Miracle-dz/UniFAR-FTUs huggingface dataset:
A Signal Processing Perspective of Financial Engineering

Despite the different nature of financial engineering and electrical engineering, both areas are intimately connected on a mathematical level. The foundations of financial engineering lie on the statistical analysis of numerical time series and the modeling of the behavior of the financial markets in order to perform predictions and systematically optimize investment strategies. Similarly, the foundations of electrical engineering, for instance, wireless communication systems, lie on statistical signal processing and the modeling of communication channels in order to perform predictions and systematically optimize transmission strategies. Both foundations are the same in disguise. It is often the case in science that the same or very similar methodologies are developed and applied independently in different areas. A Signal Processing Perspective of Financial Engineering is about investment in financial assets treated as a signal processing and optimization problem. It explores such connections and capitalizes on the existing mathematical tools developed in wireless communications and signal processing to solve real-life problems arising in the financial markets in an unprecedented way. A Signal Processing Perspective of Financial Engineering provides straightforward and systematic access to financial engineering for researchers in signal processing and communications so that they can understand problems in financial engineering more easily and may even apply signal processing techniques to handle some financial problems.
Uma Nova Abordagem Fonetico-Fonologica em Sistemas de Reconhecimento de Fala Espontânea

This work describes a continuous speech recognition system. using a phonetic-phonological ap­ proach, covering a large vocabulary. The basic theory and implementation technique for the acoustic pattern recog­ nition is the well-known Hidden Markov Models (HMM). Furthermore, the linguistic approach is enhanced, spotting the concepts, definitions and research lines in Linguistics, providing useful and applicable elements to build a large vocabulary speech recognition system. This system im­ proves the speech recognition performance with phonetic­ phonological modeling. The general likelihood scores are increased, getting a better recognition performance, due to the statistical phonetic structure enhancement of some fre­ quent phonetic combinations usually found in the idiom. The utilization of this new phonetic-phonological approach is strongly recommended in spontaneous speech recognition systems.
Traffic Flow Prediction Based on Extended Multi-component Graph Convolutional Network

Traffic flow prediction is always considered to be a challenging task due to the complex periodicity of traffic flow data, the dynamic nature of real-time change and the spatial-temporal dependence of road network. Aiming at the above problems, this paper proposes a new traffic flow prediction model based on Extended Multi-component Graph Convolutional Network (EMGCN), which solves the problem that the existing traffic flow prediction methods are not sufficient to extract spatial-temporal features. Specifically, we introduce extended multi-component module to extract periodic temporal diffusion information of traffic flow. Then, the encoder consists of gated recurrent unit and graph convolutional network to capture the spatial-temporal features of traffic flow, and finally converts the spatial-temporal features into future prediction sequences through the decoder. Extensive experiments are carried out on the public traffic datasets PEMSD8, and the experimental results show that the proposed model achieves the best results in all aspects.
Motivation and Design of the Sirocco Storage System Version 1.0.

Sirocco is a massively parallel, high performance storage system for the exascale era. It emphasizes client-to-client coordination, low server-side coupling, and free data movement to improve resilience and performance. Its architecture is inspired by peer-to-peer and victim- cache architectures. By leveraging these ideas, Sirocco natively supports several media types, including RAM, flash, disk, and archival storage, with automatic migration between levels. Sirocco also includes storage interfaces and support that are more advanced than typical block storage. Sirocco enables clients to efficiently use key-value storage or block-based storage with the same interface. It also provides several levels of transactional data updates within a single storage command, including full ACID-compliant updates. This transaction support extends to updating several objects within a single transaction. Further support is provided for con- currency control, enabling greater performance for workloads while providing safe concurrent modification. By pioneering these and other technologies and techniques in the storage system, Sirocco is poised to fulfill a need for a massively scalable, write-optimized storage system for exascale systems. This is version 1.0 of a document reflecting the current and planned state of Sirocco. Further versions of this document will be accessible at http://www.cs. sandia.gov/Scalable_IO/ sirocco .
Cloud Computing Risk Analysis

This paper studied the data security issues faced by Hadoop for large-scale business-critical systems. With the use of cloud computing in depth, the safety problem becomes more evident. The paper, first, gave an overview of the cloud computing concept, characteristics, and then analyzed the security requirement of cloud computing, finally, identified the cloud assets, analyzed the cloud-specific vulnerability and cloud computing risks.
Implementation of the Algorithm for Congestion control in the Dynamic Circuit Network (DCN)

Transport Control Protocol (TCP) incast congestion happens when a number of senders work in parallel with the same server where the high bandwidth and low latency network problem occurs. For many data center network applications such as a search engine, heavy traffic is present on such a server. Incast congestion degrades the entire performance as packets are lost at a server side due to buffer overflow, and as a result, the response time becomes longer. In this work, we focus on TCP throughput, round-trip time (RTT), receive window and retransmission. Our method is based on the proactive adjust of the TCP receive window before the packet loss occurs. We aim to avoid the wastage of the bandwidth by adjusting its size as per the number of packets. To avoid the packet loss, the ICTCP algorithm has been implemented in the data center network (ToR).
The Research on Multi-Sensor Information Fusion with Out-Of-Sequence Measurement

In a multiple sensor tracking system, out-of-sequence measurement(OOSM) always occurs due to communication delays. The system needs to solve with the OOSMS in order to improve the precision. Updating the state estimation is one method of dealing with such problems. It presents one method of solving with OOSMS in the multi-sensor information fusion, and the simulation shows that the algorithm can improve the estimation effectively.
Phase Control in Interpolation for Backprojection of THz FMCW SAR Signals

The THz frequency spectrum opens a lot of applications in the imaging at sub-mm level. The increase of the operating frequency band for SAR imaging systems to the THz range has proportionally affected the amount of raw data to be stored and used for accurate image reconstruction. As a consequence, improvements in the existing SAR imaging algorithms to reduce the amount of data needed to achieve the appropriate quality of imaging is desired. This paper introduces the phase control procedure as an extension to the existing sinc interpolator for backprojecting complex-valued FMCW SAR data into a defined image plane. The proposed extension controls the phase of interpolated complex-valued SAR data parameters so that it includes appropriate information about the range distance between the SAR system and the given point of space. The extended algorithm is incorporated into the global backprojection algorithm and examined on the measurement data acquired via the 2πSENSE FMCW SAR system. The efficiency of the extended algorithm is evaluated through the comparison with the conventional nearest neighbor and sinc interpolation algorithms.
A machine learning perspective on responsible gambling

Abstract Gamblers are frequently reminded to ‘gamble responsibly’. But these qualitative reminders come with no quantitative information for gamblers to judge relative product risk in skill-based gambling forms. By comparison, consumers purchasing alcohol are informed of product strength by alcohol by volume percentage (ABV%) or similar labels. This paper uses mixed logistic regression machine learning to uncover the potential variation in soccer betting outcomes. This paper uses data from four bet types and eight seasons of English Premier League soccer, ending in 2018. Outcomes across each bet type were compared using three betting strategies: the most-skilled prediction, a random strategy and the least-skilled prediction. There was a large spread in betting outcomes, with, for example, the per-bet average loss varying by a factor of 54 (from 1.1% to 58.9%). Gamblers’ losses were positively correlated with the observable betting odds across all bets, indicating that betting odds are one salient feature that could be used to inform gamblers about product risk. Such large differences in product risk are relevant to the promotion of responsible gambling.
A Method for Automatic Detection of Ships in Harbor Area in High-Resolution Remote Sensing Image

In high-resolution optical remote sensing images the gray-scale and texture features,of the ships docking in harbor area are similar to that of the coast,so it is difficult to automatically detect them compared with the ships at sea.In view of the stability of the geometric layout of harbor,an automatic ship detection method based on geographic information is presented.This method stores geographic information in the form of template,which integrates both advantages of vector data and grid data,then roughly segments targets using automatic threshold.After that,based on a priori information and relative knowledge,connected targets are divided and broken parts are linked.Simulation experiments show that this method can detect ship targets in harbor area accurately and efficiently.
Reinforcement Learning Algorithms: Survey and Classification

Reinforcement Learning (RL) has emerged as a strong approach in the field of Artificial intelligence, specifically, in the field of machine learning, robotic navigation, etc. In this paper we try to do a brief survey on the various RL algorithms, and try to give a perspective on how the trajectory is moving in the research landscape. We are also attempting to classify RL as a 3-D (dimensional) problem, and give a perspective on how the journey of various algorithms in each of these dimensions progressing. We provide a quick recap of basic classifications in RL, and some popular, but old, algorithms. This research paper then discusses some of the recent trends; and also summarizes the entire landscape as can be seen from a bird’s eye view. We provide our perspective in saying that Reinforcement learning is a 3D problem and conclude with challenges that remain ahead of us. We have deliberately kept any deep mathematical equations and concepts out of this paper, as the purpose of this paper is to provide an overview and abstractions to a serious onlooker. We hope this paper provides a brief summary and trends in RL for researchers, students and interested scholars.
Research on Text Information Processing:Review

The object of text information processing is to analyze and transact information about text from superficial to interior,here to there.It includes extracting information from the text file,getting some meaning hidden in the text by analyzing and mining it.We discussed the work about text information processing in detail,and summarized the history of text information processing.We summed up text information transaction into word segmentation,information extrac-ting from text,text classification,text information retrieval,automatically summary from text etc,and summarized the correlation research work and pointed out the problem in the fields.At last we discussed the key technology and chal-lenge in the text information processing and pointed out that the object is text semantics analysis,induction,deduction and conversion between text and language.
Neonatal imitation: Temporal characteristics in imitative response patterns.

Neonatal imitation has been an area that has attracted intense attention within developmental psychology. Reported here are data from 33 newborn infants (16 girls; mean age: 47 hr) assessed for imitation of tongue protrusion (TP) and mouth opening (MO). The stimuli were presented dynamically, in three 20-second-long gesture modeling intervals, interwoven with three 20-second-long intervals in which the presenter kept a passive face. Imitation of TP emerged among a majority of the infants during the first 60 s of the experiment. In contrast, MO showed a protracted response and a majority exhibited imitation after 60 s. The individual response pattern of the participating infants varied substantially over the course of the experiment. The study provides renewed support for neonatal imitation of MO and TP, and, in addition, suggests that the temporal organization of the responses observed is an important factor to consider, which in turn has methodological and theoretical implications.
SEMANTIC QUERY BASED SERVICE DISCOVERY SCHEME USING MAPREDUCE

-Cloud computing environment provides large scale resources and services for the users through the Internet environment. Shared services are provided to execute user required services with cloud resources. Big data applications are building to manage huge amount of data values. MapReduce techniques are applied to divide and process the data and tasks. Hadoop is a widely-adopted distributed computing platform using the MapReduce parallel processing paradigm. Service details and user access information are maintained under the cloud for service discovery process. Service access information are maintained for the future references to assess the performance levels. Service recommendation tools are employed to discover appropriate services for the users. Big data applications are constructed to manage customer, services and access information for the service recommendation process. Scalability and inefficiency are the main problems identified under the traditional service discovery process. The service recommender systems use the same rating and ranking model for the discovery process. Keyword-Aware Service Recommendation (KASR) method is adapted for the service discovery process. The KASR method is mainly focused to perform personalized service recommendation process with user preferences. Keywords are used to indicate users' preferences. The user-based Collaborative Filtering algorithm is adopted to generate appropriate recommendations. Semantic query based service discovery process is supported by the KASR scheme. KASR is implemented on Hadoop to improve the scalability and efficiency on big data. KASR significantly improves the accuracy and scalability of service recommender systems.
The development of science process skills in visually impaired students: analysis of the activities

Students with visual impairments face tremendous challenges in daily life while learning life skills as they do not have the benefit of visual cues. The skills that visually impaired students are expected to learn include not only everyday life skills, but also scientific process skills too. In this study, case study was used to develop an instructional design to teaching science concepts to visually impaired students. The aim of this study is to analyze the efficacy of science activities of this developed instructional design. The study consists of three basic stages. In the first stage, visually impaired students’ learning needs are identified. In the second stage teaching materials and activities are designed and developed. In the last stage, these activities were analyzed in terms of scientific process skills through observation forms. As a result, most of the developed activities are suited for development of the scientific process skills.
Algorithms, Interfaces, and the Circulation of Information: Interrogating the Epistemological Challenges of Facebook

As social and political life increasingly takes place on social network sites, new epistemological questions have emerged. How can information disseminated through new media be understood and disentangled? How can potential hidden agendas or sources be identified? And what mechanisms govern what and how information is presented to the user? By drawing on existing research on the algorithms and interfaces underlying social network sites, this paper provides a discussion of Facebook and the epistemological challenges, potentials, and questions raised by the platform. The paper specifically discusses the ways in which interfaces shape how information can be accessed and processed by different kinds of users as well as the role of algorithms in pre-selecting what appears as representable information. A key argument of the paper is that Facebook, as a complex socio-technical network of human and non-human actors, has profound epistemological implications for how information can be accessed, understood, and circulated. In this sense, the user's potential acquisition of information is shaped and conditioned by the technological structure of the platform. Building on these arguments, the paper suggests that new epistemological challenges deserve more scholarly attention, as they hold wide implications for both researchers and users.
Entendiendo la percepción de las madres sobre la actividad física de los niños y niñas

Currently, there is little research on mothers’ perceptions of the social support they provide for their children to be physically active, which could yield important information in the construction of interventions that promote active lifestyles in childhood. We conducted individual interviews and three focus groups with 15 mothers of children 6 to 8 years old. The data were thematically analyzed using a qualitative approach, applying Ecological Model constructs to guide coding and categorization of results and the discussion of these results. The majority of mothers acknowledged that their sons and daughters were relatively less active and indicated that they perceived a need for increased physical activity among their children. The use of social support strategies was minimal, limited to accompanying their children. Mothers reported environmental factors such as cost, time constraints, lack of extracurricular-community activities and unsafe environments as the main barriers to their children’s physical activity. This study generated three main categories of results: the information gathered following the ecological model as a framework for analysis generated suggests that mothers are not aware of lack of physical activity of their children; mothers do not know ways to use social support for active lifestyles in their children, and recognize barriers to increase children’s physical activity. These research findings may contribute to health promotion strategies and programs that educate parents on how to effectively support their child in developing an active style of life.
A Role-Based Web Security Access Control System

A role-based access control model is analyzed and the related concepts are defined. The implemented model and algorithms are presented. A new feasible security solution is provided for the problems existing in the authentication and authorization on web application. As a result, a web security management system is implemented by using the role-based access control model. The system has sound, stable and valid performances of application in real environments.
Student Performance in E-Learning Environments: An Empirical Analysis through Data Mining

The aim of this chapter is to explore the application of data mining for analyzing performance and satisfaction of the students enrolled in an online two-year master degree programme in project management. This programme is delivered by the Academy of Economic Studies, the biggest Romanian university in economics and business administration in parallel, as an online programme and as a traditional one. The main data sources for the mining process are the survey made for gathering students’ opinions, the operational database with the students’ records and data regarding students activities recorded by the elearning platform are. More than 180 students have responded, and more than 150 distinct characteristics/ variable per student were identified. Due the large number of variables data mining is a recommended approach to analysis this data. Clustering, classification, and association rules were employed in order to identify the factor explaining students’ performance and satisfaction, and the relationship between them. The results are very encouraging and suggest several future developments.
O ensino dos meios táticos de grupo do handebol utilizando jogos e brincadeiras: Uma proposta pedagógica para a iniciação esportiva

O objetivo deste estudo e apresentar possibilidades para o ensino dos meios tecnico-taticos basicos ofensivos do handebol para criancas e adolescentes na iniciacao esportiva, no ensino formal e nao formal. Para isso, sao apresentados conceitos do ludico, brincadeira e jogo, alem dos diversos conceitos dos meios tatico-tecnicos, e exemplos praticos para ensina-los utilizando jogos e brincadeiras. Dessa forma, este estudo torna possivel aos professores de educacao fisica, tanto do ensino formal, quanto das escolinhas de iniciacao esportiva, desenvolver aspectos taticos do handebol de maneira ludica, prazerosa, sem que ocorra o treinamento especializado, utilizando atividades motivadoras e ao mesmo tempo pedagogicas para o ensino da modalidade. Abstract The purpose of this study is to present possibilities for the teaching of the basic technical-tactical elements of handball for children and adolescents in sports initiation, as in formal and non-formal education. Therefore, we present concepts of ludic, play and games, as well as the different concepts of technical-tactical elements, and practical examples to teach them using games. Thus, this study makes it possible for physical education teachers, both in formal education and in sports initiation schools, to develop tactical aspects of handball in a playful and enjoyable way, without the need of specialized training, using motivational and pedagogical activities to teach sport. Resumen El objetivo del estudio es presentar posibilidades para la ensenanza de los medios tecnico-tacticos basicos ofensivos del balonmano para ninos y adolescentes en la iniciacion deportiva, en la ensenanza formal y no formal. Para ello, se presentan conceptos del ludico, broma y juego, ademas de los diversos conceptos de los medios tecnico-tacticos, y ejemplos practicos para ensenarles utilizando juegos y bromas. De esta forma, este estudio hace posible a los profesores de educacion fisica, tanto de la ensenanza formal y de las escuelas de iniciacion, desarrollar aspectos tacticos del balonmano de manera ludica, placentera, sin que ocurra el entrenamiento especializado, utilizando actividades motivadoras y al mismo tiempo pedagogicas para la ensenanza de la modalidad.