Miracle-dz/UniFAR-FTUs huggingface dataset:
Local Support Vector Regression for Financial Time Series Prediction

We consider the regression problem for financial time series. Typically, financial time series are non-stationary and volatile in nature. Because of its good generalization power and the tractability of the problem, the Support Vector Regression (SVR) has been extensively applied in financial time series prediction. The standard SVR adopts the lp-norm (p = 1 or 2) to model the functional complexity of the whole data set and employs a fixed e-tube to tolerate noise. Although this approach has proved successful both theoretically and empirically, it considers data in a global fashion only. Therefore it may lack the flexibility to capture the local trend of data; this is a critical aspect of volatile data, especially financial time series data. Aiming to address this issue, we propose the Local Support Vector Regression (LSVR) model. This novel model is demonstrated to provide a systematic and automatic scheme to adapt the margin locally and flexibly; the margin is fixed globally in the standard SVR. Therefore, the LSVR can tolerate noise adaptively. We provide both theoretical justifications and empirical evaluations for this novel model. The experimental results on synthetic data and real financial data demonstrate its advantages over the standard SVR.
Deep Learning in Finance

We explore the use of deep learning hierarchical models for problems in nancial prediction and classication. Financial prediction problems { such as those presented in designing and pricing securities, constructing portfolios, and risk management { often involve large data sets with complex data interactions that currently are dicult or impossible to specify in a full economic model. Applying deep learning methods to these problems can produce more useful results than standard methods in nance. In particular, deep learning can detect and exploit interactions in the data that are, at least currently, invisible to any existing nancial economic theory.
Annotation-Based Diagrams for Shared-Data Concurrency

In languages such as Java and Ada, there are a number of significant concurrency-related design decisions that may not be manifest locally in code. These include, for example, the identification of shared state, how that state is protected, which threads may visit that state, and so on. These decisions relate threads, code, and shared data. We describe new UML-style diagrams that can help make explicit some useful aspects of these relationships. In addition, by using lightweight annotations on source code, we can document how these decisions are realized. By combining diagrams and annotations, we can support both forward and reverse engineering, using tools and analyses to keep the diagrams consistent with the annotated code.
A Study of Finding Similarities in Web Service Using Metrics

Newest mounting and escalated recognition of services and its equivalent building of significant Web service mature to be a considerable rally. Web service expertise for permitting right to entry for promoting services regardless of locality and execution policies exist already. On the other hand, a huge discrepancy on structural, semantically and technological intensity all along with the emergent number of offered web services formulate their discovery a signi ocant challenge. Our proposal progresses to classify an ultimate approach for identifying web service resemblance with the help of metrics. In particular, we analyzed the intrinsic worth of using metrics based Models, WordNet metrics and semantic similarity metrics for this evaluation purpose. Index Terms—Web Service, metrics, Web Service Architecture, Simple Object Access Protocol (SOAP), (SOAP) based multicast protocol (SMP). (Web Service Manipulation Language) WSDL, Universal Description, Discovery and Integration (UDDI), XML, Web Ontology Language (OWL) ontology —————————— a —————————— 1 I eb service allows different application from differ- ent sources to communicate with each other with- out time consuming and custom coding. It is a standardized way of integrating web based applications. It allows organizations and users to communicate data without intimate knowledge of each other and share business logic, data and process through a programmatic interface across a network. It has been employed in a wide range of applications and has become a key tech- nology in developing business operations on the web. I n order to leverage on the use of web services, web service discovery and composition need to be fully supported. Several systems have been proposed to meet this need. The search and concepts lets to turn out the useful infor- mation retrieval and matching scenarios. Determination of conceptual overlap simplifies phrasing an adequate search concept. These results are ordered by degree of similarity to the searched and compared to the concepts. Delivering a flexible degree of conceptual overlap to a searched concepts gives the similarity measurements and it would additionally deliver the concepts of whose in- stances are located inside and adjacent to the search re- sult. These concepts are close and identical to the user intended concepts. Identifying the attribute filler or rela- tions for identifying the similarity in WSML (Web Service Manipulation Language) and the service integration sce- narios the similarities between the concepts are based on their specification and their chosen representation lan- guages. This proposal leads to develop metrics for identi- fying the service similarities in web services that can help the clients / users to get serviced by
An Enhanced Community Detection Method Based on Neighborhood Similarity

Detection of community structure in a social network is important for understanding the structure and dynamics of the network. Yet, most community detection algorithms do not take attributes of nodes and connections into consideration, or only make use of connections' attributes information, not fully capturing the richness of the information contained in the data. Thus, by exploring the information of nodes and connections together in a social network, we propose an enhanced community detection method, the core of which is an agglomerative hierarchical clustering algorithm. The clustering algorithm bases on an improved evaluation algorithm of neighborhood similarity. Besides, the proposed method can provide several candidate partitions obtained according to the qualitative function modularity for users to choose. Finally, a real collaborative network of scientists is constructed with the data from DBLP and experiments on the network show that our method performs well.
A parallel and distributed‐processing model of joint attention, social cognition and autism

The impaired development of joint attention is a cardinal feature of autism. Therefore, understanding the nature of joint attention is central to research on this disorder. Joint attention may be best defined in terms of an information‐processing system that begins to develop by 4–6 months of age. This system integrates the parallel processing of internal information about one's own visual attention with external information about the visual attention of other people. This type of joint encoding of information about self and other attention requires the activation of a distributed anterior and posterior cortical attention network. Genetic regulation, in conjunction with self‐organizing behavioral activity, guides the development of functional connectivity in this network. With practice in infancy the joint processing of self–other attention becomes automatically engaged as an executive function. It can be argued that this executive joint attention is fundamental to human learning as well as the development of symbolic thought, social cognition and social competence throughout the life span. One advantage of this parallel and distributed‐processing model of joint attention is that it directly connects theory on social pathology to a range of phenomena in autism associated with neural connectivity, constructivist and connectionist models of cognitive development, early intervention, activity‐dependent gene expression and atypical ocular motor control.
Involvement in extra-curricular activities facilitated by former students encourages intercultural communication, sustains student engagement and promotes positive academic outcomes

There has been significant interest in Australia and around the world about the importance of the first year university experience as a critical factor influencing first year attrition rates and the performance of students throughout their university studies. This experience includes both in-class and out of class engagement of students with university life. This paper reports an ongoing approach at UOW College, where a group of ex-College students has been employed to facilitate a number of lunchtime activities for current College students. These ex-students engage with new and existing students, both domestic and international, effectively due to their familiarity with their home cultures, languages, and confidence gained through university and life experience in Australia. Qualitative feedback and students’ performance data continue to demonstrate the effectiveness of this program. The practical guidelines and results of this initiative will have broad application for most institutions supporting first year university (particularly international) students.
Optimal Asynchronous Newton Method for the Solution of Nonlinear Equations

Etude d'une modification de la methode de Newton pour la solution de l'equation F(X)=0, sur un multiprocesseur. Introduction d'une classe de methodes asynchrones de Newton et on montre une methode optimale dans cette classe ainsi que sa mise en œuvre parallele optimale
Micro mobility management for dual connectivity in LTE HetNets

A Dual Connectivity architecture has been proposed by 3GPP for enhancement of small cells in long term evolution heterogeneous networks. A Master eNodeB (MeNB) handles handovers on behalf of the Mobility Management Entity (MME) and the Serving Gateway (SGW) for secondary eNodeBs (SeNB) located within the coverage of MeNB. Workloads of the MME and the SGW are moved to the MeNB. Small cells can be concentrated in crowded downtown or buildings in the heterogeneous network environment. The number of handovers may be increased due to concentrated small cells having small coverage, so the workload of the MeNB can be increased inside the hot spot. We propose a micro mobility management scheme to offload the workload of the MeNB to other components. The proposed scheme introduces a mobility anchor (MA) which processes the handovers between SeNBs on behalf of MeNB. Simulation results indicate the reduction of the workload of the MeNB due to the MA.
Release of Adenosine and ATP During Ischemia and Epilepsy

Eighty years ago Drury & Szent-Györgyi described the actions of adenosine, AMP (adenylic acid) and ATP (pyrophosphoric or diphosphoric ester of adenylic acid) on the mammalian cardiovascular system, skeletal muscle, intestinal and urinary systems. Since then considerable insight has been gleaned on the means by which these compounds act, not least of which in the distinction between the two broad classes of their respective receptors, with their many subtypes, and the ensuing diversity in cellular consequences their activation invokes. These myriad actions are of course predicated on the release of the purines into the extracellular milieu, but, surprisingly, there is still considerable ambiguity as to how this occurs in various physiological and pathophysiological conditions. In this review we summarise the release of ATP and adenosine during seizures and cerebral ischemia and discuss mechanisms by which the purines adenosine and ATP may be released from cells in the CNS under these conditions.
A Macroeconomic Approach to Optimal Unemployment Insurance: Applications

In the United States, unemployment insurance (UI) is more generous when unemployment is high. This paper examines whether this policy is desirable. The optimal UI replacement rate is the Baily-Chetty replacement rate plus a correction term measuring the effect of UI on welfare through labor market tightness. Empirical evidence suggests that tightness is inefficiently low in slumps and inefficiently high in booms, and that an increase in UI raises tightness. Hence, the correction term is positive in slumps but negative in booms, and optimal UI is indeed countercyclical. Since there remains some uncertainty about the empirical evidence, the paper provides a thorough sensitivity analysis.
Artificial Intelligence and Data Mining Techniques in Medicine – Success Stories

Artificially Intelligent (AI) powered tools are able to deal with uncertain and incomplete data sets. Neural network classifiers have been successfully used for prediction purposes in many complex situations. Research shows that Al-based data mining tools have been also successfully used in many medical environments. This paper advances the understanding of the application of Artificial Intelligence and Data Mining tools to clinical data by demonstrating the potential of these techniques in complex clinical situations.
Using SLA Context to Ensure Quality of Service for Composite Services

As service-orientation is establishing itself as the dominant design and integration paradigm for large heterogeneous and open systems, the lines between wired and wireless consumers and providers begin to blur. Due to the availability of toolkits and standards it is now fairly easy to build nomadic service consumers that provide users transparent access to enterprise services. However, since nomadic consumers are typically characterized by limited computational resources, they are very dependent on reliable service providers. Unlike their more resource rich wired counterparts, that can in case of a provider slowdown or failure simply rebind to an alternative provider, the nomadic consumers lack the bandwidth to execute to do so in sufficient time. This leads to the question of how to ensure QoS for providers of nomadic consumers. Especially for composite services that aggregate other services this is still an open question. This paper presents an approach for ensuring QoS for nomadic applications that consume composite services. Using transparent proxies that are control the access to each service provider the scheduling of requests and therefore the enforcement of QoS becomes possible.
A game-theoretic pricing model for Energy Internet in day-ahead trading market considering distributed generations uncertainty

This paper designs a distributed trading mechanism for Energy Internet in which the uncertainty of distributed generations (DGs) is considered. In order to match up Energy Internet, the new energy frame, a novel energy accessing mode called We-Energy (WE) is proposed for the convenience of energy regulation, energy trading and information interaction. First, multiple interconnected WEs are considered in a region where, at a given time, some WEs have superfluous energy for sale to make profits called Surplus-WEs, but some WEs need to buy additional energy to meet local demands called Short-WEs. Under the trading mechanism, the market clearing price (MCP) is determined by supplies as well as demands. Then, a Bayesian game model considering distributed generations (DGs) uncertainty is established to analyze the strategies among WEs, which are assumed as the bidding supplies and demands. A unique Bayesian-Nash equilibrium among Surplus-WEs and Short-WEs are proved respectively according to hessian matrix, and solved by using the Karush-Kuhn-Tucker (KKT) conditions. Numerical results show that the designed MPC can reflect the relationship of supply and demand better, and maximize the utility of all the WEs.
Is Tax Evasion Unethical?

A few years ago the Roman Catholic Church issued a revised catechism that categorizes tax evasion as a sin. Part I of this article explores the arguments that could be used to support the view that tax evasion is a sin, or is unethical. Part II presents arguments to support the position that there is nothing sinful or ethically wrong with tax evasion. The article concludes that the arguments offered to support the view that tax evasion is sinful or unethical do not hold up under analysis, and suggests that it is the tax collectors who might be guilty of sin, since they participate in the taking of property without the owner's consent.
An analysis of depth estimation within interaction range

Interactions between humans or humanoids and their environment through tasks like grasping or manipulation typically require accurate depth information. The human vision system integrates various monocular and binocular depth estimation mechanisms in order to achieve robust and reliable depth perception. Such an integrated approach can be applied to humanoid depth perception. Integration requires a knowledge of the characteristics of the methods being combined. Three different methods incorporating active vision (stereo disparity, vergence and familiar size) were statistically examined and combinations of these methods based on this statistical examination were investigated. We found evidence that active vision provides better depth estimations than the standard static-parallel stereo methods examined within interaction range and therefore is better suited for tasks like reaching, grasping and manipulation. We also demonstrate that a combination of methods have the potential to increase the accuracy of estimations.
A threshold-based algorithm of fall detection using a wearable device with tri-axial accelerometer and gyroscope

Fall events are the external causes of injury in the elderly adults, even leading to disability and death. In this study, we used a weightless and wearable device with built-in tri-axial accelerometer and gyroscope to record 8 types of stimulated-falls and 6 types of different activities of daily living (ADL) preformed by 6 health young subjects. A threshold-based algorithm using our device was developed to determine a fall event. Using our fall detection system, falls could be distinguished from ADL successfully for a total data set.
Alternative Tax-Benefit Strategies to Support Children in the European Union: Recent Reforms in Austria, Spain, and the UK. ENEPRI Working Paper, No. 49, 5 February 2007

We compare three EU countries that have recently experienced substantial but very different reforms of their family support systems: Austria, Spain and the UK. The structure of these systems is different: Austria emphases universal benefits, Spain tax concessions and the UK means-tested benefits. First the paper compares the distributional implications of these three approaches. The recent reforms have reinforced existing structures while increasing the amount of spending for children. The second step is to ask: What would have happened if these countries had transformed the architecture of their systems in either of the other two directions? We use EUROMOD, the European tax-benefit microsimulation model that is designed for making cross-country comparisons and answering “what if” questions such as these. We find that the three factors that can be distinguished – the level of spending, its structure, and the way it impacts in a national context – are all important to varying degrees.
Functional cerebral reorganization: a signature of expertise? Reexamining Guida, Gobet, Tardieu, and Nicolas' (2012) two-stage framework

In 2012, Guida, Gobet, Tardieu and Nicolas proposed a two-stage framework to explain how cognitive changes due to practice could shape experts' brain physiologically and thus explain neuroimaging data of expertise acquisition. In this paper, after presenting the motivations for such a framework and the framework itself, we examine the idea that functional cerebral reorganization (FCR) could be used as a signature for expertise.
Staff toward E-Government Programs In Denpasar Municipality

Holmes (2001) explains that e-government is an information technology usage, especially internet to provide better service while also bringing it closer to customer, budget efficiency with different means but better outcome. E-government brings advantages such as: cutting cost and improve efficiency, meet citizen expectations and improve citizen relationships, and facilitate economic development. The Government of Indonesia seeks the emerging of information and technology as an opportunity and uses it to enhance good governance implementation. The enhancement of good governance in Indonesia is the expected influence innovation in bureaucracy management. E-government implementation in Indonesia is based on President Instruction No. 3 year 2003 regarding E-Government Development Policy and National Strategy. On its attachment, it is also stated about the principles of e-government implementation in Indonesia. The demand in bureaucracy management innovation for good governance is stated in president instruction as well. With so many demands on civil servant to work on, e-government is the best answer. Programs are specially designed to increase effectiveness and efficiency while aslo obtaining excellent service quality for the society. This is a good opportunity for Denpasar Municipality as the local government has lack of IT staff. Staff are expected to obtain high productivity even though the tasks given are increasing. INFORMASI ART IKEL ABSTRACT
Detection of closely linked multiple quantitative trait loci using a genetic algorithm.

The existence of a quantitative trait locus (QTL) is usually tested using the likelihood of the quantitative trait on the basis of phenotypic character data plus the recombination fraction between QTL and flanking markers. When doing this, the likelihood is calculated for all possible locations on the linkage map. When multiple QTL are suspected close by, it is impractical to calculate the likelihood for all possible combinations of numbers and locations of QTL. Here, we propose a genetic algorithm (GA) for the heuristic solution of this problem. GA can globally search the optimum by improving the "genotype" with alterations called "recombination" and "mutation. " The "genotype" of our GA is the number and location of QTL. The "fitness" is a function based on the likelihood plus Akaike's information criterion (AIC), which helps avoid false-positive QTL. A simulation study comparing the new method with existing QTL mapping packages shows the advantage of the new GA. The GA reliably distinguishes multiple QTL located in a single marker interval.
µLibCloud: Providing High Available and Uniform Accessing to Multiple Cloud Storages

The increasing popularity of cloud storage services attracts large amounts of companies to store their data in cloud instead of building their own infrastructures. With large amounts of data stored in the cloud, it is expected to provide high availability and fine global access experiences. However, there are still major concerns of the availability of major cloud services, especially in a sparsely connected global network with complicated issues. In this paper, we introduce μLibCloud, a system based on Apache libCloud, aiming to improve the availability and global access experience of clouds, and to tolerate provider failures and outages. μLibCloud works as a library at client side, transparently spreading and collecting data smartly to/from different cloud providers through erasure code. In evaluation, we deployed the system into 7 major cloud providers and run a global benchmarks from 9 locations around the world. The results were compared to the original clouds and a content delivery network. We observed that μLibCloud achieved a higher and more uniformed read availability in most cases, with reasonable estimated extra costs. For example, the read latency of some original providers could be reduced by 50%-70% at different locations.