Miracle-dz/UniFAR-FTUs huggingface dataset:
THE IMPACT OF FINANCIAL LITERACY OF OWNERS ON THE PERFORMANCE OF SMALL AND MEDIUM SCALE ENTERPRISES IN SRI LANKA

The developing countries' Small and Medium Scale Enterprises have stagnated instead of expanding and sophisticating. The chosen population involves the women entrepreneurs in Sri Lanka in regard to the Women Entrepreneurs Finance Initiative (We-Fi). The study aims at studying the impact of financial literacy on entrepreneurs' performance. The financial literacy and corporate performance composite index were computed, and a regression analysis was carried out to determine the effect of financial literacy on corporate performance. The study found that financial literacy in Sri Lanka has a statistically significant impact on the business performances of the selected sample. Through improved financial literacy, the SME owners along with their ventures can therefore boost their performance. The research found that financial literacy allows entrepreneurs to escape corporate failure resulting from poor financial decision-making. However, only general analysis and observational studies have examined the impact of financial literacy on entrepreneurs' business performance. Therefore, financial literacy is an essential component of knowledge in our modern society for entrepreneurial performance. Entrepreneurs with insufficient financial literacy are therefore more likely to make financial decisions with negative effects on their businesses. Nevertheless, it can be a crucial factor to improve financial literacy education both for primary and tertiary institutions. strong connection between business financial literacy and entrepreneurs' business performance. Other studies indicate that financial literacy influences entrepreneurs' performance through their engagement with other factors such as financial inclusion and financial awareness. Some studies also show that entrepreneurial financial literacy improves access to the use of financial services that allow enterprises to invent and take advantage of opportunities for growth. Entrepreneurial financial literacy impacts a business's financial inclusion in the search and use of financial services. Students and policymakers recognise that financial literacy is an entrepreneurial skill that allows enterprises to succeed in a gradually unstable climate. Financial resources are considered vital to the acquisition and configuration of other resources, and entrepreneurs must be financially informed to properly manage their business, offering an adequate basis for examined the connection between financial literacy in entrepreneurs and business performance, in which this study attempts to determine whether entrepreneurs' business performance depends on their financial
Malware Detection in Android platform using DNN

The android platform market is growing exponentially and so the attacks on android platform are increased. The attacks usually performed by installing an android application with malicious code inside the application. On initializing the malicious application an attacker is able to get device access, network information and so on. In the past, many researchers have performed research on this problem. This research is performed aiming to solve and add extra layer of defence in android platform using deep learning technology. The research is carried out by developing hybrid malware detection models in which static model was developed using static features of an android application such as manifest permissions, Intents and API calls whereas the dynamic model was developed using dynamic features such as system calls and system binder calls. The recurrent neural network particularly Long Short-Term Memory technique is utilized to developed both the models. Both the static and dynamic models are trained and the efficiency of the models is analysed using confusion matric and roc & auc scores. The developed models will be used in the organisation to add an extra layer of security in their current working mobile threat detection system.
Exploring T rade-offs A mong E nvironmental S ervices to S upport L andscape P lanning

Spatial planning of land-use and human activities for natural resource management often involves many stakeholders, each with their own values and preferences, and complex biological processes. We present an exploratory approach named Landscape IMAGES, which can be employed to determine interactions among various environmental services. These services can represent productive, economic, cultural or ecological dimensions of (agro-)ecosystems in landscapes or small regions. The approach provides insight in the full range of possible futures without prioritizing preferences beforehand. Moreover, it offers room for discussion and perspective sharing, to inform decision making and to increase understanding and support of stakeholders. The methodology of Landscape IMAGES is illustrated with an example of the redesign of an agri-ecological zone in the Netherlands, where economical, ecological and culture-historical aspects were considered. The aim of research involvement was to support an NGO involved in landscape management with the evaluation of a sketch design landscape plan of adjustments to the hedgerow structure typical of the landscape. To offer insight in the quality of the landscape plan the following landscape characteristics and their interactions were explored: The resulting seven indicators environmental served objectives in a multi-objective decision problem. To solve this problem we used a heuristic technique: the evolutionary
Performance of Naive Bayes method with data weighting

: Classification using naive bayes algorithm for air quality dataset has an accuracy rate of 39.97%. This result is considered not good and by using all existing data attributes. By doing pre-processing, namely feature selection using the gain ratio algorithm, the accuracy of the Naive Bayes algorithm increases to 61.76%. This proves that the gain ratio algorithm can improve the performance of the naive bayes algorithm for air quality dataset classification. Classification using naive bayes algorithm for air quality dataset. While the Water Quality dataset has an accuracy rate of 93.18%. These results are considered good and by using all existing data attributes. By doing pre-processing, namely feature selection using the gain ratio algorithm, the accuracy of the Naive Bayes algorithm increases to 95.73%. This proves that the gain ratio algorithm can improve the performance of the naive bayes algorithm for air quality dataset classification. Classification using Naive Bayes algorithm for Water Quality dataset. Based on the tests that have been carried out on all data, it can be seen that the Weight nave Bayes classification model can provide better accuracy values because there is a change in the weighting of the attribute values in the dataset used. The value of the weighted Gain ratio is used to calculate the probability in Naïve Bayes, which is a parameter to see the relationship between each attribute in the data, and is used as the basis for the weighting of each attribute of the dataset. The higher the Gain ratio of an attribute, the greater the relationship to the data class. So that the accuracy value increases than the accuracy value generated by the Naïve Bayes classification model. The increase in accuracy in the Naïve Bayes classification model is due to the amount of weight accuracy from the attribute selection in the Gain ratio.
Automated Negotiation of Smart Contracts for Utility Exchanges between Prosumers in Eco-Industrial Parks

Peer-to-Peer (P2P) Markets of prosumers trading utility surpluses (e.g., heating, cooling, or electric power) is a plausible realization of industrial symbiosis for companies in Eco-Industrial Parks (EIPs) in order to reach signiﬁcant economic beneﬁts and cut emissions. Through the synergistic co-generation and trading of utilities and industrial services, a P2P Market design makes room for socially desirable behavior despite the inherent selﬁsh nature of each prosumer company. In this paper, a P2P Market prototype for the automated negotiation of utilities between prosumers in an EIP is proposed as a mechanism design to encourage prosumers to participate in trading surpluses. Blockchain transactions and Smart Contracts, combined with Internet of Things (IoTs) technology such as smart meters, are the implementation means to secure that the terms of exchange agreed upon will be automatically enforced. During the simulation of the EIP, each prosumer (represented by a negotiation agent) chooses whether to negotiate with another prosumer or to buy or sell its surpluses to a traditional service provider, such as a main electric power service provider or a gas provider, according to a previously learned policy while considering the context it is immersed in. Utilities between prosumers are exchanged based on a digital currency, the token, which could be readily implemented over Ethereum/Solidity platforms. Smart contract negotiations between prosumers revolve around agreeing (or not) on the price expressed in tokens of a utility proﬁle, given the private and public information available to diﬀerent parties. Simulation results highlight how automated negotiations allow prosumers to reach higher proﬁts in the P2P Market from trading utility surpluses. Automated Negotiation · Blockchain and Smart Contracts · Game Theory · Reinforcement Learning.
Drivers and barriers to implement green building practices in higher education institutes in Sri Lanka

Higher education institutes have a vast variety of humans, processes, and activities with significant waste generation, transportation, water and material consumption, and energy and electricity consumption. They have the potential to disseminate and lead future generations in the transition towards sustainability. Green buildings are designed, constructed, and operated by efficiently utilizing resources to provide a healthy and comfortable built environment while minimizing the life cycle cost. Higher education institutes across the world are several steps ahead of Sri Lanka in implementing green building practices. Thus, this research aimed to find approaches to increase the implementation of green building practices in higher education institutes in Sri Lanka. The research aim was approached through a qualitative case study. Accordingly, three cases were studied by collecting data through nine semi-structured interviews. Collected data were coded by using the NVivo 11 software and analysed using the cross-case analysis. Findings revealed that benefits associated with green buildings, leadership, specialization of the institute, institutional policy, and imposed regulations drive Sri Lankan higher education institutes to implement the green building practices. Lack of awareness, professional knowledge, skilled labour, and funds, political regime changes, poor planning, and stakeholder management were identified as barriers. The research outcomes guide the policymakers and management of the Sri Lankan higher education institutes to effectively implement green building practices. Further, the research outcomes will help to make strategies to reinforce the drivers and mitigate the barriers.
Male Circumcision: A Means to Reduce HIV Transmission between Truckers and Female Sex Workers in Kenya

Kenya records over 1.5 million cases of HIV-infected people with a prevalence of 4.8% among adultsin 2019, ranking Kenya as the seventh-largest HIV population in the world. A recent study showed that55.9% of Kenyan truckers pay for sex in while 46.6% had a regular partner along their trucking route inaddition to a wife or girlfriend at home. The complexity in the sexual network of Truckers, which can be aconduit for the widespread of HIV, necessitated the need to better understand the dynamics of transmissionof HIV/AIDS between truckers and female sex workers. In this study, a model is formulated for HIV/AIDSdynamics along the Northern corridor highway in Kenya. The reproduction number, disease-free equilibriumand endemic equilibrium points were determined and their stabilities were also determined using the nextgenerationmatrix method. The disease-free equilibrium is stable when R0u < 1, R0c < 1 and R0f < 1 whilethe endemic equilibrium point is stable when R0u > 1, R0c > 1 and R0f > 1. It is found that circumcision canbe used as an intervention to minimize the infection of HIV among truckers and female sex workers.
An efficient framework for glioma tumor classifications and diagnosis using proposed CNN architecture

This article proposes the deep learning algorithm-Convolutional Neural Networks (CNN) for both Glioma tumor classifications and diagnosis process. This proposed CNN architecture is derived from the conventional CNN architecture to obtain the optimum classification and diagnosis accuracy. This proposed CNN architecture is derived from the conventional system for obtaining the high classification and diagnosis performance. This proposed methodology stated in this paper uses BRATS 2015 open access dataset for obtaining the brain Magnetic Resonance Image (MRI) for tumor region detection. The proposed methodology stated in this paper for tumor diagnosis achieves 97.7% of Jaccard Index (J) and 83.8% of Dice Similarity Index (DSI) and 99.025 of Diagnosis Rate (DR) using CNN algorithm.
Flow and Heat Transfer Performance of Channels with 45 Degree Ribs in Staggered Array

The cooling efficiency of blade is growing demand with increasing turbine inlet temperature in gas turbine development. Ribs used in cooling channels is a common cooling structure, therefore, many configurations were studied by previous literatures, including angle, spacing, shape etc. However, there are less research about the dislocation ribs structure. In this paper, the 45-deg parallel ribs, crossed ribs and dislocation ribs were investigated by numerical simulation, in order to reveal the heat transfer performance and flow mechanism. Refer to the experiment, SST k-ω model was applied in steady simulation, at Re from 20000 to 50000. Due to the angled ribs can induce the secondary flow and generate small helical vortices at front corner, heat transfer performance was elevated. The large rotating vortices influenced by the ribs arrangement occupy the center channel, thence the dislocation caused different flow and heat transfer results. The results shown that parallel rib has higher heat transfer enhancement than crossed ribs, but pressure loss possess considerable level. At Re=21587, the averaged turbulent kinetic energy of Case2.2 with dislocation ribs is 22.4% lower than parallel ribs. The all 45-deg crossed ribs present higher level of overall thermal performance, and Case2.2 is optimal for the range of Re investigated.
Aerial Surveys of Bristol Bay Beluga Whales, Delphinapterus leucas , in 2016

—Beluga whales, (Delphi- napterus leucas), of the Bristol Bay stock were counted from 7 to 11 July 2016, during aerial surveys in Bristol Bay, Alaska. These surveys were a follow-up of surveys flown in Bristol Bay in 1993, 1994, 1999, 2000, 2004, and 2005, and used the same methods. Nine surveys were flown during 7–11 July. The total count of belugas per survey ranged from 484 to 1,024 (= 660; CV = 0.26). Cor-recting the average count for the number of belugas that are diving and not available to be sampled (2.62) and the proportion of calves (1.18) that cannot be seen from the aircraft suggests there are ~2,040 belu- gas (660 × 2.62 × 1.18) in Bristol Bay. The mean and range of counts made in 2016 is similar to those in 2004 and 2005 suggesting that the population growth observed during 1993–2005 has slowed or ceased. The great-est challenge with how belugas are surveyed within Bristol Bay is the difficulty in counting large groups. Separate counts of large groups had high variance and we suggest future surveys consider photo-documenting groups to determine if groups of belugas can be counted more consistently or using video to adjust for beluga behavior in real-time.
Species composition, population dynamics, and assessment of biopesticide application on thrips (Thysanoptera) in Sacred lotus Nelumbo nucifera Gaertn.

Species composition and population dynamics of thrips in sacred lotus, Nelumbo nucifera Gaertn, were examined in natural and cultivated areas. The results indicated that three species of thrips ( Scirtothrips dorsalis Hood, Selenothrips rubrocinctus (Giard) and Frankliniella schultzei (Trybom)) were present on various parts of the plant. S. dorsalis had the widest niche breadth; it was the predominant species and was more abundant in cultivated area than in natural areas. The abundance was related to seasonal variations and farmer’s practices. Three biopesticides, namely wood vinegar, azadiractin, and the entomopathogenic fungus Beauvaria bassiana , were experimentally found to reduce S. dorsalis on lotus. The efficiency against S. dorsalis of imidacloprid was not significantly different from that of wood vinegar. The value of Shannon-Wiener diversity index was lower than in the other treatments, but Simpson’s index indicated that diversity of the aquatic organism after wood vinegar treatment was highest. Although the efficiency of biopesticides and chemical control did not differ much, from biodiversity perspective the biopesticides are easily biodegradable and do not cause resistance build-up among the pests. Therefore, biopesticides, such as wood vinegar, are alternative methods for thrip control in
Reduction of transverse corner cracks in Tata Steel’s Direct Sheet Plant in Ijmuiden

In the thin slab casting and rolling plant in Tata Steel in IJmuiden, breakouts and quality issues occurred due to the occurrence of transverse corner cracks. Transverse corner cracks are thought to originate during the casting process and become apparent in the slab and in the hot rolled coil. In order to tackle the problem a multi-fold approach was used. Analysis of breakout shells indicated an insufficient shell lubrication. Trials with adapted mould oscillation practice were conducted to control crack formation. The different mould oscillation practices did not result in improved corner crack performance. Mould measurements showed that the liquid mould slag layer was sometimes very thin. An alternative mould powder with reduced free carbon content was tested, leading to improved slag infiltration and a reduction in breakouts due to corner cracks. In the product mix, both low carbon and high strength low alloyed (HSLA) steel grades show a large percentage of transverse corner cracks, making the solution direction difficult. A thermomechanical study was done to verify in what temperature range the onset of nitride and carbide precipitation occurred, which was linked to the crack sensitive temperature region in secondary cooling. With an FEM model, the slab temperatures in secondary cooling were calculated. It was shown that the cooling of the slab corners was too high, leading to cold corners in the bending points. Adaptations were made to the upper secondary cooling segment to reduce cooling of the corners, which resulted in hotter slab corners at caster exit. Additional data analysis showed that next to casting parameters, also rolling mill parameters play a significant role in the corner crack performance. Especially the edger draft proved to be an important parameter. Successful trials were started with increased edger draft, which lead to improved corner crack performance.
Isolation and screening of extracellular lipase- 2 producing endophytic fungi from Handroanthus 3 impetiginosus 4

15 Aims: This study aimed to screen extracellular lipase-producing endophytic fungi isolated from Handroanthus impetiginosus ( H. impetiginosus ). Study design: Endophytic fungi were isolated and screened for extracellular lipase production. The best strains obtained were tested for lipase production, via submerged fermentation, using two different carbon sources. Place Study: Chemistry, of Alfenas, between June 2016 and December 2017. Methodology: Healthy and mature leaves were collected from H. impetiginosus in Alfenas/Minas Gerais, Brazil. Endophytic fungi were isolated from leaves by following standard microbiological methods. All isolated fungi (122) were used in the screening for potential lipase production. Submerged fermentation cultivations, using two different carbon sources, were carried out based on the previous screening results obtained. The best lipase-producing endophytic fungus was identified using molecular biology techniques. The produced lipase by submerged fermentation was purified by organic solvent precipitation and characterized by SDS-PAGE analysis. Results: A total of 122 isolates of endophytic fungi were obtained. Two isolated fungi showed high lipase activity in the plate screening and were chosen for submerged fermentation cultivations using glucose and cottonseed oil as carbon sources. A maximum lipase activity of 5.9 U/mL was obtained for one strain after 48 h of fermentation for the culture medium using cottonseed oil as carbon source. This strain was genetically identified as Preussia africana . A single protein band with an apparent molecular mass of 64 kDa was detected by SDS-PAGE analysis after lipase purification (purification factor of 18.5). Conclusion: A potential microorganism, able to produce an extracellular lipase in submerged fermentation, was isolated from H. impetiginosus . To date, this is the first report of extracellular lipase production by Preussia africana . The potential for this new lipase should be evaluated through a full characterization of these lipase properties in further studies.
Automatically Generating Java Benchmarks with Known Errors

With the constant increase in code development, testing has become essential. Because of the higher cost of dynamic testing, static testing is preferred. One of the existing techniques is using static analyzers. These can be tested by using benchmarks. However, generating benchmarks that expose a particular type of issue can be time-consuming if the developers of static analyzers write these benchmarks manually. In this thesis, we present a technique to automate the process of generating valid benchmark programs in Java for null pointer analysis. Although we instantiate our procedure only for the null pointer analysis, the approach is also suited for generalization to other types of static analysis. Moreover, we explore ways to ensure the quality of the generated benchmarks by defining our own lightweight definition of equivalence between programs. Unlike the already existing published papers and archives that describe solutions related to the generation of valid benchmark programs in Java, we focus on a solution that does not require significant human effort to be used in practice.
Machine Learning Software for Automated Satellite Telemetry Monitoring

During the lifetime of a satellite malfunctions may occur. Unexpected behaviour are monitored using sensors all over the satellite. The telemetry values are then sent to Earth and analysed seeking for anomalies. These anomalies could be detected by humans, but this is considerably expensive. To lower the costs, machine learning techniques can be applied. In this research many diﬀerent machine learning techniques are tested and compared using satellite telemetry data provided by OHB System AG. The fact that the anomalies are collective, together with some data properties, is exploited to improve the performances of the machine learning algorithms. Since the data comes from a real spacecraft, it presents some defects. The data covers in fact a small time-lapse and does not present critical anomalies due to the spacecraft healthiness. Some steps are then taken to improve the evaluation of the algorithms.