Miracle-dz/UniFAR-FTUs huggingface dataset:
Techniques for the decoding of low density parity check codes: efficient simulation, algorithm improvement and implementation

After the introduction of iterative coding, Low Density Parity Check (LDPC) codes have received a lot of attention due to their remarkable near Shannon-limit performance and practical decoder implementation. However, when employing an LDPC code for various applications, multiple issues do arise at the simulation, algorithm and implementation levels. The first issue is the performance evaluation of the iterative LDPC decoder in the very low Bit Error Rate (BER) regions. So far, no analytical tool has been developed to evaluate the performance of LDPC codes. Unfortunately standard Monte Carlo (MC) simulations cannot be used for performance estimation in these low BER regions due to prohibitive execution times. The second issue is the efficiency of the decoding algorithm. Due to the presence of short cycles in the bipartite graph, sum-product decoding algorithms lead to considerable performance loss for short block-length LDPC codes and produce error floors for longer codes. In addition, the iterative processing and estimation of soft probabilistic values with these algorithms result in very high computational complexity, which in turn impedes the adoption of LDPC codes for power constrained systems. Another prime objective is to design a high throughput decoder architecture which is capable of supporting multiple rates and variable code lengths within minimal area. This work aims to address and provide solutions to the above problems. As a solution to the performance estimation problem of LDPC codes, a highly efficient and novel fast BER simulation technique is developed. At the algorithm level, a performance improvement and error floor avoidance method is introduced, and a computationally efficient algorithm is developed for the sum-product decoding of LDPC codes. And finally, at the architecture level, a high throughput multi-rate variable code length implementation is presented which, when implemented, efficiently minimizes device resources while alleviating the routing complexity of the decoder.
İneklerde Kromozomal, Hormonal, Beslenme Sorunlarına ve Isı Stresine Bağlı Erken Embriyonik Ölümler.

Ineklerde tek tohumlama sonrasi, %45-65 oranlari arasinda bir gebelik orani bildirilmektedir. Bunun yaninda fertilizasyon orani ise %89-100 arasinda bildirilmistir. Fertilizasyon orani ile gebelik orani arasindaki bu farkin nedeni embriyonik veya fotal olumlere baglanmaktadir. Embriyonik olumler ayrica genetik olarak uygun olmayan embriyolarin dogumdan once eleminasyonu olarak da tanimlanabilirler (1). Hazirlanan bu derlemede de ineklerde kromozomal, hormonal, beslenme sorunlarina ve isi stresine bagli erken embriyonik olumler ozetlenmistir.
Thinking in Objects Towards an Infrastructure for Semantic Representation of Verb-Centred Structures

This paper describes a component-driven population of a language resource consisting of semantically interpreted verb-centred structures in a cross- lingual setting. The overall infrastructure is provided by the Unified Eventity Rep- resentation (UER) - a cognitive theoretical approach to verbal semantics and a graphical formalism, based on the Unified Modeling Language (UML). The verb predicates are modeled by eventity frames which contain the eventities' compo- nents: static modeling elements representing the characteristics of participants and the relations between them; dynamic modeling elements describing the be- haviour of participants and their interactions.
An assessment of the ocular tear film in patients with thyroid disorders

Objective: To investigate the ocular tear film in patients with thyroid disorders using various tests. Methods: The study involved the assessment of the ocular tear film in 20 patients with thyroid disorders (6 men and 14 women) aged 18–43 years (mean±standard deviation=34.3±3.2 years). An age-matched control group consisting of 20 subjects (8 males and 12 females) ranging in age from 18 to 43 years (31.3±2.9 years) was also examined under similar conditions. All patients completed the Ocular Surface Disease Index questionnaire, followed by the tear ferning test within the right eye. A phenol red thread test was carried out 10 mins later followed by the fluorescein tear break-up test with a 10-min gap between the tests being implemented. Results: The median score for the Ocular Surface Disease Index (P<0.05) showed the condition of mild dry eyes [median (IQR)=15.5 (21.9)] in patients with thyroid disorders compared to the control group [5.6 (3.6)]. The mean score for the phenol red thread test within both the right and left eyes showed acceptable tear volumes of 11.7±8.1 and 10.5±7.4 mm, respectively, but this was much lower (P<0.05) compared to those recorded within the control group (22.2±6.5 and 20.7±5.2 mm, respectively). In addition, the mean for the tear break-up time (P<0.05) scores in both eyes within the patients with thyroid disorders revealed a certain degree of eye dryness (4.9±1.6 and 4.2±1.9 s), while the control group showed normal eye scores (13.2±2.6 and 12.3±2.2 s). The median score for tear ferning grades showed eye dryness [2.0 (2.2)] within the study group and normal eyes [1.2 (0.9)] within the control group. Conclusions: Patients with thyroid disorders have a significant level of eye dryness compared to normal eye subjects.
Comparison on pattern analysis performance of SVM and RVM based on RBF kernel

Making use of standard dataset such as synth and BC,compared the pattren analysis performance of SVM and RVM using 5-fold verification based on RBF kernel.Test result indicates that the mistake rate and time complication degree is lower than that of SVM.Research shows under the condition of this paper RVM's pattern analysis performance is more excellent.
Framing the framework the rigorous responsibilities of library and information science

The ACRL Framework for Information Literacy for Higher Education offers library and information science (LIS) professionals a conceptual approach for leading information literacy efforts in a digital environment. But while a good start, Nathan Filbert suggests that it is not enough to validate librarianship’s transdisciplinary potential. In this column, Filbert addresses the programmatic and directional efforts necessary for LIS to realize expansive expertise in information resource management, reference, and user services in the evolving, complex, information ecosystem. Drawing on the profession’s past and present, he suggests a vision and a philosophy for mediating the infosphere of the future. —Editor
A Review on an Efficient Approach to Manage Small Files in Distributed File Systems

Nowadays, to manage excessive number of small files is became a challenge in Distributed File System. Currently, the combined block storage technique is used to store the files this technique is used in existing system such as Extfs and Xfs. This technique is liable to inefficiency when accessing files randomly. We present the proposed system to manage small files which is based on simple metadata and storage architecture. Our system focuses on replacing the existing system drawbacks in Data servers that used to store excessive number of small files and retrieval of files in a better way. We designed new metadata structure which will decrease the size of original metadata that will help to increase the speed of file accessing.
Reversible Logic Synthesis of Modulo Operation using an Optimized Parallel Binary Adder/Subtractor

Reversible logic is gaining importance in recent years largely due to its property of low power consumption. It has a wide range of applications which include advance computing, low power CMOS, optical information processing, quantum computing, DNA cryptography and nanotechnology. Reversible gates are the building blocks of quantum computation. This paper presents an optimized parallel binary adder/subtractor using existing reversible gates which is further used to implement a novel circuit capable of performing modulo operation. All circuits have been modeled and verified using Verilog and Modelsim. An overall analysis of the modulo circuit and a comparative study of the proposed parallel adder/subtractor with respect to previous designs in terms of the number of gates, number of garbage outputs and quantum costs is presented. General Terms Reversible logic, Quantum Cost, Reversible Gates, Reversible Modulo Operation, Reversible Parallel Binary Adder/Subtractor.
Endophenotype Potential of Nucleus Accumbens Functional Connectivity: Effects of Polygenic Risk for Schizophrenia Interacting with Childhood Adversity

Epidemiological and genetic studies suggest that schizophrenia (SCZ) is associated with both polygenic and environmental risk factors. Little is known if these factors project on common functional circuits relevant to the pathophysiology of SCZ. Here we focussed on resting state functional MRI (rsfMRI) as a biological measure to investigate if genetic and environmental factors for SCZ risk affect the same circuits in healthy controls as well as patients. For this, we compared the effects of a polygenic risk score for SCZ (PGRS), childhood adversity (CA) and their interaction on functional connectivity density (FCD) mapping and nucleus accumbens (NAcc) seed connectivity between 23 patients with SCZ or schizoaffective disorder and 253 healthy subjects. Patients demonstrated strong FCD increases compared with healthy controls mainly in subcortical nuclei including the NAcc, replicating previous reports. In healthy subjects, FCD of the NAcc was positively correlated with both the PGRS and the PGRS-CA-interaction. Both for high PGRS and PGRS-CA-interaction, fine-mapping revealed higher connectivity between the NAcc and visual association cortices. In conclusion, polygenic risk for SCZ shifted global and regionally specific connectivity of the NAcc in healthy subjects into the direction of the connectivity pattern observed in SCZ, and this shift was intensified by higher levels of CA.
Multi-view-based cross-organizational emergency response process similarity computation

A multi-view oriented similarity computation method was proposed to meet general demands for process retrieval,recommendation and reconstruction in an emergency response management scenario.Based on the formalization of emergency tasks,the different coordination patterns among emergency organizations were divided into task synchronization pattern,task selection pattern and message transmission.To reflect the diversity of cross-organizational emergency response process,the different process views included task logic view,inner-organization process view,coordination relation view and cross-organization process view were built correspondingly.On this basis,the similarity computation methods were defined for individual emergency response process views.The proposed simi-larity computing methods for cross-organizational emergency response processes were implemented and verified in the emergency response management platform for coal mine accidents.
Complexity and naturalness in first language and second language phonotactic learning

This thesis sought to test learning biases present in first language (L1) and second language (L2) acquisition. It was predicted that a bias for phonetically grounded, typologically common (" natural ") patterns would be present in L1 learning, and that a bias for patterns involving a small number of phonetic features (" simple ") would be present in L2 learning. A methodology similar to Hayes and White (2013) was used to test the presence of these biases in the learning of 30 speakers of Canadian English and Canadian French by having the subjects perform grammaticality judgment tasks in both of these languages. The results suggest biases for simple and natural constraints could be more active in L1 learning than in L2 learning. This falls in line with past studies and raises questions about the nature of L2 acquisition. Future research could explore whether L2 phonological learning has fewer biases in general, or if it has biases other than naturalness and complexity. iv ACKNOWLEDGEMENTS First of all, thank you to the Juanita A. Melchert Graduate Excellence Fund for the money to run and advertise the experiment for this thesis. Thanks to my family and to my fiancée for all of their support during a year when I was often too busy to see them as much as I would have liked to. I was lucky enough to discuss my thesis with Joe Pater and John McCarthy who gave some helpful advice and pointed me toward some great resources of relevance—so thank you to both of them. Several graduate students from other universities offered their assistance, Rachel Broad and Katya Pertsova for their advice and assistance during Sporklab meetings and to the other members of UNC's P-Side group. Chris Wiesen at the Odum Institute has now done the statistical analysis for two of my theses, and for his patience and helpfulness I am very grateful. A big thanks goes to my thesis committee members, Jennifer Smith and Jeff Mielke, who not only advised me during the process of making the thesis, but were invaluable when I was recruiting subjects for my experiment. And the biggest thanks of all goes to Elliott Moreton for both advising this project and encouraging me to get my master's degree in the first place. This research—and any other phonological research I do—is a direct result of the " Intro to Phonology " class that he taught when …
Online model stacking

The quickly evolving field of large-scale machine learning, or “data mining,” brings with it several challenges. First, interesting large datasets, while perhaps not a problem to store, may be too large to hold in memory in their entirety while processing. A related issue is that of a dataset that is never complete; observations, or groups of observations, are constantly being added to “streaming” data. In both cases, the ability to fit models piecemeal and later combine estimates would be advantageous. An “online” algorithm does just that. “Online” learning is a paradigm in which models are fit to data coming in a “stream,” eliminating the need to store all past observations or fit on the entire dataset en masse. An online algorithm, in the form we will discuss below, takes each block of incoming data and uses it to update the fit of the model. The data are subsequently discarded. However, before the fit is updated, each new block can also be used to assess the performance of the model (a sort of cross-validation). Any algorithms that can be fit with stochastic gradient descent are a perfect fit for this situation. Another problem encountered in data mining is the selection of the best learning algorithm. A wide variety of prediction algorithms are available, but for any new prediction problem, it’s not clear which one will best capture the true relationship between the features and the outcome. One potential solution is the use of “model stacking,” an ensemble method where many algorithms, possibly from different types of models, are combined to form a final estimator. This is accomplished by training the individual algorithms concurrently, then combining them via a weighted average, using using either hold-out data or cross-validation to avoid overfitting. One example of such an ensemble method is Super Learner, implemented in R, which combines competing algorithms by minimizing a suitable loss function of a linear combination of their predictions under cross-validation. This combined approach has been shown to perform asymptotically as well as or better than the “best” algorithm in the library of algorithms (van der Laan et al., 2007). In this project, we seek to find a combined solution to the two problems detailed above. Specifically, we aim to develop an online/streaming approach to training stacking algorithms, and to do so efficiently by training each algorithm on each data block concurrently.
Knowledge pre-processing in decision making

Process of decision making represents so important part of the activity of managers that some people have dedicated their lives seeking for tools helpful in this process. Nowadays, importance of these tools has increased due to the increasing amount of available information. During last years many tools supporting decision making have arisen along with many new buzzwords. In this article we explain three different types of tools which can be used as pre-processing tools in decision making: text categorization, text clustering, and spatial analyses including results visualisation.
Effects of exogenous plant hormones on sugar accumulation and related enzyme activities during the development of longan (Dimocarpus Longan Lour.) fruits

ABSTRACT Exogenous hormone treatment is a widely used and effective method to promote fruit ripening. To our knowledge, the effects of exogenous hormones on the sugar accumulation and related enzyme activities during the development of longan fruits have not yet been elucidated. In this study, the contents of sucrose, glucose and fructose, activities and transcriptional levels of sucrose phosphate synthase (SPS), sucrose synthase (SS), acid invertase (AI) and neutral invertase (NI) were detected during fruit development of exogenous hormone-treated and non-treated longan. The results indicated that exogenous hormones (IAA, ABA, GA3) could not alter the sugar contents when fruits were ripe but accelerate the sugar accumulation. IAA and ABA increased the gene transcriptional levels and enzyme activities of SS and SPS, and also showed the tendency of increasing the transcriptional levels and enzyme activity of AI. However, GA3 decreased the gene transcriptional levels of SS and SPS, and increased the gene transcriptional level of AI. Interestingly, GA3 also increased the enzyme activity of SPS which indicated GA3 may regulate the SPS activity at post-translational levels. Our results suggested that IAA, ABA and GA3 may regulate sugar accumulation during fruit development of longan.
Markov Process for Behaviour Analysis in Social Media

Social Network Analysis (SNA) provides tools to examine relationships between people. Here Markov Process is used to examine the behavior of the people involved in Social Networks. Markov process is the stochastic process in which the behavior evolves over time in a probabilistic manner. In this paper, Markov process is used to describe people&apos;s interests and to find out the people with similar interests. It is found that the expected positive relationship between sharing interests and communicating among people. Here focus is on analyzing the behavior of people who are using Social Networking sites.
C‐reactive protein level as a predictor of difficult emergency laparoscopic cholecystectomy

Studies focused on C‐reactive protein (CRP) as a marker of difficult laparoscopic cholecystectomy are limited to small case series. The aim of this study was to evaluate the association between preoperative CRP concentration and difficulty of laparoscopic cholecystectomy in patients admitted with a biliary emergency presentation.
Helicobacter pylori Mutations Conferring Resistance to Fluoroquinolones and Clarithromycin among Dyspeptic Patients Attending a Tertiary Hospital, Tanzania

Objectives. Helicobacter pylori (H. pylori) isolates resistant to clarithromycin and quinolones are increasing worldwide. Data regarding the magnitude of H. pylori resistance are limited in developing countries. Here, we report the prevalence of mutations conferring resistance to clarithromycin and fluoroquinolones among dyspeptic patients attending a tertiary hospital, Tanzania. Methods. Between August 2014 and August 2016, patients undergoing upper gastrointestinal endoscopy at the Bugando Medical Centre were enrolled. Biopsies were taken for polymerase chain reaction (PCR) and sequencing to detect mutations conferring resistance to clarithromycin and fluoroquinolones. Results. A total of 208 nonrepetitive biopsies were examined of which 188 (90.4%) tested positive for H. pylori specific 23S rRNA PCR. Clarithromycin resistance mutations were detected in 54/188 (28.7%) of patients tested. The most frequently detected mutation was A2143G (30) followed by A2142G (20). Out of 131 nonrepetitive biopsies tested for fluoroquinolones resistance mutations, 77/131 (58.8%) were positive, with N87I (20) mutation being the most frequently detected mutation followed by A92T mutation which was detected in 16 samples. Conclusion. A significant proportion of dyspeptic patients attending tertiary hospital in Tanzania are infected with H. pylori strains harbouring clarithromycin or fluoroquinolones resistance mutations. Detection of more than 50% of strains with fluoroquinolones resistance mutations makes the H. pylori second line treatment questionable in our setting. There is a need of surveillance of H. pylori resistance patterns in Tanzania to provide data that can guide empirical treatment to reduce associated morbidity of H. pylori infections. The correlation between A92T fluoroquinolone mutation and phenotypic resistance requires further investigations.
HUMAN MOOD DETECTION USING GENETIC ALGORITHM

- Perception modeling of facial expression is the vital step of human-machine interaction, which is an important study area of the present time. In this paper I have determined five well known human moods ‘happy’, ‘sad’, ‘angry’, ‘surprise’ and ‘normal’ by extracting three basic facial attributes eye opening (EO), mouth opening (MO) and eyebrow constriction (EBC) from faces of still images. After that using suitable membership function extracted attributes are converted into three fuzzy sets i
Issues in corpus-informed research and learning in ESP

To date, corpora have been widely used in general English language research (lexicography, phraseology, discourse, etc.), and increasingly in specialised language and genres. However, little of this has yet had any concrete impact on the material and pedagogy of ESP courses or on the students' involvement in the learning process. There is also a largely unfulfilled need for ESP support for academics who have to publish in English in their disciplinary area. With its emphasis on concrete applications, this book attempts to fill this gap. It is organised into two main sections: a) applications of corpus linguistics for language research, and b) applications of corpus linguistics for language teaching and learning. However, these are essentially two sides of the same coin: all the articles address teaching/learning issues, and the findings are therefore directly applicable in the higher education context to nonnative speakers (NNS) who need to use ESP/EAP.
The Theory of Probability: Explorations and Applications

Part I. Elements: 1. Probability spaces 2. Conditional probability 3. A first look at independence 4. Probability sieves 5. Numbers play a game of chance 6. The normal law 7. Probabilities on the real line 8. The Bernoulli schema 9. The essence of randomness 10. The coda of the normal Part II. Foundations: 11. Distribution functions and measure 12. Random variables 13. Great expectations 14. Variations on a theme of integration 15. Laplace transforms 16. The law of large numbers 17. From inequalities to concentration 18. Poisson approximation 19. Convergence in law, selection theorems 20. Normal approximation Part III. Appendices: 21. Sequences, functions, spaces.