Miracle-dz/UniFAR-FTUs huggingface dataset:
Workshop on Exploring Musical Information Spaces

In the sound archive field, a long-term maintenance of the collective human memory in its original form is not sustainable. All physical carriers are subject to degradation and the information stored on such carriers is bound to vanish. Only a re-mediation action can prevent precious knowledge from being permanently lost. We present the first results carried out by a joint cooperation project between the University of Verona and the Arena di Verona Foundation, with the scientific support of EyeTech (Udine, Italy), which aims at establishing a HW/SW platform with the purpose of preserving and restoring the Vicentini archive of the Arena Foundation.
Automatic Arabic Document Classification Based on the HRWiTD Algorithm

The documents contain a large amount of valuable knowledge on various subjects and, more recently, documents on the Internet are available from various sources. Therefore, automatic, rapid and accurate classification of these documents with less human interaction has become necessary. In this paper, we introduce a new algorithm called the highest repetition of words in a text document (HRWiTD) to classify the automatic Arabic text. The corpus is divided into a train set and a test set to be applied to proposed classification technique. The train set is analyzed for learning and the learning data is stored in the Learning Dataset file. The category that contains the highest repetition for each word is assigned as a category for the word in Learning Dataset file. This file includes non-duplicate words with the value of higher repetition and categories and they get from all texts in the train set. For each text in the test set, the category of words is assigned to a specific category by using Learning Dataset file. The category that contains the largest number of words is assigned as the predicted category of the text. To evaluate the classification accuracy of the HRWiTD algorithm, the confusion matrix method is used. The HRWiTD algorithm has been applied to convergent samples from six categories of Arabic news at SPA (Saudi Press Agency). As a result, the accuracy of the HRWiTD algorithm is 86.84%. In addition, we used the same corpus with the most popular machine learning algorithms which are C5.0, KNN, SVM, NB and C4.5, and their results of classification accuracy are 52.86%, 52.38%, 51.90%, 51.90% and 30%, respectively. Thus, the HRWiTD algorithm gives better classification accuracy compared to the most popular machine learning algorithms on the selected domain.
Using Cooperative Game Theory in Energy Supply Planning

This paper is dedicated to the task of energy supply planning in the market environment. The possibili- ties of forming coalitions between companies competing within energy production, distribution and sales are con- sidered. In this case, for justifying the decisions and dis- tributing the gains a cooperative game theory is used. Various methods of forming a coalition and distributing additional gains are described in this paper. The example of Riga district heating system planning presented in the paper shows the rationality and efficiency of using the considered approach. A number of power supply planning tasks where application of the cooperative game theory seems to be promising is listed.
LoGos: Internet‐Explorer‐Based Malicious Webpage Detection

Malware propagated via the World Wide Web is one of the most dangerous tools in the realm of cyber‐attacks. Its methodologies are effective, relatively easy to use, and are developing constantly in an unexpected manner. As a result, rapidly detecting malware propagation websites from a myriad of webpages is a difficult task. In this paper, we present LoGos, an automated high‐interaction dynamic analyzer optimized for a browser‐based Windows virtual machine environment. LoGos utilizes Internet Explorer injection and API hooks, and scrutinizes malicious behaviors such as new network connections, unused open ports, registry modifications, and file creation. Based on the obtained results, LoGos can determine the maliciousness level. This model forms a very lightweight system. Thus, it is approximately 10 to 18 times faster than systems proposed in previous work. In addition, it provides high detection rates that are equal to those of state‐of‐the‐art tools. LoGos is a closed tool that can detect an extensive array of malicious webpages. We prove the efficiency and effectiveness of the tool by analyzing almost 0.36 M domains and 3.2 M webpages on a daily basis.
The Influence of Beauty Vlogs on Consumer's Purchase Intention

Author Thu Nguyen Minh Vo Title Year 2018 Language English Pages 57 + 7 Appendices Name of Supervisor Rosmeriany Nahan-Suomela Today, consumers rely more on an information given by other users and make decision based on what they perceive especially with cosmetic product. As YouTube channel and beauty vloggers have achieved popularity among the internet users, their impact on the consumer buying behavior has become one of the most concerned issues facing both marketers and brands. The thesis aimed at examining the perceived factors that affect purchase intention of consumers who watch beauty product related content on YouTube. Based on the objective of the study, a female consumer is chosen as a main target audience. The hypothesis was adapted from the study of Yüksel Hale (2016), which is focus on the perceived of credibility and usefulness of video blogs as well as the video characteristic. The thesis was divided into theoretical and empirical research. In the first section, the theoretical research was discussed to give a general understanding idea of beauty vlogs and consumers’ purchase intention. In addition, the adapted hypotheses of this study were also explained. In the second section, the empirical research was conducted by using a quantitative method and was implicated among the student of Vaasa University of Applied Sciences via email. The data collected was systemized and analyzed to draw up the conclusion. The results suggested that the consumers’ perception towards video appearance, credibility, and the usefulness of the source motivate the respondents to use beauty created contents on YouTube as an information searching tool and it positively affect the purchase intention. However, the study indicated that despite the impacts of YouTube beauty created contents and beauty influencers, there are still various factors affecting the consumers’ buying intention rather than the given information. Moreover, the results presented the rise of other social media channels, which also have impact on the beauty consumers today.
Long-term effects of a behavioural management technique for nurses on aggressive behaviour in brain-injured patients

Objective: the abc method (antecedent events, target behaviours, consequent events) is a behavioural management technique developed for nurses. The objective of the present study was to examine the long-term effects of the abc method on aggressive behaviour in 40 patients with acquired brain injury. Method: four aggression outcome measures and a questionnaire about the implementation of the abc method were filled out by the nursing staff in this longitudinal intervention study. Results: Contrary to expectations, a significant increase of aggression was found on two aggression measures. A possible explanation may be that the ABC method increased awareness of aggression in the nursing staff. Results of the implementation questionnaire indicated that the abc method was not part of usual care at the long-term follow-up. Conclusions: It seems that the quality of the implementation process was insufficient to find an effect of the ABC method on aggression. suggestions for improving the implementation process are made in this paper.
Formalization Structure and Team Creativity in High Tech Firms

This research paper investigated the effect of the role of formalization structure on team creativity mediated by task conflict. The object of this research is high tech organizations in China, while the subject is 417 employees in 67 teams and 55 team leaders. Data was gathered through a questionnaire in two waves, first, through the employees’ survey questionnaires administered to team members and three months later to team leaders. The measurements were assessed using the Exploratory Factor Analysis (EFA) in SPSS, and Confirmatory Factor Analysis (CFA) was conducted using AMOS version 23. A multiple linear regression model was fitted to the data to test how far structure affects team creativity using the SPSS 24.0 version. Findings indicated that the formalization structure affects team creativity, and that task conflict mediated the relationship between formalization structure and team creativity. Thus, teams with a formalization structure have moderate task conflict, which in turn contribution towards team creativity.
An evaluation of Green Road Incentive Procurement in road construction projects by using the AHP

Abstract Road construction is an important activity which emits a huge amount of greenhouse gases. Voluntary actions to reduce the emissions from construction practices have rarely received attention from contractors because eco-construction methods tend to incur extra project costs and induce the bidders’ concern to lose the bidding competitions. This study developed an incentive procurement system named Green Road Incentive Procurement (GRIP) to persuade contractors to adopt environmental-friendly construction methods. Initially, GRIP proposed six highly potential alternative construction methods of emission reduction for which bidders could choose as their preference. To ensure the acceptance and collaboration of this new GRIP, a survey study was conducted on two directly involved parties of road construction projects, contractors and public owners, which were selected as a sample group. The Analytical Hierarchy Process (AHP) was used to evaluate an opinion by three options based on eight criteria. The results showed that both contractors and the public owners gave the highest weighted scores for the GRIP full implementation alternative. The users’ readiness was an AHP criterion, which both parties were mutually concerned as the highest significance. These results confirmed that both involved parties agreed with the concept of GRIP and were pleased to cooperate with the GRIP implementation.
Design and verification of an indoor wireless UWB positioning system for civil structures

The rapid development of wireless communication and sensor technology provides an infinite possibility for extending the inherent function of civil structures through various methods. As an important branch of wireless communication technology, UWB technology has the advantages of strong anti-interference ability, high multipath resolution, and can provide decimeter level positioning accuracy. Based on this, we design and implement an indoor positioning system based on UWB wireless communication technology, and propose an improved least squares (ILS) algorithm to verify the performance of the system. The system adopts star network topology, which consists of one target node (TN) and several anchor nodes (ANs). In the process of positioning, the TN communicates with all the known ANs by polling. In this process, the respective receiving and sending timestamps are obtained, after unified collection and then convert it to the distance between the TN and each ANs. Finally, the location of the TN is achieved by the algorithm of the host computer. The ILS algorithm obtains more positioning results and more accurately reflects the position of the TN after solving the arithmetic mean. Experiments on a large number of different scenes to verify the stability of the system and prove the effectiveness of the ILS algorithm. In a word, the system realizes the acquirement of the target position information in the building space and improves the intelligence of the civil structure.
On the Efficiency of Stock Markets: A Case of Selected OPEC Member Countries

The study investigates the stock market efficiency of selected OPEC member countries within the context of random walk hypothesis and volatility approaches using monthly data on stock market indices from January, 2005 to April, 2016. Parametric (variance ratio: homoskedastic and heteroskedastic martingale), nonparametric (the Wright ranks and scores) tests and ARCH type estimation are performed. Results of both parametric and nonparametric tests indicate that only Qatar's stock market is weak-form efficient. The volatility results suggest that monthly stock returns of OPEC countries are volatile, with Qatar being most volatile and shocks to volatility of stock returns are asymmetric. The implications of this are that: first, investors should be conscious of these shocks when making risk-return decision of their portfolios; second, the results provide useful information to regulators to enable them develop safeguard mechanisms to shield the market from possible asymmetric information emanating from the participants.
The dynamics of house prices and fiscal policy shocks in Turkey

This study examines the interaction between house prices and gov-ernment spending, mortgage interest rates, and gross domestic product in Turkey. The ARDL bounds test approach is applied to quarterly data covering the 2010:1–2017:4 period. Findings indicate that there is a statistically significant long-run and short-run cointegration between the two house price indexes and government spending, mortgage rates, and GDP. An increase in government spending has a statistically sig-nificant positive effect on house prices. The study also indicates that mortgage interest rate and GDP have a statistically signifi-cant effect on house prices.
Historical state stability and economic development in Europe

Abstract In this paper, we show that state stability exhibits a persistent and robust non-monotonic relationship with economic development. Based on observations in Europe spanning from 1 to 2000 AD, regions that have historically experienced either short- or long-duration state rule on average lag behind in their local wealth today, while those that have experienced medium-duration state rule fare better. These findings support the argument that both an absence as well as an excess of state stability are bad for economic development. State instability hinders investment for growth, while too much stability is likely indicative of elite capture and subsequent stagnation of innovation.
Modelling the relationship between innovation, strategy, strategic human resource management and organisation competitiveness

Several studies have been conducted to establish the link between strategy, human resource management (HRM) practices and organisation performance, yet no study has explored the alignment between strategy, innovation, strategic HRM and their impacts on organisation competitiveness. Therefore, the present study sets out to align strategy, innovation, strategic human resource management (SHRM) and organisation competitiveness. The present study relies on in-depth review and synthesis of related literature in the field of strategy, innovation, strategic human resource management and organisation competitiveness to propose a model. The results show that aligning innovation and SHRM can enhance organisation competitiveness. The study found strategic HRM practices; learning, knowledge management, reward systems, recruitment, and performance management as critical to organisations’ innovativeness. The study offers both theoretical and practical implications for scholars as well as practitioners interested in the innovation. Despite all these claims, the study cautions against over-reliance on the findings, because of the qualitative nature of the study, hence future studies should consider empirically driven data (perhaps triangulations) to corroborate these results. The study offers a conceptual framework that could offer new insights into the relationship between strategy, innovation, SHRM and organisation competitiveness that has not been empirically tested before. Key words: Knowledge management, innovation, organisation competitive, human resource management, learning organization.
How Well the Implementation of Carhart Model in Market Overreaction Condition? Evidence in Indonesia Stock Exchange

This study aims to determine an ability of the four-factor model of Carhart in explaining the portfolio returns formed in condition of market overreaction. The four-factor model is basically a model proposed by Fama and French and then developed by Carhart which adds price momentum factor into the model. While market overreaction is a market condition caused by excessive reactions from investors when receiving information. The portfolios used are the winner and loser formed based on the returns of each portfolio to the average of the returns. Both portfolio consist are the stocks of non-financial sector in Indonesia Stock Exchange during the period July 2005 December 2015. The data used are the Composite Stock Price Index (CSPI), stock market capitalization, book to market ratio of each shares and the difference of returns of the loser over of the winner, as an indicator of price momentum factor that formed in market overreaction condition characterized by occurance the reversal of returns. The results show that the four-factor model can explain the portfolio return well. Implementation of the GARCH (1,1) model to improve the accuracy of the estimation results also shows similar findings.
Multi-task learning with group information for human action recognition

Human action recognition is an important and challenging task in computer vision research, due to the variations in human motion performance, interpersonal differences and recording settings. In this paper, we propose a novel multi-task learning framework with group information (MTL-GI) for accurate and efficient human action recognition. Specifically, we firstly obtain group information through calculating the mutual information according to the latent relationship between Gaussian components and action categories, and clustering similar action categories into the same group by affinity propagation clustering. Additionally, in order to explore the relationships of related tasks, we incorporate group information into multi-task learning. Experimental results evaluated on two popular benchmarks (UCF50 and HMDB51 datasets) demonstrate the superiority of our proposed MTL-GI framework.
A Riemannian approach for structured low-rank matrix learning

We consider the problem of learning a low-rank matrix, constrained to lie in a linear subspace, and introduce a novel factorization for modeling such matrices. A salient feature of the proposed factorization scheme is it decouples the low-rank and the structural constraints onto separate factors. We formulate the optimization problem on the Riemannian spectrahedron manifold, where the Riemannian framework allows to develop computationally efficient conjugate gradient and trust-region algorithms. Experiments on problems such as Hankel matrix learning, non-negative matrix completion, and robust matrix completion demonstrate the efficacy of our approach.
Using Biological Profile Data to Inform a DNA Sequencing Strategy

Frequency distributions of antemortem stature and age for individuals who were casualties onboard the USS Oklahoma are visually compared to frequency distributions of point estimates for long bone stature and pubic symphysis age drawn from the large commingled assemblage that is associated with this loss incident. Based on similarities in the means and standard deviations of these distributions, a four-tiered DNA sequencing strategy is devised to prioritize the sampling of elements that are at least one standard deviation from Oklahoma antemortem mean age and/or stature. The rationale for this approach is that elements providing estimates that are at least one standard deviation from antemortem stature and/or age means are more likely to be from individuals who also fall at least one standard deviation from the means for one or both of these categories. This prioritization strategy resulted in nearly doubling identifications during the initial phases of the project. This success demonstrates the ability to use biological profile data to aid in the DNA sequencing process and the importance of continued interdisciplinary work in resolving commingled assemblages.
Nominal Compound Compositionality: A Multilingual Lexicon and Predictive Model

Nominal compounds (NCs) like ivory tower and first lady are recurrent MWEs in many languages. While their syntactic interpretation has been studied (Nakov, 2008), their semantics pose problems to NLP systems (Hendrickx et al., 2013). This is due to the fact that the contribution of the sense of each element for the meaning of the NC may vary considerably along a spectrum of idiomaticity (e.g. police car vs. crocodile tears). Applications dealing with phrasal semantics, like MT, must correctly deal with NCs, e.g. to avoid translating dead end literally into French (? fin morte) or Portuguese (? fim morto). The meaning of NCs can be modeled using numerical scores (Reddy et al., 2011; Farahmand et al., 2015; Roller et al., 2013). Low values mean idiomatic NCs while high values represent compositional ones. For example, olive oil could be 90% compositional and dead end only 30%. Separate scores can be provided for each component; e.g. olive oil could be 80% related to olives and 100% oil, whereas dead end is 5% dead and 90% end. We present a multilingual lexicon and experiments for predicting the numerical degree of compositionality of NCs in French (FR), English (EN) and Portuguese (PT). We believe that our lexicon and method can guide syntactic and semantic applications by reducing ambiguity of these frequent constructions.
Entrepreneurial marketing and hybrid entrepreneurship: the case of JM Reid Bamboo Rods

ABSTRACT Through the presentation of the case of James Reid, a hybrid entrepreneur that transitioned towards full-time entrepreneurship, this paper discusses a number of entrepreneurial marketing issues faced by a small business. When presented with several opportunities for business growth, Reid evaluates the extent to which growth could impact his business model, brand image and his passion. The case study demonstrates the importance of maintaining brand values and establishing a clear strategic orientation in order to create a strong brand. However, these are shown to also significantly limit the growth prospects of the business. The discussion of the case delves into these issues together with an examination of the entrepreneurial journey of a highly skilled transitory hybrid entrepreneur. This paper further introduces the concept of a comfort entrepreneur, one that willingly halts the growth of their venture, and examines the business implications thereof.