Miracle-dz/UniFAR-FTUs huggingface dataset:
Cooperative Learning in Extension of Participatory Agriculture Nataliningsih

Cooperative learning or the learning of mutual cooperation is one method of learning is done by dividing the responsibility to work together on the task in achieving its objectives. Cooperative learning in formal learning activities is often implemented in study groups or lab, but in non-formal learning activities, especially agricultural extension has not been done, therefore it is necessary to study the implementation of cooperative learning in participatory agricultural extension. The method used is a qualitative approach, by taking purposively, research carried out in Pangalengan, West Java, Indonesia, in potato cultivation farmer groups. Conclusion of The study shows agricultural extension participatory process followed by cooperative learning method produces learning activities that fit their needs and fully followed by all participants of extension. The behaviors transformation after counseling showed 6 (54.54%) said it will produce revenue in the processing chips of potato. The improvement of potato chips is 69.74% in each production. Suggestions submitted to potato farming communities, namely potato chips processing technology to increase revenue, need further development to large-scale production processes with better technology. Keywords— Cooperative learning; non-formal education participation method; change in attitude; increased revenue, agriculture extension
Using object-oriented image analysis to map and monitor land cover change in the Region Costa Maya, México: 1993-2010

espanolLa informacion espacio-temporal multiple, precisa, rentable y pertinente sobre los cambios en la cobertura del suelo es fundamental para el mejor manejo del medio ambiente. De esta forma, en este estudio se aplico la segmentacion y clasificacion orientada a objetos a las imagenes de Landsat TM /ETM + para mapear la cobertura del suelo en la Region Costa Maya, de 1993, 2000 y 2010. Se obtuvo una precision global de mapeo del mapa del ano 2000 de 94,32% (ĸ= 0.9141). Para caracterizar las tasas y los patrones espacio-temporales de cambio en la cobertura terrestre, se aplico la comparacion en post-clasificacion, utilizando tabulaciones cruzadas de tres mapas, posteriormente generados, para inferir los principales procesos de cambios durante 17 anos. Los resultados revelaron una rapida urbanizacion, el abandono de tierras agricolas (transicion forestal) y la destruccion de los manglares, mediado por factores socio-economicos vinculados al desarrollo del turismo, como los principales impulsores del cambio, con graves implicaciones sobre la sostenibilidad del medio ambiente en la Costa Maya. El estudio ha confirmado el valor de la segmentacion y clasificacion orientadas a objetos en el mapeo y monitoreo del cambio de cobertura terrestre a escala regional. EnglishAccurate, cost effective and timely multiple spatial-temporal information on the patterns of land cover change is crucial for environmental management and understanding. For this reason, segmentation and object-oriented classification was applied to Landsat TM/ ETM+ imagery to map and monitor land cover dynamics in the Region Costa Maya (RCM) in 1993, 2000 and 2010. Overall mapping accuracy for land-cover map in 2000 was 94.29% (ĸ= 0.9141). Post-classification approach, involving cross tabulation of three generated maps, was used to characterize spatial temporal rates and patterns of land cover change to infer major processes of changes over 17 years. Results revealed rapid urbanization, agricultural land abandonment (forest transition) and destruction of mangrove forests, mediated by socio-economic factors linked to tourism development as the leading drivers of land cover change, with grave implications on environmental sustainability in the Costa Maya area. The study has confirmed the value of segmentation and object-oriented classification for mapping and monitoring land cover change at regional scale.
Continued use of e-learning technology in higher education: a managerial perspective

ABSTRACT This paper develops a managerial-influence perspective in the context of e-learning technology in higher education. Drawing on principal-agent theory and the information systems (IS) continuance model, a new research model is developed and tested. The study finds support for the effects of goal congruence between managers and educators and managerial incentives on educators’ intention to continue using e-learning technology. Additionally, the results show that managerial goal congruence reduces the positive relationship between incentives and educators’ continuance intention. While the IS continuance model demonstrates an explained variance of 27%, the full model explains 47% of the dependent variable's variance, indicating that the extended model is more powerful in explaining educators’ e-learning continuance than the IS continuance model in isolation. By modifying and extending the IS continuance model, this paper fills a gap in the literature by addressing educators’ continued use of IS from a personal-use perspective, as well as a managerial-influence perspective.
ALGORITHMS APPLIED IN AUTONOMOUS VEHICLE SYSTEMS

Many research centres in the world that deal with the problems of the manufacture of land vehicles, especially those intended for transport and communication in urban traffic, are still working on the development of a vehicle equipped with systems that do not require human participation in the process of driving a vehicle. The goals to be pursued are to ensure maximum safety (minimize accidents involving people) and to optimize transport costs (eliminating the driver from the vehicle, optimal route selection). This article, which is the result of broad studies conducted at OBRUM, discusses the development paths of autonomous vehicles and key algorithms of autonomous vehicles described in detail in the literature cited. The presented results constitute a starting point for further work on an autonomous vehicle to be carried out at OBRUM.
Android application security: detecting Android malware and evaluating anti-malware software

Mobile devices have become widespread computing technology, people prefer to use than desktop devices. These connected devices and their features like an exchange of data, video calling etc. have made our lives simple but, this has also increased data security concerns. At present, Google's Android is dominating the market share of mobile devices; as a result, it has become a big target for malware writers. Android users can download applications from official or third-party stores. Google implements various security policies to ensure secure distribution of applications but third-party application stores have less efficient or no such policies. This makes such markets more attractive for malware writers. This paper investigates Android application security by analysing 1,946 free most downloaded Android applications in the year 2016: 1,300 from Google Play Store and 646 from third-party Android applications. 100 samples from 33 different malware families (with variants) prominent in the Android market during January 2016 to April 2016 were also collected that acted as a template for malware detection. Further, based on detected malware samples, an evaluation-based study on ten anti-malware applications is performed to identify how well they protect users from malware.
Tempt a Saint ? Evidence from the Schengen Acquise on Crime Rates in German Border Regions

The abolishment of passport and any other type of border controls at the German-Polish and German-Czech border in December 2007 provoked public concerns that open borders would increase cross-border crime. Despite these widespread concerns, empirical research on whether public fears are justified is still scarce. Based on official data on reported crimes from the German Police Crime Statistics, this essay evaluates whether the implementation of the Schengen Acquise in Poland and the Czech Republic in December 2007 increased crime rates in German counties (Landkreise) that share a border with one of these two countries. Conditional difference-in-difference estimation allows the evaluation of the Schengen effects in a causal way. Results show that no significant Schengen effect can be observed for overall crime rates as well as for most types of criminal offenses. Only for burglaries can a significant positive effect be observed. This suggests that for this type of criminal offense, public concerns proved to be justified. In contrast, for overall crime rates as well as for common types of crime against poverty no significant effect can be observed, indicating that there is only little empirical evidence for the widespread concerns about public security.
The contingent effect of work roles on brokerage in professional organizations

Abstract In this paper, we consider whether brokerage in an intra-organizational communication network and type of work role interact to predict individual performance in a professional organization. The independent–interdependent nature of work roles is considered a key factor in structural contingency theory, but is yet to be studied in relation to brokerage. We propose that a brokerage position has a joint effect on performance along with work role in a study of organization-wide communication network in an architectural firm with 65 employees. Our analysis suggests an association between brokerage and role-prescribed performance for individuals in both interdependent and independent types of work roles. Our findings also suggest that interdependent roles requiring broad, organization-wide collaboration, and communication with others, brokerage is positively associated with the performance prescribed by the role, but for independent roles, wherein collaboration and communication are somewhat limited by the formal role, brokerage has far less of an effect. Our findings contribute to brokerage theory by comparing how brokerage affects performance in two distinct work roles by illustrating how the benefits of brokerage seem more restricted to those in interdependent work roles. The contribution of this paper is to suggest the independent–interdependent nature of work role as a boundary condition for brokerage.
BREEDING DROUGHT RESISTANCE IN FIG VIA CONTROLLED HYBRIDIZATION

This study as a part of a fig drought tolerance breeding program, was conducted to evaluate the effects of pollen sources and maternal plants on drought tolerance of first generation seedlings. Three Iranian cultivars were selected as maternal plants from hot dry lands of central Iran and cross pollinated with four Iranian caprifigs. The offsprings were subjected to drought stress by stopping irrigation for 15 days and reirrigated for 10 days to screen drought tolerance. The results indicated hybrids 1, 7, 8, 9 and 11 were able to preserve water status and growth rate at higher levels during the water stress period. These hybrids were able to accumulate higher concentrations of proline and soluble carbohydrates for osmoregulation and prevent structural damages under water stress. It was concluded that drought tolerance in fig offsprings is highly related to drought tolerance of their parents, and using a highly drought tolerant parent in controlled pollinations may result in a drought tolerant hybrid. Hence, using caprifig ‘Khormaei’ as paternal parent and fig ‘Siah’ or ‘Sabz’ as maternal parent in controlled pollinations to obtain drought tolerant fig hybrids was suggested.
The taxman cometh: A virtuous cycle of compliance and state legitimacy in the D.R. Congo

How do states in a low-tax, low-capacity equilibrium spur citizens to start paying taxes? Public-finance models hinge on citizen perceptions of enforcement, while political scientists emphasize the legitimacy of the state in generating voluntary compliance. This paper examines the determinants of payment in the first-ever citizen property tax campaign in a large Congolese city that raised average compliance from 0% to 10%. Aside from ability to pay, prior beliefs about the legitimacy of the provincial government are the strongest predictor of tax payment. Legitimacy is itself influenced by tax collectors’ identities: tax compliance is higher when collectors work in the areas in which they live; minority ethnic citizens are more likely to pay to minority ethnic collectors. Further, on average the tax campaign leads individuals to update positively about the legitimacy of the provincial government, indicating a positive feedback loop of state building and citizen tax compliance.
Enhancement of Power Harvesting by Tuning Moment of Inertia

This investigation examines the design of an innovative independent mechanism for tuning the resonant frequency and thus generate greater amounts of energy. The proposed concept is based on adjusting the resonant frequency by automatically modifying the mass moment of inertia. A frequency tuning algorithm is used to maintain the system in the case of resonant continuously, and that by change the proof mass position within the tuning range. The electromagnetic energy harvester is used to convert the vibration energy into electrical energy. The proposed design is analyzed using the methodology of approximate single degree of freedom system to study the effect of the mass position on Eigen-frequency and also to determine the response of the system as well as the harvested power. Analytical results were confirmed and verified to high accuracy with laboratory results. It is worth mentioning that this proposed design is suitable for low frequencies and can be considered as a good step towards the production of autonomous energy harvesters.
Tilburg University Modeling Comovements in Trading Intensities to Distinguish Sector and Stock Specific

In this paper we propose a bivariate model for the trading intensities of stocks in a particular industry. The model consists of a univariate duration model for trades in either of the stocks and a probit-specification for which of the two stocks is traded. We apply the model to the trading intensities of stocks of US department store operators listed on the NYSE, using high frequency transaction data during the period August 1 until October 31, 1999. We establish significant comovements in the trading intensities of US department stocks, which we explain by distinguishing sector and stock specific news contained in the trading intensities. We provide estimates of the amounts of sector and stock specific news contained in the trading intensities and show that all stocks under consideration convey both sector and stock specific news.
Enactment of Ensemble Learning for Review Spam Detection on Selected Features

review spam. This study aims to evaluate the performance of ensemble learning on review spam detection with selected features extracted from real and semi-real-life datasets. We study various performance metrics including Precision, Recall, F-Measure, and Receiver Operating Characteristic (RoC). Our proposed ensemble learning module (ELM) with ChiSquared feature selection technique outperformed all others with 0.851 Precision.
A Machine Learning-Based Fast-Forward Solver for Ground Penetrating Radar With Application to Full-Waveform Inversion

The simulation, or forward modeling, of ground penetrating radar (GPR) is becoming a more frequently used approach to facilitate the interpretation of complex real GPR data, and as an essential component of full-waveform inversion (FWI). However, general full-wave 3-D electromagnetic (EM) solvers, such as the ones based on the finite-difference time-domain (FDTD) method, are still computationally demanding for simulating realistic GPR problems. We have developed a novel near-real-time, forward modeling approach for GPR that is based on a machine learning (ML) architecture. The ML framework uses an innovative training method that combines a predictive principal component analysis technique, a detailed model of the GPR transducer, and a large data set of modeled GPR responses from our FDTD simulation software. The ML-based forward solver is parameterized for a specific GPR application, but the framework can be applied to many different classes of GPR problems. To demonstrate the novelty and computational efficiency of our ML-based GPR forward solver, we used it to carry out FWI for a common infrastructure assessment application—determining the location and diameter of reinforcement bars in concrete. We tested our FWI with synthetic and real data and found a good level of accuracy in determining the rebar location, size, and surrounding material properties from both data sets. The combination of the near-real-time computation, which is orders of magnitude less than what is achievable by traditional full-wave 3-D EM solvers, and the accuracy of our ML-based forward model is a significant step toward commercially viable applications of FWI of GPR.
Influence on Kerf Width in Machining Polystyrene by Heating Element Profile Maker using Nichrome Wire

Heating element profile maker is a designed on the basis of the non-traditional machining process. This paper represents the investigation on the effect and optimization of machining parameters on the kerf width and material removal rate. The experimental studies were conducted under varying current keeping voltage constant. The electric power transmitted to the wire is modulated to keep the wire temperature constant. Since the feed rate and kerf width both directly depends upon the wire temperature.
A Study of the Graduate Theses on Distance Learning Administration in Turkey from 1999 to 2019

This study covers 117 masters and 28 doctorate theses published between 1999-2019 in Turkey for a total of 145 theses on distance learning administration. Due to the goal of analyzing graduate theses published in the field of distance learning administration in Turkey between the years of 1999-2019, qualitative research method was used in this study. The distribution of subjects within these theses was found to focus on 6 main themes. These themes, in decreasing frequency, were services required by distance education institutions, analysis – evaluation studies, factors influencing distance education services, issues encountered in distance learning administration, recommendation studies, and comparative studies. The policy recommendations of research in distance learning administration focused on three categories. These categories, in decreasing frequency order, were policy recommendations towards services required by distance education institutions, policy recommendations regarding factors influencing distance education services, and policy recommendations regarding issues faced in distance learning administration. No other research, evaluating the research on distance learning administration in Turkey along with the policy recommendations made by these studies was encountered in the literature review. The other findings of this study are presented in a discussion regarding the findings of other studies in the literature.
Antioxidant Capacity of a Bee Pollen Sample Obtained from Giresun, Turkey

This study was related to evaluating the antioxidant of one pollen sample which was collected from Giresun, Turkey. The antioxidant properties of this sample were determined to use total phenolic contents (TPCs), total flavonoid contents (TFCs), proanthocyanidin contents (PCs), and ferric reducing antioxidant power (FRAP) assays. The mean of the total phenolic content was 6.33±0.11 mg GAE/ g sample, total flavonoid content was 1.88±0.11 mg QE/g sample, proanthocyanidin content was 0.86±0.00 mg CE/g sample, FRAP was also 72.38±0.21 µmoL FeSO4.7H2O/g, respectively. The obtaining results revealed that the pollen could be seen as a valuable natural source thanks to its significant antioxidant capacity.
Virtual Synchronous Generator Based Current Synchronous Detection Scheme for a Virtual Inertia Emulation in SmartGrids

Renewable energy sources, such as photovoltaic wind turbines, and wave power converters, use power converters to connect to the grid which causes a loss in rotational inertia. The attempt to meet the increasing energy demand means that the interest for the integration of renewable energy sources in the existing power system is growing, but such integration poses challenges to the operating stability. Power converters play a major role in the evolution of power system towards SmartGrids, by regulating as virtual synchronous generators. The concept of virtual synchronous generators requires an energy storage system with power converters to emulate virtual inertia similar to the dynamics of traditional synchronous generators. In this paper, a dynamic droop control for the estimation of fundamental reference sources is implemented in the control loop of the converter, including active and reactive power components acting as a mechanical input to the virtual synchronous generator and the virtual excitation controller. An inertia coefficient and a droop coefficient are implemented in the control loop. The proposed controller uses a current synchronous detection scheme to emulate a virtual inertia from the virtual synchronous generators. In this study, a wave energy converter as the power source is used and a power management of virtual synchronous generators to control the frequency deviation and the terminal voltage is implemented. The dynamic control scheme based on a current synchronous detection scheme is presented in detail with a power management control. Finally, we carried out numerical simulations and verified the scheme through the experimental results in a microgrid structure.
Adaptive Bitrate Video Transmission Over Cognitive Radio Networks Using Cross Layer Routing Approach

Due to the recent developments in the wireless mesh and ad-hoc networks, multi-hop cognitive radio networks (MCRNs) have attained the significant attention towards providing the reliable multimedia communications. However, in reliable multimedia communications each multimedia application observed a very stringent quality-of-service (QoS) requirements. Moreover, in MCRNs, channel allocated to the multimedia secondary users (MSUs) can be re-occupied by the primary users (PUs) at any time which causes the end-to-end path discontinuity that severely affect the performance of the MCRNs. Therefore, under the dynamic channel availability, selecting an end-to-end path that is not only stable but also fulfills the QoS requirements of the real time and multimedia (RM) applications is a challenging task and still an open research problem. Hence, in this paper, we propose a cross-layer routing scheme that supports adaptive bit-rate multimedia (ABM) transmissions over MCRNs. Moreover, our path selection is based on the QoS-aware end-to-end path delay, and PU-activity aware end-to-end path stability metrices. Furthermore, to avoid the PU interference, continuity in transmission, efficient channel utilization, and supporting error resilience over time varying wireless channels our selected end-to-end path is periodically updated. Simulation study shows that the proposed scheme is more robust and suitable for supporting ABM over MCRNs.