Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic speech data clustering with human perception based weighted distance

Speech data from internet contain different speaking styles relating to information genre, emotions, sentiments, speaker characters, etc. Automatic classification of such data remains a challenging problem due to the difficulty in defining the categories to characterize different speaking styles clearly. To address the problem, this paper proposes a method based on x-means clustering, an extended version of k-means without fixed number of classes, for the task. Moreover, x-means method clusters the data according to a pre-defined distance measurement considering different features. Current methods on distance measuring only focus on features themselves while ignoring the impact of these features on human perception. To derive a more reasonable distance measurement, this paper also proposes a human perception based weighted distance to capture the contribution of different acoustic features on human perception. In this way, the automatic classification of internet speech data will make use of the prior knowledge of human perception as well as capture the speaking style characteristics in different datasets with varying categories. Experiments on listening test demonstrate that it is useful to introduce the human perception prior knowledge in distance measurement and our proposed method outperforms the baseline with conventional Euclidian distance with 10% improvement in classification accuracy.
Integrating parson's programming puzzles into a game-based mobile learning application

Understanding of elementary programming concepts, logic, and syntax is a vital part of learning to program. Unfortunately, learning programming is found to be difficult and boring, especially for novices. For example, drill type of exercises designed for learning elementary programming can be very tedious, making it hard to motivate learners. This study focused on the development of a mobile application, which integrates puzzle-based Parson's programming exercises into a strategy board game with the aim of facilitating the teaching and learning of programming. With the mobile application, learners play Ayo, a variant of the famous traditional African strategy board game Mancala. In each round of the game, the learners will solve a Parson's puzzle, which consist of small programming tasks where students are required to build programs by drag and drop, selection, indenting and ordering code fragments. The proposed solution of integrating the Parson's puzzles to Ayo game provides a new perspective on how to use mobile devices in programming education. The long-term aim of our work is to create a framework for integrating board games into computing education. The study reported in the article is the first step towards creating the framework.
ggplot2 - Elegant Graphics for Data Analysis (2nd Edition)

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Interpreting Rhythm in Optical Music Recognition

We present a method for understanding the rhythmic content of a collection of identified symbols in optical music recognition, designed for polyphonic music. Our object of study is a measure of music symbols. Our model explains the symbols as a collection of voices, while the number of voices is variable throughout a measure. We introduce a dynamic programming framework that identifies the best-scoring interpretation subject to the constraint that each voice accounts for the musical time indicated by the known time signature. Our approach applies as well to the situation in which their are multiple possible hypotheses for each symbol, and thus combines interpretation with recognition in a top-down manner. We present experiments demonstrating a nearly 4-fold decrease in the number of false positive symbols with monophonic music, identify missing tuplets, and show preliminary results with polyphonic music.
Multiple Transfer Used on Repairing Transparent and Electric Film Based on CVD - Grown Graphene

We optimized the CH4 and H2 gas flow rate of chemical vapor deposition (CVD) graphene growth and obtained larger area, fewer-layered graphene grown on Cu foils. After transfering to SiO2 substrate by PMMA more than 3 times to repair the defect of monolayer graphene film, we synthesized large area, transparent and continuous graphene film. The morphology and structure were characterized by SEM and Raman spectroscopy. Analysis of electrical properties and optical properties show that we obtained low resistance and high transparency of ~90%, which could be used on photoelectric device as solar cell and acceptable for replacing commercial ITO electrodes.
HRSPCA: Hybrid recommender system for predicting college admission

This paper presents a new college admission system using hybrid recommender based on data mining techniques and knowledge discovery rules, for tackling college admissions prediction problems. This is due to the huge numbers of students required to attend university colleges every year. The proposed HRSPCA system consists of two cascaded hybrid recommenders working together with the help of college predictor, for achieving high performance. The first recommender assigns student's tracks for preparatory year students. While the second recommender assigns the specialized college for students who passed the preparatory year exams successfully. The college predictor algorithm uses historical colleges GPA students admission data for predicting most probable colleges. The system analyzes student academic merits, background, student records, and the college admission criteria. Then, it predicts the likelihood university college that a student may enter. A prototype system is implemented and tested with live data available in the On Demand University Services (ODUS) database resources, at King Abdulaziz University (KAU). In addition to the high prediction accuracy rate, flexibility is an advantage, as the system can predict suitable colleges that match the students' profiles and the suitable track channels through which the students are advised to enter. The system is adaptive, since it can be tuned up with other decision makers attributes performing trusted needed tasks faster and fairly.
Polarities & Focussing: a journey from Realisability to Automated Reasoning

This dissertation explores the roles of polarities and focussing in various aspects of Computational Logic.These concepts play a key role in the the interpretation of proofs as programs, a.k. a. the Curry-Howard correspondence, in the context of classical logic. Arising from linear logic, they allow the construction of meaningful semantics for cut-elimination in classical logic, some of which relate to the Call-by-Name and Call-by-Value disciplines of functional programming. The first part of this dissertation provides an introduction to these interpretations, highlighting the roles of polarities and focussing. For instance: proofs of positive formulae provide structured data, while proofs of negative formulae consume such data; focussing allows the description of the interaction between the two kinds of proofs as pure pattern-matching. This idea is pushed further in the second part of this dissertation, and connected to realisability semantics, where the structured data is interpreted algebraically, and the consumption of such data is modelled with the use of an orthogonality relation. Most of this part has been proved in the Coq proof assistant.Polarities and focussing were also introduced with applications to logic programming in mind, where computation is proof-search. In the third part of this dissertation, we push this idea further by exploring the roles that these concepts can play in other applications of proof-search, such as theorem proving and more particularly automated reasoning. We use these concepts to describe the main algorithm of SAT-solvers and SMT-solvers: DPLL. We then describe the implementation of a proof-search engine called Psyche. Its architecture, based on the concept of focussing, offers a platform where smart techniques from automated reasoning (or a user interface) can safely and trustworthily be implemented via the use of an API.
Automatic Generation of Remediation Procedures for Malware Infections

Despite the widespread deployment of malware-detection software, in many situations it is difficult to preemptively block a malicious program from infecting a system. Rather, signatures for detection are usually available only after malware have started to infect a large group of systems. Ideally, infected systems should be reinstalled from scratch. However, due to the high cost of reinstallation, users may prefer to rely on the remediation capabilities of malware detectors to revert the effects of an infection. Unfortunately, current malware detectors perform this task poorly, leaving users' systems in an unsafe or unstable state. This paper presents an architecture to automatically generate remediation procedures from malicious programs--procedures that can be used to remediate all and only the effects of the malware's execution in any infected system. We have implemented a prototype of this architecture and used it to generate remediation procedures for a corpus of more than 200 malware binaries. Our evaluation demonstrates that the algorithm outperforms the remediation capabilities of top-rated commercial malware detectors.
Techniques for minimizing power dissipation in scan and combinational circuits during test application

Reduction of power dissipation during test application is studied for scan designs and for combinational circuits tested using built-in self-test (BIST). The problems are shown to be intractable. Heuristics to solve these problems are discussed. We show that heuristics with good performance bounds can be derived for combinational circuits tested using BIST. Experimental results show that considerable reduction in power dissipation can be obtained using the proposed techniques.
Preparation and properties of several Chinese herbal residue/polylactic acid composites

Disposal of Chinese herbal residues (CHRs) during Chinese herbal medicine production and processing has become a problem that requires attention. In this study, CHRs were pretreated by steam explosion or pulverization and composites were prepared by mixing pretreated CHRs with polylactic acid. The mechanical properties of composites of CHRs pretreated by two different methods were compared, the main compositions of CHRs were analyzed, and the morphology of various CHRs and brittle fracture surfaces of composites were observed by scanning electron microscopy. The results show that the mechanical properties of the composites are closely related to the herbal species and pretreatment methods. The mechanical properties of CHR composites pretreated by steam explosion are superior to those pretreated by pulverization. Choosing CHRs with large fiber cell wall–lumen ratio, high lignin and cellulose contents, low contents of hetero cells and hemicellulose are helpful in making composites with good comprehensive performance.
Head Pose Recommendation for Taking Good Selfies

We present a head-pose recommendation system that guides a user in how to best pose while taking a selfie. Given an input face image, the system finds the most attractive angle of the face and suggests how the pose should be adjusted. The recommendation results are determined adaptively to the appearance and initial pose of the input face. The user study shows the recommendation performance of the system is moderately related to the degree of conformity among the photographers' recommendations.
Optic nerve sheath diameter measurement as a risk marker for significant intracranial hypertension

Raised intracranial pressure (ICP) is a frequent condition in many medical and surgical situations and is often difficult to detect. Noninvasive estimates of raised ICP are of interest to allow rapid detection of significant intracranial hypertension. In the anterior part of the optic nerve, the sheath is distensible and can inflate in the case of raised pressure in the cerebrospinal fluid. Measurement of optic nerve sheath diameter using ocular sonography or MRI has been shown to correctly estimate the risk of raised ICP in various settings, including traumatic brain injury. Ocular sonography is simple, rapid, noninvasive and can be performed at the patient’s bedside, but it requires training and experience. The cut-off value for ICP greater than 20 mmHg is 5.8 mm, with a 90% probability of correct diagnosis. When raised ICP is suspected, but invasive ICP monitoring cannot be used or is not clearly recommended, this estimation of the risk of raised ICP may be of great clinical value, aiding in the detection of patients at risk of raised ICP.
Open Versus Closed: A Cautionary Tale

Workload generators may be classified as based on a closed system model, where new job arrivals are only triggered by job completions (followed by think time), or an open system model, where new jobs arrive independently of job completions. In general, system designers pay little attention to whether a workload generator is closed or open. Using a combination of implementation and simulation experiments, we illustrate that there is a vast difference in behavior between open and closed models in real-world settings. We synthesize these differences into eight simple guiding principles, which serve three purposes. First, the principles specify how scheduling policies are impacted by closed and open models, and explain the differences in user level performance. Second, the principles motivate the use of partly open system models, whose behavior we show to lie between that of closed and open models. Finally, the principles provide guidelines to system designers for determining which system model is most appropriate for a given workload.
A Novel Online Reliability Prediction Approach for Service-Oriented Systems

Service composition is an emerging technology in System of Systems Engineering (SoS Engineering or SoSE), which aims to construct a robust and value-added complex system by outsourcing external component systems. A serviceoriented SoS runs under a dynamic and uncertain environment. To assure the overall Quality of Service (QoS), online reliability time series prediction, which aims to predict the reliability in near future for service-oriented SoS arises as a grand challenge in SoS research. In this paper, we tackle the prediction challenge by exploiting two Markov independence assumptions resulted from the special system dynamics of a SoS environment. A novel motifs-based Dynamic Bayesian Networks model is proposed that supports the independence assumptions. Experimental results conducted on real Web services demonstrate the effectiveness of our approach.
The use of nanoscale fluorescence microscopic to decipher cell wall modifications during fungal penetration

Plant diseases are one of the most studied subjects in the field of plant science due to their impact on crop yield and food security. Our increased understanding of plant–pathogen interactions was mainly driven by the development of new techniques that facilitated analyses on a subcellular and molecular level. The development of labeling technologies, which allowed the visualization and localization of cellular structures and proteins in live cell imaging, promoted the use of fluorescence and laser-scanning microscopy in the field of plant–pathogen interactions. Recent advances in new microscopic technologies opened their application in plant science and in the investigation of plant diseases. In this regard, in planta Förster/Fluorescence resonance energy transfer has demonstrated to facilitate the measurement of protein–protein interactions within the living tissue, supporting the analysis of regulatory pathways involved in plant immunity and putative host–pathogen interactions on a nanoscale level. Localization microscopy, an emerging, non-invasive microscopic technology, will allow investigations with a nanoscale resolution leading to new possibilities in the understanding of molecular processes.
PBFVMC: A New Pseudo-Boolean Formulation to Virtual-Machine Consolidation

Over the course of the last decade, there have been several improvements in the performance of Boolean Satisfiability (SAT), Integer Linear Programming (ILP) and Pseudo-Boolean Optimization (PBO) solvers. These improvements have encouraged the applications of SAT, ILP and PBO techniques in modeling complex engineering problems. One such problem is the Virtual Machine Consolidation. The Virtual Machine Consolidation problem consists in placing a set of virtual machines in a set of hardware in a way to increase workload on hardware where they can operate more energy-efficient. This paper proposes an improved PBO formulation of the Virtual Machine Consolidation problem, PBFVMC. The improved formulation and enhancements are built on top of a previous work and a new set of constraints is created and rationalized to work more friendly with current PBO solvers. It is observed that this new formulation goes a step ahead and more problems can now be solved.
A new construction of differentially 4-uniform (n, n-1)-functions

In this paper, a new way to construct differentially 4-uniform $(n,n-1)$-functions is presented. As APN $(n,n)$-functions, these functions offer the best resistance against differential cryptanalysis and they can be used as substitution boxes in block ciphers with a Feistel structure. Constructing such functions is assumed to be as difficult as constructing APN $(n,n)$-functions. A function in our family of functions can be viewed as the concatenation of two APN $(n-1,n-1)$-functions satisfying some necessary conditions. Then, we study the special case of this construction in which the two APN functions differ by an affine function. Within this construction, we propose a family in which one of the APN functions is a Gold function which gives the quadratic differentially 4-uniform $(n,n-1)$-function $(x,x_n)\mapsto x^{2^i+1}+x_n x$ where $x\in \mathbb{F}_{2^{n-1}}$ and $x_n\in \mathbb{F}_2$ with $\gcd(i,n-1)=1$. We study the nonlinearity of this function in the case $i=1$ because in this case we can use results from Carlitz which are unknown in the general case. We also give the Walsh spectrum of this function and prove that it is CCZ-inequivalent to functions of the form $L \circ F$ where $L$ is an affine surjective $(n,n-1)$-function and $F$ is a known APN $(n,n)$-function for $n\leq 8$, or the Inverse APN $(n,n)$-function for every $n\geq 5$ odd, or any AB $(n,n)$-function for every $n>3$ odd, or any Gold APN $(n,n)$-function for every $n>4$ even.
Fault Detection and Recovery in a Transactional Agent Model

Servers can be fault-tolerant through replication and checkpointing technologies in the client server model. However, application programs cannot be performed and servers might block in the two-phase commitment protocol due to the client fault. In this paper, we discuss the transactional agent model to make application programs fault-tolerant by taking advantage of mobile agent technologies where a program can move from a computer to another computer in networks. Here, an application program on a faulty computer can be performed on another operational computer by moving the program. A transactional agent moves to computers where objects are locally manipulated. Objects manipulated have to be held until a transactional agent terminates. Some sibling computers which the transactional gent has visited might be faulty before the transactional agent terminates. The transactional agent has to detect faulty sibling computers and makes a decision on whether it commits/aborts or continues the computation by skipping the faulty computers depending on the commitment condition. For example, a transactional agent has to abort in the atomic commitment if a sibling computer is faulty. A transactional agent can just drop a faulty sibling computer in the at-least-one commitment. We evaluate the transactional agent model in terms of how long it takes for the transactional agent to treat faulty sibling computers .
Can pure mode III fatigue loading contribute to crack propagation in metallic materials

The possibility of pure mode III crack growth is analysed on the background of theoretical and experimental results obtained in the last 20 years. Unlike for modes I and II, there is no plausible micromechanistic model explaining a pure mode III crack growth in ductile metals. In order to realize ‘plain’ mode III fracture surface, we propose the propagation of a series of pure mode II cracks along the crack front. Fractographical observations on crack initiation and propagation in a low alloy steel under cyclic torsion support such a model. The authors have not seen any clear indication of a pure mode III crack growth micromechanism in metals until now.
Modification of the responses of hippocampal neurons in the monkey during the learning of a conditional spatial response task

In order to analyze the function of the hippocampus in learning, the activity of single neurons was recorded while monkeys learned a task of the type known to be impaired by damage to the hippocampus. In the conditional response task, the monkey had to learn to make one response when one stimulus was shown, and a different response when a different stimulus was shown. It had previously been shown that there are neurons in the hippocampal formation that respond in this task, to, for example, a combination of a particular visual stimulus that had been associated in previous learning with a particular behavioral response. In the present study, it was found that during such conditional response learning, the activity of 22% of the neurons in the hippocampus and parahippocampal gyrus with activity specifically related to the task altered their responses so that their activity, which was initially equal to the two new stimuli, became progressively differential to the two stimuli when the monkey learned to make different responses to the two stimuli. These changes occurred for different neurons just before, at, or just after the time when the monkey learned the correct response to make to the stimuli. In addition to these neurons, which had differential responses that were sustained for as long as the recordings continued, another population of neurons (45% of those with activity specifically related to the task) developed differential activity to the two new stimuli, yet showed such differential responses transiently for only a small number of trials at about the time when the monkey learned. These findings are consistent with the hypothesis that some synapses on hippocampal neurons modify during this type of learning so that some neurons come to respond to particular stimulus‐response associations that are being learned. Further, the finding that many hippocampal neurons started to reflect the new learning, but then stopped responding differentially (the transient neurons), is consistent with the hypothesis that the hippocampal neurons with large sustained changes in their activity inhibited the transient neurons, which then underwent reverse learning, thus providing a competitive mechanism by which not all neurons are allocated to any one learned association or event.