Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Chest X-rays Analysis using Statistical Machine Learning Strategies

AUTOMATIC CHEST X-RAYS ANALYSIS USING STATISTICAL MACHINE LEARNING STRATEGIES by Hermann Yepdjio Nkouanga June 2020 Tuberculosis (TB) is a disease responsible for the deaths of more than one million people worldwide every year. Even though it is preventable and curable, it remains a major threat to humanity that needs to be taken care of. It is often diagnosed in developed countries using approaches such as sputum smear microscopy and culture methods. However, since these approaches are rather expensive, they are not commonly used in poor regions of the globe such as India, Africa, and Bangladesh. Instead, the well known and affordable chest x-ray (CXR) interpretation by radiologists is the technique employed in those places. Nevertheless, if this method is obsolete in other parts of the world nowadays it is because of its many flaws including: i) it is a tedious task that requires experienced medical personnel --which is scarce given the high demand for it--, ii) it is manual and difficult when executed for a large population, and iii) it is prone to human error depending on the proficiency and aptitude of the interpreter. Researchers have thus been trying to overcome these challenges over the years by proposing software solutions that mainly involve computer vision, artificial intelligence, and machine learning. The problems with these existing solutions are that they are either complex or not reliable enough. The need for better solutions in this specific domain as well as my desire to bring my contribution to something meaningful are what led us to investigate in this direction. iii In this manuscript, I propose a simple fully automatic software solution that uses only machine learning and image processing to analyze and detect anomalies related to TB in CXR scans. My system starts by extracting the region of interest from the incoming images, then performs a computationally inexpensive yet efficient feature extraction that involves edge detection using Laplacian of Gaussian and positional information retention. The extracted features are then fed to a regular random forest classifier for discrimination. I tested the system on two benchmark data collections --Montgomery and Shenzhen-and obtained state-of-the-art results that reach up to 97% classification accuracy.
Developing an Urban Land Use Simulator for European Cities

Introduction Cities are among the most complex structures created by human societies, and unlike other complex man-made objects, like computers, we do not pretend to understand them fully. Furthermore, cities in Europe, as in most parts of the world, are currently undergoing rapid and profound changes which affect the quality of life for hundreds of millions of people—changes which should be managed to preserve or enhance the quality of life, and to ensure economic and environmental sustainability. Effective planning and management requires both data on current conditions and an ability to foresee the likely consequences of proposed projects and policies. The Space Applications Institute (European Commission—Joint Research Centre) has as one of its objectives to enhance the value of Earth observation data by stimulating user oriented data services. In this context, the MURBANDY project is aimed specifically at enhancing the use of remotely sensed data for urban planning by implementing the following component projects: (1) building a data base of land use change over approximately the last 40 years for a representative sample of European cities, (2) developing a number of urban environmental indicators related to sustainability, and (3) developing a generic model of urban dynamics that will support the realistic exploration of urban futures under a variety of planning and policy scenarios—or a scenario of no planning. All three components make use of a recent extension to the CORINE land use/land cover database which significantly extends the number of urban land use classes and thus makes possible a much more detailed study of urban areas. In this paper we discuss work carried out under the third component, the development of a generic model of urban land use dynamics. The goal of developing a generic model—one that will be applicable to essentially any European city— implies the rather strong assumption that at some level cities are fundamentally similar, evolving by the same processes. Especially in the European context, where cities grow out of and express a wide variety of cultural, economic, and historical contexts, this seems a bold hypothesis. However, the fractal analysis of land use patterns provides evidence in its favour (Frankhauser, 1994; White and Engelen, 1993), and suggests that the substantial differences among cities are largely due to city-specific boundary conditions. In particular, we hypothesise that it is such city-specific factors as local topography, the geometry of the transport network, and local planning regulations (which themselves represent a particular local intervention in what might otherwise be a generic process of urban development) that determine the observed differences among cities. The project in effect constitutes a test of this hypothesis.
A Hardware/Application Overlay Model for Large-Scale Neuromorphic Simulation

Neuromorphic computing is gaining momentum as an alternative hardware platform for large-scale neural simulation. However, with several major devices and systems available and planned, often with very different characteristics, it is not always clear which platform is suitable for which application. Simulating the platform on conventional computers is typically too slow to be of use, but an alternative approach is to implement an ‘emulation’ of the hardware in FPGAs which can execute at near-hardware speeds but does not commit to a specific hardware architecture. We present an overlay model - a method which superimposes bespoke features on top of a standard template - in both hardware and software to implement neuromorphic architectures using the POETS (Partially Ordered Event Triggered Systems) system. This combination of overlays permits very large-scale simulations to be performed in real time for hardware exploration or application verification, while retaining the flexibility to redefine either the hardware or software layer, if results indicate potential to improve performance, or significant design problems. Using this system we simulate up to 500,000 neurons on a single-box system, that can be scaled to ∼4,000,000 neurons in an 8-box configuration. Results indicate the crucial constraint for real-time simulation: peak input spike rate per neuron; and help to optimise both hardware and software around neural application requirements. The preliminary architecture demonstrates the feasibility of an overlay model, while indicating directions for future neuromorphic systems. With POETS, we introduce a platform that can help to shape and investigate the neuromorphic architectures of the future.
The Use of ARM-Assembly Language and a Raspberry Pi 1 B+ as a Server to Improve Computer Architecture Skills

Prompting students' interest and engagement in learning environments is crucial to achieve the best results. Academia and educators in general are constantly adapting materials and methodologies in order to maximise the acquisition of contents by their students. In this case-study, a new teaching/learning methodology is presented and evaluated through a final questionnaire survey. This case-study aims to understand students' efficiency and motivation levels regarding a new teaching/learning methodology adopted in the second module of a Computer Systems and Architectures course attended by first-year Computer Sciences undergraduates. The new teaching/learning methodology relies on a specific programming language - ARMv6 assembly - to improve students' efficiency levels, and an innovative always-visible in-class mobile test scenario, implemented through a low-cost computing platform - Raspberry Pi 1 B+ - as a server, mimicking as much as possible a real-life environment, so that students believe they are working on real hardware, thus enhancing their motivation levels. The results of the questionnaire survey allowed to infer that the use of a specific programming language, such as ARMv6 assembly, coupled with a new always-visible in-class mobile test scenario were in fact efficient in raising the levels of motivation among Computer Sciences students and, consequently, improved their skills in Computer Architecture.
Exploiting BGP Scoping Services to Violate Internet Transit Policies

—Inter-domain path propagation limitation services are commonly implemented by IP transit providers, to offer ﬂexible trafﬁc engineering means to their customers. By combining such limitation services with the injection of more speciﬁc preﬁxes, operators of an Internet service provider can bring the global Internet routing system in a state which violates the policies of some other Internet service providers. In this paper, we describe the conditions for such policy violations to happen, and provide a speciﬁc analysis for the case of violations within the Tier-1 Internet service provider clique. We discuss the incentives for each actor of the violation and show that these can be beneﬁcial to the parties causing them. We present two approaches to tackle this problem. The ﬁrst one is to instrument ways to detect the violations and react a posteriori, while the violation is happening. The second approach is to pro-actively defend against the violations, notably by black-holing policy violating trafﬁc. Acknowledging its simplicity, we ﬁnally advocate for the former approach, as we observe that typically, the ISPs concerned by the violation have established business relationships and may hence prefer solutions which do not break the IP transit service.
Liquidity Traps in a Monetary Union – Globalization Institute Working Paper No. 397 – Dallas Fed

The closed economy macro literature has shown that a liquidity trap can result from the self-fulfilling expectation that future inflation and output will be low (Benhabib et al. (2001)). This paper investigates expectations-driven liquidity traps in a two-country New Keynesian model of a monetary union. In the model here, country-specific productivity shocks induce synchronized responses of domestic and foreign output, while country-specific aggregate demand shocks trigger asymmetric domestic and foreign responses. A rise in government purchases in an individual country lowers GDP in the rest of the union. The results here cast doubt on the view that, in the current era of ultra-low interest rates, a rise in fiscal spending by Euro Area (EA) core countries would significantly boost GDP in the EA periphery (e.g., Blanchard et al. (2016)). JEL codes: E3, E4, F2, F3, F4.
Modelling of solar granulation-Implementation and comparison of numerical schemes

The mathematical part covers the implementation and comparison of different numerical schemes to solve the equations of radiation hydrodynamics. One and the same two-dimensional model of solar granulation is simulated with different high resolution numerical methods (essentially non-oscillatory and convex non-oscillatory) and non-grey short characteristic radiative transfer. Furthermore the influence of artificial diffusivities is studied. The second part covers two astrophysical applications. A two-dimensional non-grey high resolution simulation of a downflowing plume in the sun and a grey three-dimensional simulation of the quiet sun are presented.
Analysis of Ambient Air Quality Based On Exceedance Factor and Air Quality Index for Siliguri City, West Bengal

Bad air is one of the key concerns for most of the urban centres today, and Siliguri is no exceptions to this. In order to assess the air quality of Siliguri, Exceedance factor (EF) method was applied based on the average annual concentration of the pollutants named as; NO2, SO2, PM2.5 and PM10 and it is found that PM2.5 and PM10 are the major pollutants that pose a severe threat for the city. After applying the EF method, it is found that the values of PM2.5 was between moderate to high pollution level and for PM10 it falls under high to critical pollution level. On the other hand, the concentration of NO2and SO2 falls under moderate to low pollution level. Through trend analysis of the various pollutants, it is found that their concentration was varying in nature. In case of PM10, the trend shows high concentration which exceeds national standard; whereas PM2.5 shows its concentration near towards violating the national standard soon if not checked. In contrast, trends of NO2 and SO2 were recorded lower than the national standard. The present situation of ambient air of Siliguri was analyzed based on Air Quality Index which reveals that air quality of the city can be classified into two seasons, i.e. clean air period (from April to October) and polluted period (from November to March). Lastly, the annual trends of PM2.5and PM10 were constructed as they are the major pollutants, and it shows their skewed nature during winter months which results in smog episodes. It unveils how critical the situation of air quality of Siliguri became especially during winter months which seek immediate attention. Thus the study tries to present a vivid scenario about the present air quality of Siliguri, which concludes with some of the suggestions to restrain the air quality. Current World Environment www.cwejournal. org ISSN: 0973-4929, Vol. 15, No. (2) 2020, Pg. 236-246
SWORDFISH ABUNDANCE TRENDS IN DRIFTING SURFACE LONGLINE GREEK FISHERIES

Indices of abundance of swordfish (Xiphias gladius) from the Greek drifting surface longline fisheries targetting swordfish in the eastern Mediterranean are presented for the period 19872015. Annual standardized indices were estimated by means of Generalized Linear Modeling techniques and the predictor variables included the Year, Month, Gear type and Area of fishing. In addition catchability changes occurred in the fisheries were also taken into account. CPUE differences were found to be statistically significant for all predictors examined and the standardized annual indices from 2000 onwards are generally lower than those estimated for the previous years.
Modal Analysis of a Tapered Timoshenko Beam Using Force-Based Finite Element Formulation

Abstract: Finite element method is a tool used to analyse civil engineering structures. It gives approximate results. Displacement based finite elements are the most widely. Since, it uses assumed displacement field, tapered beams cannot be modelled using a single element. Discretization is required. Force based finite element formulation uses satisfaction of equilibrium of forces at an internal point. In this study, modal analysis results obtained by force based finite element formulation for fundamental flexural mode of vibration using a single element for modal analysis of a linear elastic two-dimensional Timoshenko cantilever beam element with complex geometries is compared against results from a finely discretised displacement based finite element formulation model. To take account of distribution of mass and stiffness instead of using lumped mass matrix, consistent mass matrix is adapted. From the results, it is evident that force based finite element formulation gives better results efficiently with a single element and the discretised displacement based model results converge to that of force-based approach.
Weight-Dropped Long Short Term Memory Network for Stock Prediction with Integrated Historical and Textual Data

— Investors and traders need an accurate stock prediction model to help them make decisions. They can use deep learning models such as Long Short-Term Memory Network (LSTM). However, a weakness of LSTM is that it tends to overfit to the training data and have unstable results. To overcome this weakness, this paper proposes using Averaged Stochastic Gradient Descent and Weight-Dropping on an LSTM network (AWD-LSTM). The proposed model regularizes the network by weight-dropping with DropConnect and optimizes the training process using a Non-Monotically Triggered Averaged Stochastic Gradient Descent (NT-ASGD). Additionally, this paper tested with integrating historical data with textual data which was shown to be valuable by other studies. This paper evaluated six variants of the model with different regulizers, optimizers, and data. The results show that (1) DropConnect regulizer performed better than DropOut or No Drop; (2) Adam optimizer is better for stock prediction than NT-ASGD; (3) Adding textual data slightly increases performance; (4) The models were able to gain consistent profits in a market simulation; (5) A variant of the model outperformed a previous study in 4 out of 5 indexes.
STUDY OF THE DRYING BEHAVIOR OF SOLAR DRYER AND PROXIMATE ANALYSIS OF THE DRIED PEAR (Pyrus communis) AND PEACH (Prunus persica)

Post-harvest losses of agricultural products occur due to many biological, microbiological and chemical factors. Some of the environmental factors such as temperature, humidity, and solar radiation also contribute to these losses. The farmers gain considerably low profit due to these losses (Ali et al., 2017). These losses can be minimized by conserving the resources and increasing the availability of agricultural products by having better facilities, technologies, and management practices. The agricultural products are preserved to increase their availability and maintain the nutritional value without any kind of deterioration. Vitamins, minerals, and fiber are the essential nutrients of food products and also a big source of digestion. They are categorized as perishable food material because of moisture (more than 70%) present in the agricultural product (Changrue et al., 2006). The nutritional value of the food product can only be maintained when it is being kept fresh. But it’s not an easy job to maintain the low temperature, which is a fundamental need of most of the storage processes (Weaver et al., 2014). Deterioration due to micro-organisms decreases the quality of agricultural products (Rahman, 1999). These microorganisms need certain conditions like adequate moisture content, nutrients, oxygen and the right temperature. Moisture content among these is the most essential entity which is responsible for many processes of deterioration (Jacoby et al., 2017). They cannot grow due to the shortage of moisture, therefore, the products can be avoided from disruption/spoilage (Mujumdar, 2008). Agricultural products are dried for improving food security and enhancing the shelf life in most of the world (Grabowski et al., 1992). Therefore, drying is an appropriate option for managing and preservation of the products after harvesting. Drying is a process in which moisture is removed from the Pak. J. Agri. Sci., Vol. 57(5),1413-1420; 2020 ISSN (Print) 0552-9034, ISSN (Online) 2076-0906 DOI: 10.21162/PAKJAS/20.821 http://www.pakjas. com.pk
STRATEGY AND PERFORMANCE INTERRELATION: THE MEDIATING ROLE OF THE SOLIDARITY

The present study provides insights for the SMEs to enhance their performance. For instance, SMEs managers or owners are expected to develop an understanding of the relationship among SMEs performance and business strategy. The main purpose of the study is to examine the impact of the entrepreneurial orientation and the business strategy on the firm’s performance of the SMEs operating in the Indonesia. In addition to that the study has also examined the mediating role of solidarity in the relationship between entrepreneurial orientation and business strategy and firm performance. We have adopted second generation method for data examination which is Partial least square Structural Equation Modelling PLS-SEM to avoid the limitations of first-generation methods. With the help of PLS technique the researcher can control number of interdependent links simultaneously. The response rate for present study was 59%. The findings of the study have provided support to the hypothesized results. The study will be helpful for the policymakers, and researchers in understanding the issues related to SMEs performance in Indonesia.
How the change in crude oil price impacts the financial markets in BRICS : The tale of wavelet-based copula

Crude oil plays a significant role in the economic activities of several countries. Higher prices of energy commodities lead to an increase in inflation and production costs, which results in declined output, demand, and trade in the economy. Therefore, several studies examine the relationship of oil price shocks and its effect on the financial markets in developed economies. However, the economic landscape has dramatically changed over the last two decades with the international trade and growth in economic activities of emerging economies. Despite this fact, there are relatively fewer studies on the dependence dynamics between crude oil and the financial markets of emerging economies. Furthermore, the existing literature on correlation quantification mainly relies on standard time series econometric model to provide an estimate of linkage. The time series models account for information from time and frequency domain as segregate, thereby neglecting information from either domain. Whereas, the financial and commodity markets comprise of agents with distinctive term objectives and different investment horizons. Therefore, in this study, we employ wavelet-based copula to evaluate the temporal and spectral dependence between crude oil and the financial markets of five emerging countries namely Brazil, Russia, India, China, and South Africa. Specifically, we implement maximal overlap discrete wavelet transform (MODWT) to decompose the underlying return series into various signals. Furthermore, to evaluate the frequential connectedness, we employ time-varying student-t copula on each series. Our findings indicate moderate level dependence between crude oil and stock markets of Brazil, Russia, and South Africa over the original returns, short-, and medium-run investment horizon. The correlation between crude oil and the financial market of India and China is relatively low over the original returns and short-run trend. Whereas, the level of dependence increases significantly over the long-run investment horizon.
Soil dehydrogenase enzyme and microbial biomass carbon as influenced by integrated nutrient management under cabbage cultivation in acid Inceptisol of Meghalaya

To investigate the influence of integrated nutrient management on soil dehydrogenase enzyme activity and microbial biomass carbon in acid Inceptisol, a field experiment was conducted at School of Natural Resource Management, College of Post Graduate Studies in Agricultural Sciences, Umiam, Meghalaya during rabi 2017-18. Cabbage (Brassica oleracea L. var. capitata) cv. Wonder Ball was raised as test crop with eight different combinations of doses of Farm Yard Manure (FYM), Vermicompost (VC) and recommended doses of NPK fertilizers (RDF). The treatment combination consists of control (T1), 100% RDF (T2), 100% N through FYM (T3), 100% N through VC (T4), 50% RDF + 50% N through FYM (T5), 75% RDF + 25% N through FYM (T6), 50% RDF + 50% N through VC (T7) and 75% RDF + 25% N through VC (T8). The experiment was laid out in RBD and replicated thrice. The experimental soil was having pH 4.87, SOC 1.24%, Alkaline KMnO4- N 160 kg/ha, available P2O5 18.60 kg/ha and available K2O 238.4 kg/ha. The experimental results revealed that treatment T7 with 50% RDF + 50% N through VC produced highest cabbage yield (60.44 t/ha) which was statistically comparable with T5 of 50% RDF + 50% N through FYM (54.33 t/ha). Significantly higher soil dehydrogenase enzyme activity (DHA) and soil microbial biomass carbon (SMBC) was observed under all organic manures treatments over the control and sole inorganic treatments. Among the organic treatments, T3 (100% N through FYM) recorded highest DHA and SMBC. In both combined treatments, farm yard manure treated soils (T5 and T6) showed higher DHA and SMBC over vermicompost treated soils (T7 and T8) indicating superiority of FYM over VC in maintaining soil biological health after harvest of cabbage.