Miracle-dz/UniFAR-FTUs huggingface dataset:
An Analysis of the Repeated Financial Earthquakes

Since the seismic behavior of the earth’s energy (which follows from the power law distribution) can be similarly seen in the energy realized by the stock markets, in this paper we consider a statistical study for comparing the financial crises and the earthquakes. For this end, the TP statistic, proposed by Pisarenko and et al. (2004), is employed for estimating the critical point or the lower threshold, i.e. the point beyond that the market energy follows from the power law (Pareto) distribution. The results confirm the deviation of the energy from the Pareto distribution in the high quantiles of the energy data. The upper threshold that the energy's distribution is changed from the Pareto to another distribution is also estimated by TP statistic. A simulation study is employed for checking out the statistical behavior of the estimated thresholds. Finally, the magnitude of the financial earthquakes is studied. The results indicate that the domestic and the international events have caused the financial earthquakes in Tehran Stock Exchange. Also, the positive relation between the daily energy released and the daily magnitude of the shocks that was connected by Gutenberg and Richter (1956) is confirmed.
Under-Rewarded Efforts: The Elusive Quest for Prosperity in Mexico

Why has an economy that has done so many things right failed to grow fast? Under-Rewarded Efforts traces Mexico’s disappointing growth to flawed microeconomic policies that have suppressed productivity growth and nullified the expected benefits of the country’s reform efforts. Fast growth will not occur doing more of the same or focusing on issues that may be key bottlenecks to productivity growth elsewhere, but not in Mexico. It will only result from inclusive institutions that effectively protect workers against risks, redistribute towards those in need, and simultaneously align entrepreneurs’ and workers’ incentives to raise productivity.
CCEPAS: the creation and validation of a fast and sensitive clinical whole exome analysis pipeline based on gene and variant ranking

Aim: Whole exome sequencing technology has permitted the discovery of genes that cause Mendelian disorders and was used in clinical laboratories. However, identifying the disease causing variant(s) for a specific disorder from thousands of variants is challenging. In this study, we describe the Cincinnati Clinical Exome Pipeline Analysis Suite (CCEPAS) that utilizes a four-level framework into one analysis procedure that rapidly identify the most likely causative gene variants to establish a clinical diagnosis. Methods: We developed and validated CCEPAS using 100 clinical exome cases. We applied this pipeline to clinical cases by first translating phenotypic information into candidate gene lists using Pheno2Gene. This list of candidate genes was given to the VarEval algorithm to guide variant filtering and prioritization. Finally, a short list of filtered variants was produced for clinical interpretation. Results: We demonstrated the development and implementation of CCEPAS to aid in the variant prioritization and filtering to produce a short list of candidate variants for clinical diagnosis. Its unique Pheno2Gene tool utilized an extensive list of resources and provided an accurate, sensitive and specific way to obtain gene lists from clinical feature keywords. In addition, VarEval narrowed down the variants from ~150,000 to the top 20 (trios) and top 50 (singleton) for further variant curation and candidate determination. Conclusion: Significantly, employment of CCEPAS rapidly provided causative variants in the top 20 and top 50 variants for single and trio cases, respectively, thus, ending the diagnostic odyssey in more than 30% of our clinical exome cases.
Distributed OPAC System Using Z39.50 Protocol

1675 | P a g e A u g 2 0 , 2 0 1 3 Distributed OPAC System Using Z39.50 Protocol K. Madhuri Y. Chandramohan Reddy Reddy K.Neeraja 1M-Tech in CSE, CMRTC, Hyderabad, India, madhuri.it1234@gmail.com 2M-Tech in CSE, CMRTC, Hyderabad, India, chandram97@gmail.com 3Associate Professor CSE, CMRTC, Hyderabad, India, kneeraja123@gmail.com ABSTRACT Online Public Access Catalogue is playing a vital role in Central Libraries and University/College Libraries. Most of the College libraries are using OPAC for easy search and retrieval of the books and it’s Status in a Particular Library. The main limitation in the OPAC we are using in current system is; that we are able to search and retrieve the information about the books of that particular library, but not outside of it. When we have a scenario like if we have multiple libraries in a campus, if we need to search a book in all the libraries, we have only two possibilities to build OPAC, once to make the single database for all the Libraries or you need to ask the user to search in all OPAC Systems of respective Library manually. But both above solutions are not feasible in real time environment. So in order to have the above scenario a feasible solution we need to build a distributed environment for the OPAC, which will have all the individual databases connected remotely. KEY TERMS Catalogue, Distributed databases, Remote Databases, Z39.50 Protocol,
Plantas utilizadas como antidiabéticas na medicina popular do Rio Grande do Sul, Brasil

VI INTRODUÇÃO . 01 OBJETIVOS . 06 MATERIAL E MÉTODOS . 07 RESULTADOS . 09 DISCUSSÃO . 12 CONSIDERAÇÕES FINAIS. 19 REFERÊNCIAS BIBLIOGRÁFICAS . 27
Construction of a Robust Background Model for Moving Object Detection in Video Sequence

Background Subtraction (BGS) is one of the main techniques used for moving object detection which further utilized in video analysis, especially in video surveillance systems. Practically, acquiring a robust background (reference) image is a real challenge due to the dynamic change in the scene. Hence, a key point to BGS is background modeling, in which a model is built and repeatedly used to reconstruct the background image. From N frames the proposed method store N pixels at location(x,y) in a buffer, then it classify pixel intensity values at that buffer using a proposed online clustering model based on the idea of relative run length, the cluster center with the highest frequency will be adopted as the background pixel value at location (x,y). For background updating, two approaches has been proposed to repeatedly update background image. The experiment results show that the average Precision, Recall and F-measure for the proposed method was 0.89, 0.96 and 0.93 respectively. While the average time in seconds required to construct background pixel from a buffer of size 50, 100 and 150 pixel was 0.0022813 sec , 0.0510166 sec and 0.12240419 sec respectively.
Data mining student choices: A new approach to business curriculum planning

ABSTRACT The authors used a clustering technique to analyze business course choices made by students who completed an individualized degree in a large, urban, public university. They looked for patterns to answer the research question, “What can we learn from students' choices to inform the curricular redesign process in business programs? ” The authors found five well-defined clusters; two clusters (marketing-management and marketing-management economics) did not correspond to academic paths in the university's business school. These clusters illuminate trends to be considered in business curricular design. This is the first known study to data mine students' courses choices for curricular design purposes.
Tree-LSTM and Cross-Corpus Training for Extracting Biomedical Relationships from Text

A key aspect of machine learning-based relationship extraction algorithms is the availability of training data. Manually annotated corpora are valuable resources for this task, but the time and expertise required for their development explain that still few corpora are available. For tasks related to precision medicine, most of them are rather small (i.e., hundreds of sentences) or focus on specialized relationships (e.g., drug-drug interactions) that rarely fit what one wants to extract. In this paper, we experiment Tree-LSTM, to extract relationships from biomedical texts with high performance. In addition we show that relatively large corpora, even when focusing on a distinct type of relationships, can be use to improve the performance of deep learning-based system for relationship extraction tasks for which initial resources are scarce.
Key Points for an Ethical Evaluation of Healthcare Big Data

Background: The article studies specific ethical issues arising from the use of big data in Life Sciences and Healthcare. Methods: Main consensus documents, other studies, and particular cases are analyzed. Results: New concepts that emerged in five key areas for the bioethical debate on big data and health are identified—the accuracy and validity of data and algorithms, questions related to transparency and confidentiality in the use of data; aspects that raise the coding or pseudonymization and the anonymization of data, and also problems derived from the possible individual or group identification; the new ways of obtaining consent for the transfer of personal data; the relationship between big data and the responsibility of professional decision; and the commitment of the Institutions and Public Administrations. Conclusions: Good practices in the management of big data related to Life Sciences and Healthcare depend on respect for the rights of individuals, the improvement that these practices can introduce in assistance to individual patients, the promotion of society’s health in general and the advancement of scientific knowledge.
Probabilistic inference-based reinforcement learning

We introduce probabilistic inference-based reinforcement learning (PIReL), an approach to solve decision making problems by treating them as probabilistic inference tasks. Unlike classical reinforcement learning, which requires explicit reward functions, in PIReL they are implied by probabilistic assumptions of the model. This would enable a fundamental way to design the reward function by model selection as well as bring the potential to apply existing probabilistic modeling techniques to reinforcement learning problems.
A VISUALIZATION ARTEFACT TO SUPPORT LEARNING IN DATABASES

This paper focuses on how the concept of visualization can assist learners in their endeavour to understand, model and practically implement databases. From the perspective of an honours learner working as a student assistant in databases, as well as being a learner in that same subject modules only recently; the difficulties learners experience in this class initiated the identification of a problem. The main obstacles include understanding, interpreting and compiling Entity Relationship Diagrams that needs to be implemented as database tables before the construction of Structured Query Language queries can commence. In assisting learners to overcome the struggles mentioned, the idea of creating an artefact that will help learners to visualize the link between an Entity Relationship Diagram and the queries to be built, presented itself. The main objective of creating the suggested visualization artefact in this context is to facilitate the mapping between the Entity Relationship Diagram and the queries to be built. Understanding how to compile a logical Entity Relationship Diagram, as well as its physical counterpart, the Database Schema, are both important modelling tools to include in a third year computer science learner's skills list when they finish their degree course and start working. Likewise, the implementation of the model in a database environment and the subsequent manipulation of the data are valuable skills. The suggested artefact intends enhancing learners' understanding of the analysis, design, development, and support of databases through visualization. Since the development of an artefact is only a first step towards assisting learners, especially those from disadvantaged communities, potential further studies are scrutinized.
Demonstrace možností technologie Cisco OnePK

This bachelors thesis aims to demonstrate the uses of Quality of Services (QoS) within Cisco onePK technology. The created prototype (Gosia) enables the dynamic direction of previously defined data on the basis of a simple configuration language. Individual changes in the direction of the data flow are derived from the state of the network infrastructure. Klíčová slova Cisco onePK, Cisco ONE, OpenFlow, SDN, QoS, RSVP, Gosia
A Fluidic Vibrational Energy Harvester for Implantable Medical Device Applications

SUMMARY In this paper, we report on a proof-of-concept level energy harvester device that could earn electric power of 0.093 μ W/cm 2 by the fluidic motion in a polydimethylsiloxane microfluidic channel placed on a silicon substrate with built-in permanent electrical charges or so-called electrets. Targeting implantable medical devices such as respiratory pacemaker, the heart beat or aspiration is thought to be the source of motion as a final shape of the energy harvesting system. C ⃝ 2018 Wiley Periodicals, Inc.
Performance and Improvement of Antenna Designs in Modern Wireless Communication System

In this paper, the cell innovation and the remote correspondence innovation is creating and enhancing quickly. The reception apparatus goes about as the scaffold between the client terminal and the base station controller. Being a key segment of the remote correspondence framework, the reception apparatus’ fundamental capacity is to communicate and to get electromagnetic waves. It will, to an expansive degree, influence the quality and the speed of the correspondence. With the advancing of the reception apparatus innovation, the versatile terminal gadgets have developed from the unique specialized devices to exceptionally intellectualized types of gear. The imparted content was likewise expanded, as there are presently FM programs, TV shows and web. All these, be that as it may, conveys requesting benchmarks to the reception apparatus. For instance, it requires a considerably higher data transmission and best exhibitions from the reception apparatus to help the complex applications and correspondence capacity of the versatile terminals. Furthermore, the correspondence system’s convenient terminal has almost bolted the position of the recieving wire, which requests that the span of the radio wire must be downscaled. The control of the wave speed, shape and its directivity can be typically streamlined by enhancing the radiation qualities of the recieving wires, which will help the general execution of a framework. In along these lines, additionally enhanced are the channel limit and the recurrence use proportion. This paper, starting with the presentation of the improvement status of the remote correspondence framework and the radio wires, contemplates a portion of the plans of new reception apparatuses. With that review, this paper likewise breaks down the advancement heading fitting to current correspondence framework and the important gadgets, and in addition the structure adjustment and pattern of reception apparatuses.
Neighbourhood Gentrification and upgrading in Montreal, Toronto and Vancouver

The complete study is reported on in R. Alan Walks and Richard Maaranen, The Timing, Patterning, and Forms of Community Gentrification and Neighbourhood Change in Montreal, Toronto, and Vancouver, 1961 to 2001, Research paper 211 (Toronto: Centre for Urban and Community Studies, University of Toronto, 2008).
Catégorisation automatique de propositions textuelles en types de discours

De nombreuses methodes de classification automatique de textes (supervisee ou non) existent. Elles se sont particulierement developpees depuis la creation du web en vue d'ameliorer les moteurs de recherche. Au dela de ce champs d'application, elles peuvent aussi etre utiles pour « decouvrir » ou « redecou­vrir » ce qui caracterise une classe de textes aussi simplement que possible. Dans l'approche statistique developpee ici, il s'agira de partitionner des parties de textes en types de discours tels que narratif, explicatif, argumentatif etc. en utilisant un minimum d'information, a savoir les categories morphosyn­taxiques (CMS). Les premiers resultats obtenus mettent en evidence des liens significatifs entre les CMS, les types de discours et des textes annotes par un expert humain ; ces relations sont toutefois encore incompletes et difficiles a interpreter d'un point de vue linguistique.
Parametrization and Effectiveness of Moving Target Defense Security Protections within Industrial Control Systems

Author(s): Chavez, Adrian R. | Abstract: Critical infrastructure systems continue to foster predictable communication patterns and static configurations over extended periods of time. The static nature of these systems eases the process of gathering reconnaissance information that can be used to design, develop, and launch attacks by adversaries. In this research effort, the early phases of an attack vector will be disrupted by randomizing application port numbers, IP addresses, and communication paths dynamically through the use of overlay networks within Industrial Control Systems (ICS). These protective measures convert static systems into "moving targets," adding an additional layer of defense. Moving Target Defense (MTD) is an active area of research that periodically changes the attack surface of a system to create uncertainty and increase the workload for an adversary. To assess the effectiveness of MTD strategies within an ICS environment, performance metrics have been captured to quantify the impacts introduced to the operational network and to the adversary. Our MTD strategies are implemented using Software Defined Networking (SDN) to provide a scalable and transparent solution to the end devices within the network. We show that our MTD techniques are feasible within an ICS environment and that they can improve the resiliency of ICS systems. Our MTD strategies meet the real-time constraints of ICS systems and incur latency impacts of less than 50 ms and in most cases, well under 20 ms. Resiliency is improved by introducing crash tolerant and Byzantine fault tolerant algorithms to detect and prevent attacks against the SDN controller. We also evaluate the success rates of individual adversaries, distributed adversaries, and those attempting side-channel attacks to learn the frequencies at which the MTD techniques reconfigure the system. We demonstrate the effectiveness of our approaches in simulated, virtualized, and representative ICS environments.
EBE-YOLOv4: A lightweight detecting model for pine cones in forest

Pine cones are important forest products, and the picking process is complex. Aiming at the multi-objective and dispersed characteristics of pine cones in the forest, a machine vision detection model (EBE-YOLOV4) is designed to solve the problems of many parameters and poor computing ability of the general YOLOv4, so as to realize rapid and accurate recognition of pine cones in the forest. Taking YOLOv4 as the basic framework, this method can realize a lightweight and accurate recognition model for pine cones in forest through optimized design of the backbone and the neck networks. EfficientNet-b0 (E) is chosen as the backbone network for feature extraction to reduce parameters and improve the running speed of the model. Channel transformation BiFPN structure (B), which improves the detection rate and ensures the detection accuracy of the model, is introduced to the neck network for feature fusion. The neck network also adds a lightweight channel attention ECA-Net (E) to solve the problem of accuracy decline caused by lightweight improvement. Meanwhile, the H-Swish activation function is used to optimize the model performance to further improve the model accuracy at a small computational cost. 768 images of pine cones in forest were used as experimental data, and 1536 images were obtained after data expansion, which were divided into training set and test set at the ratio of 8:2. The CPU used in the experiment was Inter Core i9-10885@2.40Ghz, and the GPU was NVIDIA Quadro RTX 5000. The performance of YOLOv4 lightweight design was observed based on the indicators of precision (P), recall (R) and detection frames per second (FPS). The results showed that the measurement accuracy (P) of the EBE-YOLOv4 was 96.25%, the recall rate (F) was 82.72% and the detection speed (FPS) was 64.09F/S. Compared with the original YOLOv4, the precision of detection had no significant change, but the speed increased by 70%, which demonstrated the effectiveness of YOLOv4 lightweight design.
Disruptive Technologies and the Language Classroom: A Complex Systems Theory Approach

Although new technologies are embedded in students’ lives today, there is often an assumption that their use is transparent, inconsequential, or a distraction. This book combines complex systems theory with sociocultural theory and the multimodal theory of communication, providing an innovative theoretical framework to examine how communication and meaning-making in the language classroom have developed over time, how technology impacts on meaning-making, and what the implications are for learners, teachers, institutions and policy makers. Recent studies provide evidence for the disruptive effect of technology which has resulted in a phase shift that is reshaping language education by creating new interaction patterns, allowing for multimodal communication, and introducing real-world communication into the classroom. The book proposes ways of responding to this shift before concluding that the new technologies are radically transforming the way we learn. It is likely to appeal to a range of readers, including students, academics, teachers and policy-makers.
Game Mechanics as Videogame Genre Identifier

Contemporary genre system of video games is formed by the video game industry and it is divided into groups quite freely. This study determines the genre dominant of a video game on the basis of the analysis of theoretical literature, the findings of the developers of the gaming industry and on the basis of the analysis of video games, which are world leaders in sales. It is shown that such structural video game units, as dynamics and components, do not reveal an established connection with the category “genre” and vary from one gaming project to another. The only constant parameter, presented in video games, is mechanics that are repeated in popular projects of one genre, identifying the “face” of the genre, and its established core. Comprehensive methodology analyses of 2017 statistics data of the online digital distribution platforms of computer games “Steam” (“VALVE” company) and “Blizzard.battle. net” (“Blizzard” company) and game mechanics list of the American company-developer of social games “SCVNGR” (SCaVeNGeR) gave the opportunity to see repeated core mechanics in the videogame projects of the most widespread genres.