Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual-Arm Robotic Manipulation under Uncertainties and Task-Based Redundancy

Robotic manipulators are mostly employed in industrial environments, where their tasks can be prescribed with little to no uncertainty. This is possible in scenarios where the deployment time of robot workcells is not prohibitive, such as in the automotive industry. In other contexts, however, the time cost of setting up a classical robotic automation workcell is often prohibitive. This is the case with cellphone manufacturing, for example, which is currently mostly executed by human workers. Robotic automation is nevertheless desirable in these human-centric environments, as a robot can automate the most tedious parts of an assembly. To deploy robots in these environments, however, requires an ability to deal with uncertainties and to robustly execute any given task. In this thesis, we discuss two topics related to autonomous robotic manipulation. First, we address parametric uncertainties in manipulation tasks, such as the location of contacts during the execution of an assembly. We propose and experimentally evaluate two methods that rely on force and torque measurements to produce estimates of task related uncertainties: a method for dexterous manipulation under uncertainties which relies on a compliant rotational degree of freedom at the robot’s gripper grasp point and exploits contact with an external surface, and a cooperative manipulation system which is able to identify the kinematics of a two degrees of freedom mechanism. Then, we consider redundancies in dual-arm robotic manipulation. Dual-armed robots offer a large degree of redundancy which can be exploited to ensure a more robust task execution. When executing an assembly task, for instance, robots can freely change the location of the assembly in their workspace without affecting the task execution. We discuss methods that explore these types of redundancies in relative motion tasks in the form of asymmetries in their execution. Finally, we approach the converse problem by presenting a system which is able to balance measured forces and torques at its end-effectors by leveraging relative motion between them, while grasping a rigid tray. This is achieved through discrete sliding of the grasp points, which constitutes a novel application of bimanual dexterous manipulation.
Query Optimization Revisited: An AI Planning Perspective

The generation of high quality query plans is at the heart of query processing in traditional database management systems as well as in heterogeneous distributed data sources on corporate intranets and in the cloud. A diversity of techniques are employed for query plan generation and optimization, many of them proprietary. In this paper we revisit the problem of generating a query plan using AI automated planning. Characterizing query planning as AI planning enables us to leverage state-of-the-art planning techniques, as well as supporting the longer-term endeavor of purposeful information gathering as part of a larger data-intensive, task-driven system. While our longterm view is broad, here our efforts focus on the specific problem of cost-based join-order optimization, a central component of production-quality query optimizers. We characterize the general query planning problem as a delete-free planning problem, and query plan optimization as a contextsensitive cost-optimal planning problem. We propose algorithms that generate high quality query plans, guaranteeing optimality under certain conditions. Our approach is general, supporting the use of a broad suite of domain-independent and domain-specific optimization criteria. Experimental results demonstrate the effectiveness of AI planning techniques for query plan generation and optimization.
Instability of unsaturated compacted soil slope due to rain infiltration

The stability analyses of compacted embankments are conventionally determined extending the mechanics of saturated soils using saturated shear strength parameters. This approach is considered to be conservative; however, it may not always be reliable as other scenarios may contribute to compacted embankments failure. In many cases, the instability of compacted embankments is associated with the loss of suction values due to rainfall induced infiltration. A rational procedure for studying the embankment stability should take account of the variation of matric suction and the coefficient of permeability associated with different rainfall events. In the study presented in this paper, stability analyses were carried out on a homogeneous embankment constructed using typical glacial till from Western Canada. Three different types of triaxial shear tests were performed to determine shear strength parameters of compacted soil specimens for four possible scenarios of failure taking account of both saturated and unsaturated conditions using conventional and modified triaxial shear apparatus. Finite element analysis was undertaken using GEO-SLOPE software considering infiltration of water into embankment due to different rainfall events. The results of study show that typically shallow circular failures above water front occur due to infiltration rather than infinite slope type failures in compacted embankments. RÉSUMÉ L’analyse de la stabilité des remblais compactés est conventionnellement basée sur la mécanique des sols saturés en utilisant les paramètres de résistance au cisaillement à l’état saturé. Cette approche est jugée conservatrice; cependant, celle-ci n’est pas toujours fiable puisque d’autres facteurs pourraient contribuer à la rupture des remblais compactés. Dans de nombreux cas, l'instabilité des remblais compactés est associée à la perte de succion en raison de l'infiltration d'eau lors de précipitations. Une procédure rationnelle pour étudier la stabilité du remblai doit tenir compte de la variation de la succion matricielle et du coefficient de perméabilité associés à différents événements de précipitations. Dans l'étude présentée dans le présent article, les analyses de stabilité ont été effectuées sur un remblai homogène typique construite en utilisant un till glaciaire de l'Ouest canadien. Trois différents types d'essais de cisaillement triaxial ont été effectués pour déterminer les paramètres de résistance au cisaillement de spécimens de sol compacté pour quatre scénarios possibles de rupture en tenant compte des conditions saturées et non saturés en utilisant un appareil triaxial de cisaillement cenventionnel aussibien que modifié. L'analyse par éléments finis a été effectuée à l'aide du logiciel GEO-SLOPE et considérant l'infiltration d'eau dans le remblai sous différents événements de précipitations. Les résultats de l'étude montrent que généralement, dans des remblais compactés, des plans de rupture circulaires de faible profondeur se produisent au-dessus du front d'eau en raison de l'infiltration plutôt que des plans de rupture de pente infinie.
Water tracing with environmental DNA in a high-Alpine catchment

Abstract. Alpine streams are particularly valuable for downstream water resources and for ecosystem conservation. However, the details of where and when water is stored and released in the heterogeneous mountain environment are rarely known. The use of physico-chemical flow path tracers is particularly challenging due to the temporary accumulation and storage of water in the form of snow and ice. Alternatively, biological tracers might complement information on flow and storage of water, especially as the different microhabitats in Alpine aquatic systems are inhabited by characteristic organismal communities. In this study, we explored the potential of particles of environmental DNA found in the water (eDNA) to characterize hydrological flow paths and connectivity in an Alpine catchment in Switzerland. Between March and September 2017, we sampled water at multiple time points at 11 sites distributed over the 13.4 km2 Vallon de Nant catchment for genetic species information based on naturally occurring eDNA. The sites correspond to three different water source types and habitats (main channel, tributaries, and springs). Comparison of typical hydrological tracers and eDNA with temporal evolution of streamflow revealed that in the main channel and in the tributaries, the change in streamflow, dq/dt, is strongly correlated with biological richness. In springs, electrical conductivity was found to have a positive but not as strong correlation with biological richness. At the catchment scale, our results show that biological richness as indicated by the diversity detected by eDNA samples. When streamflow is increasing, transport of additional, and probably terrestrial, DNA into water storage or flow compartments is occurring. Such processes include overbank flow, stream network expansion and retraction, and hyporheic exchange. In general, our results highlight the importance of considering the at-site sampling habitat in combination with upstream connected habitats to understand how streams integrate eDNA over a catchment and to interpret spatially distributed eDNA samples, both for hydrological and biodiversity assessments. We identify next steps to be addressed to use eDNA as an independent tracer of Alpine water sources and we provide recommendations for future observation of eDNA in Alpine stream ecosystems.
Hey Siri. Ok Google. Alexa: A topic modeling of user reviews for smart speakers

User reviews provide a significant source of information for companies to understand their market and audience. In order to discover broad trends in this source, researchers have typically used topic models such as Latent Dirichlet Allocation (LDA). However, while there are metrics to choose the “best” number of topics, it is not clear whether the resulting topics can also provide in-depth, actionable product analysis. Our paper examines this issue by analyzing user reviews from the Best Buy US website for smart speakers. Using coherence scores to choose topics, we test whether the results help us to understand user interests and concerns. We find that while coherence scores are a good starting point to identify a number of topics, it still requires manual adaptation based on domain knowledge to provide market insights. We show that the resulting dimensions capture brand performance and differences, and differentiate the market into two distinct groups with different properties.
IIT-KGP at COIN 2019: Using pre-trained Language Models for modeling Machine Comprehension

In this paper, we describe our system for COIN 2019 Shared Task 1: Commonsense Inference in Everyday Narrations. We show the power of leveraging state-of-the-art pre-trained language models such as BERT(Bidirectional Encoder Representations from Transformers) and XLNet over other Commonsense Knowledge Base Resources such as ConceptNet and NELL for modeling machine comprehension. We used an ensemble of BERT-Large and XLNet-Large. Experimental results show that our model give substantial improvements over the baseline and other systems incorporating knowledge bases. We bagged 2nd position on the final test set leaderboard with an accuracy of 90.5%
A Programming Language for Software Product Lines

A software product line is a set of software systems with well-defined commonalities and variabilities defined in terms of product features. In order to implement feature-based variability within the object-oriented programming paradigm, we present a novel linguistic approach based on the concept of program deltas. The implementation of a product line is divided into a core module and a set of delta modules. The core module comprises a set of classes that implement a valid product of the product line. Delta modules specify changes to the core module in order to incorporate specific product features. A product implementation is obtained by changing the core module according to the applicable delta modules. We propose a constraint-based type system for core and delta modules that provides static guarantees that the resulting product implementations are safe without having to generate all possible products. In order to show the feasibility of our approach, we use Featherweight Java for the implementation of product classes.
Molecular genetic diversity and conservation priorities of Egyptian rabbit breeds

The limited rabbit resources in Egypt are threatened by the danger of extinction, whereas genetic diversity studies of native breeds could play a vital role in conservation and improvement of these breeds. In this study, 3 native rabbit breeds: Gabali (G), Baladi Red (BR) and Baladi Black (BB), in addition to New Zealand White (NZW), were genotyped using 12 microsatellite markers. All the typed microsatellites were polymorphic by average number of alleles 5.25 per locus. Observed and expected heterozygosity per locus averaged 0.62 and 0.68, respectively. The average polymorphic information content was 0.71 and the highest polymorphic information content was recorded in locus SOL33 by 0.85. All the studied loci except SAT7 and SAT2 showed deviation from Hardy-Weinberg equilibrium with significant level. The inbreeding coefficient of the individuals relative to the total population was 0.07. The within-population heterozygote deficit averaged 0.07 and ranged from 0.141 in BR to 0.015 in BB breeds. The highest pairwise differentiation among the populations was recorded between BB and NZW (0.071), while the lowest value was recorded between BR and both of G (0.038) and BB (0.039). The lowest pairwise Nei’s genetic distance was recorded between BR and BB (0.190), while the highest was recorded between NZW and BB breeds (0.409). BR and G populations were clustered together forming an admixed mosaic cluster. BR recorded the highest contribution in the aggregate genetic diversity based on the three prioritisation methods used.
Predicting Paper Acceptance Rank in citation graph

Measuring research impact and having an objective picture of the institutions is essential for students, parents and funding agencies. We tend to apply several machine learning methods to rank research institutions based on predicting the number of accepted papers at upcoming top conferences. In our proposal, We aim at a three-phase experiment, starting with a simple average method and then extend our training dataset by finding the similarity of conferences, engineer trend features and use linear regression, rank SVM and ensemble models to improve our predictions.
Experimental Determination of Penetration Loss into Multi-Storey Buildings... (AL Imoize et al)

Received Mar 01, 2019 Revised Apr 30, 2019 Accepted Aug 23, 2019 This study presents building pentration loss into and around multi-storey buildings at 900 and 1800MHz based on experimental data obtained through drive test, using Test Mobile System (TEMS) investigation tools. The received signal level was measured inside and outside three buildings; the Senate building of the University of Lagos (B1), Mike Adenuga Towers (B2) and the Sapetro Towers (B3) located in Victoria Island, Lagos Nigeria. The building penetration loss (BPL) was derived from measurements, and the average and standard deviations of the BPL were computed. Results showed that the average BPL of 17.0dB and 13.8dB obtained from building B1 at 900 and 1800MHz, respectively, are comparatively higher than those of buildings B2 and B3. The standard deviation of the BPL shows an increase from 5.2dB at 900MHz to 7.8dB at 1800MHz for building B1, whereas it fell drastically from 8.65dB at 900MHz to 1.40dB at 1800MHz for B2, and a similar behaviour as in B1 is seen for building B3, where it rises sharply from 1.55dB at 900MHz to 6.55dB at 1800MHz. This is in agreement with the general trend of increasing penetration loss with increase in frequency except for building B2 where an anomaly is observed. In order to examine the correlation between the measured and the predicted BPL, cubic regression was used to fit a third order polynomial to the measured BPL. Overrall, the fitted models could find useful applications in the design of novel and robust BPL models for modern multi-floored buildings. Keyword:
Mutual Information Input Selector and Probabilistic Machine Learning Utilisation for Air Pollution Proxies

An air pollutant proxy is a mathematical model that estimates an unobserved air pollutant using other measured variables. The proxy is advantageous to fill missing data in a research campaign or to substitute a real measurement for minimising the cost as well as the operators involved (i.e., virtual sensor). In this paper, we present a generic concept of pollutant proxy development based on an optimised data-driven approach. We propose a mutual information concept to determine the interdependence of different variables and thus select the most correlated inputs. The most relevant variables are selected to be the best proxy inputs, where several metrics and data loss are also involved for guidance. The input selection method determines the used data for training pollutant proxies based on a probabilistic machine learning method. In particular, we use a Bayesian neural network that naturally prevents overfitting and provides confidence intervals around its output prediction. In this way, the prediction uncertainty could be assessed and evaluated. In order to demonstrate the effectiveness of our approach, we test it on an extensive air pollution database to estimate ozone concentration.
The Antecedents and Rebroadcast Consequences of Clickbait

Clickbait is a method of framing articles’ titles to induce readers to click on them, and is a common feature of online media today. We use a publicly available data set consisting of articles from 25 media organizations, each of which is rated as clickbait or not by human respondents, and augment it with Twitter retweet count, sentiment analysis and topic modeling. We demonstrate that human interest articles are positively associated with clickbait. We also show that the fraction of people with journalistic backgrounds in an organization’s top management team is positively related to its clickbait usage. Finally we show that clickbait is rebroadcast less than non-clickbait on social media. Our results serve as a cautionary message to media organizations and digital marketers, who may be inadvertently harming the reach of their content by using clickbait.
Assessment of Joint Range of Motion Measured by a Stereo Camera

Many studies have been conducted to measure joint Range of Motion (ROM) to approach Activities of Daily Living (ADL) assessments using nonintrusive three-dimensional (3D) sensors, such as motion capture devices and the Kinect, as alternatives to goniometer. While these sensors have been widely used to measure joint angles, the measuring range is restrictive and the complexity to setup has prevented these devices to be used as self-measurements during home-based training. With the recent progress on human pose estimation using computer vision approach, locations of joints can be detected from a vision camera in real time. This achievement opens a possibility to measure ROMs in a wide area and in any locations as long as the subject is located inside the camera’s Field of View (FOV). This study extends the current human pose estimation to capture joints in 3D using a stereo camera and compares the ROMs of shoulder and elbow derived from the proposed method with those derived from the Kinect. Measurements of ROM using both devices show good agreement indicating that the proposed method is valid to measure ROMs, as a replacement for the Kinect. Keywords-rehabilitation; computer vision; range of motion; activities of daily living; 3D human pose estimation.
Viitanen Childcare voucher and labour market behaviour : Experimental evidence from Finland

This paper provides experimental estimates of the impact of a voucher for private care within the Nordic system of universal provision of public care. The private childcare voucher acted as a significant boost for new childcare entrepreneurs to enter the market thus increasing the overall childcare provision in the municipalities participating in the experiment. In a market that was providing high-quality, lowcost public childcare, a voucher is nevertheless found to have a significant, positive effect for the use of private childcare with zero to negligible effects on the use of public care and labour force participation.
Efficacy of oregano oil as a biocide agent against pathogens in vitro, using lux reporter gene technology

This study aimed to determine the antimicrobial activity and strength of kill of Himalayan oregano oil (HOO) across a range of dilutions typically formulated for potential topical use in healthcare settings, using bioluminescent constructs of bacterial pathogens as real time biosensors for rapid bactericidal monitoring. Escherichia coli, Pseudomonas aeruginosa and Methicillin sensitive Staphylococcus aureus, previously genetically modified by addition of the luxCDABE operon to express bioluminescence, were used as reporters of viable metabolically active cells to show a real time in situ antimicrobial effect of oregano oil. On the other hand, for genetically non-modified methicillin resistant S. aureus and Candida albicans, viable count method was used to assess the antimicrobial effect of oregano oil. Minimal inhibitory concentration of Himalayan oregano oil (HOO) and its major components, carvacrol and thymol, were found to be between 0.03 and 0.16%. High positive correlation was obtained between viable count and bioluminescence. These findings suggest that bioluminescence has the capability to replace the plate culture method for evaluating the efficacy of antimicrobial products. HOO may have the potential as a natural potent bactericide in the health care setting, as it has demonstrated bactericidal action towards pathogens in a short time (40-220 s). This is the first in vitro method used to assess the antimicrobial activity of oregano oil using lux reporter gene technology as an accurate measure of kill rates which is captured in real-time with high reproducibility and fidelity of responses such that comparisons are accurate. Key words: Oregano oil, bioluminescence, viable count, lux operon, antimicrobial.
Molecular cloning and characterization of pearl millet polyphenol oxidase and its role in defense against downy mildew

Polyphenol oxidase partial gene PG-PPO was cloned and characterized from Pennisetum glaucum (pearl millet) which showed 42% identity to a PPO sequence isolated from wheat at the region of Copper B with a score of 40 and e-value of 2.8. Multiple sequence alignment results revealed similarity to polyphenol oxidase (PPO) sequences from wheat, trifolium, lettuce, apricot, tobacco, tomato, pokeweed, apple, grape and poplar especially at the Copper B region of PPO. The 395 bp pearl millet PPO sequence was AT rich (53.3%) and contained the highly conserved amino acids of histidine-rich copper binding sites similar to PPO sequences from other crops. Results also indicated that PPO in pearl millet exists in multi copy. The role of the isolated PPO gene during pearl millet-downy mildew interaction was analyzed and the results showed significantly higher and rapid accumulation of PPO mRNAs in resistant pearl millet seedlings inoculated with Sclerospora graminicola in comparison to the susceptible control, demonstrating that the PPO plays a prominent role in pearl millet defense against pathogens, particularly downy mildew pathogen.