does not guarantee the integrity of the log. Data tampering can be done through unauthorized access and in some cases through authorized users. Results of such action can be unpleasant for business and their clients. Therefore, a demand for audit log security is needed more than ever. This paper describes a mechanism based on cryptographic hash functions and trusted timestamping that prevents an outsider or inside intruder from silently corrupting the audit log. In addition it is shown that the proposed mechanism can be realized in database systems with little overhead and that the hash based techniques and trusted timestamping can be used efficiently and correctly to determine if the audit log has been compromised.
Toward machine mediated training of motor skills. Skill transfer from human to human via virtual environment

We investigate a possibility of skill mapping from human to human via a visual/haptic display system. Our goal in the future is to develop a training system for motor skills such as surgical operations. We have proposed a new concept of visual/haptic display called a WYSIWYF Display; (What You See Is What You Feel). The proposed concept ensures correct visual/haptic registration which is important for effective hand-eye coordination training. Using the prototype WYSIWYF display, we did a preliminary experiment of skill training. Our idea of skill transfer is very simple; basically it is a "record-and-replay" strategy. Questions are "What is the essential data to be recorded for transferring the skill? " and "What is the best way to provide the data to the trainee? ". Several methods were tried but no remarkable result was obtained, presumably because the chosen task was too simple.
Enhancing Python Compiler Error Messages via Stack

Background: Compilers tend to produce cryptic and uninformative error messages, leaving programmers confused and requiring them to spend precious time to resolve the underlying error. To find help, programmers often take to online question-and-answer forums such as Stack Overflow to start discussion threads about the errors they encountered.Aims: We conjecture that information from Stack Overflow threads which discuss compiler errors can be automatically collected and repackaged to provide programmers with enhanced compiler error messages, thus saving programmers’ time and energy.Method: We present Pycee, a plugin integrated with the popular Sublime Text IDE to provide enhanced compiler error messages for the Python programming language. Pycee automatically queries Stack Overflow to provide customised and summarised information within the IDE. We evaluated two Pycee variants through a think-aloud user study during which 16 programmers completed Python programming tasks while using Pycee.Results: The majority of participants agreed that Pycee was helpful while completing the study tasks. When compared to a baseline relying on the official Python documentation to enhance compiler error messages, participants generally preferred Pycee in terms of helpfulness, citing concrete suggestions for fixes and example code as major benefits.Conclusions: Our results confirm that data from online sources such as Stack Overflow can be successfully used to automatically enhance compiler error messages. Our work opens up venues for future work to further enhance compiler error messages as well as to automatically reuse content from Stack Overflow for other aspects of programming.
FPGA-based SoC Implementation of a RISC Processor and Enhanced Computer Architecture Teaching Approach for Engineering Technology Students

FPGA-based processor implementation offers many learning opportunities that simulation approaches cannot challenge. The objectives of the paper are to endorse processor and integrated systems design in FPGAs; to show that FPGA-based System-on-Chip (SoC) technology is a better approach than ASICs in academia; and to enable students to design and build their own custom processors and integrated systems. The goal of the paper is to demonstrate a full-featured pipelined simple processor that runs Assembly code and fits in an affordable Altera Cyclone II FPGA. The proposed approach not only considers the area and the performance but also takes the simplicity and ease-of-understanding into account. In this research work, a proof by example is introduced in which an entire processor can be built as a system-on-a-chip in a modest FPGA, using inexpensive tools and can be developed and used by engineering technology students to enhance hands-on experience in computer architecture courses.
Discriminative analysis for feature reduction in automatic speech recognition

A dimensionality reduction method of the frame feature space based on discriminative analysis is discussed. A significant dimensionality reduction is obtained without loss of recognition performance in speaker independent experiments on a variety of speech databases. In addition, this procedure allows the selective incorporation of new feature components into an existing feature set. <<ETX>>
Método semi-automático de construção de ontologias parciais de domínio com base em textos.

The recent developments related to knowledge management, the semantic web and the exchange of electronic information through the use of agents have increased the need for ontologies to describe, in a formal way, shared understanding of a given domain. For computers and people to work in cooperation it is necessary that information have well defined and shared definitions. Ontologies are enablers of that cooperation. However, ontology construction remains a very complex and costly process, which has hindered its use in a wider scale. This work presents a method for the semi-automatic construction of ontologies using texts of any domain for the extraction of concepts and relations. By comparing the relative frequency of terms in the text with their expected use and extracting specific linguistic patterns, the method identifies concepts and relations and specifies the corresponding ontology using OWL for further use by other applications.
Potential use of the ECMWF Ensemble Prediction System in cases of extreme weather events

The combined use of the European Centre for Medium‐range Weather Forecasts (ECMWF) high‐resolution operational model, at T213 spectral triangular truncation and with 31 vertical levels (T213L31), and the Ensemble Prediction System (EPS), during cases of intense Mediterranean storms, is studied. In particular, it is discussed how EPS products can be used to provide a measure of confidence in the high‐resolution precipitation forecast. Three case studies (two extreme events plus one false‐alarm case) are analysed. The first event took place between 21 and 22 October 1994 over Greece, where heavy rainfall led to local flash‐floods in many areas that cost the loss of 12 lives, and caused significant property damage. The second event occurred in northwest Italy (and some parts of southern France) exactly two weeks later. More than 60 lives were lost and the cost of damage was enormous. For both these cases, the EPS probability values for precipitation occurrence supported the medium‐range T213L31 prediction, which proved to be successful. A third case is also investigated, where the high‐resolution forecast suggested heavy rainfall over northern Italy but was not supported by the EPS. The T213L31 prediction for this case was poor. Finally, the reliability of EPS probability predictions is discussed. It is shown that probability forecasts of low‐level temperature and wind show considerable skill. Reliability statistics of clusters of large‐scale flow show considerable skill as well. Probabilistic precipitation predictions are less skilful, possibly due to the EPS model resolution. Copyright © 1997 Royal Meteorological Society.
An Improved Transfer Logic of the Two-Path Algorithm for Acoustic Echo Cancellation

Adaptive echo cancellers with two-path algorithm are applied to avoid the false adaptation during the double-talk situation. In the two-path algorithm, several transfer logic solutions have been proposed to control the filter update. This paper presents an improved transfer logic solution. It improves the convergence speed of the two-path algorithm, and allows the reduction of the memory elements and computational complexity. Results of simulations show the improved performance of the proposed solution.
Designing a neural network for coin recognition by a genetic algorithm

This paper presents a method to design a neural network for coin recognition by a genetic algorithm (GA). The GA specifies an architecture of neural network, but does not train the network. The back-propagation (BP) method trains the network. After training it by the BP, the GA varies the architecture of the network to fit the environment, which is to achieve a 100% recognition accuracy and to make the network small in size. The network reduced by the GA is further decreased by using the BP with forgetting of weight. The object of this paper is to design a smaller neural network for hardware implementation of coin recognition system. Results by computer simulation show the effectiveness of the method to variably rotated coin recognition problem.
Quality Assurance in Cardiac Disease Diagnostic using Computerised Feature Extraction of ECG Signal

The bio-potentials generated by the muscles of the heart result in an electrical signal called electrocardiogram (ECG). It is one of the most important physiological parameter, which is being extensively used for knowing the state of cardiac patients. Electrocardiograph enables a rapid observation of the behavior of the heart activity in terms of heart rhythm, conduction intervals, morphological aspects of the waves (P, Q, R, S, T) associated to depolarization and repolarization of the auricles and ventricles. Feature extraction of ECG is most essential task in the manual and automated ECG analysis for use in instruments like ECG monitors, Holter tape recorders and scanners, ambulatory ECG recorders and analysers. Reliable detection of the QRS complex in either a normal or an abnormal ECG and its analysis is the first and foremost task in almost every ECG signal analysis system aimed at the diagnostic interpretation of ECG. A good amount of research work has been carried out during the last five decades for the accurate and reliable detection of QRS segment in the ECG signal. In the present paper, a bibliographic survey of different feature extraction methods has been presented. A comparative study of the work carried out in the department of Electrical Engineering of Indian Institute of Technology Roorkee has also been discussed. The element of subjectivity is totally eliminated in cardiac disease diagnostic by using computerised feature extraction of the ECG signal. All modern state-of-art hospitals use computer based ECG machines for feature extraction and disease diagnostic with a view to assure quality of their health care services.
3D motion estimation of head and shoulders in videophone sequences

In this paper, an approach for 3D motion estimation of head and shoulders of persons in videophone sequences is presented. Since head and shoulders are linked together by the neck, constraints for the motion of head and shoulders exist which are exploited to improve the motion estimation. In this paper, the human neck joint is modeled by a spherical joint between head and shoulders and its 3D position is calculated. Then, rotation and translation of the shoulders are estimated and propagated to the head. Finally, a rotation of the head around the neck joint is estimated. The presented approach is applied to the videophone sequences Akiyo and Claire. Compared with an approach without using a neck joint, anatomically correct positions of head and shoulders are estimated.
A Modified Particle Swarm Optimization with Adaptive Mutation Operator Selection

To enhance the performance of the particle swarm optimization (PSO), various mutation operators were proposed. But it is hard to select a proper operator in advance in the real word, because the objects are quite different. To incorporate the characteristic of the operators, several known operators were implemented to PSO all together, the results have shown that the performance was enhanced for most functions, but deteriorated for few functions. Besides which the function evaluations increased sharply with the increase of operators. To address the problem, an adaptive operator selection strategy is introduced where the swarm is divided into groups with different probabilities to employ the operators. The probabilities are adjusted adoptively by comparing the effectiveness of the groups to select a proper operator. The simulation results have shown PSO with the strategy provides robust and consistent performance.
PBQ: A Priority-Based Query Processing Algorithm in Opportunistic Wireless Sensor Network

Opportunistic wireless sensor network is a kind of opportunistic network that consists of nodes with sensing capabilities and actively or passively adopts the form of opportunistic transmissions. Due to the lack of stable end-to-end links and query-supporting infrastructures such as clustering or routing trees, the query processing in opportunistic wireless sensor networks is a challenging problem. In this paper, we propose a priority-based algorithm called PBQ for query processing in opportunistic wireless sensor network. Through the user-defined query priorities, the proposed algorithm properly selects the relay nodes and controls the forwarding of the messages. Meanwhile, the query priorities are adjusted dynamically so that the query results could be forwarded back to the query requester quickly and the residual query request messages could be cleaned up from the network, saving lots of unnecessary transmissions. Simulating results show that PBQ improves the overall utility of query processing. It could effectively improve the success rate of queries, and reduces the cost and delay of query processing in opportunistic wireless sensor networks.
The Design and Evaluation of a Pen-Based Computer Interface for Novice Older Users

The population of older people is growing rapidly worldwide, so it is necessary for all governments to provide them more services in order to improve their quality of life. In a digital era, most of these services can be provided by information technologies. However, older people have a very limited computer use due to economical, physical, sensory and cognitive barriers. In addition, few efforts have been dedicated to the design of specialized computer interfaces for them despite the fact that they have computer interaction problems with the WIMP standard (Windows, Icons, Menus, and Pointers). Recently, some researchers have shown that older people have a better computer interaction with the use of directmanipulation devices such as digital pens than with indirect-manipulation devices such as the mouse. This research goes one step further, proposing and analyzing a pen-based interface for older people in order to explore the usability of gesture paradigm for them.
Activity Theory as a Framework for Activity Taxonomy in HCI

In this article, the Activity Theory (AT) is analyzed to take it as a basis for the definition of an Activity classification Model of Interactive Systems called: Activity Taxonomy (ATx) for Interactive Systems. Our purpose is to use the ATx for: a. Set discussions about the effectiveness of the artifacts used in software engineering to specify the activity, b. The incorporation of the Human Computer Interaction (HCI) in the processes of software development, c. Definition of the minimum activity classifiers to specify interactive systems that promote HCI, d. Evaluation and integration of languages and/or software development processes, e. Promote normalization of the artifacts used in the specification of software, f. The specification of the execution models of interactive systems. This paper focuses specifically on b, c, d and f.
Drawing on Air: Input Techniques for Controlled 3D Line Illustration

Stretch-free surface flattening has been requested by a variety of applications. At present, the most difficult problem is how to segment a given model into nearly developable atlases so that a nearly stretch-free flattening can be computed. The criterion for segmentation is needed to evaluate the possibility of flattening a given surface patch, which should be fast computed. In this paper, we present a method to compute the length-preserved free boundary (LPFB) of a mesh patch, which speeds up the mesh parameterization. The distortion on parameterization can then be employed as the criterion in a trial-and-error algorithm for segmenting a given model into nearly developable atlases. The computation of LPFB is formulated as a numerical optimization problem in the angle space, where we are trying to optimize the angle excesses on the boundary while preserving the constraints derived from the closed-path theorem and the length preservation.
A computer-based tutoring system for visual-spatial skills: dynamically adapting to the user's developmental range

A basic principle of applied developmental psychology is that teaching is maximally effective when it is targeted to a student's developmental level. However, it is difficult for a single teacher to deliver the curriculum to the individualized needs of twenty or more students in a typical classroom. Even a single individual will vary in competence within a domain under the influence of complex and interrelated dynamically changing variables such as social context, motivation, and physiological state. This project represents an attempt to leverage technology to help educators overcome these challenges, by providing a computer system that supports the efficient training of key cognitive faculties such as visual-spatial ability. The core of the system is an automated tutor that can dynamically track and adapt to a user's fluctuating skill level in a given knowledge domain. Rasch modeling provides tools for measuring the relative complexity of specific tasks and associating these with specific user abilities. Armed with this knowledge, the tutoring system can assess a user's ability in real time and generate educational tasks that are levelled appropriately.
The Impact of Visual Aesthetics on the Utility, Affordance, and Readability of Network Graphs

The readability of networks – how different visual design elements affect the understanding of network data – has been central in network visualization research. However, existing studies have mainly focused on readability induced by topological mapping (based on different layouts) and overlooked the effect of visual aesthetics. Proposed is a novel experimental framework to study how different network aesthetic choices affect users' abilities of understanding the network structures. The visual aesthetics are grouped in two forms: 1) visual encoding (where the aesthetic mapping depends on the underlying network data) and 2) visual styling (where the aesthetics are applied independent of underlying data). Users are given a simple task – identifying most connected nodes in a network – in a hybrid experimental setting where the visual aesthetic choices are tested in a within-subject manner while the network topologies are tested in a between-subject manner based on a randomized blocking design. This novel experimental design ensures an efficient decoupling of the influence of network topology on readability tests. The utility of different visual aesthetics is measured comprehensively based on task performance (accuracy and time), eye-tracking data, and user feedback (perceived affordance). The results show differential readability effects among choices of visual aesthetics. Particularly, node based visual encoding significantly enhances network readability; specifically, glyphs allow participants to create more robust strategies in their utilization. The study contributes to both the understanding of the role of visual aesthetics in network visualization design and the experimental design for testing the network readability.