Miracle-dz/UniFAR-FTUs huggingface dataset:
Reference corpus of historical Slovene goo300k 1.2

goo300k is a manually annotated reference corpus of historical Slovene. It contains 1,100 pages (about 300,000 tokens) sampled from 89 texts from the period 1584-1899. Each text contains extensive meta-data and per-page links to facsimiles, while the word tokens in the texts are annotated with their modernised word-form, lemma, part-of-speech, and, for archaic words, their nearest modern synonyms or short explanation. The corpus is available in source TEI P5 XML and in the simpler and smaller vertical format, used by various concordancers. Note that the vertical format does not contain all the information from the source TEI.
RIGORITYJ: Deployment-quality Detection of Java Cryptographic Vulnerabilities

Cryptographic API misuses threaten software security. Examples include exposed secrets, predictable random numbers, and vulnerable certificate verification. Our goal in this work is to produce deployment-quality program analysis tools for automatically inspecting various cryptographic API uses in complex Java programs. The main challenge is how to reduce false positives (FP) without compromising analysis quality. Unfortunately, state-of-the-art solutions in this space were not designed to be deployment-grade and did not address this issue. Our main technical innovation is a set of algorithms for systematically removing irrelevant elements (from program slices) to reduce false alerts. We compared the detection capability of our tool, RIGORITYJ with popular commercial tools (e.g., DHS SWAMP and Synopsys Coverity) which shows that RIGORITYJ offers more coverage and soundness than all of them. Our evaluation on 46 high-impact large-scale Apache projects and 6,181 Android apps, which generates many security insights. We observed violations for most of our 16 rules. 96\% of the Android vulnerabilities come from the libraries. There is a widespread insecure practice of storing plaintext passwords. We manually went through the 2,008 Apache alerts and confirmed 1,961 true positives (2.34% FP rate). We contacted Apache with our security findings. This helped multiple popular Apache projects to harden their code, including Spark, Ranger, and Ofbiz. We also discuss the pragmatic constraints that hinder secure coding.
Microsoft Office Powerpoint

This free Microsoft Office Powerpoint book is not a point-for-point review of all PowerPoint’s functions. Instead it is more task-oriented, so you will be able to perform the tasks for which PowerPoint is normally used. Basically, PowerPoint cannot do anything apart from making presentations, so the book will be about how you put up your slides, and how to add text, graphics, charts, pictures and video clips. You will also learn how to work with animations, so the presentations can become livelier. To ensure that your message does not drown in colours and effects, you will also receive some good advice on presentation skills along the way. A good presentation does not only depend on making an impressive PowerPoint presentation. If you have not worked with Microsoft Office PowerPoint before, I recommend that you read the entire book from one end to another. You can then use it as a reference, since I have tried to arrange the book in a logical manner, so you can quickly find a chapter that deals with a problem similar to the one you must solve. If you already have a lot of experience with Microsoft Office PowerPoint, you can probably skip some of the first sections if you want to get to the more advanced features.
Calculating the turbulent fluxes in the atmospheric surface layer with neural networks

Abstract. The turbulent fluxes of momentum, heat and water vapour link the Earth's surface with the atmosphere. Therefore, the correct modelling of the flux interactions between these two systems with very different timescales is vital for climate and weather forecast models. Conventionally, these fluxes are modelled using Monin–Obukhov similarity theory (MOST) with stability functions derived from a small number of field experiments. This results in a range of formulations of these functions and thus also in differences in the flux calculations; furthermore, the underlying equations are non-linear and have to be solved iteratively at each time step of the model. In this study, we tried a different and more flexible approach, namely using an artificial neural network (ANN) to calculate the scaling quantities u* and θ* (used to parameterise the fluxes), thereby avoiding function fitting and iteration. The network was trained and validated with multi-year data sets from seven grassland, forest and wetland sites worldwide using the Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton backpropagation algorithm and six-fold cross validation. Extensive sensitivity tests showed that an ANN with six input variables and one hidden layer gave results comparable to (and in some cases even slightly better than) the standard method; moreover, this ANN performed considerably better than a multivariate linear regression model. Similar satisfying results were obtained when the ANN routine was implemented in a one-dimensional stand-alone land surface model (LSM), paving the way for implementation in three-dimensional climate models. In the case of the one-dimensional LSM, no CPU time was saved when using the ANN version, as the small time step of the standard version required only one iteration in most cases. This may be different in models with longer time steps, e.g. global climate models.
Resistance to ERK 1 / 2 pathway inhibitors ; sweet spots , fitness deficits and drug addiction

MEK1/2 inhibitors are clinically approved for the treatment of BRAF-mutant melanoma, where they are used in combination with BRAF inhibitors, and are undergoing evaluation in other malignancies. Acquired resistance to MEK1/2 inhibitors, including selumetinib (AZD6244/ARRY-142866), can arise through amplification of BRAF or KRAS to reinstate ERK1/2 signalling. We have found that BRAF amplification and selumetinib resistance are fully reversible following drug withdrawal. This is because resistant cells with BRAF amplification become addicted to selumetinib to maintain a precise level of ERK1/2 signalling (2%-3% of total ERK1/2 active), that is optimal for cell proliferation and survival. Selumetinib withdrawal drives ERK1/2 activation outside of this critical “sweet spot” (~20%30% of ERK1/2 active) resulting in a p57-dependent G1 cell cycle arrest and senescence or expression of NOXA and cell death with features of autophagy; these terminal responses select against cells with amplified BRAF. ERK1/2-dependent p57 expression is required for loss of BRAF amplification and determines the rate of reversal of selumetinib resistance. Growth of selumetinib-resistant cells with BRAF amplification as tumour xenografts also requires the presence of selumetinib to “clamp” ERK1/2 activity within the sweet spot. Thus, BRAF amplification confers a selective disadvantage or “fitness deficit” during drug withdrawal, providing a rationale for intermittent dosing to forestall resistance. Remarkably, selumetinib resistance driven by KRAS amplification/upregulation is not reversible. In these cells ERK1/2 reactivation does not inhibit proliferation but drives a ZEB1-dependent epithelialto-mesenchymal transition that increases cell motility and promotes resistance to traditional chemotherapy agents. Our results reveal that the emergence of drug-addicted, MEKi-resistant cells, and the opportunity this may afford for intermittent dosing schedules (“drug holidays”), may be determined by the nature of the amplified driving oncogene (BRAF vs. KRAS), further exemplifying the difficulties of targeting KRAS mutant tumour cells.
A framework for pervasively shared situational awareness in mobile ad hoc environments

This dissertation presents a novel approach to sharing situational awareness among a group of geographically dispersed mobile networked devices. We divide our efforts into two parts: getting the information to the right places, and keeping it there. We start by introducing a stochastic approach to transporting geospatial messages that shows significantly better performance than the existing deterministic approaches, particularly in adverse network topologies. Under normal conditions, our model performs better than comparable existing approaches. Under pathological conditions, however, all other approaches fail while our model remains viable. Next, we introduce a novel cooperative spatial-aware cache that can be thought of as residing in a region rather than in any given node. Each node that participates in the cache holds an expendable part of the data, so that the loss of any node or small group of nodes can be tolerated with little or no degradation of service. The results of both our analysis and simulations show that our approach works significantly better than local caching alone both in terms of hit-ratios as well as cache survivability. In fact our shared spatial caches perform one order of magnitude better than local caches in terms of cache hit ratios.
Method of Blindly Estimating Speech Transmission Index in Noisy Reverberant Environments

The speech transmission index (STI) is an objective measurement that is used to assess the quality of speech transmission as well as listening difficulty in room acoustics. Blindly estimating STI in real environments is, therefore, an important challenge. The authors previously developed a simplified method for blindly estimating STI on the basis of the concept of the modulation transfer function (MTF). The proposed scheme could be used to estimate STIs from observed reverberant signals in which the room impulse response (RIR) was approximated by Schroeder’s model, without measuring the RIRs. There were, however, four remaining issues: whether the method (1) could suitably approximate RIR, (2) was robust against different types of observed signals, (3) was robust against background noise, and (4) could feasibly estimate STI in real environments. This paper extends our previously proposed scheme to resolve these problems by proposing generalized RIR models, by considering the relationship between MTF and modulation spectrum, and by simultaneously estimating their inverse MTFs in noisy reverberant environments. Simulations were carried out to determine whether the proposed method could correctly estimate STIs from the observed speech signals in noisy reverberant environments even if the RIR could not be approximated as Schroeder’s model. The results revealed that the proposed approach could be used to effectively estimate STIs from noisy reverberant speech signals even if people were in the room and background noise existed.
MODELAGEM DE COMPONENTES DE SISTEMA HÍBRIDO FOTOVOLTAICO/ DIESEL COM MATLAB/SIMULINK

Hybrid energy systems are a solution to the problem of energy demand in remote communities, not being included by the electricity grid and conventional distribution. In this sense, this work proposes a study of the behavior of the basic elements of a hybrid system composed by two sources of energy, photovoltaic and diesel generator. For the modeling of each component of the proposed system, Simulink software was used, analyzing their behavior individually, thus enabling a better understanding of individual performance. The results of the simulation presented values within the expected for each component.
Projeto Otimizado de Transformadores de Média Frequência para Conversores de Potência Isolados

The construction of transformers requires taking into account various parameters in relation to the transformer as well as the desired profile design in which the transformer is to be inserted. With various input parameters and sometimes drawing methods relatively complex to be calculated becomes important to automate this process as well as the possibility to choose between various drawing methods. Using optimization techniques based on Lagrange multipliers, these drawings are implemented methods and the results can then be used for simulation of transformer models. Three case studies were tested, one based on a Cuk converter, one based in a Buck converter and the last one based on a Flyback converter. The early stages of understanding what is involved in designing a transformer at the level of characterization of the various losses was studied for further implementation of algorithms that used these same models of losses. It has achieved an intuitive interface and the implementation of two design methods which were eventually validated.
A Green and Secure IoT Framework for Intelligent Buildings based on Fog Computing

The Internet of Things (IoT) provides an opportunity to connect plethora devices and make them capable of serving the cities better in a collaborative manner. However, energy-efficiency and security problems are the two hugest chanllenges that severely hinder the development of IoT-based smart cities. In this article, we attempt to provide a green and secure IoT framework for Intelligent Buildings which are basic elements in smart cities. Specifically, a smart agent node is installed for each Intelligent Building to make it an autonomous region. The IoT data are divided into different categories according to their application domain, priorities, meanings and potential value. The resources of IoT are precisely controlled and managed to satisfy the data users under the strictly limitation. Simulation results illustrate the effectiveness of our framework in terms of quality of service (QoS). We believe that this is a meaningful and initiatory explonation to make the smart cities more practical. Finally, some research challenges are highlighted.
Integrating depth-HOG and spatio-temporal joints data for action recognition

In this paper, we propose an approach for human activity recognition using gradient orientation of depth maps and spatio-temporal features from body-joints data. Our approach is based on an amalgamation of key local and global feature descriptors such as spatial pose, temporal variation in ‘joints’ position and spatio-temporal gradient orientation of depth maps. Additionally, we obtain a motion-induced global shape feature describing the motion dynamics during an action. Feature selection is carried out to select a relevant subset of features for action recognition. The resultant features are evaluated using SVM classifier. We validate our proposed method on our own dataset consisting of 11 classes and a total of 287 videos. We also compare the effectiveness of our method on the MSR-Action3D dataset.
Orbiting Strings in AdS 5 Black Hole Backgrounds

Following Armoni, Barbon and Petkou [hep-th/0205280], we study the orbits of classical closed strings in AdS5 black hole backgrounds. A geodesic equation describing the orbits of classical closed strings in arbitrary spacetimes is derived. We consider the string configuration given by the ansatz in [hep-th/0205280] for the AdS5 Schwarzschild, Kerr-AdS5 and AdS5-ReissnerNordström black hole backgrounds. We find that such a string configuration results in the classical closed string to orbit around the black hole horizons for the AdS5 Schwarzschild, Kerr-AdS5 and AdS5-Reissner-Nordström black hole backgrounds.
Taking Control

Abstract Libraries are at a crossroad. Down one road are the traditions long accepted by libraries as the proper way to run a library. The other way leads the libraries into the challenges and chaos of the Internet. There are innovative attempts to use the potential of the Internet to redirect traditional patterns of access to information and services.
A Research on Network Similarity Search Algorithm for Biological Networks

The biological network database presents exponential growth, how to find the target network accurately from the network database becomes the difficult problem. This paper proposes a new network similarity search algorithm, the similar network of Top k is calculated by two methods, the similar networks returned by the two algorithms are then filtered by overlap fractions, the weighted reordering algorithm is used to reorder the two sets of data, a precise set of similar network data sets is returned finally.In this paper, the accuracy of the query is judged by the comparison of the edge correctness (EC) value and the maximum public connection subgraph (LCCS) value of the returned sorted similar network data set, and compare query time with other algorithms.From the results, this algorithm is superior to other algorithms in query accuracy and query speed.
Increasing of down passing skills for mini volleyball game by using reciprocal teaching model

The aim of this study was to increase students’ down passing skill for miny volleyball game at class of elementary school by using reciprocal teaching model. Reciprocal teaching model can increase the activity of students in participating to the teacing-learning process. The implementation of this model gave a positive impact on the students’ agility and physical fitness particularly for increasing students’ down passing skill in the game of mini volleyball. This study used a research and development method. Subjects of this study were fifth grade students from elementary. The result of this result reported that by using reciprocal teaching model can improve students’ down passing skill in the playing of Mini Volleyball game and enhyances students’ physical fitness and health as well as master with basic technique of the mini volleyball game. Sport education teacher could use this model to Elementary students level for improving their down passing skill in the game of mini volleyball.
Cryptanalysis and Enhancement of Two-pass Authenticated Key Agreement with Key Confirmation Protocols

Abstract In NRSC24, Elkamchouchi et al. proposed a new approach for key controlled agreement to provide key control in the Pour public key distribution system. In NRSC25, they further proposed an efficient and confirmed protocol for authenticated key agreement to provide forward secrecy in their previously proposed protocol. This paper, however, will show that Pour’s protocol and Elkamchouchi et al.’s two protocols cannot withstand key compromise impersonation resilience, and man-in-the-middle attacks, and do not have perfect forward secrecy resilience. To eliminate the pointed out security leaks, we further propose a new two-pass authenticated key agreement with a key confirmation protocol. The proposed protocol has the following properties: (i) it is proved to be secure against above attacks and stronger adversary attacks, and provides the desirable security properties as a three-pass authenticated key agreement protocol. (ii) It can provide entity authentication and assurance for key reception in an indirect way. (iii) It can withstand denial of service attacks. In addition, we also propose a derivation one-pass protocol from the proposed two-pass protocol to fit a one-way communication channel, which is suitable for mobile stations and electronic business transactions. The security and the computational complexities of the proposed two protocols outperform those of previously proposed protocols.
Using software fault insertion to improve CCS network

In the past two years, there have been serious common channel signaling (CCS) network outages caused by software faults. Recovery from those outages required intervention of a craftsperson. A pro-active approach in which potential abnormal situations are created as test drill cases by inserting software faults of different types is proposed. These faults are systematically inserted in the critical software components in the CCS nodes. The goal is to both motivate improved fault-tolerant capabilities of the network elements and to help the CCS operation staff cope with the abnormal situations that require human intervention. <<ETX>>
Turning a MAV into an Effective Tool for Vessel Inspection through a Reconfigurable Framework

Vessels constitute one of the most cost effective ways of transporting goods around the world. Despite the efforts, maritime accidents still occur, with catastrophic consequences. For this reason, vessels are submitted to periodical inspections for the early detection of cracks and corrosion. These inspections are nowadays carried out at a great cost. In order to contribute to make ship inspections safer and more cost-efficiently, this paper presents a novel framework to turn a Micro-Aerial Vehicle into a flying camera that can virtually teleport the human surveyor through the different structures of the vessel hull. The system architecture has been developed to be reconfigurable so that it can fit different sensor suites able to supply a proper state estimation, being at the same time compatible with the payload capacity of the aerial platform and the operational conditions. The control software has been designed following the Supervised Autonomy paradigm, so that it is in charge of safety related issues such as collision avoidance, while the surveyor, within the main control loop, is supposed to supply motion commands while he/she is concentrated on the inspection at hand. In this paper, we report on an extensive evaluation of the platform capabilities and usability, both under laboratory conditions and on board a real vessel, during a field inspection campaign.
Content Based Image Retrieval for Big Visual Data using Map Reduce

With high availability of portable and low cost digital cameras and improvement in image capture technology, huge amount of visual data (photos and videos) is being generated everyday. The processing capability of standalone devices is insufficient to handle such massive data also known as big data. Apache Hadoop, a distributed computing model that is based on Map Reduce framework is an easy to use solution for managing big data with freely available implementation models. Hadoop is mainly designed for cost-effective commodity hardware or inexpensive cloud computing infrastructure. Hence, access to expensive hardware or in-depth understanding of parallel programming is no longer required to work on big data. With high availability of portable and low cost digital cameras and improvement in image capture technology, huge amount of visual data (photos and videos) is being generated everyday. The processing capability of standalone devices is insufficient to handle such massive data also known as big data. Apache Hadoop, a distributed computing model that is based on Map Reduce framework is an easy to use solution for managing big data with freely available implementation models. Hadoop is mainly designed for cost-effective commodity hardware or inexpensive cloud computing infrastructure. Hence, access to expensive hardware or in-depth understanding of parallel programming is no longer required to work on big data.
Discovering methods of scoring in soccer using tracking data

In soccer, when analyzing the performance of a team one of the key events to analyze is that of shots and goal-scoring. With the availability of fine-grained player and ball tracking data, it is now possible to find the common patterns a team uses via clustering multi-agent trajectories. The effectiveness of these methods can be then quantified by using a "expected goal value" (EGV) model which was recently proposed. Using an entire season of player and ball tracking data from Prozone, we show a method of both "discovering" and "quantifying" goal scoring methods of a team, which we also use to compare the "goal-scoring styles" of teams.