Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature Engineering for Entity Resolution

Entity resolution or record linkage is the task of identifying records referring to the same entity across multiple data sources. In the absence of a unique identifier entities must be resolved on the basis of possibly noisy and incomplete quasiidentifiers, such as names, ages, and addresses or geographic locations. Our goal is to improve estimates of the total observed casualty count in the ongoing Syrian civil war. Estimating the total victim tools in a conflict is an important element to understand its extend and magnitude, drive intervention policies and also to aid in bringing justice to perpetrators and mass murderers. Our data comprise multiple lists of casualties, compiled by the Human Rights Data Analysis Group. To arrive at an estimate of the number of unique casualties we first need to detect duplicate entries within and across lists. By focusing on Arabic names and their structure, we develop new features for comparing records and demonstrate meaningful improvements over existing classifiers (which have already seen significant engineering), empirically supporting the importance of language-specific analysis. We expect that these features will be useful in other contexts where it is necessary to measure the similarity between Arabic names.
The evolution from watershed hydrological science to integrated watershed management

Contemporary hydrology, as it is currently practiced, is essentially based on mathematical modelling. Over the past 40 years, with the emergence of information technology, increasingly complex hydrological models have been developed. More recently, water quality models have been integrated into those models. Prior to this, some elementary tools for analysis and decision making at the watershed level had been available. More recently, with the development of geographic information systems and the availability of satellite data, the heterogeneity of watersheds can be accounted for. Models integrating these new tools are well adapted to evaluate development scenarios in the context of integrated watershed management. The GIBSI model, used in Quebec, demonstrates the efficiency of integrated management concepts and illustrates the importance of implementing this management philosophy.
Proceedings of the Society for Computation in Linguistics Proceedings of the Society for Computation in Linguistics

Since most people in the world today are multilingual (Grosjean and Li, 2013), code-switching is ubiquitous in spoken and written interactions. Paving the way for future adaptive, multilingual conversational agents, we incorporate linguistically-motivated strategies of code-switching into a rule-based goal-oriented dialogue system. We collect and release C OMMON A MIGOS , a corpus of 587 human–computer text conversations between our dialogue system and human users in mixed Spanish and English. From this new corpus, we analyze the amount of elicited code-switching, preferred patterns of user code-switching, and the impact of user demographics on code-switching. Based on these exploratory ﬁndings, we give recommendations for future effective code-switching dialogue systems, highlighting user’s language proﬁ-ciency and gender as critical considerations. 1
ST Changes Observed in Short Spaced Bipolar Leads Suitable for Patch Based Monitoring

This article investigates the selection of optimal ECG leads for the detection of ST changes more likely to appear in patch systems with closely spaced leads. Method: We analysed body surface potential maps (BSPMs) from 44 subjects undergoing PTCA. BSPMs were recorded at 120 sites and these were expanded to 352 nodes (Dalhousie torso) using Laplacian interpolation. A total of 88 BSPMs were investigated. This included the 44 subjects at baseline and the 44 subjects at peak balloon inflation (PBI). At PBI the subjects had various coronary arteries occluded (14 LAD, 15 LCX, 15 RCA). All possible bipolar leads were calculated for each subject. Leads were ranked based on the maximum ST-segment change between baseline and PBI for each subject. Leads with electrode spacing of more than 100 mm were excluded. The highest ranked lead was chosen as the short spaced lead (SSL) on the anterior torso. Result: The median ST-segment change for the chosen SSL for each vessel was LAD = 134 μV, LCX = 65 μV, RCA = 166 μV. The maximum ST segment change observed for the same lead was LAD = 277 μV, LCX = 166 μV, RCA = 257 μV. For comparison, the highest median observed on the 12-lead ECG for each vessel was LAD = 137 μV (V3), LCX = 130 μV (III), RCA = 196 μV (III).
Crop and Soil segmentation in precision agriculture applications from remotely sensed data

One of the most challenging problems in precision agriculture is the correct identification and separation of crop and soil. Thresholding techniques based on Normalized Difference Vegetation Index (NDVI) or other such similar metrics have the advantage of being simple, easy to read transformations of the data packed with useful information. Obvious difficulties arise when crop/tree and soil have similar spectral responses as in case of grass filled areas in vineyards. In this case grass and canopy are close in terms of NDVI values and thresholding techniques will generally fail. In this paper we present the FANSCAN algorithm to segment crops and/or tree objects over soil by using high-resolution images starting from Digital Surface Models that are usually available when the data have been acquired by using unmanned platforms. The FANSCAN algorithm uses vector or radial raster scanning across the image to increase the frequency resolution of the scanned data. This approach could be used to segment crops and/or tree objects over soil that is a mandatory task in precision agriculture applications.
Chapter 2 Development of a Questionnaire Measuring Art-of-Living 2 . 1 Introduction 2 . 1 . 1 Questions Regarding the Concept

Firstly, we perform a study aiming to investigate how people think about art-of-living: Are their opinions similar to the ones we phrased in the introduction? Do they believe that art-of-living can be learnt? Do they see a way to perform art-of-living? To answer these questions, in this study we were asking openas well as closed questions regarding the concept of art-of-living. To be precise, our research questions regarding the concept are:
Analyzing and Estimating the Performance of Concurrent Kernels Execution on GPUs

GPUs have established a new baseline for power efficiency and computing power, delivering larger bandwidth and more computing units in each new generation. Modern GPUs support the concurrent execution of kernels to maximize resource utilization, allowing other kernels to better exploit idle resources. However, the decision on the simultaneous execution of different kernels is made by the hardware, and sometimes GPUs do not allow the execution of blocks from other kernels, even with the availability of resources. In this work, we present an in-depth study on the simultaneous execution of kernels on the GPU. We present the necessary conditions for executing kernels simultaneously, we define the factors that influence competition, and describe a model that can determine performance degradation. Finally, we validate the model using synthetic and real-world kernels with different computation and memory requirements.
Design of a 10-bit SAR A/D converter with 2-bit/step and threshold configuring comparator

In this paper, we designed an A/D converter that can be applied to a system that enables interface between human body and device such as touchpad. As devices become more sophisticated, higher operating speeds are required. Portable devices have been developed to minimize power consumption and miniaturize devices. The upper 5 bits are determined by digital code using a reference voltage variable comparator. The reference voltage variable comparator changes the offset by connecting the current path to the input pair, and the reference voltage is sequentially shifted according to the digital code of the upper 5 bits. The lower 5 bits change the reference voltage by the switching of the capacitor D/A converter to determine the digital code. This technique reduces the capacitance of the capacitor D/A converter, reduces dynamic power consumption, and reduces chip area. The clock double circuit reduces the period of the external clock by 2 times and increases the operation speed by 2 bits per step. The designed 10 bit SAR A/D converter was fabricated with Magna chip 0. 18μm CMOS 1Poly 6Metal process. Simulation results showed 56 power consumption and 9.5 bit ENOB at maximum sampling frequency of 10MHz for 1.8V supply voltage and 1 kHz sinusoidal input. The proposed SAR A/D converter with 7.73fJ/step FoM is expected to be applied to low power systems. Keywords—A/D converter, Clock double, Offset voltage, Reference voltage variable comparator
A Software and Hardware Evaluation of Revolutionary Turbo MIMO OFDM Schemes for 5GHz WLANs

Globally, WLANs operating in the 5GHz band have been standardized by the IEEE (North America), ETSI (Europe) and ARIB (Japan). A harmonized physical layer is specified offering up to 54 Mbits/s using rate adaptive Coded Orthogonal Frequency Division Multiplexing (COFDM). Multiple Input Multiple Output (MIMO) antenna architectures coupled with Soft Input Soft Output (SISO) iterative decoding algorithms represent a revolutionary approach to the design of WLANs. At present, these techniques are the subject of intense theoretic research. In this contribution, the performance of a newly proposed iterative MIMO-OFDM architecture is explored using MIMO channel data captured in the 5GHz band. Theoretically, this technology has the potential to significantly increase future WLAN data rates. However, little practical evaluation has been reported in the literature. To address this situation, this paper describes the construction of a broadband 5GHz MIMO-OFDM test-bed. This advanced baseband/RF platform will be used in the future to evaluate emerging MIMO-OFDM WLAN architectures.
Bionics Based Solar Powered Clothing for Treating Parkinson’s Disease and Epilepsy

This research paper incorporates bionics based solar powered clothing for treatment of Parkinson’s disease and Epilepsy. Firstly, the clothing will use the most recent research and technology in which the electronic circuit would be embedded to store data (such as tremors of Parkinson’s disease and Epilepsy) and deliver drugs to specific parts of the brain, thus, preventing the cumbersome method of surgery by the method of neurostimulator. Secondly, the electronic circuit will be charged by solar
Danish University Colleges Designing for competences-professional development of teacher education in Denmark Christiansen,

for presentation at the Fourth Conference, held in Stockholm, May 7-9 2014. The abstract address the category of “research (and development) studies in progress” Authors: Peter Gundersen, associate professor at Educationlab: Research Program for Technology and Educational Design, Dept. of Research and Innovation, University College Zealand, University of Applied Science, Denmark. Mail: pgu@ucsj.dk Rene B Christiansen, associate professor at Educationlab: Research Program for Technology and Educational Design, Dept. of Research and Innovation, University College Zealand, University of Applied Science, Denmark. Mail: rbc@ucsj.dk
Learning to Drive using Waypoints

Traditional autonomous vehicle pipelines are highly modularized with different subsystems for localization, perception, actor prediction, planning, and control. Though this approach provides ease of interpretation, its generalizability to unseen environments is limited and hand-engineering of numerous parameters is required, especially in the prediction and planning systems. Recently, Deep Reinforcement Learning (DRL) has been shown to learn complex strategic games and perform challenging robotic tasks, which provides an appealing framework for learning to drive. In this paper, we propose an architecture that learns directly from semantically segmented images along with waypoint features to drive within CARLA simulator using the Proximal Policy Optimization (PPO) algorithm. We report significant improvement in performance on the benchmark tasks of driving straight, one turn and navigation with and without dynamic actors.
Factors Affecting the Usability of Mobiles in Healthcare- A Peep into the Indian Scenario

Mobiles today have proliferated as a ubiquitous means of communication. Every industry is depending on this medium in some or the other form. Healthcare industry is also leaping ahead with its might to come at par with other industries in terms of communication and use of information and technology. Earlier use of mobiles in healthcare was limited due to lack of memory, small screen space, poor graphical display and inability to transfer or store huge data. Emergence of tablets and smart phones has changed the overall experience of using mobiles. It has improved service delivery, empowered consumers, businesses and entrepreneurs and changed the way in which people access information and make transactions (Darrel West, 2011). The real time tailored personalized information available through mobile devices has the potential to transform healthcare. When integrated properly this technology has the potential to provide solutions to increased demands in quality, efficiency and improved workflow to help streamline healthcare operations (Beaver, 2003). In various hospitals ICT has shown improvements in adherence to guidelines, enhanced disease surveillance and reduced medication errors (Chaudhary et al., 2006). Use of mobile in the healthcare can offer many benefits to the various stakeholders than any other ICT medium. The patients can monitor their condition, stay connected with the providers and also get involved in the decision making process about their health with the healthcare provider. The healthcare providers or organizations can reduce their cost of communication and treatment by reducing the number of hospital visits and hospital stays and enhancing the productivity and availability of staff (Gollol, et al., 2004). The providers can be offered access to patient’s records, consultation with the experts, access to medical knowledge databases anytime and anywhere and thus enhancing their productivity. The objective of this research is to study the current status of usability of mobiles in healthcare and to analyze the factors affecting the usability of mobiles among the healthcare professionals. This study was conducted in four districts of Karnataka: two with good health indicators (Bangalore urban and Belgaum) and two with poor health indicators (Koppal and Raichur).
Comparative Study of Crude and Wine-Processing Corni Fructus on Chemical Composition and Antidiabetic Effects

Wine processing is a specialized technology which involves sautéing crude herbal medicine using Chinese rice wine. Herein, we identified the changes in chemical profiles and antidiabetic effects of Corni Fructus (CF) after wine processing in high-fat diet (HFD) streptozotocin- (STZ-) induced diabetic mice. A novel high-efficiency method for simultaneously quantifying gallic acid, 5-hydroxymethylfurfural, morroniside, loganin, sweroside, and cornuside by UPLC was developed, and validating crude and wine-processing CF was done for the first time. Mice were randomly divided into the following groups and orally given different solutions for 4 weeks: normal group (NC, 0.4% (w/v) CMC-Na), model group (DM, 0.4% (w/v) CMC-Na), crude CF group (CP, 3.87 g/kg), and wine-processing CF group (PP, 3.87 g/kg) followed by HFD and multiple subcutaneous injection of STZ (40 mg/kg) to induce the diabetes model except the NC group. Biochemical indexes (body weight, fasting blood glucose level, lipid level, insulin, and free fatty acid) and other parameters involving liver toxicity were measured with commercial kits and immunohistochemical method. Comparative studies on pharmacology showed that the crude extracts possess higher efficacy on hypoglycemia and hypolipidemia, while wine-processing products exhibit better effects on liver preservation. Our data suggested that wine processing was recommended when CF was used for protecting the liver; however, crude products should be used as antidiabetic drugs.
Comparative Study of Light-GBM and a Combination of Survival Analysis with Deep Learning for Early Detection of Sepsis

Sepsis is a severe medical condition caused by body’s extreme response to an infection causing tissue damage, organ failure and even death. The emergence of advanced technologies like Artificial Intelligence and machine learning, allowed faster exploration of advanced way to recognize sepsis cases. In this paper, we will present two main approaches that has been tested using medical data. First is the combination of survival analysis and neural networks, and the second is based on booting trees.
Data Quality Assessment of Capacitively-Coupled ECG Signals

Acquisition of capacitively-coupled ECG (ccECG) from daily life scenarios is limited by its sensitivity to motion and its variability in signal quality. 48 features, in combination with different classifiers, were evaluated for quality classification on a dataset of 10000 ccECG segments of 15 seconds. Feature subsets with potential high discriminatory power were identified and evaluated in multiple supervised models, for two classification problems with different tolerance to artefacts. This resulted in balanced accuracies of 94.02% and 92.4%, achieved using a Linear SVM and a fine KNN respectively. These models are useful tools for real-time and offline processing of ccECG signals recorded in real-life scenarios
Robust Imitative Planning: Planning from Demonstrations Under Uncertainty

Learning from expert demonstrations is an attractive framework for sequential decision-making in safety-critical domains such as autonomous driving, where trial and error learning has no safety guarantees during training. However, naïve use of imitation learning can fail by extrapolating incorrectly to unfamiliar situations, resulting in arbitrary model outputs and dangerous outcomes. This is especially true for high capacity parametric models such as deep neural networks, for processing high-dimensional observations from cameras or LIDAR. Instead, we model expert behaviour with a model able to capture uncertainty about previously unseen scenarios, as well as inherent stochasticity in expert demonstrations. We propose a framework for planning under epistemic uncertainty and also provide a practical realisation, called robust imitative planning (RIP), using an ensemble of deep neural density estimators. We demonstrate online robustness to out-of-trainingdistribution scenarios on the CARLA autonomous driving simulator, improving over other probabilistic imitation learning models and reducing the total number of hazardous events while improving runtime to real-time using a trajectory library.
Approaching Neural Network Uncertainty Realism

Statistical models are inherently uncertain. Quantifying or at least upper-bounding their uncertainties is vital for safety-critical systems such as autonomous vehicles. While standard neural networks do not report this information, several approaches exist to integrate uncertainty estimates into them. Assessing the quality of these uncertainty estimates is not straightforward, as no direct ground truth labels are available. Instead, implicit statistical assessments are required. For regression, we propose to evaluate uncertainty realism -- a strict quality criterion -- with a Mahalanobis distance-based statistical test. An empirical evaluation reveals the need for uncertainty measures that are appropriate to upper-bound heavy-tailed empirical errors. Alongside, we transfer the variational U-Net classification architecture to standard supervised image-to-image tasks. We adopt it to the automotive domain and show that it significantly improves uncertainty realism compared to a plain encoder-decoder model.
The Comparison of Children’s Caloric Expenditure During Elementary Physical Education Class And Free-Choice Recess Time

The physical benefits of structured physical education (PE) classes and free-choice recess time in elementary school and how they compare to each other is unknown. National health objectives encourage 50% of PE class time being spent in moderate to vigorous physical activity (MVPA), while no set standards for elementary recess exist. PURPOSE: To determine if a difference existed in the caloric amounts expended by elementary age children during structured physical education class compared to free-choice recess time. METHODS: Twenty-eight third and fourth grade children (male= 18, female= 10) were recorded, with a hip-placed accelerometer, during one day each of PE class and recess time. Each recording lasted exactly 30 minutes and they were taken a day apart. Data was collected during a three week period in which the PE class participated in tennis and badminton. RESULTS: A paired samples t-test compared differences in steps, total energy expenditure (EE), total EE in males, and average kilocalories expended per minute. Steps: t(26) = 3.79, p=. 001; total EE:t(27) = 1.85, p= . 075; total EE (males): t(17) = 3.78, p= . 006; energy expenditure per minute: t(26) = 1.75, p= . 091. The average percentage of time spent in MVPA during PE was 64.37%. CONCLUSION: There was a statistically significant difference in total EE in males and steps, with recess being higher than PE class. Further tests on the steps showed this also was only significantly different in the male children. It is important to note, on average, the children met the national objective and spent over 50% of the PE class period in MVPA.
R&D Investments, Technology Spillovers, and Equity Prices*

I find that R&D investment is crucial in order for a firm to effectively absorb and benefit from potential technology spillovers. When firms are exposed to large technology spillover pools I find that firms that make higher R&D investments earn significantly higher subsequent equity returns. I also show that in the presence of large technology spillovers, firms with higher R&D investments generate more future patents (or patent citations) per unit of available spillovers and exhibit higher operating performance. I further demonstrate that the complementary effect of R&D and spillovers on subsequent stock returns is most pronounced among low investor attention stocks. My findings suggest that the market appears to undervalue the benefits of R&D investments in absorbing potential technology spillovers, and that limited investor attention contributes to this undervaluation. JEL Classification: G11, G12, G14, O31, O32, O33
Clusters development as a best organizational Business Practice

It is widely known that the clusters represent a powerful mechanism of economic development of regions and often even of entire nations. From the theoretical point of view the clusters represent an organizational model which advantages can be demonstrated by the use of transactional approach. Each single enterprise inside a cluster specializes in completing a particular stage of production, which ensures lower costs, flexibility and innovation realizing, besides, a significant contribution to social cohesion in a certain territory being strongly integrated with the local socio-economic environment. In this study we analyze the best practice of clusters development (Italian model) and the factors of its success. Besides, its comparative analysis with the Russian economic reality, where this phenomenon is quite recent, is provided. The research is conducted on the base of Special Economic Zones, the analogue of cluster model in Russia, which is being developed under the direct control of Russian government. The case analysis methodology was applied. At the end the research delivers the analysis of different features of Russian clusters’ development process represented in a SWOT table and defines some directions of possible future research development.