Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting translingual plagiarism and the backlash against translation plagiarists

Plagiarism detection methods have improved signiVcantly over the last decades, and as a result of the advanced research conducted by computational and mostly forensic linguists, simple and sophisticated textual borrowing strategies can now be identiVed more easily. In particular, simple text comparison algorithms developed by computational linguists allow literal, word-for-word plagiarism (i.e. where identical strings of text are reused across diUerent documents) to be easily detected (semi-)automatically (e.g. Turnitin or SafeAssign), although these methods tend to perform less well when the borrowing is offuscated by introducing edits to the original text. In this case, more sophisticated linguistic techniques, such as an analysis of lexical overlap (Johnson, 1997), are required to detect the borrowing. However, these have limited applicability in cases of ‘translingual’ plagiarism, where a text is translated and borrowed without acknowledgment from an original in another language. Considering that (a) traditionally non-professional translation (e.g. literal or free machine translation) is the method used to plagiarise; (b) the plagiarist usually edits the text for grammar and syntax, especially when machine-translated; and (c) lexical items are those that tend to be translated more correctly, and carried over to the derivative text, this paper proposes a method for ‘translingual’ plagiarism detection that is grounded on translation and interlanguage theories (Selinker, 1972; Bassnett and Lefevere, 1998), as well as on the principle of ‘linguistic uniqueness’ (Coulthard, 2004). Empirical evidence from the CorRUPT corpus (Corpus of Reused and Plagiarised Texts), a corpus of real academic and non-academic texts that were investigated and accused of plagiarising originals in other languages, is used to illustrate the applicability of the methodology proposed for ‘translingual’ plagiarism detection. Finally, applications of the method as an investigative tool in forensic contexts are discussed.
Bulletin of Applied Computing and Information Technology Integrating RFID technology into a drug administration system 03 : 01 2005

Errors in the administration of drugs to patients, along with other types of adverse drug events (ADEs), have proven to be very costly to the healthcare sector. One commonly proposed solution to the problem is the use of barcodes to uniquely identify both patients and drugs. The size of the ADE problem, and the success of a limited number of barcode-based systems, has prompted US healthcare regulators to endorse, or even mandate, their use. However, it has been suggested that limitations of barcodes adversely affect the usability of such systems, and that RFID technology offers a more suitable alternative. p>This paper documents the design and development of an extension to an existing barcodebased anaesthetic drug identification system, IDAS, which would allow it to functionally replace barcodes with RFID technology. The design is informed by a review of RFID application case studies, experiments with RFID hardware, and observation and interviews of anaesthetists. A demonstration of the prototype system suggests that RFID technology could functionally replace barcodes, but significant issues remain to be addressed.
Language and the Law Where the science ends and the law begins : likelihood ratio-based forensic voice comparison in a $ 150 million telephone fraud 1

The first use of likelihood ratios for the evaluation of forensic voice comparison evidence in a real trial in Australia is documented. Important steps in the process of estimating the strength of evidence – from acoustic-phonetic features in the utterances ‘yes’ and ‘not too bad’ – are described and explained. These comprise the nature and currency of likelihood ratios, choice of features, graphical demonstration of similarity and typicality of suspect and offender speech samples, and their multivariate likelihood ratio evaluation against a reference sample. Improvements in likelihood ratio estimation since the case are exemplified; in particular how to demonstrate that the approach actually works. The reception of the likelihood ratio-based evidence during the trial is used to highlight some problems in its rational evaluation by a court.
Modelo test-bed de simulación y evaluación de criptografía de curva elíptica en redes IPv6 de próxima generación Simulation test-bed for the evaluation of elliptic curve cryptography on next generation wireless IPv6-enabled networks

Currently, mobile networks and next generation wireless networks such as, IPv6 low-power Wireless Personal Area networks 6LoWPAN, wireless sensor networks and hierarchical mobile networks in IPv6, are under rigorous research and development, thereforethose networks represent the next step in the evolution of the Machine-to-Machine M2M networks, while supporting broadband access for the next generation of intelligent systems, technologies and future Internet. These next generation networks impose restrictions on the processing power, bandwidth and energy resources, which represents a major constraint in the implementation of security mechanisms. In this regard, in recent years there have been various proposals for key management, digital signature procedures and data encryption based on elliptic and hyper-elliptic curves, to achieve levels of safety equivalent to convenRivest-Shamir-Adleman RSA, but reducing the key length and thus the computational and network resources. This paper reviews algorithms based on Elliptic Curves Cryptography ECC and their application to IPv6-enabled new generation wireless networks. This paper also describes a simulation test-bed for the evaluation of ECC, where we compare computational resources required and limitations for lightweight security mechanisms in secure neighbor discovery, and DNS security extensions.
Attitude to health as a factor of accident-free truck drivers

The article discusses the factors related to health in connection with the accidents of truck drivers. The basis of the study of implicit attitudes towards health and disease lies in the model of orthogonal implicit attitudes. The study of longdistance drivers used the Double-Target IAT method (a modified version of the Single-Target IAT), based on a model of orthogonal implicit attitude. Keywords— Implicit attitudes to health, accident rate of drivers, type of injury
The Design and Research of the Sliding Mode Control of a New Chaotic System

This thesis makes a research about the Sliding Mode Control of a new chaotic system. Taking advantage of PI switching manifold method, it projects a kind of sliding mode controller and fuzzy the switching function of sliding mode surface with membership function, then finally adopts the output of fuzzy controller. What’s more, this method simultaneously makes full use of PI control as well as SMC based on the new area control error, choosing the integral sliding surface equation which makes the system enter into the state of sliding mode from the beginning. Then it turns into the PI control on the basis of new area control error. Making the system output track a given goal until the elimination of tracking error in the main theoretically proves the global stability of this sliding mode controller, and the numerical simulation experiment further shows its simplicity as well as availability, besides, makes sure the steady availability of the whole system.
Reconhecimento de informações padronizadas no conteúdo de emails

The information that is received daily in the mailbox is, for most of the cases, a concern due to it’s volume. However, the management and organization of the information in mailboxes is a task that is already supported by some technologies that allow the access to information in a faster, simpler and accurate way. This project, titled “Recognition of Standardized Information on Emails Content”, took place in Portugalmail Comunicacoes, S.A and consists in a system able to recognize various types of information in the content of emails. This system is to be incorporated in the webmail platform. This project is motivated by the creation of a new concept of email service, developping new features that allow the system to help the user getting relevant information from his emails content, presenting that information in a more friendly and distinctive way. The main goals is to develop a tool capable of recognising, interpreting and presenting several kinds of information contained on emails. In the end of this, it is expected to develop an effective methodology to recognition schedulable events on emails content, create a group of modules capable of recognising different kinds of information returning different kinds of results and finally concebe a system to attach all these modules. After defining the features, there were developed some modules, each one with it’s recognition system. The main module of this thesis is the schedulable event recognition module. It uses learning and classification algorithms together with regular expressions. It lead the a study with the goal to undestand how significant regular expressions, combined with bayesian algorithm, are to detect information effectively in no context and noisy environmets. This study was converted on this thesis’s background, from which it was possible to conclude that regular expressions are very effective filtering emails that don’t contain schedulable events and that bayesian algorithm, with the proper training, is capable of doing a nice job detecting emails that do contain events. In the end of this project, almost all the objectives were completed, missing the integration with the calendar because it is still being developed. Anyway, it was possible to create a functional prototype as a proof of concept. It is working with three modules, where one of them is the schedulable event recognizer.
Surrogate modelling for observation likelihood calculation in a particle filter framework for automated diagnosis and prognosis

In a structural health monitoring framework, most of the diagnostic and prognostic tasks require the solution of inverse problems, such as the identification of damage parameters (e.g., damage position and its extent) or the estimation of damage evolution model parameters from the observation of damage dependent features. Bayesian approaches have proven to be successful for inverse problem solution, by the evaluation of the posterior distribution of a vector of parameters of interest, conditioned on the observations of some signal features, which relies on the direct calculation of the observations likelihood. Unfortunately, for realistic structures, a numerical simulation might be required for the evaluation of each sample likelihood, which can make the whole procedure for the posterior pdf estimation computationally unfeasible. In this work, this problem is solved by leveraging on surrogate modelling. Sequential importance Monte-Carlo sampling, also known as particle filter, is used as a general framework for the health state estimation and prognosis of a skin panel subject to fatigue crack growth, while observing the strain field pattern acquired at some specific locations. A surrogate model consisting of an artificial neural network, trained on a set of analytical simulations, is used to predict the strain as a function of the crack position and length, thus allowing a fast calculation of the strain observation likelihood. The algorithm is tested with reference to an analytic case study of a crack propagating in an infinite plate, allowing for a simultaneous diagnosis of the crack position and length, as well as a realtime updating of the evolution model parameters and system prognosis.
Interaction and mechanisms of GRP 78 and HSP 70 in LPS-treated mice microglia cell

Objective: To study the interaction between glucose-regulated protein 78 (GRP78) and heat shock protein 70 (HSP70) in lipopolysaccharide (LPS) treated mouse microglial cells, and explore its mechanism. Methods: mouse microglia (BV2) was the research object, bacterial lipopolysaccharide (LPS) infected BV2 cells were used to observe the active status which were stimulated by LPS. We analyzed TLR2, TLR4 expression level of the infected cells. We also investigated LPS stimulated BV2 cell. Expression level of IL-1β, TNF-α, IFN-β and other cytokines were observed. When GRP78 and HSP70 were injected into BV2 LPS-stimulated cells, changes of nitric oxide synthase (iNOS) and reactive oxygen species (ROS) were observed. Results: Immunofluorescence staining showed that surface of normal BV2 cell appeared red fluorescent particles, with some activation state. After LPS, GRP, HSP70 protein and LPS treatment, microglia activation state had different degrees of incensement. Expression results of TLR2 and TLR4 showed that after LPS stimulated TLR2 expression showed significant difference (P>0.05) compared with the normal cells, while expression of GRP78 and HSP70 injected LPS stimulated TLR2 showed significant difference compared with the normal group and the LPS-treated group with significant difference (P<0.05); expression of TLR4 in LPS stimulated group, GRP78 + LPS group and HSP70 + LPS group showed statistical difference (P<0.05) compared with the normal cells. ELISA results showed that the IL-1β had significant difference between five experimental groups (P<0.05), while it was increased significantly in HSP70 + LPS treatment group, and LPS treatment group was followed; TNF-α in normal cells group showed statistical significance (P<0.05) compared with the rest four experimental groups; IFN-β in normal cells and LPS-treated group showed statistical significance compared with GRP78 + LPS group and HSP70 + LPS group (P<0.05), but there was no difference when compared with LPS stimulated neurons. Expression of iNOS, compared with the five experimental groups, had significant difference (P<0.05), while HSP70 + LPS treatment group showed the most obvious incensement. The results of ROS had significant difference (P<0.05) compared with the results of five experimental groups, while HSP70 + LPS treatment group also showed the most obvious incensement. Conclusion: LPS stimulation can cause microglial activation in mice. Through TLR4 pathway, IL-1β, TNF-α and other cytokines can be secreted extensively, leading iNOS and reactive oxygen species (ROS) increased. Meanwhile, GRP78 protein may play a more important role in the inhibition of LPS-stimulated microglia inflammation and other stress.
Effect of soluble CD14 subtype on the prognosis evaluation of acute paraquat poisoning patients.

OBJECTIVE To study the relationship between soluble CD14 subtype (also named presepsin) and the prognosis of acute paraquat poisoning (APP) patients. METHODS We studied 85 APP patients who were divided into three groups: light (21 cases), moderate (37 cases) and heavy poisoning (27 cases) groups. Fifty healthy subjects were as control group. According to the conditions of prognosis, they were divided into two groups: survive group (28 cases) and death group (57 cases). We measured the concentration of presepsin in serum and the levels of CRP, TNF-α, IL-6 and IL-10 in venous blood. APACHE II scores were observed before treatment, 72 h and 7 d after treatment. RESULTS The levels of presepsin, CRP, TNF-α, IL-6 and the scores of APACHE II in patients of three poisoning groups were increased at three different time points compared with control group, while the level of IL-10 was decreased. And there were significant differences between each poisoning groups (P<0.05). The levels of prespsin, CRP, TNF-α, IL-6 and the scores of APACHE II in patients of death group were higher than survive group at three different time points, while the level of IL-10 was lower (P<0.05). The mortality rates of three poisoning groups were 28.57%, 70.27% and 92.59%, and there were significant differences between each poisoning groups (P<0.05). The area under curve (AUC) of presepsin level and APACHE II scores of APP patients on admission were 0.862 and 0.731, respectively. Presepsin had a better predictive ability than APACHE II score for 28-day mortality rate in APP patients (P<0.05). The level of presepsin was negatively correlated with survival rates (r=0.291, P=0.007). CONCLUSION Monitoring the level of presepsin in serum has an important role in assessing the severity of APP patients, guiding treatment and predicting prognosis.
Neuromorphic Circuits and Devices exploiting Noise and Fluctuations

This paper provides an overview of the recent development of our noise-driven electrical circuits and devices whose architectures were inspired by biological nervous systems. Noises are inevitable under natural environment, however, one usually tries to “attenuate” noises and fluctuations on semiconductor circuits and devices by using, for example, special shielding equipments, precise fabrication process, special layout or circuit techniques, and so on. On the other hand, biological systems certainly “exploit” noises to increase performances on neural computation. In this paper, some examples of noise-driven neural computing on semiconductor circuits and devices are presented, which may show what noise-driven circuits and systems can do now, and what they may do in the future.
A case study of NeuroPage: a reminder system for memory-disabled people

NeuroPage is a computer-based reminding system, recently developed in the USA, specifically for memory-disabled people. The aim of the designers was to keep the complexities of operation 'behind the scenes', presenting end-users with a deceptively simple device which avoids the problems of conventional memory aids. It uses a combination of computing and telecommunications to achieve this and is the first memory aid to capitalise on this technology. The NeuroPage system has three constituents. A centrally-located desktop computer stores schedules of reminder messages for different users, for any date and time in the future. At the appropriate moment, a message is automatically dispatched via a modem to a commercial paging company and transmitted within seconds to the appropriate pager. The paging device alerts the wearer to the incoming message by bleeping or vibration. The device has just one button to press which simultaneously cancels the alert signal and displays the reminder message on the 80-character screen.
Inequality in Turkey : Girls only ?

Aim of this study is to ascertain and evaluate the determinants of educational inequality in Turkey. In this study, national and international assessments and research results regarding the Turkish Education system have been examined, determinants of inequality in education were ascertained and evaluations have been performed. Educational inequality in Turkey is identified by three determinants of gender, socio-economic conditions, and quality of schools. Socioeconomic level is in itself an element of inequality and the basic determinants of inequality. It is clearly seen that inequality of income negatively effects education according to the findings. Turkey should therefore take precautions against income inequality and socio cultural structure should also be considered. Quality of schools can change according to region and school types. Analyses of problems in education impacted by economic, political, social, and cultural factors by the Ministiry of Education are the main recommendation of this study.
Agile game development : lessons learned from software engineering

This paper proposes an agile model to develop games that simulate professional practices and policy evaluation. During the last decades, agile development models have evolved in a related design science, viz., software engineering, to increase the quality and efficiency of large software development projects. Taking into account the similarities and dissimilarities between game development and software development, we show a first step towards an agile game development model based on a formal design approach called Triadic Game Design (TGD). We further devised a workshop to initiate an agile game development process during the first phase of a game design project.
The Young Designer ’ s Guide to Speculative and Critical Design

1) Political and social changes: During the last four decades, almost every aspect of design practice has been reframed [2]. To allow novel approaches, design education and practice need restructuring: When designers widen their scope towards larger-scale issues—ethical, political or social—it requires diligent self-reflection and a critical attitude towards why we design. One can ask if such restructuring is possible if designers invariably must adhere to the norms of commercial industry.
Performance Analysis of Quasi-Z-Source Inverter using Model Predictive Controller for Photovoltaic Power Generation Systems

This paper presents the performance analysis of Quasi-Z-Source Inverter (QZSI) using Model Predictive Controller (MPC) for Photovoltaic (PV) generation system. This QZSI employs a unique impedance network to couple the inverter main circuit to the power source. It’s providing unique features that cannot be obtained in the conventional Voltage Source Inverter (VSI) and Current Source Inverter (CSI). The main aim of MPC is predicting the future values of output variables using a dynamic model of the process. Using a cost function optimization the error should be minimized and the best switching state is selected. QZSI inductor current and capacitor voltage are changed based on the same cost function. The MATLAB simulation results show the performance analysis of QZSI using MPC. Keywords-Photovoltaic (PV) power generation, Quasi-ZSourceInverter (QZSI), Model Predictive Control (MPC).
A SNS Message Type Classification System Using Language Independent Features and Modified ECCD

This study proposes a SNS message type classification system combining language independent and dependent features that can be used in short message for type classification in social network service environments and verifies the effectiveness of this system. The language independent features are the Metadata of SNS message and the language dependent features are the bag-of-word selected by the modified ECCD feature selection method reflecting the short message characteristics. The experiment shows that the proposed system has better performance than comparable methods which use other language independent features or dependent features only.
Load Balancing Memcached Traffic Using SDN

Memcached is an in-memory key-value distributed caching solution, commonly used by web servers for fast content delivery. Keys with their values are distributed between Memcached servers using a consistent hashing technique, resulting in an even distribution (of keys) among the servers. However, as small number of keys are significantly more popular than others (a.k.a., hot keys), even distribution of keys may cause a significantly different request load on the Memcached servers, which, in turn, causes substantial performance degradation. Previous solutions to this problem require complex application level solutions and extra servers. In this paper, we propose MBalancer–a simple L7 load balancing scheme for Memcached that can be seamlessly integrated into Memcached architectures running over Software-Defined Networks (SDN). In a nutshell, MBalancer runs as an SDN application and duplicates the hot keys to many (or all) Memcached servers. The SDN controller updates the SDN switches forwarding tables and uses SDN ready-made load balancing capabilities. Thus, no change is required to Memcached clients or servers. Our analysis shows that with minimal overhead for storing a few extra keys, the number of requests per server is close to balanced (assuming re-