Miracle-dz/UniFAR-FTUs huggingface dataset:
Cyber Defense Operation using CyCOP: A Cyber Situational Awareness Tool to Support Decision-Making

We have developed the Cyber Common Operational Picture (CyCOP) that helps users to recognize current cyber situations and make appropriate decisions for cyber defense. There is an operational concept based on the OODA (observation, orientation, decision, and act) loop for decision making in CyCOP. CyCOP provides several views that visualize the current state of cyber assets, the network topology of the organization and cyber threat situations. It also presents information to the users to determine the best course of actions (CoAs) against potential or current threats.
A NEW DESIGN FOR THE U.S. GEOLOGICAL SURVEY'S NATIONAL DIGITAL CARTOGRAPHIC DATA BASE

In analyzing the requirements for the U.S. Geological Survey's next generation of digital cartographic systems, several enhancements to the National Digital Cartographic Data Base regarding spatial data structures and data management systems were identified as key items. These included the development and implementation of a new data structure having enhanced attribute and feature identification characteristics to support product generation and analytical re quirements and the development and implementation of an improved data management capability. A data base design incorporating these enhancements has been completed. Research and development activities pursuant to these design concepts are underway. A prototype of the spatial data base environ ment will be developed on a standalone workstation (32-bit supermicro) using relational data base software and anticipating a network of workstations con nected to a central data archive.
Prediction modelling of academic performance with logistic regression: A case of rural primary school students in Kenya

Every year, when the Kenya Certificate of Primary Education (KCPE) examination results are released, the same story of mass failure in rural schools is repeated. Academic performance prediction modelling could provide an opportunity for learners' outcomes to be known early, before they sit for final examinations. This would be particularly useful for education stakeholders to initiate intervention measures to help students who require high intervention to pass final examinations. This study proposed that an academic performance prediction model could be built using Logistic Regression to classify students into two categories: those that will pass and those that will need intervention to pass. A six-step Cross-Industry Standard Process for Data Mining (CRISP-DM) theoretical framework was used to support the modelling process. Modelling was conducted using two datasets collected in Kwale County and Mombasa County. The first dataset had 2426 records having 22 features, collected from 54 rural primary schools. The second dataset had 1105 records with 19 features, collected from 11 peri-urban primary schools. Evaluation was conducted to investigate: (i) the prediction performance of Logistic Regression on the two datasets with all the features and; (ii) the prediction performance with an optimal subset of features. Two common performance measures (ROC area and F-Measure) were adopted. It was found that the model achieved a ROC area measure of 88.7% with all features and 88.5% with the optimal feature dataset. Similarly the F-Measure rate was 89.7% for all the features and 89.6% for the optimal feature subset. Further, a mobile application was implemented to facilitate the model use in rural areas where desktops cannot be used. Teachers in 15 schools used the model for two weeks to classify their Class Six and Class Seven students. Results show that nearly 80% of the students requiring high intervention could be determined. This high prediction performance means that the students who need high intervention could be determined early enough before the final examination. Further, this accuracy of prediction is good enough to motivate stakeholders to initiate strategic intervention measures.
Scalable Compatibility for Embedded Real- Time components via Language Progressive Timed Automata

The proper composition of independently developed components of an embedded realtime system is complicated due to the fact that besides the functional behavior also the non-functional properties and in particular the timing have to be compatible. Nowadays related compatibility problems have to be addressed in a cumbersome integration and configuration phase at the end of the development process, that in the worst case may fail. Therefore, a number of formal approaches have been developed, which try to guide the upfront decomposition of the embedded real-time system into components such that integration problems related to timing properties can be excluded and that suitable configurations can be found. However, the proposed solutions require a number of strong assumptions that can be hardly fulfilled or the required analysis does not scale well. In this paper an approach based on timed automata is represented that can provide the required guarantees for the later integration without strong assumptions, which are difficult to match in practice. The approach provides a modular reasoning scheme that permits to establish the required guarantees for the integration employing only local checks and therefore scales. It is also possible to determine potential configuration settings by means of timed game synthesis.
SOLUTION OF THE EULER EQUATIONS IN THE THREE-DIMENSIONAL SPACE USING THE MACCORMACK ALGORITHM-PART I

The present work studies the MacCormack algorithm applied to the solution of the Euler equations in threedimensional space, solving aerospace problems. A finite volume formulation is used, as also a cell centered data structure and structured spatial discretization of the flow equations. The scheme is second order accurate in space and time. The time integration uses a predictor-corrector scheme with a forward spatial discretization in the predictor step and a backward spatial discretization in the corrector step. An artificial dissipation operator based on the Azevedo work is implemented to guarantee scheme numerical stability in the presence of shock waves and background instabilities. A spatially variable time step is implemented to accelerate the convergence process to the steady state solution. The physical problems of the supersonic flow along a ramp and of the “cold gas” hypersonic flow along a diffuser are studied. In the ramp problem the shock wave is well detected and in the diffuser problem the shock interference is well solved. A final analysis of the computational performance (cost, maximum CFL number and iterations to convergence) is accomplished. The importance of this work is to describe numerical tools that can be used to solve the steady state flowfield of physical problems of interest in the aeronautical and aerospace industry. In this work, the MacCormack algorithm is presented and some results are presented that can be used as reference results to the CFD community.
Solution reuse for textual cases

The reuse stage in textual CBR identifies reusable textual constructs in solution content. This involves content annotation so that reusable solution text is easily identifiable from the rest. We present a generic architecture, Case Retrieval Reuse Net (CR2N), that can be used to annotate text to denote text content as reusable or not. Initial results from a weather forecast revision dataset shows up to 80% accuracy and a significantly better precision over a retrieve-only system. Although our work with CR2N is still on going, it also provides useful insight into the text revision stage. Keyword Textual CBR, Case Reuse, Case Retrieval Net, NLG
Enabling the Sleep Mode in Non-beaconed 802.15.4 Multihop Networks-A Simulative Investigation

Large wireless sensor network deployments used for environmental monitoring or cargo tracking, require energy efficient mesh topologies. This implies duty cycling of sensor nodes to be coordinated with the routing protocol. Staying in the context of ZigBee, we simulate the combination of the sleep enabled non-beaconed mode of 802.15. 4 and AODV routing and compare the duty cycling effects of synchronized and unsynchronized sleep scheduling. We consider two different link layer feedback schemes for AODV, denoted as regular and smooth AODV.
General purpose methodology and tooling for Text-to-Speech support in voice services for under-resourced languages

In Africa, mobile telephony has become widespread in recent years. This trend has induced growth in development of mobile applications and services. However, due to low literacy levels as well as a huge linguistic diversity across the continent, it proves challenging to create accessible applications for a wide range of African communities. Implementing voice-based services is one possible way to bypass the problem of illiteracy, but not linguistic diversity. In this paper the Text-to-Speech Slot and Filler system, originally developed as part of the Lwazi II project, is presented. The system is aimed at under-resourced languages and supports a limited dictionary of words. Thanks to its relative simplicity of use, it allows for rapid development and creating support for new languages by non-experts. The Text-to-Speech Slot and Filler system has the potential to help existing mobile services overcome the linguistic diversity in Africa. To show this, the system was used to create TTS support for a new language, Twi, spoken in Ghana. With the help of a native speaker, a number of suitable recordings was created in the domain of weather forecast and then used to build the system. To test the quality of the TTS conversion, several new sentences in the language of Twi were synthesised and evaluated by a group of native speakers in a feedback form. Most of the syntheses were deemed easy to understand and sounded mostly natural. In some cases, a word was mispronounced due to incorrect unit selection, indicating that this part of the system may need to be revised. Finally, the system was integrated into an existing voice-based service called InfoMétéo, extending it by the language of Twi. Based on this use case, a general purpose methodology and tooling of limited domain TTS support for under-resourced languages is provided.
Towards Robust Motion Planning for Synthetic Cells in a Circulatory System

The immune system protects the body by recognizing and reacting to foreign invaders, known as antigens. When white blood cells find an antigen, they multiply and communicate among themselves to collectively carry out an immune response. Recent advances in the design of active synthetic cells and active Brownian particles have shown that artificial microscopic agents are cable of rudimentary communication, computation and locomotion in response to stimuli. We consider the problem of designing robust exploration strategies for collectives of microscopic agents in a circulatory system. In such an environment, agents are not guaranteed to have perfect sensing, reliable communications or be capable of complex locomotion. Here, we present preliminary efforts in generating locomotion strategies for ensembles of microscopic agents without onboard computation. By leveraging advances in embodied computation and active matter, along with recent results in decentralized coverage algorithms, we propose a robust algorithm for control of synthetic cell swarms.
Rump Device Drivers: Shine On You Kernel Diamond

BSD-based operating systems implement device drivers in kernel mode for historical, performance, and simplicity reasons. In this paper we extend the Runnable Userspace Meta Program (rump) paradigm of running unmodified kernel code directly in a userspace process to kernel device drivers. Support is available for pseudo device drivers (e.g. RAID, disk encryption, and the Berkeley Packet Filter) and USB hardware drivers (e.g. mass memory, printers, and keyboards). Use cases include driver development, regression testing, safe execution of untrusted drivers, execution on foreign operating systems, and more. The design and NetBSD implementation along with the current status and future directions are discussed.
Human Resources Challenges in Apparel Industry in Sri Lanka

This study aims to identify the human resources challenges existing in the apparel sector of Sri Lanka and provide recommendations to secure with managing the barriers to go ahead with future sustainability in the industry. The research approach is qualitative and followed the case study method. Face to face interviews was the method of collecting data by following a semi-structured questionnaire for the research, and the data analysis method was the thematic analysis. The finding demonstrates nine core human resources challenges in the apparel industry
The Impact of Automation on the Unemployed ∗

This paper examines the distributional consequences of routine-task biased technological change across unemployed job seekers with different task competencies. Using representative data on unemployed job seekers and vacancies from an online job platform, we predict a job seeker’s expected unemployment duration from the tightness (i.e. the ratio of vacancies over unemployed job seekers) in detailed jobs for which she fully or partially qualifies based on her task competencies. The first main contribution is to show that the labor market is, at least in part, organized along jobs and their task content, in that tightness in jobs for which an unemployed job seeker fully qualifies in terms of her task competencies is predictive of her unemployment duration. We also find that overlap across jobs in terms of task content matters – i.e. unemployed job seekers also compete for jobs for which they only partially qualify based on their task competencies. However, the importance of this task overlap is limited: unemployed job seekers can only compete in markets where they possess at least 80% of the required task competencies. This implies that adverse task-biased shocks are likely to have pronounced distributional consequences on unemployment durations of job seekers with different task competencies. The second main contribution of this paper therefore is to quantify the distributional impact on unemployed job seekers of ongoing routine-biased technological change. In particular, our results show that unemployment durations for job seekers with mainly routine-task competencies are four times longer compared to a single market scenario where unemployed job seekers can compete for jobs irrespective of their task competencies. This paper therefore reveals that ongoing technological progress imposes substantial labor adjustment costs that are highly unevenly distributed across unemployed job seekers with different task competencies.
Undercurrents of Participatory Groundwater Governance in Rural Jalna, Western India

This paper analyses a participatory groundwater governance project called Purna Groundwater Management Association (PGWMA). A pilot project under the World Bank-funded Maharashtra Water Sector Improvement Project, the PGWMA project spanned eight villages in the Marathwada region of Maharashtra. In the case study, we used ethnographic interviews, discussions with villagers, and analysis of project materials. At the governance level, we found that the groundwater problem was conceptualised in a depoliticised way and involved an oversimplified notion of the community; it also deployed a checklist-type approach to equity, sustainability and participation, and attempted to commodify water. At the level of the community, our observations of people’s access to groundwater, and of their perceptions and knowledge, showed that the project failed to inculcate the idea of groundwater as commons. While the project led to slightly improved water access, for the most part it redeployed caste, class and gender relations and led to negligible improvement in community participation. The study examines the paradoxical coexistence of the 'success' of the participatory governance model and the actual failure to steer the community-groundwater relationship towards sustainability. The case could not be entirely explained by existing critiques within development studies (the root cause of the over-extraction problem was unsustainably high groundwater need); it did not fit the 'implementation failure' critique, nor did we find a semblance of an 'ideal', 'traditional' system of resource management; a politicised understanding of the community was also insufficient. Using the Cultural Political Economy approach, we found that the historical sedimentation of high groundwater demand was linked to an imaginary of a 'better life' through social structures, political economy, technology access and postcolonial development policies that have influenced agricultural practices. The situation has become unsustainable due to dwindling water tables. Thinking through these 'undercurrents' of groundwater governance leads to a deeper understanding of the groundwater problem, its framings and meanings at multiple levels, and its links to equity and sustainability.
Horizon Effects in Average Returns: The Role of Heterogeneous Information Diffusion

We show that when stocks incorporate systematic information at different speeds, observed short-horizon returns of buy-and-hold portfolios are downward-biased. This is surprising given existing theory, which shows that average buy-and-hold portfolio returns are unaffected if noise in prices is independent of fundamentals. Heterogeneous information diffusion, however, implies measurement errors correlated with fundamentals. Confirming predictions, we show downward bias in average returns exceeding 6% annualized in daily and monthly style portfolios and international indices. Slow reaction to market information is the primary cause of horizon effects in average returns. These findings have natural consequences for performance evaluation. ∗We thank Hank Bessembinder, Carole Comerton-Forde, Cam Harvey, Andrew Karolyi, and seminar participants at ESSEC Business School, the University of New South Wales, University of North Carolina at Chapel Hill, the University of Southern California, the University of Toronto, SUNY-Buffalo, Wilfred Laurier University, the Finance Down Under Conference, the Northern Finance Association Meetings, the Pacific Northwest Finance Conference, and the Red Rock Finance Conference at Brigham Young University for helpful comments. This paper previously circulated under the title “On Horizon Effects and Microstructure Bias in Average Returns and Alphas. ” Boguth: oliver.boguth@asu.edu; W. P. Carey School of Business, Arizona State University, PO Box 873906, Tempe, AZ 85287-3906. Carlson and Fisher: murray.carlson@sauder.ubc. ca; adlai.fisher@sauder.ubc. ca; Sauder School of Business, University of British Columbia, 2053 Main Mall, Vancouver, BC, V6T 1Z2. Simutin: mikhail.simutin@rotman.utoronto. ca; Rotman School of Management, University of Toronto, 105 St. George Street, Toronto ON, Canada, M5S 3E6. Support for this project from the Social Sciences and Humanities Research Council of Canada and the UBC Bureau of Asset Management is gratefully acknowledged. Horizon Effects in Average Returns: The Role of Heterogeneous Information Diffusion
The evaluation of class 1 to 3 integrons in Salmonella and antimicrobial resistance pattern isolated from Ross 308 broiler chickens

High prevalent of multiple drug resistant (MDR) Salmonella is considered as a threat for human’s health. Integrons are one of the most important factors that can contribute to the occurrence of MDR bacteria. The aim of this study was to determine the prevalence of class 1, 2 and 3 integrons among Salmonella strains isolated from broiler chicks. This study was performed on 100 Salmonella isolated strains, collected from male and female broiler chicks samples in southwest of Iran. The prevalence of class 1-3 integrons were verified using specific primers by multiplex PCR assay. Also antimicrobial susceptibility testing by disk diffusion method was performed for each isolate. Screening of Salmonella isolates revealed the prevalence of class 1, 2 and 3 integrons (50%), (28%) and (48%), respectively. Based on the results of this study significant correlations were between MDR and integrons, this is a serious problem in human and veterinary medicine. According to these results Ampicillin was the most resistant antibiotics against Salmonella isolated strains. The resistance to Gentamicin and Tetracycline and Chloramphenicol has increased in the presence of integrons. The presence of all three classes of integrons and its direct connection with the MDR in Salmonella is concerned.
Clinical Score System to Differentiate Severe Fever with Thrombocytopenia Syndrome Patients from Patients with Scrub Typhus or Hemorrhagic Fever with Renal Syndrome in Korea

Background Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with high mortality in East Asia. This study aimed to develop, for primary care providers, a prediction score using initial symptoms and basic laboratory blood tests to differentiate between SFTS and other endemic zoonoses in Korea. Methods Patients aged ≥ 18 years diagnosed with endemic zoonoses during a 3-year period (between January 2015 and December 2017) were retrospectively enrolled from 4 tertiary university hospitals. A prediction score was built based on multivariate logistic regression analyses. Results Of 84 patients, 35 with SFTS and 49 with other endemic zoonoses were enrolled. In multivariate logistic regression analysis, independent predictors of SFTS included neurologic symptoms (odds ratio [OR], 12.915; 95% confidence interval [CI], 2.173–76.747), diarrhea (OR, 10.306; 95% CI, 1.588–66.895), leukopenia (< 4,000/mm3) (OR, 19.400; 95% CI, 3.290–114.408), and normal C-reactive protein (< 0.5 mg/dL) (OR, 24.739; 95% CI, 1.812–337.742). We set up a prediction score by assigning one point to each of these four predictors. A score of ≥ 2 had 82.9% sensitivity (95% CI, 71.7%–87.5%) and 95.9% specificity (95% CI, 88.0%–99.2%). The area under the curve of the clinical prediction score was 0.950 (95% CI, 0.903–0.997). Conclusion This study finding suggests a simple and useful scoring system to predict SFTS in patients with endemic zoonoses. We expect this strategic approach to facilitate early differentiation of SFTS from other endemic zoonoses, especially by primary care providers, and to improve the clinical outcomes.