Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection and Operation of Unintentional Islands in the Presence of Distributed Generation Units

The complexities and challenges for reliable operation of power system have increased due to various types of Distributed Generators (DG) in the Distribution Network (DN) to supply the increasing load demand. It necessitates a comprehensive approach in planning the system towards effective and reliable operation of the system. During the operation of the system, detection of unintentional islanding is critical as non-detection of islanding event could lead to cascaded failure of the system due to active or reactive power imbalance leading to frequency, angle or voltage instability. If undetected, the instability in the islanded part can cascade into the stable part of the system resulting in complete failure of the system. A robust Modified Islanding Detection Technique (MIDT) has been proposed for identifying the islanding event early and accurately in the distribution networks with DGs installed for multiple objectives and is compared with existing passive Islanding Detection Techniques (IDT). A rank-based load shedding scheme is proposed for stable and reliable operation of the identified island, which sheds only the most vulnerable loads in the island for regaining the frequency and voltage stabilities. The proposed MIDT and rank based load shedding schemes were tested on 11kV IEEE 118 Bus Test system.
Innovations in the Content of Professional Training of Interpreters and Translators in Countries of Europe, the USA and Ukraine: Comparative Analysis

The article deals with the analysis of innovations in the content of professional training of interpreters / translators at universities of Europe, the USA and Ukraine. It has been established that at European and American universities the innovation data involves directing professional education of translators and interpreters towards studying CAT-systems within the context of traditional disciplines, specialized disciplines, extracurricular courses, trainings and in the process of students’ translation/interpretation traineeship and study placement. Based on the comparative analysis of the curricula for specialists’ training in translation/interpretation in European countries, the USA and Ukraine, the conclusion is drawn that in higher education of Ukraine theoretical training traditionally prevails over practical field experience, general classroom hours are not sufficient for students, while Ukrainian universities’ curricula lack disciplines aimed at the formation of technological (information, computer) expertise of prospective interpreters and translators. The authors of the article recommend using the experience of western universities on implementing innovations within the content of professional training of interpreters and translators at Ukrainian universities, namely: a) increasing the number of classroom activity hours in practical training of interpretation/translation students by means of reducing extracurricular hours; b) changing the ratio of disciplines of theoretical and practical training of future interpreters and translators in favour of the latter by decreasing the number of theoretical subjects; c) including disciplines aimed at the formation of prospective experts’ information competency into the curricula; d) providing both short-term and long-term traineeship in interpreter/translator training programs, preferably at international organizations (enterprises) operating in Ukraine or at foreign companies abroad; e) providing specialization of professional training of interpreters and translators (technical translation, legal translation, economic translation, medical translation, literary translation, etc.).
Financial bootstrapping: external financing dependency alternatives for SMEs

The sensitivity of external financing is the main issue in developing small and medium-sized enterprises (SME) in general. A similar problem is also experienced by several batik small and medium enterprises in Central Java, Indonesia. This research strives to explore the creative alternative strategies done by batik micro, small, and medium enterprises to reduce the dependence on external capital. The samples were chosen based on a purposive sampling method in three Central Java regions, namely Pekalongan Regency, Rembang Regency, and Surakarta Municipality. The data were then analyzed using a quantitative and qualitative descriptive approach. These research findings reveal that there are variations in the bootstrapping financing method; as well as financing profiles of each in the three regions that reveal the dynamics of business funding. Referring to the description of alternative funding patterns carried out by entrepreneurs, the bootstrapping strategy can be grouped into six (6) types based on the available resources. Batik entrepreneurs can overcome their financial problem by applying bootstrapping methods, so that businesses can operate properly.
Editorial - Implementing online learning: Stories from the field

After more than two decades of online learning in Australian higher education, the provision of online programs has moved closer to the mainstream in many Australian universities. According to the IBISWorld (2018), online education in Australia is booming with expected growth in revenue from online learning of 3.6% in 2018, making it a $5 billion industry. In 2018, more than 20 Australian Universities offered some form of online classes and least six Australian universities have launched large-scale online learning initiatives in recent years. To support these initiatives, there is increasing emphasis on good practice in online teaching and learning. Once seen as fringe activity or niche innovation, online learning has been increasingly central to universities’ responses to changed revenue streams and efforts to open and cater to new markets.
Using reliable and surprising item sets for the characterization of protein-protein interfaces

Numerous research effort have aimed to characterize and predict protein-protein interfaces. This paper introduces a method that rely only on known protein-protein interfaces (positive instances only). It combines frequent item set mining techniques with statistical tests to ensure the selection of interesting features. Starting from a database of known interfaces described with geometrical elements, the method produces the elements and combinations thereof that are emphcharacteristic of the interfaces. This approach allows one to easily interpret the results, as compared to techniques that operate as ``black-boxes’’ and ensures a satisfactory proportion of reliable item sets. The results obtained on a set of 459 protein-protein interfaces from the DOCKGROUND database confirm that the findings are consistent with current knowledge about protein-protein interfaces.
Social reproduction, gender equality and economic growth

This paper presents a conceptual Kaleckian macroeconomic model and principal component analysis that link structures of economic growth and development with those of social reproduction and gender inequality. Employment, output and long-run prospects for growth are driven by class dynamics as well as social reproduction, defined as the time and money it takes to produce, maintain and invest in the labour force. How social reproduction is organised—the extent to which reproduction takes place in the household, public or market sectors, and the gender distribution of the labour in each—influences current aggregate demand and long-run productivity growth. Based on this model, and using data for a panel of 156 countries between 1991 and 2015, the paper presents empirical estimates of social reproduction regime by country and region, identifying under what circumstances systems of growth on the one hand and social reproduction on the other reinforce or contradict one another.
Neural assemblies as core elements for modeling neural networks in the brain

How does the brain process and memorize information? We all know that the neuron (also known as nerve cell) is the processing unit in the brain. But how do neurons work together in networks? The connectivity structure of neural networks plays an important role in information processing. Therefore, it is worthwhile to investigate modeling of neural networks. Experiments extract different kinds of datasets (ranging from pair-wise connectivity to membrane potential of individual neurons) and provide an understanding of neuronal activity. However, due to technical limitations of experiments, and complexity and variety of neural architectures, the experimental datasets do not yield a model of neural networks on their own. Roughly speaking, the experimental datasets are not enough for modeling neural networks. Therefore, in addition to these datasets, we have to utilize assumptions, hand-tuned features, parameter tuning and heuristic methods for modeling networks. In this thesis, we present different models of neural networks that are able to produce several behaviors observed in mammalian brain and cell cultures, e.g., up-state/down-state oscillations, different stimulus-evoked responses of cortical layers, activity propagation with tunable speed and several activity patterns of mice barrel cortex. An element which is embedded in all of these models is a network feature called neural assembly. A neural assembly is a group (also called population) of neurons with dense recurrent connectivity and strong internal synaptic weights. We study the dynamics of neural assemblies using analytical approaches and computer simulations. We show that network models containing assemblies exhibit dynamics similar to activity observed in the brain.
High-resolution hyperspectral ground mapping for robotic vision

Recently released hyperspectral cameras use large, mosaiced filter patterns to capture different ranges of the light’s spectrum in each of the camera’s pixels. Spectral information is sparse, as it is not fully available in each location. We propose an online method that avoids explicit demosaicing of camera images by fusing raw, unprocessed, hyperspectral camera frames inside an ego-centric ground surface map. It is represented as a multilayer heightmap data structure, whose geometry is estimated by combining a visual odometry system with either dense 3D reconstruction or 3D laser data. We use a publicly available dataset to show that our approach is capable of constructing an accurate hyperspectral representation of the surface surrounding the vehicle. We show that in many cases our approach increases spatial resolution over a demosaicing approach, while providing the same amount of spectral information.
Improving the efficiency and capabilities of document structuring

Natural language generation (NLG), the problem of creating humanreadable documents by computer, is one of the major fields of research in computational linguistics. The task of creating a document is extremely common in many fields of activity. Accordingly, there are many potential applications for NLG almost any document creation task could potentially be automated by an NLG system. Advanced forms of NLG could also be used to generate a document in multiple languages, or as an output interface for other programs, which might ordinarily produce a less-manageable collection of data. They may also be able to create documents tailored to the needs of individual users. This thesis deals with document structure, a recent theory which describes those aspects of a document’s layout which affect its meaning. As well as its theoretical interest, it is a useful intermediate representation in the process of NLG. There is a well-defined process for generating a document structure using constraint programming. We show how this process can be made considerably more efficient. This in turn allows us to extend
Methods Based on Spatial Processes

We present methods of cluster analysis to identify and classify patterns which are formed by stationary point processes and used e.g. in the modeling of human cartilage cells. In particular, we consider a generalization of the single-linkage approach which has been appropriately adapted to deal with inhomogeneous data and describe how the random-forest methodology can be applied to the classification of the previously identified clusters. Furthermore, we show how statistical techniques for spatial point processes can be used to validate the methods of cluster identification and cluster classification considered in this chapter.
OBJECT LOCALIZATION FOR SUBSEQUENT UAV TRACKING

Abstract. The paper is devoted to the problem of semi-automatic initialization of the tracking algorithm, i.e. selecting an object of interest by unmanned aerial vehicles or drones. In this work, we propose an algorithm to refine the position and dimensions of the boundary box of the tracked object at the initial time (on the first frame), based on saliency detection algorithm, which simulates the map of human attention. We tested existing algorithms for object tracking by UAVs on the largest and most complex dataset – UAV 123. It is shown that the quality of tracking as a result of initialization by the proposed algorithm varies within acceptable limits for successful tracking of the object. The advantage of the proposed approach is that it applies the principles, used by the human visual system: the color, contrast, central focus.
Framing the Flint Water Crisis: Interrogating Local Nonprofit Sector Responses

The Flint Water Crisis captured the attention of the world in January 2016 when both the state and federal governments declared a public health emergency in Flint, MI. Building on framing theory, we look to both the theory of casual stories and critical intersectionality to explain both how and why local grassroots associations (GAs) and high-capacity nonprofits (HCNPs) differed in their rhetorical responses to the crisis. Interviews, speeches, and op-eds published from both groups between May 2014 and May 2017 were analyzed using qualitative content analysis. We find that, while all spoke in terms of helping the community recover from the crisis, the narratives surrounding the crisis unfolded along two distinct paths—one focusing on the technical responses and moving forward, while the other focused on identifying root causes and calling for intersectional solutions.
Considering Network Effects in the Design and Analysis of Field Experiments on State Legislatures

Recent work on legislative politics has documented complex patterns of interaction and collaboration through the lens of network analysis. In a largely separate vein of research, the field experiment—with many applications in state legislatures—has emerged as an important approach in establishing causal identification in the study of legislative politics. The stable unit treatment value assumption (SUTVA)—the assumption that a unit’s outcome is unaffected by other units’ treatment statuses—is required in conventional approaches to causal inference with experiments. When SUTVA is violated via networked social interaction, treatment effects spread to control units through the network structure. We review recently developed methods that can be used to account for interference in the analysis of data from field experiments on state legislatures. The methods we review require the researcher to specify a spillover model, according to which legislators influence each other, and specify the network through which spillover occurs. We discuss these and other specification steps in detail. We find mixed evidence for spillover effects in data from two previously published field experiments. Our replication analyses illustrate how researchers can use recently developed methods to test for interference effects, and support the case for considering interference effects in experiments on state legislatures.
Business Cycles and Admissions to Substance Abuse Treatment

We study the effect of business cycles on admissions to specialty substance abuse treatment using administrative data between 1992 and 2015. We proxy business cycles with the state unemployment rate and apply a panel fixed&#8208;effects model. While previous economic research has shown that substance abuse is counter&#8208;cyclical, we observe no change in the total number of admissions across the business cycle. However, focusing on average effects misses important heterogeneity. In substance&#8208;specific regressions we find statistically significant evidence that heroin&#8208;related admissions are counter&#8208;cyclical while stimulant&#8208;related admissions are procyclical. Our findings add to the literature on business cycles and health.
Zakupy online - wybrane aspekty związane z decyzjami klientów

Rozwoj technologii informacyjnych i komunikacyjnych, a w szczegolności rozwoj Internetu, wplynąl znacząco na funkcjonowanie i prowadzenie dzialalności wielu organizacji. Od lat obserwowany jest rozwoj handlu elektronicznego, w ktorym wystepują rozne formy relacji miedzy dostawcami a klientami. Kreowanie nowych form wspolpracy i realizowanie dzialan gospodarczych, spolecznych i ekonomicznych wplywa na zachowanie klientow oraz determinuje ich postepowanie. Celem niniejszego opracowania jest scharakteryzowanie wybranych aspektow związanych z dokonywaniem zakupu towarow i uslug online. Zaprezentowano wyniki badan autorskich związanych z podejmowaniem decyzji o zakupie towarow i uslug online.
COMPARISON OF TYPE OF THE MEDIA USED FOR TRANSFER AND CONTENT BEING READ AND USED IN HIGH SCHOOL ENVIRONMENT

The goal of this paper is to determine the relationship of the channel of information transmission in comparison to the art of information and the age of information recipients to establish the proper channel for dissemination of learning materials. For this purpose, we used a survey as a research method. The questionnaire was conducted under the title "Comparison of media transfer and content being read". We first divided the respondents by gender, and then by age. The pre-examination conducted before the survey has demonstrated that having three age groups is sufficient for the analysis. Furthermore, the use of the media has been investigated with three forms of written works: literary works (novels), newspapers/magazines/journals, and ultimately, scientific literature. We present the distribution of the ownership of the type of media transfer. The ownership of the printing media means a subscription to newspapers or permanent lending (membership) in libraries. We noticed the lack of usage of electronic readers, with even fewer respondents relying on printed material. There is also a 100% possession of cell phones/tablets and almost the same percentage for computer ownership. We paid special attention to the choice of the type of media transfer. E-readers such as Kindle were used very rarely. Printed media make up for 21% of all media, which is also showing the reducing trend of usage of printed media. On the other hand, computers and mobile phones (tablets) have an equal share in the usage of transfer media. This was also expected. Interestingly, none of the respondents, even those who possess ereaders, have chosen this medium as their choice for usage in media transfer if they have to select just one. The analysis according to the age groups is showing interesting indications. Younger respondents are turning to modern transfer media, and are replacing paper media with a cell phone or tablet, while the older age groups are continuing to use printed media. It is very interesting that, regardless of age, all respondents equally embraced the computer as a media transfer for information. In the distribution according to the sex of respondents, the female respondents report significantly larger usage of printed media than mobile media comparing to male respondents. In further analysis, the research will focus on the relationship between the channel of information transmission in comparison to the art of information. Those finding will determine the methodology for preparing learning materials for our students and will be compared with adult learner habits predicted by a contemporary andrologist.
Review Paper: Sarcasm Detection and Observing User Behavioral

Sarcasm is a sort of sentiment where public expresses their negative emotions using positive word within the text. It is very tough for humans to acknowledge. In this way we show the interest in sarcasm detection of social media text, particularly in tweets. In this paper we study new method pattern based approach for sarcasm detection, and also used behavioral modelling approach for effective sarcasm detection by analyzing the content of tweets however by conjoint exploiting the activity traits of users derived from their past activities. By using the various classifiers such as Random Forest, Support Vector Machine (SVM), k Nearest Neighbors (k-NN) and Maximum Entropy, we check the accuracy and performance.
Environmental Management Practices within Agritourism Boarding Houses in Romania: A Qualitative Study Among Managers

Small accommodation businesses such as agritourism boarding houses (ATBHs) provide a large share of accommodating capacity in certain rural destinations. Despite their small accommodation capacity, ATBHs consume substantial quantities of water and energy; this consumption implies high environmental costs. The present study aims to explore opinions of ATBH owner-managers regarding water and energy consumption in their businesses, what motivates them to adopt environmental practices, and the specific saving measures used within the tourist accommodation units they manage. A qualitative research was conducted, using semi-structured interviews among 12 Romanian ATBH owner-managers. Data analysis revealed that the interviewed owner-managers understand the importance of natural resource conservation in tourist destinations but they are not willing or have insufficient financial, time, organizational resources, etc. to engage in serious water and energy saving initiatives. Moreover, most interviewed managers indicated that tourists cannot make a significant contribution to natural resources conservation in accommodation units and perceive water and energy saving systems as more effective than the environmental education of visitors in their facility. These findings may be useful to tourism policy-makers and environmental organizations in order to develop effective environmental strategies in ATBHs.
A Pricing-Based Rate Allocation Game in TVWS Backhaul and Access Link for Rural Broadband

The traditional cellular technology is not profitable to serve the sparsely populated and clustered remote rural areas because of huge network set-up cost and lesser return from low density of rural population. To provide broadband service in those remote rural areas, in this paper, we consider a TV white space (TVWS)-based hierarchical network architecture where sparsely located clustered rural pieces of user equipment (UEs) are connected to far-off central base station (CBS) via intermediate TVWS nodes, known as the pieces of customer premises equipment (CPEs) through TVWS link. The CBS has direct broadband connectivity to the Internet through optical fiber backhaul. In such a network architecture, we adopt a two-stage market model among UEs, CPEs, CBS, and propose a pricing-based Stackelberg game to distribute the total available data rate at CBS among CPEs and then to the UE. Extensive simulations have been carried out to study the data-rate distribution, and the behavior of utilities of CPE, CBS, and UE with variation of different parameters for a particular network scenario. The study of the outcome suggests that using this simple price exchange mechanism, it is possible, based on each UE's willingness-to-pay and the total available data rate, to distribute data rate optimally among the UEs where each of the network entities behaves selfishly.