nils-herrmann/clean_scirepeval huggingface dataset:
A low-cost LoRaWAN testbed for IoT: Implementation and measurements

One of the challenges in deploying IoT applications is the cost of building and operating the communication infrastructure. This paper studies the feasibility of building a low-cost IoT network based on LoRa, a leading Low-Power Wide-Area Network (LPWAN) technology, using off-the-shelf components and open source software. To this end, we describe our LoRa testbed, which includes gateways, end devices and a variety of sensors. We then present extensive measurement results to characterize the performance of our LoRa network over the 915 MHz unlicensed ISM band in both indoor and outdoor scenarios for various network setups. Our results show that even in a harsh propagation environment, e.g., when the gateway is located inside a concrete building, the low-cost network is able to achieve great coverage. Specifically, we observed that: i) the indoor coverage is sufficient to cover an entire seven-story office building with minimal packet drop, ii) the outdoor coverage is very dependent on the environment, where in our experiments, a communication range of 4.4 km was achieved with only 15% packet drop, iii) network parameters such as spreading factor and packet size greatly affect the coverage; for example, we observed that a payload size of 242 bytes leads to 90% packet drop versus less than 5% drop with a payload size of 1 byte.
Triplet Loss in Siamese Network for Object Tracking

Object tracking is still a critical and challenging problem with many applications in computer vision. For this challenge, more and more researchers pay attention to applying deep learning to get powerful feature for better tracking accuracy. In this paper, a novel triplet loss is proposed to extract expressive deep feature for object tracking by adding it into Siamese network framework instead of pairwise loss for training. Without adding any inputs, our approach is able to utilize more elements for training to achieve more powerful feature via the combination of original samples. Furthermore, we propose a theoretical analysis by combining comparison of gradients and back-propagation, to prove the effectiveness of our method. In experiments, we apply the proposed triplet loss for three real-time trackers based on Siamese network. And the results on several popular tracking benchmarks show our variants operate at almost the same frame-rate with baseline trackers and achieve superior tracking performance than them, as well as the comparable accuracy with recent state-of-the-art real-time trackers.
Beginning Application Lifecycle Management

Beginning Application Lifecycle Management is a guide to an area of rapidly growing interest within the development community: managing the entire cycle of building software. ALM is an area that spans everything from requirements specifications to retirement of an IT-system or application. Because its techniques allow you to deal with the process of developing applications across many areas of responsibility and across many different disciplines, the benefits and effects of ALM techniques used on your project can be wide-ranging and pronounced. In this book, author Joachim Rossberg will show you what ALM is and why it matters. He will also show you how you can assess your current situation and how you can use this assessment to create the road ahead for improving or implementing your own ALM process across all of your team’s development efforts. Beginning Application Lifecycle Management can be implemented on any platform. This book uses Microsoft Team Foundation Server as a foundation in many examples, but the key elements are platform independent and you’ll find the book written in a platform agnostic way.
Estimating common trends in multivariate time series using dynamic factor analysis

This paper discusses dynamic factor analysis, a technique for estimating common trends in multivariate time series. Unlike more common time series techniques such as spectral analysis and ARIMA models, dynamic factor analysis can analyse short, non-stationary time series containing missing values. Typically, the parameters in dynamic factor analysis are estimated by direct optimisation, which means that only small data sets can be analysed if computing time is not to become prohibitively long and the chances of obtaining sub-optimal estimates are to be avoided. This paper shows how the parameters of dynamic factor analysis can be estimated using the EM algorithm, allowing larger data sets to be analysed. The technique is illustrated on a marine environmental data set.
Contributions of Theodor Wilhelm Engelmann on phototaxis, chemotaxis, and photosynthesis

Theodor Wilhelm Engelmann (1843–1909), who had a creative life in music, muscle physiology, and microbiology, developed a sensitive method for tracing the photosynthetic oxygen production of unicellular plants by means of bacterial aerotaxis (chemotaxis). He discovered the absorption spectrum of bacteriopurpurin (bacteriochlorophyll a) and the scotophobic response, photokinesis, and photosynthesis of purple bacteria.
Combining Difficulty Ranking with Multi-Armed Bandits to Sequence Educational Content

We address the problem of how to personalize educational content to students in order to maximize their learning gains over time. We present a new computational approach to this problem called MAPLE (Multi-Armed Bandits based Personalization for Learning Environments) that combines difficulty ranking with multi-armed bandits. Given a set of target questions MAPLE estimates the expected learning gains for each question and uses an exploration-exploitation strategy to choose the next question to pose to the student. It maintains a personalized ranking over the difficulties of question in the target set and updates it in real-time according to students’ progress. We show in simulations that MAPLE was able to improve students’ learning gains compared to approaches that sequence questions in increasing level of difficulty, or rely on content experts. When implemented in a live e-learning system in the wild, MAPLE showed promising initial results.
DIRCM jamming effect analysis of spin-scan reticle seeker

The function of DIRCM (directed infrared countermeasures) jamming is to cause the missile to miss its intended target by disturbing the seeker tracking process. The DIRCM jamming uses the pulsing flashes of infrared (IR) energy and its frequency, phase and intensity have the influence on the missile guidance system. In this paper, we analyze the DIRCM jamming effect of the spin-scan reticle seeker. The simulation results show that the jamming effect is greatly influenced by frequency, phase and intensity of the jammer signal.
Causation, Statistics, and Sociology

Three di¡erent understandings of causation, each importantly shaped by the work of statisticians, are examined from the point of view of their value to sociologists: causation as robust dependence, causation as consequential manipulation, and causation as generative process. The last is favoured as the basis for causal analysis in sociology. It allows the respective roles of statistics and theory to be clari¢ed and is appropriate to sociology as a largely non-experimental social science in which the concept of action is central.
A review of the déjà vu experience.

For more than a century, the déjà vu experience has been examined through retrospective surveys, prospective surveys, and case studies. About 60% of the population has experienced déjà vu, and its frequency decreases with age. Déjà vu appears to be associated with stress and fatigue, and it shows a positive relationship with socioeconomic level and education. Scientific explanations of déjà vu fall into 4 categories: dual processing (2 cognitive processes momentarily out of synchrony), neurological (seizure, disruption in neuronal transmission), memory (implicit familiarity of unrecognized stimuli),and attentional (unattended perception followed by attended perception). Systematic research is needed on the prevalence and etiology of this culturally familiar cognitive experience, and several laboratory models may help clarify this illusion of recognition.
Comparison of new activation functions in neural network for forecasting financial time series

In artificial neural networks (ANNs), the activation function most used in practice are the logistic sigmoid function and the hyperbolic tangent function. The activation functions used in ANNs have been said to play an important role in the convergence of the learning algorithms. In this paper, we evaluate the use of different activation functions and suggest the use of three new simple functions, complementary log-log, probit and log-log, as activation functions in order to improve the performance of neural networks. Financial time series were used to evaluate the performance of ANNs models using these new activation functions and to compare their performance with some activation functions existing in the literature. This evaluation is performed through two learning algorithms: conjugate gradient backpropagation with Fletcher–Reeves updates and Levenberg–Marquardt.
Motivations for Augmented Reality Gaming

In Augmented Reality (AR), interfaces consist of a blend of both real and virtual content. In this paper we examine existing gaming styles played in the real world or on computers. We discuss the strengths and weaknesses of these mediums within an informal model of gaming experience split into four aspects; physical, mental, social and emotional. We find that their strengths are mostly complementary, and argue that games built in AR can blend them to enhance existing game styles and open up new ones. To illustrate these ideas, we present our work on AR Worms, a re-implementation of the classic computer game Worms using Augmented Reality. We discuss how AR has enabled us to start exploring interfaces for gaming, and present informal observations of players at several demonstrations. Finally, we present some ideas for AR games in the area of strategy and role playing games.
Lev Vygotsky: Philologist and Defectologist, A Sociointellectual Biography

Among the pioneers of psychology, Lev Vygotsky (1896-1934) may be the best known of those who are least understood. This is not just a problem of historical scholarship: The misunderstanding of Vygotsky started with his own students and collaborators—during his lifetime—and continued after his death. It is, in other words, integrated into the literature. And that literature, as a result, appears fractured and inconsistent. Indeed, the largest and the best intellectual biography of Vygotsky is titled Understanding Vygotsky: A Quest for Synthesis (van der Veer & Valsiner, 1991). Yet even this excellent book is far from providing a full and complete story. The discovery of the real Vygotsky is still to come.
Science Fiction as an Introduction to AI Research

The undergraduate computer science curriculum is generally focused on skills and tools; most students are not exposed to much research in the field, and do not learn how to navigate the research literature. We describe how science fiction reviews were used as a gateway to research reviews. Students learn a little about current or recent research on a topic that stirs their imagination, and learn how to search for, read critically, and compare technical papers on a topic related their chosen science fiction book, movie, or TV show.
Proposals for Master Degree Thesis Research Group on Blockchain and Social Networking Reference :

1. Tecnologia blockchain per il trading energetico peer-to-peer Il mercato dell’energia sta attraversando una vera e propria rivoluzione dovuta alla sua liberalizzazione e all’avvento dei prosumers, consumatori che sono al tempo stesso piccoli produttori di energia da fonti rinnovabili. I modelli tradizionali di trading basati su un mercato centralizzato che opera su base giornaliera o settimanale non sono quindi piú adeguati per scenari in cui il numero e la frequenza delle transazioni fra micro-produttori cresce esponenzialmente. Lo scopo della tesi é di progettare e sviluppare le API di accesso e gestione di una piattaforma di trading peer-to-peer dell’energia basata su tecnologie blockchain open source, che permetta agli utenti di inviare, eseguire ed archiviare ordini e transazioni in modo flessibile e con tempi di risposta brevi. La tesi prevede la realizzazione di una dApp che definisca un front-end utilizzato dai trader per ricevere ed eseguire le transazioni. La tesi si inquadra nell’ambito di una collaborazione del mio gruppo di ricerca con IIT-CNR, nell’ambito di un progetto su blockchain che raggruppa sia partner accademici che industriali.
Neuroimaging in anxiety disorders

Over the last few years, neuroimaging techniques have contributed greatly to the identification of the structural and functional neuroanatomy of anxiety disorders. The amygdala seems to be a crucial structure for fear and anxiety, and has consistently been found to be activated in anxiety-provoking situations. Apart from the amygdala, the insula and anterior cinguiate cortex seem to be critical, and ail three have been referred to as the "fear network." In the present article, we review the main findings from three major lines of research. First, we examine human models of anxiety disorders, including fear conditioning studies and investigations of experimentally induced panic attacks. Then we turn to research in patients with anxiety disorders and take a dose look at post-traumatic stress disorder and obsessive-compulsive disorder. Finally, we review neuroimaging studies investigating neural correlates of successful treatment of anxiety, focusing on exposure-based therapy and several pharmacological treatment options, as well as combinations of both.
Methods for the Preparation and Manufacture of Polymeric Nanoparticles

This review summarizes the different methods of preparation of polymer nanoparticles including nanospheres and nanocapsules. The first part summarizes the basic principle of each method of nanoparticle preparation. It presents the most recent innovations and progresses obtained over the last decade and which were not included in previous reviews on the subject. Strategies for the obtaining of nanoparticles with controlled in vivo fate are described in the second part of the review. A paragraph summarizing scaling up of nanoparticle production and presenting corresponding pilot set-up is considered in the third part of the review. Treatments of nanoparticles, applied after the synthesis, are described in the next part including purification, sterilization, lyophilization and concentration. Finally, methods to obtain labelled nanoparticles for in vitro and in vivo investigations are described in the last part of this review.
Nursing Informatics: Decades of Contribution to Health Informatics

In this paper we present a contemporary understanding of "nursing informatics" and relate it to applications in three specific contexts, hospitals, community health, and home dwelling, to illustrate achievements that contribute to the overall schema of health informatics.



We identified literature through database searches in MEDLINE, EMBASE, CINAHL, and the Cochrane Library. Database searching was complemented by one author search and hand searches in six relevant journals. The literature review helped in conceptual clarification and elaborate on use that are supported by applications in different settings.



Conceptual clarification of nursing data, information and knowledge has been expanded to include wisdom. Information systems and support for nursing practice benefits from conceptual clarification of nursing data, information, knowledge, and wisdom. We introduce three examples of information systems and point out core issues for information integration and practice development.



Exploring interplays of data, information, knowledge, and wisdom, nursing informatics takes a practice turn, accommodating to processes of application design and deployment for purposeful use by nurses in different settings. Collaborative efforts will be key to further achievements that support task shifting, mobility, and ubiquitous health care.
MagicToon: A 2D-to-3D creative cartoon modeling system with mobile AR

We present MagicToon, an interactive modeling system with mobile augmented reality (AR) that allows children to build 3D cartoon scenes creatively from their own 2D cartoon drawings on paper. Our system consists of two major components: an automatic 2D-to-3D cartoon model creator and an interactive model editor to construct more complicated AR scenes. The model creator can generate textured 3D cartoon models according to 2D drawings automatically and overlay them on the real world, bringing life to flat cartoon drawings. With our interactive model editor, the user can perform several optional operations on 3D models such as copying and animating in AR context through a touchscreen of a handheld device. The user can also author more complicated AR scenes by placing multiple registered drawings simultaneously. The results of our user study have shown that our system is easier to use compared with traditional sketch-based modeling systems and can give more play to children's innovations compared with AR coloring books.
Development of a CTD sensor subsystem for oceanographic application

The CTD which stands for “Conductivity-Temperature-Depth” is one of the most used instruments for the oceanographic measurements. MEMS based CTD sensor components consist of a conductivity sensor (C), temperature sensor (T) and a piezo resistive pressure sensor (D). CTDs are found in every marine related institute and navy throughout the world as they are used to produce the salinity profile for the area of the ocean under investigation and are also used to determine different oceanic parameters. This research paper provides the design, fabrication and initial test results on a prototype CTD sensor.
Echo State Networks for Hierarchical Cognitive Control

In this thesis, we will present an Echo State Network (ESN) to investigate hierarchical cognitive control, one of the functions of Prefrontal Cortex (PFC). This ESN is designed with the intention to implement it as a robot controller, making it useful for biologically inspired robot control and for embodied and embedded PFC research. We will apply the ESN to a n-back task and a Wisconsin Card Sorting task to confirm the hypothesis that topological mapping of temporal and policy abstraction over the PFC can be explained by the effects of two requirements: a better preservation of information when information is processed in different areas, versus a better integration of information when information is processed in a single area.
Emphasis on testing assimilation using cloud computing for improvised agile SCRUM framework

In today's era service development demand increasing day by day and client's ever changing requirements which made agile methodology to come in existence due to faster production, flexible, improved quality and moreover it can accommodate changes, faster feedbacks and transparent communication. But now Due to geographical distribution of team members and client, leading IT thinkers thought to strengthen the agile methodology by giving user's access an environment that has wide-spread access i.e CLOUD. This combination of agile and cloud provide a positive impact to IT companies. But for achieving Quality, we need to test all functionality so in our work we emphasis on testing assimilation using cloud services in agile environment. Cloud team members can perform testing easily using Test-as-a-Service without increasing the cost of the project and get the results faster. We can also use agile management tools to reduce the problem of communication and for all the updates in the product backlog as well as Sprint backlog list.
Artifacts in wearable photoplethysmographs during daily life motions and their reduction with least mean square based active noise cancellation method

Signal distortion of photoplethysmographs (PPGs) due to motion artifacts has been a limitation for developing real-time, wearable health monitoring devices. The artifacts in PPG signals are analyzed by comparing the frequency of the PPG with a reference pulse and daily life motions, including typing, writing, tapping, gesturing, walking, and running. Periodical motions in the range of pulse frequency, such as walking and running, cause motion artifacts. To reduce these artifacts in real-time devices, a least mean square based active noise cancellation method is applied to the accelerometer data. Experiments show that the proposed method recovers pulse from PPGs efficiently.
Holographic Pattern Synthesis With Modulated Substrate Integrated Waveguide Line-Source Leaky-Wave Antennas

We present the synthesis of one-dimensional (line-source) leaky-wave antennas (LWAs) in substrate integrated waveguide (SIW) technology with modulated geometry, demonstrating the capability to flexibly tailor the radiated fields pattern, both in nearand far-field regimes. The synthesis technique is inspired in holographic concepts, which are related to the existence of modulated leaky waves. A systematic design algorithm to obtain the requested modulation of the SIW width and distance between posts to synthesize the desired radiation pattern is described. Several design examples operating at 15 GHz are reported and experimentally validated, showing the power and versatility of the proposed holographic SIW technology.
A combination of VLC and WiFi based indoor wireless access network and its handover strategy

Visible Light Communication (VLC) has many advantages such as high-speed data transmission and non-frequency authorization, which provided a good solution for indoor access environment with an effective and energy-saving way. This paper proposes a combination VLC + WiFi based indoor wireless access network structure. Different network architectures are analyzed and optimal scheme is given. Based on the numerical calculation, the handover model is introduced. Finally, a demo system is designed and implemented.
Design, Fabrication and Experimental Validation of a Novel Dry-Contact Sensor for Measuring Electroencephalography Signals without Skin Preparation

In the present study, novel dry-contact sensors for measuring electro-encephalography (EEG) signals without any skin preparation are designed, fabricated by an injection molding manufacturing process and experimentally validated. Conventional wet electrodes are commonly used to measure EEG signals; they provide excellent EEG signals subject to proper skin preparation and conductive gel application. However, a series of skin preparation procedures for applying the wet electrodes is always required and usually creates trouble for users. To overcome these drawbacks, novel dry-contact EEG sensors were proposed for potential operation in the presence or absence of hair and without any skin preparation or conductive gel usage. The dry EEG sensors were designed to contact the scalp surface with 17 spring contact probes. Each probe was designed to include a probe head, plunger, spring, and barrel. The 17 probes were inserted into a flexible substrate using a one-time forming process via an established injection molding procedure. With these 17 spring contact probes, the flexible substrate allows for high geometric conformity between the sensor and the irregular scalp surface to maintain low skin-sensor interface impedance. Additionally, the flexible substrate also initiates a sensor buffer effect, eliminating pain when force is applied. The proposed dry EEG sensor was reliable in measuring EEG signals without any skin preparation or conductive gel usage, as compared with the conventional wet electrodes.