Miracle-dz/UniFAR-FTUs huggingface dataset:
MASQ - Towards an Integral Approach to Agent-Based Interaction

In this paper we describe MASQ (Multi-Agent Systems based on Quadrants), a model that defines four perspectives over an agent-based interaction according to two axes: internal/external and individual/collective. With MASQ, we mainly show how to integrate the essential elements that intervene in the description of the interaction process such as agents, environments, organizations and institutions. We also discuss some methodological aspects of such an approach and show that it is possible to apply it to build practical models.
Investigating Management Practices and their Impact on Social Value Creation: A Case Study of Social Enterprises in North East England

The research presented explores links between key quality management practices and social impact creation within small to medium sized social enterprises (SMSEs). In particular, this study investigates workforce management and customer relationship management practices, and their perceived influence on social impact, whilst also considering the influence of external environmental factors. The research adopted a qualitative, single case study design, framing social enterprises in North east England as its unit of analysis. Within which, fourteen distinct social enterprises, and two sector experts represented sub units creating an embedded case study. The research identified three key findings following the template analysis procedure. Firstly, there are perceived links, both implicit, and explicit, between both practices discussed and the ability to provide social impact. Most notably through understanding and being able to respond to customer and stakeholder needs and creating positive working environments which offset resource constraints by increasing motivation. Secondly, the research suggests that where management practices may well be of benefit, such elements are often overshadowed by the availability of funding, especially when SMSEs are beholden to public sector contracts and institutional funders. Finally, the research builds upon current knowledge related to workforce management practices within SMSEs, where pro social motivations appear critical to workforce performance, even in more commercially focussed social enterprises. This research is unique as it begins to build a bridge between social enterprise and quality management discourse, showing the potential importance of practice to performance relationships to social value creation. Furthermore, research on social impact performance is yet to explore the collective importance of internal practices such as those mentioned.
Contributions to Localization, Mapping and Navigation in Mobile Robotics

Rao–Blackwellized particle filters �RBPFs) are an implementation of sequential Bayesian filtering that has been successfully applied to mobile robot simultaneous localization and mapping �SLAM) and exploration. Measuring the uncertainty of the distribution estimated by a RBPF is required for tasks such as information gain-guided exploration or detecting loop closures in nested loop environments. In this paper we propose a new measure that takes the uncertainty in both the robot path and the map into account. Our approach relies on the entropy of the expected map �EM) of the RBPF, a new variable built by integrating the map hypotheses from all of the particles. Unlike previous works that use the joint entropy of the RBPF for active exploration, our proposal is better suited to detect opportunities to close loops, a key aspect to reduce the robot path uncertainty and consequently to improve the quality of the maps being built. We provide a theoretical discussion and experimental results with real data that support our claims. KEY WORDS—localization, mapping
Database Replication and Clustering for High Availability

The cloud-computing trend today has pushed ever more services that span virtually all business and government sectors to hundreds of millions of users. Users typically take it for granted that such services would be continuously available, 24 hours a day, 7 days a week. Any extended disruption in services, including both planned and unplanned downtime, can result in significant financial loss and negative social impacts. Consequently, the systems providing these cloud services must be made highly available. A cloud service is typically powered by a multi-tier system, consisting of Web servers, application servers, and database management systems, running in a server farm environment. The Web servers handle direct Web traffic and pass requests that need further processing to the application servers. The application servers process the requests according to the predefined business logic. The database management systems store and manage all mission critical data and application state so that the Web servers and application servers can be programmed as stateless servers. (Some application servers may cache information, or keep session state. However, the loss of such state may reduce performance temporarily or may be slightly annoying to the affected user, but not critical.) This design is driven by the demand for high scalability (to support large number of users) and high availability (to provide services all the time). If the number of users has increased, more Web servers and application servers can be added dynamically. If a Web server or an application server fails, the next request can be routed to another server for processing. Inevitably, this design increases the burden and importance of the database management systems. However, this is not done without good reasons. Cloud applications often access and generate huge amount of data on requests from large number of users. A database management system can store and manage the data in a well-organized and structured way (often using the relational model). It also provides highly efficient concurrency control on accesses to shared data. While it is relatively straightforward to ensure high availability for Web servers and application servers by simply running multiple copies in the stateless design, it is not so for a database management system, which in general has abundant state. The subject of highly available database systems has been studied for more than two decades and there exist many alternative solutions (Agrawal et al., 1997; Cecchet, Candea, & Ailamaki, 2008; Drake et al., 2005; Garcia, Rodrigues, & Preguiça, 2011; Kemme & Alonso, 2000; PatinoMartinez et al., 2005). In this article, we provide an overview of two most popular database high availability strategies, namely database replication and database clustering. The emphasis is given to those that have been adopted and implemented by major database management systems (Banker, 2011; Davies & Fisk, 2006; Vallath, 2004).
Trends in Free Cash Flow Company of The Issuer Stock Exchange

This study aims to examine the tendency of prioritizing management companies listed on Indonesia Stock Exchange (IDX) allocate free cash flow. Respondents there were 23 companies listed on IDX who has a wealth of at least the IDR 1.2 trillions. Questionnaires were sent based on four economic situation, namely: the situation is stable or normal, getting better, getting worse, and the uncertain economic situation. The fourth economic situation is faced with five options for allocating free cash flow, namely: payment of cash dividends, buy back stock, make acquisitions, purchase of financial assets, and distribute it to other areas of investment, such as option's Mutual Funds. Incidentally Indonesia's economic situation was observed 2015 2016 is the worsening situation in which the rupiah exchange rate against the USD around IDR 14,500. Similar to the economic situation in 1997/ 1998. The results show that the worsening economic situation the management of companies listed on IDX prefers: the purchase of shares and investments in other business fields, followed by The purchase of financial assets and acquisitions, and payment of cash dividends in the final choice
Service marketing mix as input and output of higher and technical education

Purpose The purpose of this paper is to examine the relationships of service marketing mix (SMM) as service input and service output in terms of students’ performance, satisfaction and referral act in context to higher and technical education (HTE) through the application of structural equation modeling. Design/methodology/approach A quantitative research, conducted through a self-administered survey composed by a closed-ended structured questionnaire, was incorporated for the students who were enrolled in the technical educational institutions situated in the Khandesh region of India. Findings The findings of this study revealed that traditional SMM is statistically linked with the performance of students in terms of skill and knowledge enhancement, satisfaction and referral act of students, which are perceptible new emerging SMM; performance, pleasure and pointing out in terms of service output. Practical implications Integrating SMM as service input and service output are productive for HTE in enhancing growth (quantitatively) by the inclusivity of diversified students and development (qualitatively) by enhancing their performance for global standing, making them satisfied and motivating them for recommending their institution to others. This integration can be utilized as a yardstick by the institutions for staying ahead in students’ market with a distinctive competitive advantage. Social implications Growth and development of HTE will raise a society’s quality of life and thereby increase a country’s socio-economic status. Originality/value The study has exhibited SMM as input and output of a service system that is useful for the growth and development of HTE. The measurement tool presented is effective in (re)framing policies on SMM as service input based on desired service output.
The diversity of tree and open green space (OGS) of hospitals in Banda Aceh

This study has been conducted using the quadratic method to find out the species diversity index (H’). Five quadratic plots, with size of 10 m x 10 m (tree strata) were made for each area of samples. The percentage of open green space for each unit samples was measured by the calculation of ratio of the hospital area and the area of open green space for each sample unit. The result of the study was there were 51 species of trees which belongs to 28 families. The importance of each species in all stations was small or relatively homogeneous, but there were eight species of relatively high importance plants. The results of the diversity index analysis (H’) showed that the value of H’ ranged from 1.484 to 3.082, which placed two hospitals into high H’ values including Zainal Abidin Hospital (H’ = 3.082) and Kesdam Hospital (H’ = 3.015). The other stations had H’ medium and low values. Therefore, the OGS data analysis found that 10 out of 12 observation stations had the OGS value more than 50% or the OGS ratio of 11 hospitals in Banda Aceh was > 30% and fulfil the requirements of the law on OGS.
Simulation Study on Time Series of Heart Responses

There are two main directions of studies which treat the information obtained from the recorded electrocardiograms. One is the studies with respect to the wave form of the electrocardiogram which contains the information about the heart activities during one single cycle period action of the heart. The other is the treatment of the time series regarding the R-R interval of the electrocardiogram. A lot of studies belong to the former type relating to pattern recognition and frequency analysis of some electrocardiographic waves, more especially by uSing the computer systems. And now, these techniques are applied to the clinical field [4] [10] . On the other hand, the studies in the latter direction are very few, some examples of which are the relations between the heart rate and the exercise or percentage of oxygen uptake, etc. mainly from the sports physiological point of view [2] [5] [7]. There seems to be very few examples of studies as to the R-R interval time series mOdelin.g of the heart rate. A lot of knowledge and information during the heart muscul ar exerti on wi 11 be obta ined by describing the constructions of the time series by uSing simulation technique for modeling. These results will be useful not only for the diagonosis of patients but for a side view of preventive medicine. In this paper we will discuss the problem from the view point of the latter. The information with respect to R-R interval of the heart pulse is treated as stochastic process of the time series of which obtained from the data of the electrocardiograms in state during quiet rest and quasi-rest after exercise. Also, we will discuss the stationarity of heart pulse time series, expression of the fundamental construction of the time series(simulate modeling by autoregressive process), and the spectrum analysis etc. In addition, a new estimation method for the determination of the order of autoregressive process is proposed, since this method seem to be useful for the treatment in case of the biological signals.
Distributed dataflow processing of large RDF graphs

As part of the big data world, RDF, the graph-based data model of the Semantic Web, is growing in use. Consequently, the size of available RDF data is increasing and massive datasets are becoming commonplace. Nevertheless, when analysing large RDF datasets, users are left mainly with two options: using SPARQL, the main query language for RDF, or using an existing non-RDF-specific big data language. This thesis argues that each of these two approaches has its own limitations. SPARQL is costly to compute and complex analyses can be hard to express in a purely declarative SPARQL query. On the other hand, using existing big data languages designed for tabular data commonly results in verbose, unreadable, and sometimes inefficient scripts. This dissertation, therefore, pursues defining a dataflow language specifically designed to process large RDF data on top of distributed platforms. In developing a dataflow language, this dissertation discusses three components: (i) the data query language, (ii) the underlying data model, and (iii) the physical arrangement of the underlying distributed data. On data models, we introduce RDF.co, a data model that defines a pair of a binding and a graph in the value of each expression. Compared to the SPARQL algebra, RDF.co is fully composable. We provide a formal definition of the syntax and semantics of the data model, characterise its expressivity in comparison to SPARQL, and present a number of its unique algebraic properties. Algebraic properties of RDF.co represent a unique study on relations between triple patterns. These properties, when interpreted as rewriting rules, provide theoretical foundation needed to apply cost-based query optimisation. We present rules for triple patterns elimination, insertion, and pushing down. On physical arrangement of the underlying distributed data, this dissertation focuses on graph partitioning. We define an RDF graph partitioning approach using pattern matching. This use of pattern matching allows mapping query answering over partitioned graphs to the well-studied problem of view-based query answering. Our experiments show that using pattern matching to guide graph partitioning allows leveraging knowledge that might be available about the data or the task at hand to enhance query answering time. On data query languages, this dissertation describes SYRql, a dataflow language for large scale processing of RDF data. We describe an implementation of SYRql on top of the MapReduce platform. SYRql implementation utilises the underlying data model and the partitioning of the data. Our experiments show that SYRql performance for query answering is comparable to that of other well-established big data languages such as IBM Jaql and the Apache Pig Latin.
Teachers' beliefs and technology acceptance concerning smart mobile devices for SMART education in South Korea

Teachers' beliefs are a major factor in the effective use of new technology in teaching and learning. Recently, smart mobile devices (SMDs) such as smartphones, smart pads and tablet computers have been responsible for introducing broad innovations into the education field as Self‐directed, Motivated, Adaptive, Resources‐enriched, Technology embedded education in South Korea. Teachers' beliefs and technology acceptance concerning SMDs in South Korea can be either a facilitator or a barrier to the use of SMDs in the classroom. The purpose of this study is to investigate the factors of teachers' beliefs concerning SMDs, and to examine teachers' technology acceptance of SMDs in their lessons. To address these goals, 378 primary and 390 secondary teachers participated in a survey with a 25‐item paired adjective questionnaire and a 12‐item technology acceptance questionnaire. A series of exploratory and confirmatory factor analyses and multiple regressions were applied for the statistical analysis. The results indicate that teachers' beliefs were consistently revealed the five factors of immediacy, interest, interactivity, instability and inconvenience. Regarding the effect of the technology acceptance of SMDs on teachers' beliefs, the factors of instability, inconvenience and interactivity strongly related to the perceived usefulness and ease of use of SMDs. This finding indicates that teachers' beliefs that SMDs are unstable or uncomfortable can be the main barrier to the use of technology in the classroom. [ABSTRACT FROM AUTHOR]
Location based Twitter Opinion Mining using Common-Sense Information

Sentiment analysis research of public information from social networking sites has been increasing immensely in recent years. Data available at social networking sites is one of the most effective and accurate source to identify the public sentiment of any product/service. In this paper, we propose a novel localized opinion mining model based on common sense information extracted from ConceptNet ontology. The proposed methodology allows interpretation and utilization of data extracted from social media site “Twitter” to identify public opinions. This paper includes location specific, male- female specific and concept specific popularities of product. All extracted concepts are used to calculate senti_score and to build a machine learning model that classifies the user opinions as positive or negative.
Road detection based on the fusion of Lidar and image data

In this article, we propose a road detection method based on the fusion of Lidar and image data under the framework of conditional random field. Firstly, Lidar point clouds are projected into the monocular images by cross calibration to get the sparse height images, and then we get high-resolution height images via a joint bilateral filter. Then, for all the training image pixels which have corresponding Lidar points, we extract their features from color image and Lidar point clouds, respectively, and use these features together with the location features to train an Adaboost classifier. After that, all the testing pixels are classified into road or non-road under a conditional random field framework. In this conditional random field framework, we use the scores computed from the Adaboost classifier as the unary potential and take the height value of each pixel and its color information into consideration together for the pairwise potential. Finally, experimental tests have been carried out on the KITTI Road data set, and the results show that our method performs well on this data set.
Two-Stage Stochastic Approach for Reference Network Considering Uncertain Reliability

With the increasing load level in the future, the optimal capacity of each transmission line is an important factor which can protect the power systems with contingency events. In this paper, a two-stage stochastic model is proposed to determine the optimal transmission line capacities based on reference network model , in which the generators and loads are the same as those in the existing transmission system and the expected interruption cost (EIC) under contingency events should be respected. It can guide the transmission network planning. The objective function is to minimize the generation cost, the investment cost of transmission lines and the EIC. In the first-stage, the initial power flow and generated output without contingency events is calculated. In the second-stage, the optimal line flow and generated output under contingency events is calculated. The large-scale problem can be divided into two parts: 1) the master problem; 2) a series of sub problems considering contingency. So the model can be solved by using a decomposed algorithm based on Bender’s decomposition. The model was applied to IEEE 118-node system for verification and efficiency.
A curated Domain centric shared Docker registry linked to the Galaxy toolshed

Nowadays, Docker containers are used to ease application deployment, from command lines tools to cluster management1. This technology has a strong impact in bioinformatics where specialized software can often require multiple dependencies. It is a long term preservation solution for legacy and unmaintained tools and it enables a better process isolation in a multi-user environment. Docker as a way to quickly integrate new tools is already used with Galaxy. We have setup a functional prototype of a web registry of Docker images, BioShaDock,2 dedicated to bioinformatics tools and utilities. We created a set of tools descriptors based on Docker images available in our toolshed3. Even if a general purpose registry can be used to hold shared Docker containers, we think that a domain centric registry, e.g. for the French life science community through a registry linked to the cloud of the French Institute of Bioinformatics (IFB8), would have a significant impact on bioinformatician productivity and help to spread best practices. With a clear open source and domain orientation, it could federate container providers4,5 more easily. It would also be able to include validation and curation to eliminate redundant tools, organize versioning and standardize documentation. Future works will concern advanced searching capabilities, possible referencing within the ELIXIR Tools and Data Services Registry6 and in the IFB one (as the ELIXIR French node). We want also to contribute to standardize containers7 and evaluate if benchmarks5 could be produced from a meta-data enriched, Docker registry. References: 1 Google Kubernetes, Docker container cluster management : kubernetes.io 2 BioShaDock, a Bioinformatics Shared Docker registry : http://docker-ui.genouest. org 3 GUGGO Galaxy Tooshed : http://toolshed.genouest. org 4 Hexabio Docker repository : http://biodocker.github. io 5 Nucleotid.es, continuous, objective and reproducible evaluation of genome assemblers using docker containers : http://nucleotid.es 6 ELIXIR Tools and Data Services Registry : https://elixir-registry.cbs. dtu.dk 7 Bioboxes, a standard for creating interchangable bioinformatics software containers : http://bioboxes.org 8 IFB academic Cloud : http://www.france-bioinformatique.fr/? q=en/core/e-infrastructure-team/ifb-cloud