nils-herrmann/clean_scirepeval huggingface dataset:
Combining UAV-imagery and machine learning for wildlife conservation

Semi-arid savannas are endangered by changes in the fragile equilibrium between rainfalls, fires and grazing pressure exerted by wildlife or cattle. To avoid bush encroachment and the decline of perennial grass, land managers must pay attention to keep the amount of cattle and wildlife in balance with the grass availability. In large farms and conservation parks, to estimate the animal populations is therefore an important management aspect. Traditional methods of animal census – such as transect counts from a helicopter, or mark / recapture – are too expensive and laborious to be conducted on a regular basis. In this context unmanned aerial vehicles (UAVs) appear as an interesting tool for animals detection. They can be easily deployed, for lower cost and an increased safety. The drawback is that it is difficult to visually interpret the large number of very high resolution (VHR) images that they acquire. The recent advances in machine learning techniques could allow to automate the detection of animals in these aerial images. This project aims to implementing such algorithms in order to investigate the feasibility and potential benefits of combining machine learning and UAVs for animals detection. This study uses an image dataset acquired in the Kuzikus Wildlife Reserve in Namibia and a ground truth acquired through crowd-sourcing. The machine learning techniques involved include Bags of visual Words, exemplar SVMs and active learning. The promising results show that recall rates in the range of 60 to 80% are possible, if a low precision (5 to 20%) is accepted. The study also discusses parameters related to the data acquisition, such as the image resolution and the time of the day when the images are acquired. Résumé Les savanes semi-arides sont menacées par des changements dans le fragile équilibre entre les pluies, les feux de brousse et la pression pastorale exercée par le bétail et les herbivores sauvages. Afin d'éviter l'avancement des broussailles ligneuses et le déclin des herbes pérennes, les éleveurs et gardiens de parcs doivent être attentifs à maintenir un nombre d'animaux en adéquation avec le fourrage disponible. Ainsi, estimer les populations d'herbivores des grandes fermes et parcs naturels est une étape importante dans la gestion des savanes semi-arides. Les méthodes traditionnelles pour le comptage des animaux – telles que les comptages par transectes ou par marquage et recapture – sont trop chères et trop laborieuses pour être utilisées de façon régulière. Dans ce contexte, les véhicules …
Entity Typing Using Distributional Semantics and DBpedia

Recognising entities in a text and linking them to an external resource is a vital step in creating a structured resource (e.g. a knowledge base) from text. This allows semantic querying over a dataset, for example selecting all politicians or football players. However, traditional named entity recognition systems only distinguish a limited number of entity types (such as Person, Organisation and Location) and entity linking has the limitation that often not all entities found in a text can be linked to a knowledge base. This creates a gap in coverage between what is in the text and what can be annotated with fine grained types. This paper presents an approach to detect entity types using DBpedia type information and distributional semantics. The distributional semantics paradigm assumes that similar words occur in similar contexts. We exploit this by comparing entities with an unknown type to entities for which the type is known and assign the type of the most similar set of entities to the entity with the unknown type. We demonstrate our approach on seven different named entity linking datasets. To the best of our knowledge, our approach is the first to combine word embeddings with external type information for this task. Our results show that this task is challenging but not impossible and performance improves when narrowing the search space by adding more context to the entities in the form of topic information.
Deep Reinforcement Learning for Optimal Control of Space Heating

Classical methods to control heating systems are often marred by suboptimal performance, inability to adapt to dynamic conditions and unreasonable assumptions e.g. existence of building models. This paper presents a novel deep reinforcement learning algorithm which can control space heating in buildings in a computationally efficient manner, and benchmarks it against other known techniques. The proposed algorithm outperforms rule based control by between 5-10% in a simulation environment for a number of price signals. We conclude that, while not optimal, the proposed algorithm offers additional practical advantages such as faster computation times and increased robustness to non-stationarities in building dynamics.
Leakiness and creepiness in app space: perceptions of privacy and mobile app use

Mobile devices are playing an increasingly intimate role in everyday life. However, users can be surprised when informed of the data collection and distribution activities of apps they install. We report on two studies of smartphone users in western European countries, in which users were confronted with app behaviors and their reactions assessed. Users felt their personal space had been violated in "creepy" ways. Using Altman's notions of personal space and territoriality, and Nissenbaum's theory of contextual integrity, we account for these emotional reactions and suggest that they point to important underlying issues, even when users continue using apps they find creepy.
A high-PSR LDO using a feedforward supply-noise cancellation technique

A feed-forward noise cancellation (FFNC) technique to improve the power supply noise rejection (PSR) of a low dropout regulator (LDO) is presented. The proposed FFNC operates in conjunction with a conventional LDO and extends the noise rejection bandwidth by nearly an order of magnitude. Fabricated in 0.18µm CMOS, at 10mA load current, the prototype achieves a PSR of −50dB and −25dB at 1MHz and 10MHz supply noise frequencies, respectively. Compared to a conventional LDO, this represents an improvement of at least 30dB at 1MHz and 15dB at 10MHz. The prototype uses only 20pF load capacitance and occupies an active area of 0.04mm2.
Investigating and promoting UX practice in industry: An experimental study

The efforts of addressing user experience (UX) in product development keep growing, as demonstrated by the proliferation of workshops and conferences bringing together academics and practitioners, who aim at creating interactive software able to satisfy their users. This special issue focuses on “Interplay between User Experience Evaluation and Software Development”, stating that the gap between human-computer interaction and software engineering with regard to usability has somewhat been narrowed. Unfortunately, our experience shows that software development organizations perform few usability engineering activities or none at all. Several authors acknowledge that, in order to understand the reasons of the limited impact of usability engineering and UX methods, and to try to modify this situation, it is fundamental to thoroughly analyze current software development practices, involving practitioners and possibly working from inside the companies. This article contributes to this research line by reporting an experimental study conducted with software companies. The study has confirmed that still too many companies either neglect usability and UX, or do not properly consider them. Interesting problems emerged. This article gives suggestions on how they may be properly addressed, since their solution is the starting point for reducing the gap between research and practice of usability and UX. It also provides further evidence on the value of the research method, called Cooperative Method Development, based on the collaboration of researchers and practitioners in carrying out empirical research; it has been used in a step of the performed study and has revealed to be instrumental for showing practitioners why to improve their development processes and how to do so.
Lemmatization and Morphological Tagging in German and Latin: A Comparison and a Survey of the State-of-the-art

This paper relates to the challenge of morphological tagging and lemmatization in morphologically rich languages by example of German and Latin. We focus on the question what a practitioner can expect when using state-of-the-art solutions out of the box. Moreover, we contrast these with old(er) methods and implementations for POS tagging. We examine to what degree recent efforts in tagger development pay out in improved accuracies — and at what cost, in terms of training and processing time. We also conduct in-domain vs. out-domain evaluation. Out-domain evaluations are particularly insightful because the distribution of the data which is being tagged by a user will typically differ from the distribution on which the tagger has been trained. Furthermore, two lemmatization techniques are evaluated. Finally, we compare pipeline tagging vs. a tagging approach that acknowledges dependencies between inflectional categories.
Type 2 diabetes: principles of pathogenesis and therapy

Type 2 diabetes mellitus has become an epidemic, and virtually no physician is without patients who have the disease. Whereas insulin insensitivity is an early phenomenon partly related to obesity, pancreas beta-cell function declines gradually over time already before the onset of clinical hyperglycaemia. Several mechanisms have been proposed, including increased non-esterified fatty acids, inflammatory cytokines, adipokines, and mitochondrial dysfunction for insulin resistance, and glucotoxicity, lipotoxicity, and amyloid formation for beta-cell dysfunction. Moreover, the disease has a strong genetic component, but only a handful of genes have been identified so far: genes for calpain 10, potassium inward-rectifier 6.2, peroxisome proliferator-activated receptor gamma, insulin receptor substrate-1, and others. Management includes not only diet and exercise, but also combinations of anti-hyperglycaemic drug treatment with lipid-lowering, antihypertensive, and anti platelet therapy.
Community Detection in Networks using Node Attributes and Modularity

Community detection in network is of vital importance to find cohesive subgroups. Node attributes can improve the accuracy of community detection when combined with link information in a graph. Community detection using node attributes has not been investigated in detail. To explore the aforementioned idea, we have adopted an approach by modifying the Louvain algorithm. We have proposed Louvain-ANDAttribute (LAA) and Louvain-OR-Attribute (LOA) methods to analyze the effect of using node attributes with modularity. We compared this approach with existing community detection approaches using different datasets. We found the performance of both algorithms better than Newman’s Eigenvector method in achieving modularity and relatively good results of gain in modularity in LAA than LOA. We used density, internal and external edge density for the evaluation of quality of detected communities. LOA provided highly dense partitions in the network as compared to Louvain and Eigenvector algorithms and close values to Clauset. Moreover, LOA achieved few numbers of edges between communities. Community Detection; Louvain algorithm; Node attributes; and Modularity
Modular bases for fluid dynamics

We present a new approach to fluid simulation that balances the speed of model reduction with the flexibility of grid-based methods. We construct a set of composable reduced models, or tiles, which capture spatially localized fluid behavior. We then precompute coupling terms so that these models can be rearranged at runtime. To enforce consistency between tiles, we introduce constraint reduction. This technique modifies a reduced model so that a given set of linear constraints can be fulfilled. Because dynamics and constraints can be solved entirely in the reduced space, our method is extremely fast and scales to large domains.
Design, Fabrication, and Characterization of a 3-D CMOS Fluxgate Magnetometer

A dual-core 3-D microfluxgate magnetometer fabricated by a simple and inexpensive fabrication process is described in this paper. The microfluxgate is able to operate along a nearly linear V-B relationship at the second harmonic frequency and features good characteristics of high sensitivity and low noise response. These characteristic results indicate a field-to-voltage transfer coefficient of 11 V/T measured at the second harmonic frequency, power consumption of 67.3 mW, and a field noise response less than 12 nT/√ Hz at 1 Hz. In brief, our proposed device not only enhances responsivity capability and linear V-B characteristics, but also is CMOS process compatible, which is considered both function-efficient and cost-effective.
Patent classifications as indicators of intellectual organization

Using the 138,751 patents filed in 2006 under the Patent Cooperation Treaty, coclassification analysis is pursued on the basis of threeand four-digit codes in the International Patent Classification (IPC, 8 edition). The co-classifications among the patents enable us to analyze and visualize the relations among technologies at different levels of aggregation. The hypothesis that classifications might be considered as the organizers of patents into classes, and that therefore co-classification patterns—more than co-citation patterns—might be useful for mapping, is not corroborated. The classifications hang weakly together, even at the four-digit level; at the country level, more specificity can be made visible. However, countries are not the appropriate units of analysis because patent portfolios are largely similar in many advanced countries in terms of the classes attributed. Instead of classes, one may wish to explore the mapping of title words as a better approach to visualize the intellectual organization of patents.
Integrated and autonomic cloud resource scaling

A Cloud is a very dynamic environment where resources offered by a Cloud Service Provider (CSP), out of one or more Cloud Data Centers (DCs) are acquired or released (by an enterprise (tenant) on-demand and at any scale. Typically a tenant will use Cloud service interfaces to acquire or release resources directly. This process can be automated by a CSP by providing auto-scaling capability where a tenant sets policies indicating under what condition resources should be auto-scaled. This is specially needed in a Cloud environment because of the huge scale at which a Cloud operates. Typical solutions are naïve causing spurious auto-scaling decisions. For example, they are based on only thresholding triggers and the thresholding mechanisms themselves are not Cloud-ready. In a Cloud, resources from three separate domains, compute, storage and network, are acquired or released on-demand. But in typical solutions resources from these three domains are not auto-scaled in an integrated fashion. Integrated auto-scaling prevents further spurious scaling and reduces the number of auto-scaling systems to be supported in a Cloud management system. In addition, network resources typically are not auto-scaled. In this paper we describe a Cloud resource auto-scaling system that addresses and overcomes above limitations.
Prognostics and health management using physics-of-failure

This paper presents a physics-of-failure based prognostics and health management approach for effective reliability prediction. This method permits in-situ assessment of system reliability under actual application conditions. The method uses sensor data with models that enable in-situ assessment of the deviation or degradation of a product from an expected normal operating condition (i.e., the system's ldquohealthrdquo) and the prediction of the future state of reliability. The implementation procedure of this approach includes failure modes, mechanisms, and effects analysis, data reduction and feature extraction from the life-cycle loads, damage accumulation, and assessment of uncertainty.
Hybrid PWM Strategy of SVPWM and VSVPWM for NPC Three-Level Voltage-Source Inverter

Neutral-point (NP) voltage drift is the main technical drawback of NP-clamped (NPC) three-level inverters. Traditional space vector pulsewidth modulation (SVPWM) is incapable of controlling the NP voltage for high modulation indexes and low power factors. Virtual SVPWM (VSVPWM) is capable of controlling the NP voltage under full modulation indexes and full power factors. However, this modulation strategy is more complex than SVPWM, increases the switching frequency, and deteriorates the output waveforms of the inverter. A novel PWM concept that includes NP voltage-balancing conditions is proposed. Based on this concept, a hybrid modulation scheme that uses both SVPWM and VSVPWM is presented for complete control of the NP voltage in NPC three-level inverters. The performance of this new modulation approach and its benefits over SVPWM and VSVPWM are verified by simulation and experiments.
CONSTRUCTIVISM : IMPLICATIONS FOR THE DESIGN AND DELIVERY OF INSTRUCTION

1 Constructivism! The increase in frequency with which this word appears in the discourse of educational research, theory, and policy is truly remarkable. Unfortunately much of the discussion is at the level of slogan and c1iche, even bromide. " Students should construct their own knowledge " is being reverentially chanted throughout the halls of many a school/college/department of education these days, and any approach that is other than constructivist is characterized as promoting passive, rote, and sterile learning. For example, consider Rogoff's (1994) description of what she calls the adult-run model of how learning occurs: ... learning is seen as a product of teaching or of adults' provision of information. Adults see themselves as responsible for filling children up with knowledge, as if children are receptacles and knowledge is a product... [The] children are seen as receivers of a body of knowledge, but not active participants in learning. The children have little role except to be receptive, as if they could just open a little bottle cap to let adults pour the knowledge in. In this adult-run model, adults have to be concerned with how to package the knowledge and how to motivate the children to make themselves receptive (p. 211). We wonder how many, if any, educators would recognize themselves in this description. 2 Perhaps the proponents of programmed instruction? Skinner would certainly reject the aspersion: A good program of instruction guarantees a great deal of successful action. Students do not need to have a natural interest in what they are doing, and subject matters do not need to be dressed up to attract attention. No one really cares whether PacMan gobbles up all those little spots on the screen.. .. What is reinforcing is successful play, and in a well-designed instructional program students gobble up their assignments (1984, p. 949). Skinner goes on to describe a classroom in which the students are so volubly engaged with the instruction on their " teaching machine " that they don't even look up when the teacher makes distracting noises by jumping up and down on the teacher's platform at the front of the room. It may be time to move beyond the paradigm debates of the last few years for precisely the reason that the tendency to sort the various approaches into " Good Guys " and " Bad Guys " (Cunningham, 1986) has not led in profitable directions. Skinner and …
Silver Nanowire Networks as Flexible, Transparent, Conducting Films: Extremely High DC to Optical Conductivity Ratios.

We have used aqueous dispersions of silver nanowires to prepare thin, flexible, transparent, conducting films. The nanowires are of length and diameter close to 6.5 μm and 85 nm, respectively. At low thickness, the films consist of networks but appear to become bulk-like for mean film thicknesses above ∼160 nm. These films can be very transparent with optical transmittance reaching as high as 92% for low thickness. The transmittance (550 nm) decreases with increasing thickness, consistent with an optical conductivity of 6472 S/m. The films are also very uniform; the transmittance varies spatially by typically <2%. The sheet resistance decreases with increasing thickness, falling below 1 Ω/◻ for thicknesses above 300 nm. The DC conductivity increases from 2 × 10(5) S/m for very thin films before saturating at 5 × 10(6) S/m for thicker films. Similarly, the ratio of DC to optical conductivity increases with increasing thickness from 25 for the thinnest films, saturating at ∼500 for thicknesses above ∼160 nm. We believe this is the highest conductivity ratio ever observed for nanostructured films and is matched only by doped metal oxide films. These nanowire films are electromechanically very robust, with all but the thinnest films showing no change in sheet resistance when flexed over >1000 cycles. Such results make these films ideal as replacements for indium tin oxide as transparent electrodes. We have prepared films with optical transmittance and sheet resistance of 85% and 13 Ω/◻, respectively. This is very close to that displayed by commercially available indium tin oxide.
A Multi-tenant Web Application Framework for SaaS

Software as a Service (SaaS) is a software delivery model in which software resources are accessed remotely by users. Enterprises find SaaS attractive because of its low cost. SaaS requires sharing of application servers among multiple tenants for low operational costs. Besides the sharing of application servers, customizations are needed to meet requirements of each tenant. Supporting various levels of configuration and customization is desirable for SaaS frameworks. This paper describes a multi-tenant web application framework for SaaS. The proposed framework supports runtime customizations of user interfaces and business logics by use of file-level namespaces, inheritance, and polymorphism. It supports various client-side web application technologies.
Efficacy of music therapy treatment based on cycles of sessions: a randomised controlled trial.

We undertook a randomised controlled trial to assess whether a music therapy (MT) scheme of administration, including three working cycles of one month spaced out by one month of no treatment, is effective to reduce behavioural disturbances in severely demented patients. Sixty persons with severe dementia (30 in the experimental and 30 in the control group) were enrolled. Baseline multidimensional assessment included demographics, Mini Mental State Examination (MMSE), Barthel Index and Neuropsychiatry Inventory (NPI) for all patients. All the patients of the experimental and control groups received standard care (educational and entertainment activities). In addition, the experimental group received three cycles of 12 active MT sessions each, three times a week. Each 30-min session included a group of three patients. Every cycle of treatment was followed by one month of wash-out. At the end of this study, MT treatment resulted to be more effective than standard care to reduce behavioural disorders. We observed a significant reduction over time in the NPI global scores in both groups (F(7,357) = 9.06, p < 0.001) and a significant difference between groups (F(1,51) = 4.84, p < 0.05) due to a higher reduction of behavioural disturbances in the experimental group at the end of the treatment (Cohen's d = 0.63). The analysis of single NPI items shows that delusions, agitation and apathy significantly improved in the experimental, but not in the control group. This study suggests the effectiveness of MT approach with working cycles in reducing behavioural disorders of severely demented patients.