Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploiting piano acoustics in automatic transcription

In this thesis we exploit piano acoustics to automatically transcribe piano recordings into a symbolic representation: the pitch and timing of each detected note. To do so we use approaches based on non-negative matrix factorisation (NMF). To motivate the main contributions of this thesis, we provide two preparatory studies: a study of using a deterministic annealing EM algorithm in a matrix factorisation-based system, and a study of decay patterns of partials in real-word piano tones. Based on these studies, we propose two generative NMF-based models which explicitly model di↵erent piano acoustical features. The first is an attack/decay model, that takes into account the time-varying timbre and decaying energy of piano sounds. The system divides a piano note into percussive attack and harmonic decay stages, and separately models the two parts using two sets of templates and amplitude envelopes. The two parts are coupled by the note activations. We simplify the decay envelope by an exponentially decaying function. The proposed method improves the performance of supervised piano transcription. The second model aims at using the spectral width of partials as an independent indicator of the duration of piano notes. Each partial is represented by a Gaussian function, with the spectral width indicated by the standard deviation. The spectral width is large in the attack part, but gradually decreases to a stable value and remains constant in the decay part. The model provides a new aspect to understand the time-varying timbre of piano notes, but further investigation is needed to use it e↵ectively to improve piano transcription. We demonstrate the utility of the proposed systems in piano music transcription and analysis. Results show that explicitly modelling piano acoustical features, especially temporal features, can improve the transcription performance.
Test data generation automatically based on linear independent path covering

In the traditional algorithm of generating testing data for basic path coverage,the ring complex and a group of basis paths are gotten by program chat and then generating testing data of each path,which is not only inefficient but also being with infeasible paths because of ignoring the semantic dependency of codes.A new method is presented,which can dynamically executive the program by using genetic algorithm,gradually approach the real Ring Complex and get basic paths testing data directly without infeasible paths.Results of experiments show that the proposed methods can effectively generate testing data for basic path coverage.
Image Fusion Algorithm Based on the Neighboring Relation of Wavelet Coefficients

The neighboring relation of low-frequency wavelet coefficients and the directional characteristic of the high-frequency coefficients was discussed and analyzed,then,a novel algorithm of image fusion based on the directional co-rrelation of wavelet coefficients was proposed.At first,for every coefficient of the low-frequency,the algorithm of this paper made out the fusing coefficient by using the variance.Then,for every coefficient of the high-frequency,the algorithm of this paper made out the fusing coefficient by using the directional energy in the different directional high-frequency region.At last,the fused image was obtained through the reversely lifting wavelet transformation.Entropy and Average grads were used to judge the results of the proposed algorithms.Experimental results show that the proposed method is more outstanding than the conventional methods,and it has some application value.
M-Health and Physiotherapy

Rehabilitation exercises are those exercises that help in improving joint and muscle function, helping people stand, balance, walked. But these exercises work if done regularly and done as proposed by the therapist. Sometimes the patients has problems like scheduling their daily tasks, their commitment for doing those exercises, and some other difficultiessimilar to this. Thus failing to do the movementsand get benefit from the exercises. This paper proposes a system that provides an intuitive way for rehabilitation. This systemcontains use of pervasive health technologies for addressing theover difficulty. The system would provide a graphical interfacethat would help the physiotherapist to create exercises in 3Denvironment, wherein he would be animating a humanoid to showhow the exercise is to be done. This would show to be more intuitive to patients rather thanon paper. The system would also let therapist to monitor patient while he/she is exercising.
The moderating role of culture in social media-based spatial imagery, consumer xenocentrism, and word-of-mouth for global virtual teams

This study investigates how culture moderates the interrelationships among social spatial imagery (SSI), consumer xenocentrism (C-XEN), electronic word-of-mouth (eWoM), and overall project performance for global virtual teams (GVTs) in social media networked environments. In a sample of 1240 participants from developed economies (the United States and Italy) versus 1176 from emerging economies (China, India, Colombia, Brazil, and Malaysia), partial least squares structural equation modeling and multigroup analyses were conducted to examine the above social media-based interrelationships. The results indicate that low power distance (PD), individualist, and masculine cultures exert strong and positive relationships between C-XEN and negative eWoM; while high PD, collectivist, and less masculine (or feminine) cultures strengthen positive relationships between xenocentrism and positive eWoM. Further, negative eWoM aids project success for GVTs, while positive eWoM has no impact on project performance for developed and emerging economies. Theoretical and managerial implications for understanding cross-cultural aspects of SSI, C-XEN, eWoM, and GVT project performance in online social networks are discussed.
Peer Learning for University Students' Learning Enrichment: Perspectives of Undergraduate Students.

Peer learning, which is supported by learning theories such as Behaviourism, Cognitivism, Social Constructivism, and Connectivism, is increasingly gaining the attention of researchers and practitioners with an emphasis on studentcentered learning in educational settings. A review of relevant literature indicates that higher education institutions employ a variety of peer learning programs that potentially benefit both those who receive help and also those who provide help among peers. This study was designed to find out what peer learning programs are available at the University of Windsor, Canada, where the authors teach; how they are operated; and how undergraduate students from different academic programs at this university perceive such programs. Based on the findings, recommendations are made for faculty members as well as student service units to implement various types of peer learning so as to provide students with the best possible learning experience. INTRODUCTION The purpose of this study was to investigate peer learning at the University of Windsor, a mid-sized university in Ontario, Canada. The university states that its mission is to combine “a strong and focused emphasis on the learning experience of every student” (The University of Windsor, n.d.); peer learning is deemed to be one of the useful approaches that can help to enhance the student learning experience in a higher education setting. With this in mind, we are interested in finding out what peer learning programs are available on campus and in exploring research participants’ perspectives of peer learning as it relates to their programs of study. LITERATURE REVIEW Peer learning can be defined as “the acquisition of knowledge and skill through active helping and supporting among status equals or matched companions. It involves people from similar social groupings who are not professional teachers helping each other to learn and learning themselves by so doing” (Topping, 2005, p. 631), or “students learning from and with each other in both formal and informal ways” (Boud, Cohen, & Sampson, 2001, p. 4). Research literature on peer learning has documented relevant programs with different names and formats, such as Students Supporting Students Learning (SSSL) (Best, Hajzler, Pancini, & Tout, 2011), Supplemental Instruction (SI), Peer Assisted Study Sessions (PASS), Peer Assisted Learning Sessions (PALS) (Copeman & Keightley, 2014), and peer tutoring (Topping, 1996). SSSL was a combination of a variety of peer learning and student peer mentoring strategies, and Copeman and Keightley (2014) argue that the PASS
Conceptual salience of prefixes in L2 acquisition and processing: a reading-time study within context

The paradigmatic dimension of constructed words has led to variables which have been proved to influence morphological (on-line) processing. Τhe study presented here seeks to fill a gap in this domain by considering acquisition and processing of constructed words in Greek L2 with a self-paced reading task combined with a consistency judgment, where the critical stimuli are presented within context (and not isolated). We focus on a variable of conceptual-semantic nature, the conceptual salience of the prefix, which is crossed with semantic transparency for the purposes of the experiment. The variable ‘conceptual salience’ relates to the uniqueness versus multiplicity of the prefix’s meanings, e.g., the prefix προ-, as in προβλέπω ‘foresee’ versus the prefix eπί-, as in eπίδeιξη ‘demonstration’. Our results show that distinguishing between consistent and inconsistent critical items is made easier for our advanced L2 participants for the salient conditions, both transparent and opaque, while the results are less conclusive amongst participants with a lower level of language proficiency. The data clearly show that the facilitatory effect of the variable ‘conceptual salience’ extends beyond prelexical or perceptual characteristics of the constructed words and underline the need to examine the role of language-specific information in word boundaries.
A Social Network Analysis of NBA Players

Author(s): Wang, Biancheng | Advisor(s): Handcock, Mark S. | Abstract: In this paper, we focus on the relationship of public figures using statistical network analysis methods. Specifically, we analyze the network of Instagram following relationship of NBA All-Stars in the most recent 5 seasons. Based on Latent Space Position Modeling, we find that there might be an International “gang” and a veteran "gang" within this network although it is not so clear. Triad Census Model implies that this network is more likely to be transitive. With the help of Exponential-family Random Graph Models (ERGM), we analyze this network from 4 aspects, including Demographical Characteristics, Social Media Characteristics, Business Factor and Basketball Factor. We find strong Nationality and Team homophily effects. As for Business Factors, it does show some Brand homophily effect. Also, players who have more NBA experience, more honors and are more active on social media are more likely to form a tie with others.
A Fireworks Explosion Optimization Algorithm

This paper introduces a novel fireworks explosion optimization(FEO)algorithm based on the idea of fireworks explosion.FEO generates a certain number of fireworks bombs in the search space,and each fireworks bomb enforces the operation of explosion,which can ensure plentiful sparks to explore in the neighborhood of the original fireworks bomb.Besides,FEO controls the number of fireworks bombs that perform explosive operations by adopting the partial retention of excellence strategy.Meanwhile,FEO can balance the capability of global exploration and local search by adjusting the maximum radius of the explosion.The proposed algorithm is tested on several benchmark functions.Plentiful experimental results indicate that FEO attains better performance of convergence and high-precision optimization with good stabilization.Moreover,it is simple and easy to achieve the process of FEO.
Relational Maintenance Strategies and Satisfaction in the Stepmother–Stepdaughter Dyad

Existing research demonstrates the unique communication challenges faced within stepfamilies—particularly within the stepmother–stepdaughter dyad. This study examined the stepmother–stepdaughter relationship using Canary and Stafford’s relational maintenance strategy measure (RMSM). Specifically, researchers identified which relational maintenance strategies (RMS) are utilized by stepmothers and stepdaughters and the relationship between RMS and relational satisfaction. A sample of stepmothers (n = 20) and stepdaughters (n = 61) completed the RMSM and a relational satisfaction measure. Results indicate that stepmothers and stepdaughters most frequently use positivity and share task strategies, and that the openness strategy is strongly and positively related to relational satisfaction. Theoretical implications for scholars and practical implications for counselors and stepfamilies, along with areas for future research, are discussed.
Rootkits Subverting The Windows Kernel

Thank you for reading rootkits subverting the windows kernel. As you may know, people have search hundreds times for their favorite books like this rootkits subverting the windows kernel, but end up in infectious downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they are facing with some harmful virus inside their desktop computer. rootkits subverting the windows kernel is available in our book collection an online access to it is set as public so you can get it instantly. Our book servers hosts in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the rootkits subverting the windows kernel is universally compatible with any devices to read.
A Feature Extraction Method of Computer Viruses Based on Artificial Immune and Code Relevance

Existing anti-virus methods make use of signatures to detect malicious codes.They are inefficient to detect various forms of computer viruses,especially new variants and unknown viruses.Inspired by biologic immune system,a novel artificial immune based signature extraction method is proposed.This method automatically identifies bit patterns that correlate with viruses using instruction frequency and file frequency,and then identifies higher-level genes that are associated with viruses,generating a detecting virus gene library using the negative selection algorithm which leads to a fairly low false positive rate compared with the traditional signature-based methods.The advantages of our proposed method are described as follows.In the feature extraction phase,the detecting virus gene library stores virus samples with variable number of variable length genes at individual level,and uses multiple genes coexistence in one virus to avoid the possible loss of information considerably,fully taking the advantages of relevance between viral instructions within a virus program;in the classification phase,suspicious programs are analyzed at individual level in contrast to the existing gene matching technique.Experimental results indicate that the proposed method yields high detection rates for obfuscated viruses with an averaged recognition rate of 94% in real-world conditions,the false positive rate can be maintained below 2%. The method has a good generalization ability,and is able to effectively and efficiently detect new variants of known virus and unknown viruses.
School leadership for professional development: the role of social media and networks

ABSTRACT The purpose of this study was to describe and examine how school leaders in the United States used social media and networking (SMN) for professional development (PD), and to determine which SMN platforms school leaders perceived as most useful for PD. Semi-structured interviews were conducted with six school leaders who used SMN for PD to provide the qualitative data for this multi-participant case study. This study’s main finding indicated these school leaders included SMN in a multifaceted approach to PD, primarily via Twitter, to provide teachers with opportunities for growth. Continued and future use might depend on the ability of school leaders to grant PD credit or hours to teachers who participate in SMN for PD. The need to explore how other school leaders use SMN for PD on a larger scale is needed to better understand whether this strategy changes teacher practice to improve educational outcomes. In practice, school leaders should consider using Twitter for their own PD and professional learning, as well as for teacher PD. This study contributes to the school leadership for PD knowledge base by describing and examining experiences of school leaders who regularly used SMN as a part of the leadership agendas.
The Effects Of Creativity On Mood Enhancement Caused By Laughter Therapy

This study was conducted to examine the mood-enhancing benefits of Judy Young’s Laughter Therapy and the facilitative effects of high levels of creativity on changes in mood. This program aims to teach participants purposeful laughter so that they may ‘turn on’ genuine laughter at will. Two hour exposure to Laughter Therapy revealed increases in Positive Affect (PA) and decreases in Negative Affect (NA). The full three-week program was conducted with a control group with consenting employees at a school district. The control group included beneficial components of the Laughter Therapy program (i.e. light cardiovascular exercise, diaphragmatic breathing, and social interaction) in order to isolate the effects of the purposeful laughter taught during the sessions in the Laughter Therapy condition. Creativity levels did not influence the degree of mood changes in participants. T-tests did not indicate significant changes in PA or NA when the Laughter Therapy was compared with the control group in the three-week data collection. However, correlations revealed a small change in PA and NA in the anticipated directions for the Laughter Therapy condition. These results may have been influenced by an inadequate amount of participants in the three-week data collection. While Laughter Therapy may be useful for enhancing mood, more research is needed to determine the therapeutic benefits of this approach.
A geometric approach to shape clustering and learning

Using a geometric analysis of shapes introduced in [E. Klassen, et al., 2003], we present algorithms for: (i) hierarchical clustering of objects according to the shapes of their contours, and (ii) learning of simple probability models on a shape space from a collection of observed contours. We propose a tree (or a hierarchical) structure for clustering observed shapes. Clustering at any level is performed using a modified k-mean algorithm; means of individual clusters provide shapes for clustering at the next higher level. To impose a probability model on the shape space, we use a finite-dimensional Fourier approximation of functions tangent to the shape space at the sample mean. Examples are presented for demonstrating these ideas using shapes from the surrey fish database.
Principles Of Planetary Climate

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More than words: Computerized text analysis of child welfare professionals’ Adult Attachment Interviews

ABSTRACT Studying the attachment representations of child welfare workers can benefit workers and the vulnerable populations they serve. The Adult Attachment Interview (AAI) is the most widely used and well-validated measure of adult attachment but is also costly and time-consuming to score. Linguistic Inquiry Word Count (LIWC), a text-analysis software program, has the potential to lessen the burden of AAI scoring, making it a lower-cost, faster option for providing basic attachment representation information. In the current study, we explore the use of the LIWC in the AAI transcripts of 239 child welfare professionals. Findings indicate that subsets of LIWC categories could distinguish the AAI transcripts of individuals coded as dismissing, preoccupied, and secure-autonomous in attachment. Further, a subset of LIWC categories predicted AAI classification. Specifically, discriminant function analysis revealed two functions, activation and incoherence, that accurately classified 66.2% of AAI transcripts. Implications for the child welfare workforce are discussed.
George Katona: a founder of behavioral economics

George Katona was a founder of behavioral economics. Katona first published a broad outline and agenda for the development of behavioral economics in the 1940's (1942a, 1944a, 1945, 1946a, 1946b, 1947, 1951a, 1951b). Katona conceived behavioral economics as a discipline within economics that was primary concerned with the human element in economic affairs. While some believe the adjective “behavioral” is implicit and unnecessary in the title of any social science discipline, Katona thought it was necessary to emphasize that the centerpiece of this research was human decision making whereas a significant portion of economic theory was concerned with the behavior of markets. Katona did not attempt to replace economic theory but to bolster its findings with new insights from a more complete and accurate account of economic behavior (Katona, 1951a, 1963, 1967a, 1972a, 1974, 1976a, 1980). Katona was an empirical scientist who believed that understanding economic behavior through careful observation was the best foundation on which to base advances in economic theory. That same approach has persisted for most other researchers in behavioral economics who have followed Katona (Rabin, 2002).
Research and Practice on Reform of Satellite Communication Curriculum

In this paper,several proposals are presented to improve the lecture of satellite communications within the framework of our undergraduate educations.These proposals mainly focus on the teaching content,bilingual education,teaching practices,and teaching methods,which have been proven to have some positive effects in the daily teaching activities.Correspondingly,our students have been successfully trained in practical ability and English language.As expected,they are able to acquire the knowledge in satellite communications smoothly.