Miracle-dz/UniFAR-FTUs huggingface dataset:
Transmorph: a transformer based morphological disambiguator for Turkish

: The agglutinative nature of the Turkish language has a complex morphological structure, and there are generally more than one parse for a given word. Before further processing, morphological disambiguation is required to determine the correct morphological analysis of a word. Morphological disambiguation is one of the first and crucial steps in natural language processing since its success determines later analyses. In our proposed morphological disambiguation method, we used a transformer-based sequence-to-sequence neural network architecture. Transformers are commonly used in various NLP tasks, and they produce state-of-the-art results in machine translation. However, to the best of our knowledge, transformer-based encoder-decoders have not been studied in morphological disambiguation. In this study, in addition to character level tokenization, three input subword representations are evaluated, which are unigram, bytepair, and wordpiece tokenization methods. We have achieved the best accuracy with character input representation which is 96.25%. Although the proposed model is developed for Turkish language, it is not language-dependent, so it can be applied to a larger set of languages.
A Novel, High Performance Enzyme for Starch Liquefaction DISCOVERY AND OPTIMIZATION OF A LOW pH, THERMOSTABLE -AMYLASE*

High throughput screening of microbial DNA libraries was used to identify -amylases with phenotypic characteristics compatible with large scale corn wet milling process conditions. Single and multiorganism DNA libraries originating from various environments were targeted for activity and sequence-based screening approaches. After initial screening, 15 clones were designated as primary hits based upon activity at pH 4.5 or 95 °C without addition of endogenous Ca . After further characterization, three enzyme candidates were chosen each with an exceptional expression of one or more aspects of the necessary phenotype: temperature stability, pH optimum, lowered reliance on Ca and/or enzyme rate. To combine the best aspects of the three phenotypes to optimize process compatibility, the natural gene homologues were used as a parental sequence set for gene reassembly. Approximately 21,000 chimeric daughter sequences were generated and subsets screened using a process-specific, high throughput activity assay. Gene reassembly resulted in numerous improved mutants with combined optimal phenotypes of expression, temperature stability, and pH optimum. After biochemical and process-specific characterization of these gene products, one -amylase with exceptional process compatibility and economics was identified. This paper describes the synergistic approach of combining environmental discovery and laboratory evolution for identification and optimization of industrially important biocatalysts.
DENOISING DIGITAL IMAGE USING WAVELET TRANSFORM AND MEAN FILTERING

— During the acquisition of a newly image, the clarity of the image is easily effected due to lighting of equipments that has been used to capture the image. The images contain lot of noise. The most common distortion in images is their poor contrast quality, blurred, out of focus, improperly bright. These problems obscured the detailed information of the image. So to get the proper information it is necessary to denoise the image. Edges are one of the important features of image. Sometimes while removal of noise face removes the edges that are important information for images in recognition task. To preserve that edge of the image the edge detection is necessary. So to solve all these problems it obtains the proper information from the image, we proposed a noble technique using SWT (Stationary Wavelet Transformation), Adaptive Mean Filtering, Edge Detection and Contrast Stretching approaches. We have conducted experiment on grey scale images of poor quality. The performances of the proposed method are compared with the other methods using the parameters Peak Signal Noise Ratio(PSNR), Signal Noise Ratio (SNR), Mean Square Error(MSE), Root Mean Square Error (RMSE) . The results of experiment show that the proposed algorithm is very effective in denoising the image and contrast enhancement. The method required minimum processing time than other method.
Information Selective Processing in the Complex Projects Examination the principle of equal complexity

The problem of detecting errors and improving a complex large-scale project is considered as the task of data mining. A selective research model of such project is designed. The task is to select the information files of the project, the expertise of which ensures the best achievement of the goal (for example, the maximum reduction in the cost of the project). Its decision is based on the principle of equal job complexity: modules from files studied by experts of the same qualification should be equal in complexity. A heuristic algorithm for such a solution is described. The problem of estimating the necessary number of experts is considered and solved on the basis of an assessment of the overall job complexity, taking into account the costs of their coordination. Based on the results obtained and the principles of data mining an approach to the examination of complex large-scale projects is developed. This approach is illustrated by examples in the field of transport.
DESIGN OF DUAL FREQUENCY COMPACT TRIANGULARPATCH ARRAYFORMIMO APPLICATIONS

In this paper, the design and characterization of microstrip triangular antenna array is presented. The proposed antennas are giving dual bands at 6-6.5 Ghz& 7-7.5 Ghz to support C-band applications. The proposed dual band antennas show omnidirectional radiation pattern with the gain values of 11.06dBi at 6.7 GHz & 8.470dBi at 7.36 Ghz. The patch array has two input ports for the orthogonal polarizations MIMO applications. The radiation pattern, result loss & gain of proposed antenna are presented. In this paper, an antenna diversity gain is evaluated for MIMO system by measuring the envelope correlation coefficient. The proposed antenna array is analyzed for the capacity it can offer in an ideal environment it is observed that antenna indicates quite perfect behavior & offers a good performance for utilization in a MIMO system for C band applications.
SURVEILLANCE FOR NON-STATUTORY PATHOGENS IN CULLED WILD BOAR IN THE FOREST OF DEAN BPEX-FUNDED PROJECT RDOR1035

Faeces and serum samples collected from 91 wild boar culled from the Forest of Dean were tested for • non-statutory endemic pathogens of GB pigs. Serological evidence of exposure to two Leptospira serovars was detected with a combined • seroprevalence of nearly 18%. Leptospira Bratislava, the Leptospira serovar to which most seropositive wild boar had antibody, is pig• adapted and also occurs in a range of wildlife species. The seroprevalence detected was significantly higher in older pigs, and the results are consistent with endemic infection in the wild boar population. A lower seroprevalence was detected to Leptospira Javanica which is reported in the literature to be • associated with a rodent reservoir and is zoonotic. One adult female was positive for antibody to porcine reproductive and respiratory syndrome virus by • ELISA but active infection was not detected, indicating potential for infection but not clear evidence that the wild boar population is a reservoir of infection to domestic pigs. Infection with, or exposure to, other pathogens tested was not confirmed and with the given population • and sample size this indicates at least 95% confidence that the prevalence of those pathogens in this wild boar population is less than 5%. No Salmonella species were detected, culture results for a proportion of faecal samples may have • been affected by the time interval between collection and culture. These results are relevant for a long established wild boar population in a forested region of England • which has a relatively low commercial pig density and should not be extrapolated to wild boar populations which exist, or could establish, in other regions. Suggestions regarding future wild boar surveillance are given. •
Development of an Antibiotic Guideline for Children With Suspected Ventilator-Associated Infections.

OBJECTIVES To develop a guideline for the decision to continue or stop antibiotics at 48-72 hours after their initiation in children with suspected ventilator-associated infection. DESIGN Prospective, multicenter observational data collection and subsequent development of an antibiotic guideline. SETTING Twenty-two PICUs. PATIENTS Children less than 3 years old receiving mechanical ventilation who underwent clinical testing and initiation of antibiotics for suspected ventilator-associated infection. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS Phase 1 was a prospective data collection in 281 invasively ventilated children with suspected ventilator-associated infection. The median age was 8 months (interquartile range, 4-16 mo) and 75% had at least one comorbidity. Phase 2 was development of the guideline scoring system by an expert panel employing consensus conferences, literature search, discussions with institutional colleagues, and refinement using phase 1 data. Guideline scores were then applied retrospectively to the phase 1 data. Higher scores correlated with duration of antibiotics (p < 0.001) and higher PEdiatric Logistic Organ Dysfunction 2 scores (p < 0.001) but not mortality, PICU-free days or ventilator-free days. Considering safety and outcomes based on the phase 1 data and aiming for a 25% reduction in antibiotic use, the panel recommended stopping antibiotics at 48-72 hours for guideline scores less than or equal to 2, continuing antibiotics for scores greater than or equal to 6, and offered no recommendation for scores 3, 4, and 5. The acceptability and effect of these recommendations on antibiotic use and outcomes will be prospectively tested in phase 3 of the study. CONCLUSIONS We developed a scoring system with recommendations to guide the decision to stop or continue antibiotics at 48-72 hours in children with suspected ventilator-associated infection. The safety and efficacy of the recommendations will be prospectively tested in the planned phase 3 of the study.
Detecting Trash and Valuables with Machine Vision in Passenger Vehicles

Aalto University, P.O. Box 11000, FI-00076 Aalto www.aalto. fi Author Nilusha Jayawickrama Title Detecting Trash and Valuables with Machine Vision in Passenger Vehicles School School of Engineering Master’s programme Mechanical Engineering Major Mechanical Code MEN.thes Supervisor professor Kari Tammi Advisor Klaus Kivekas Level Master’s thesis Date 30 July 2020 Pages 52 Language English
Seed Yield Components and Seed Quality of Oilseed Rape Are Impacted by Sulfur Fertilization and Its Interactions With Nitrogen Fertilization

Although the impact of sulfur (S) availability on the seed yield and nutritional quality of seeds has been demonstrated, its impact coupled with nitrogen (N) availability remains poorly studied in oilseed rape. A deeper knowledge of S and N interactions on seed yield components and seed quality could improve S and N fertilization management in a sustainable manner. To address this question, our goals were to determine the effects of nine different S fertilization management strategies (i) in interaction with different levels of N fertilization and (ii) according to the timing of application (by delaying and fractionating the S inputs) on agronomic performances and components of seed yield. The impact of these various managements of S and N fertilizations was also investigated on the seed quality with a focus on the composition of SSPs (mainly represented by napins and cruciferins). Our results highlighted synergetic effects on S and N use efficiencies at optimum rates of S and N inputs and antagonistic effects at excessive rates of one of the two elements. The data indicated that adjustment of S and N fertilization may lead to high seed yield and seed protein quality in a sustainable manner, especially in the context of reductions in N inputs. Delaying S inputs improved the seed protein quality by significantly increasing the relative abundance of napin (a SSP rich in S-containing amino acids) and decreasing the level of a cruciferin at 30 kDa (a SSP with low content of S-amino acids). These observations suggest that fractionated or delayed S fertilizer inputs could provide additional insights into the development of N and S management strategies to maintain or improve seed yield and protein quality. Our results also demonstrated that the S% in seeds and the napin:30 kDa-cruciferin ratio are highly dependent on S/N fertilization in relation to S supply. In addition, we observed a strong relationship between S% in seeds and the abundance of napin as well as the napin:30 kDa-cruciferin ratio, suggesting that S% may be used as a relevant index for the determination of protein quality in seeds in terms of S-containing amino acids.
East African Scholars Multidisciplinary Bulletin

Quick Response Code Abstract: Municipal solid waste (MSW) management is a global issue. Improper MSW management has adverse effects on human health and the environment. In view of this, promoting sound MSW management has been the focus of many policy makers, researchers and academics. In most countries including Ghana, this complex task has been entrusted to the local government. However, the success of the local government in this endeavor largely depends on the involvement of other actors of solid waste management. This study therefore seeks to evaluate the involvement of actors by the local government in MSW management using the Kumasi metropolis of Ghana as a case study. Qualitative case study approach involving observations, one-on-one interviews and focus group discussions with a wide range of actors is employed. The results of the study underscore major drawbacks in the MSW management system in the Kumasi metropolis where policies are formulated by the top-down approach. This study contributes to literature by encouraging the habit of source separation of waste among solid waste service users since it has the tendency of reducing the quantity of waste to be dumped at the disposal sites and consequently, protracting the lifespan of landfills and dumpsites in the metropolis. The study further entreats the local government to formulate MSW management regulations and policies with a bottom-up approach through broader consultations with actors to ensure that the provisions take into consideration the cultural and distinct local needs in the area.
Using Collaborative Coalition Processes to Advance Community Health, Well-Being, and Equity: A Multiple–Case Study Analysis From a National Community Transformation Initiative

Spreading Community Accelerators Through Learning and Evaluation (SCALE) was a Robert Wood Johnson Foundation–funded initiative from 2015 to 2017 to build capability of 24 community coalitions to advance health, well-being, and equity. The SCALE theory of change had three components: develop leadership capability, build relationships within and between communities, and create an intercommunity system to spread promising ideas. The theory was operationalized through training academies, coaching, and peer-to-peer learning that explicitly addressed equity and systems change. In this article, we describe how SCALE facilitated community transformation related to Collaborating for Equity and Justice Principles 1, 3, 4, and 6. We conducted a multiple–case study approach with two community coalitions including site visits, interviews, and observation to illuminate underlying mechanisms of change by exploring how and why change occurs. Skid Row Women worked with women experiencing homelessness in Los Angeles to address diabetes and food systems. Healthy Livable Communities of Cattaraugus County used a portfolio of projects in order to create system changes to improve population health and increase access to services for people with disabilities in rural New York State. Through our analysis, we describe how two coalitions used SCALE tools for collaborative coalition processes such as aim setting, relationship building, and shared decision making with community residents. Our findings suggest that advancing Collaborating for Equity and Justice principles requires self-reflection and courage; new ways of being in relationship; learning from failure; productive conflict to explicitly address power, racism, and other forms of oppression; and methods to test systems improvement ideas.
A Theoretical Overview To The Concept Of Cyberloafing

Constantly changing and developing technological tools are a necessity in life. The conveniences it provides based on time and transportation make technological tools attractive and make them a part of individual lives. It shows that with the widespread use of internet access, employees are using the internet more and more for personal purposes. This situation, called cyberloafing
Striking divergences in Earth Observation products may limit their use for REDD+

Countries are required to generate baselines of carbon emissions, or Forest Reference Emission Levels, for implementing REDD + under the United Nations Framework Convention on Climate Change and to access results-based payments. Developing these baselines requires accurate maps of carbon stocks and historical deforestation. Global remote sensing products provide low-cost solutions for this information, but there has been little validation of these products at national scales. This study compares the ability of currently available products obtained from remote sensing data to deliver estimates of deforestation and associated carbon emissions in Guinea-Bissau, a West African country encompassing the climate and vegetation gradients that are typical of sub-Saharan Africa. We show that disagreements in estimates of deforestation are striking, and this variation leads to high uncertainty in derived emissions. For Guinea-Bissau, we suggest that higher temporal resolution of remote sensing products is required to reduce this uncertainty by overcoming current limitations in differentiating deforestation from seasonality. In contrast, existing datasets of carbon stocks show better agreement, and contribute much less to the variation in estimated emissions.
REAL-TIME FRAMEWORK FOR ITER CONTROL SYSTEMS

The ITER Real-Time Framework (RTF) is a middleware providing common services and capabilities to build realtime control applications in ITER such as the Plasma Control System (PCS) and plasma diagnostics. The RTF dynamically constructs applications at runtime from the configuration. The principal building blocks that compose an application process are called Function Blocks (FB), which follow a modular structure pattern. The application configuration defines the information that can influence control behaviour, such as the connections among FBs, their corresponding parameters, and event handlers. The consecutive pipeline process in a busy-waiting mode and a data-driven pattern minimizes jitter and hardens the deterministic system behaviour. In contrast, infrastructural capabilities are managed differently in the service layer using non-real-time threads. The deployment configuration covers the final placement of a program instance and thread allocation to the appropriate computing infrastructure. In this paper, we will introduce the architecture and design patterns of the framework as well as the real-life examples used to benchmark the RTF. INTRODUCTION The Plasma Control System is a dominant factor for the ITER pulsed operation, it controls all aspects of the plasma discharge from powering the superconducting magnets up to plasma termination [1]. PCS takes data from sensors and applies sophisticated algorithms to generate commands that are sent to actuators to control plasma parameters, such as position, shape or stability in a real-time context. Design, development and verification of real-time software in general is a complex and often lengthy process requiring multiple iterations until all timing relationships are satisfied and the application is stable and predictable. The RTF is a flexible high-performance software base that facilitates the development and deployment of complex real-time applications [2]. Originally developed with the aim of control algorithms, the RTF can also be the basis for real-time data processing applications in ITER diagnostic systems. The architecture design fully considered the modularity and portability of the software, and is applicable and extendable even in none-ITER environments. It hides many details specific to real-time systems (e.g., thread management, inter-thread data transfers, etc.), making the design and development of real-time software much easier and faster. Strict Quality Assurance (QA) process and code audits enforced software integrity to bring reliable system operation. Along with the EPICS pvAccess interface that enriches functionality for operation, the Simulink wrapper block allows control model transition from the design to the application in an agnostic way.
Efficient Methods of Multimodal Biometric Security System-Fingerprint Authentication, Speech and Face Recognition

: This paper proposes the efficient methods in multimodal biometric i.e. Fingerprint, Speech, Face. Multimodal system is developed through fusion of fingerprint, Speech and face recognition. The proposed system is designed for applications where the training database contains a face, fingerprint images and voice data. This proposed system may be used in various application areas such as, for authentication number of employees working in offices, in military applications and also in all possible security applications.
A SURVEY ON NETWORK-BASED INTRUSION DETECTION SYSTEMS USING MACHINE LEARNING ALGORITHMS

Network security is of central significance in the current information world. Due to the rapid increase of network-enabled devices, there is a significant risk of network intrusion more than ever. Hackers and intruders can successfully attack to cause the crash of the networks and web services by the unauthorized intrusion, which may cause a significant loss to an organization in terms of data and money. So, it is high time to create an intrusion detection system that can detect all types of intrusion. Due to the rapid growth and significant results of machine learning (ML) algorithms in several areas, there has recently been much interest in applying them to network security. The network-based intrusion detection system (NIDS) has much promise to be the borderline of defense against intrusions in the current information communication technology (ICT) era, and it's a critical aspect of network security. Due to the dynamic nature of attacks, intrusion detection datasets are available publicly. Intrusion detection systems are the backbone of the networks and data protection. Various IDS approaches have been used over time to achieve maximum detection accuracy. This paper investigates the different machine learning methods used to deploy network-based intrusion detection systems. This survey could give scholars a better grasp of present methodologies and help them find research possibilities and do further research in this area.