Miracle-dz/UniFAR-FTUs huggingface dataset:
Keyword search over relational databases: a metadata approach

Keyword queries offer a convenient alternative to traditional SQL in querying relational databases with large, often unknown, schemas and instances. The challenge in answering such queries is to discover their intended semantics, construct the SQL queries that describe them and used them to retrieve the respective tuples. Existing approaches typically rely on indices built a-priori on the database content. This seriously limits their applicability if a-priori access to the database content is not possible. Examples include the on-line databases accessed through web interface, or the sources in information integration systems that operate behind wrappers with specific query capabilities. Furthermore, existing literature has not studied to its full extend the inter-dependencies across the ways the different keywords are mapped into the database values and schema elements. In this work, we describe a novel technique for translating keyword queries into SQL based on the Munkres (a.k.a. Hungarian) algorithm. Our approach not only tackles the above two limitations, but it offers significant improvements in the identification of the semantically meaningful SQL queries that describe the intended keyword query semantics. We provide details of the technique implementation and an extensive experimental evaluation.
Portraits of work: mapping emerging coworking dynamics

ABSTRACT Today’s patterns of work are very much defined by the ‘lean enterprise’ practice, taking form in organizations that are more competitive, customer-driven and agile on the one hand (Womack, J. P., & Jones, D. T. (2007). Lean Solutions. New York: Simon & Schuster), and the separation of work from time and space on the other (Hochschild, A. (1997). The time bind. New York, NY: Metropolitan Books). Concepts like work and workspace are subject to an evolving nature and get a new meaning (Kirsh, D. (2000). A few thoughts on cognitive overload. Intellectia, 1(30), 19–51). This triggered the rise of new working spaces, fuelled by the aftermath of the global economic crisis that transformed the practices and meanings of work. Nevertheless, this applies only to particular sectors. This paper builds on the case of Genk, an important economic pole in the Limburg Region of Belgium. The development in the region has always been related to labour-intensive industrial activities. In light of these working shifts targeting mainly big companies/employers, Genk has turned a blind eye on the local proprietors. What about the small entrepreneurs/community economies addressing mainly the local clientele? What evolution do we see in their working pattern? By using a specific visualization tool, a series of interviews were conducted in order to explore in a playful way, existing social and economic networks. The interviews reveal networks that shape a coworking model. The paper will further present the scale of this ‘coworking’ phenomenon experienced in Genk, perceived to be the ‘new model of coworking’ in the context of the collaborative and sharing economy.
Analysis of a Very Massive DA White Dwarf via the Trigonometric Parallax and Spectroscopic Methods

By two different methods, we show that LHS 4033 is an extremely massive white dwarf near its likely upper mass limit for destruction by unstable electron captures. From the accurate trigonometric parallax reported herein, the effective temperature (Teff = 10,900 K) and the stellar radius (R = 0.00368 R☉) are directly determined from the broadband spectral energy distribution—the parallax method. The effective temperature and surface gravity are also estimated independently from the simultaneous fitting of the observed Balmer line profiles with those predicted from pure-hydrogen model atmospheres—the spectroscopic method (Teff = 10,760 K, log g = 9.46). The mass of LHS 4033 is then inferred from theoretical mass-radius relations appropriate for white dwarfs. The parallax method yields a mass estimate of 1.310-1.330 M☉ for interior compositions ranging from pure magnesium to pure carbon, respectively, while the spectroscopic method yields an estimate of 1.318-1.335 M☉ for the same core compositions. This star is the most massive white dwarf for which a robust comparison of the two techniques has been made.
Community Level Physiological Profiles (CLPP), Characterization and Microbial Activity of Soil Amended with Dairy Sewage Sludge

The aim of the present work was to assess the influence of organic amendment applications compared to mineral fertilization on soil microbial activity and functional diversity. The field experiment was set up on a soil classified as an Eutric Cambisol developed from loess (South-East Poland). Two doses of both dairy sewage sludge (20 Mg·ha−1 and 26 Mg·ha−1) and of mineral fertilizers containing the same amount of nutrients were applied. The same soil without any amendment was used as a control. The soil under undisturbed native vegetation was also included in the study as a representative background sample. The functional diversity (catabolic potential) was assessed using such indices as Average Well Color Development (AWCD), Richness (R) and Shannon–Weaver index (H). These indices were calculated, following the community level physiological profiling (CLPP) using Biolog Eco Plates. Soil dehydrogenase and respiratory activity were also evaluated. The indices were sensitive enough to reveal changes in community level physiological profiles due to treatment effects. It was shown that dairy sewage amended soil was characterized by greater AWCD, R, H and dehydrogenase and respiratory activity as compared to control or mineral fertilized soil. Analysis of variance (ANOVA) and principal component analysis (PCA) were used to depict the differences of the soil bacterial functional diversity between the treatments.
Relationship of the Duration and Timing of Exercise with Sleep Quality in Community-Dwelling Adults

Background and ObjectiveaaWe aimed to compare the differences in the subjective and objective sleep quality, and quality of life (QOL) according to the duration and timing of exercise in community-dwelling adults, and to compare these between the exercise group (EG) and non-exercise group (non-EG) in insomnia patients. MethodsaaWe recruited 223 volunteers (EG: n = 119, age: 60.8 ± 12.8 years; non-EG: n = 104, age 61.6 ± 13.3 years), who visited to 3 Public Health Centers in a rural area of South Korea. The Pittsburgh Sleep Quality Index (PSQI), Korean version of Epworth Sleepiness Scale (KESS), and Short Form-12 Health Survey Questionnaire (SF-12) were administered for each subject. Actigraphy (Actiwatch-2, Philips Respironics Co.) recording was done for 7 days at home, and we included the data of 183 subjects in our analysis. We compared the scores of questionnaires and objective sleep parameters according to the duration and timing of exercise, and compared these between the EG and non-EG in insomnia patients. resultsaaPhysical component summary (PCS) scores in SF-12 were higher in the EG for more than 60 minutes per day. In the subjects with outdoor exercise, the afternoon EG had lower PSQI scores and higher KESS scores. In insomnia patients, PCS scores in the EG was higher than those of the non-EG. ConclusionsaaCommunity-dwelling adults who exercised for more than one hour showed higher physical QOL compared to those for less than one hour. Insomnia patients who exercised also showed higher physical QOL. In outdoor exercise, afternoon exercise would be beneficial for subjective sleep quality than morning exercise. Sleep Med res 2018;9(2):83-91
Packaging for power semiconductors based on the 3D printing technology Selective Laser Melting

In this paper a new packaging technique based on Selective Laser Melting is presented which tries to replace solder or sinter layers, respectively bond wires. Following the intended contact geometry and concept, simulations show the influence of the contact geometry on the thermo-mechanical stress the device is committed to. First investigations on the constraints of the production process are represented. Finally the feasibility of the proposed packaging technique is shown.
Distillation of secret key and entanglement from quantum states

We study and solve the problem of distilling a secret key from quantum states representing correlation between two parties (Alice and Bob) and an eavesdropper (Eve) via one–way public discussion: we prove a coding theorem to achieve the ‘wire–tapper’ bound, the difference of the mutual information Alice–Bob and that of Alice–Eve, for so–called classical–quantum–quantum–correlations, via one–way public communication. This result yields information–theoretic formulae for the distillable secret key, giving ‘ultimate’ key rate bounds if Eve is assumed to possess a purification of Alice and Bob's joint state. Specializing our protocol somewhat and making it coherent leads us to a protocol of entanglement distillation via one–way LOCC (local operations and classical communication) which is asymptotically optimal: in fact we prove the so–called ‘hashing inequality’, which says that the coherent information (i.e. the negative conditional von Neumann entropy) is an achievable Einstein–Podolsky–Rosen rate. This result is known to imply a whole set of distillation and capacity formulae, which we briefly review.
A Language of Life: Characterizing People Using Cell Phone Tracks

Mobile devices can produce continuous streams of data which areoften specific to the person carrying them. We show that cellphone tracks from the MIT Reality dataset can be used to reliablycharacterize individual people. This is done by treating eachperson's data as a separate language by building a standardn-gram language model for each ``author. '' We then compute theperplexities of an unlabelled sample as based on each person'slanguage model. The sample is assigned to the user yielding thelowest perplexity score. This technique achieves 85\% accuracyand can also be used for clustering. We also show how languagemodels can also be used for predicting movement and proposemetrics to measure the accuracy of the predictions. Finally, wedevelop an alternative method for identifying individuals bycounting the subsequences in a sample which are unique to theirauthors. This is done by building a generalized suffix tree of thetraining set and counting each subsequence from a sample which isunique for some person as evidence towards identifying that personas the author. We present the identification and prediction as apart of a {\sc humble} human behavior modeling framework, outlinegeneral modeling goals, and show how our methods help. Ourresults suggest that people's medium-scale movement behavioralpatterns, at the granularity of cell tower footprints, can be usedto characterize individuals.
ChangeDetector: a site-level monitoring tool for the WWW

This paper presents a new challenge for Web monitoring tools: to build a system that can monitor entire web sites effectively. Such a system could potentially be used to discover "silent news" hidden within corporate web sites. Examples of silent news include reorganizations in the executive team of a company or in the retirement of a product line. ChangeDetector, an implemented prototype, addresses this challenge by incorporating a number of machine learning techniques. The principal backend components of ChangeDetector all rely on machine learning: intelligent crawling, page classification and entity-based change detection. Intelligent crawling enables ChangeDetector to selectively crawl the most relevant pages of very large sites. Classification allows change detection to be filtered by topic. Entity extraction over changed pages permits change detection to be filtered by semantic concepts, such as person names, dates, addresses, and phone numbers. Finally, the front end presents a flexible way for subscribers to interact with the database of detected changes to pinpoint those changes most likely to be of interest.
GENETIC EVOLUTION AND CO-EVOLUTION OF GAME STRATEGIES

GENETIC EVOLUTION AND CO-EVOLUTION OF GAME STRATEGIES John R. Koza Computer Science Department Stanford University Stanford, CA 94305 USA Koza@Sunburn.Stanford. Edu 415-941-0336 ABSTRACT The problem of discovering a strategy for playing a game can be viewed as requiring discovery of a computer program. This paper describes the recently developed "genetic programming" paradigm which genetically breeds populations of hierarchical computer programs to solve problems. The computer programs are evolved using the Darwinian principle of survival of the fittest and the genetic operation of sexual recombination.
Propagation of Data Fusion

In a relational database, tuples are called “duplicate” if they describe the same real-world entity. If such duplicate tuples are observed, it is recommended to remove them and to replace them with one tuple that represents the joint information of the duplicate tuples to a maximal extent. This remove-and-replace operation is called a fusion operation. Within the setting of a relational database management system, the removal of the original duplicate tuples can breach referential integrity. In this paper, a strategy is proposed to maintain referential integrity in a semantically correct manner, thereby optimizing the quality of relationships in the database. An algorithm is proposed that is able to propagate a fusion operation through the entire database. The algorithm is based on a framework of first and second order fusion functions on the one hand, and conflict resolution strategies on the other hand. It is shown how classical strategies for maintaining referential integrity, such as DELETE cascading, are highly specialized cases of the proposed framework. Experimental results are reported that (i) show the efficiency of the proposed algorithm and (ii) show the differences in quality between several second order fusion functions. It is shown that some strategies easily outperform DELETE cascading.
Anomaly Intrusion Detection System using Hamming Network Approach

Intrusion detection is an interesting approach that could be used to improve the security of network system. IDS detects suspected patterns of network traffic on the remaining open parts through monitoring user activities. The major problems of existing models is recognition of new attacks, low accuracy, detection time and system adaptability. In this paper, evolving anomaly intrusion detection system is constructed using hamming and MAXNET Neural Network for recognize attack class in the network traffic. The result is encouraging, the detection rate is 95% which is relatively high. We describe another approach based on Multilayer Perceptrons (MLP) network and compare the results of the two approaches to evaluate the system. The experimental results demonstrate that the designed models are promising in terms of accuracy and computational time of real word intrusion detection. Training and testing data obtains from the Defense Advanced Research Projects Agency(DARPA) intrusion detection evaluation datasets.
Theory and application of annealing algorithms for continuous optimization

Simulated annealing algorithms for optimization over continuous spaces come in two vzuietiex Markov chain algorithms and moditied gradient algorithms. Unfortunately, the~ is a gap between the theory and the application of these algorithm5 the convergence conditions cannot be practically implemented. In this paper we suggest a practical methodology for implementing the modified gradient annealing algorithms based on their relationship to the Markov chain algorithms.
A Decision Tree Algorithm Pertaining to the Student Performance Analysis and Prediction

of an educational institute can be measured in terms of successful students of the institute. The analysis related to the prediction of students academic performance in higher education seems an essential requirement for the improvement in quality education. Data mining techniques play an important role in data analysis. For the construction of a classification model which could predict performance of students, particularly for engineering branches, a decision tree algorithm associated with the data mining techniques have been used in the research. A number of factors may affect the performance of students. Here some significant factors have been considered while constructing the decision tree for classifying students according to their attributes (grades). In this paper four different decision tree algorithms J48, NBtree, Reptree and Simple cart were compared and J48 decision tree algorithm is found to be the best suitable algorithm for model construction. Cross validation method and percentage split method were used to evaluate the efficiency of the different algorithms. The traditional KDD process has been used as a methodology. The WEKA (Waikato Environment for Knowledge Analysis) tool was used for analysis and prediction. Results obtained in the present study may be helpful for identifying the weak students so that management could take appropriate actions, and success rate of students could be increased sufficiently.
Global path planning for robust Visual Servoing in complex environments

We incorporate sampling-based global path planning with Visual Servoing (VS) for a robotic arm equipped with an in-hand camera. The path planning accounts for a number of constraints: 1) maintaining continuous visibility of the target within the camera's field of view, 2) avoiding visual occlusion of target features caused by the workspace obstacles, robot's body, or the target itself, 3) avoiding collision with physical obstacles or self collision, and 4) joint limits. Incorporating these constraints enhances the applicability of VS to significantly more complex environments/tasks, thereby making the resulting VS much more robust. The proposed planner explores the camera space, i.e. 3D Cartesian space, for permissible camera paths satisfying the aforementioned constraints by iteratively extending a search tree in camera space and simultaneously tracking these paths in the robot's joint space using a local planner. The planned camera path is then projected into the image space and tracked using an image-based visual servoing scheme. The validity and effectiveness of the proposed approach in accomplishing VS tasks in complex environments are demonstrated through a number of simulations on a 6-dof robot arm moving among obstacles.
Surgical procedures in neonatal rats

The explicit goal is to minimize procedural differences between young and adult animals (see Simons and Carvell, 1989) Anesthesia was induced with isoflurane and maintained with halothane in 50/50 N2/O2 mixture. For P13-15 and P20-22 pups, initial halothane concentration was 2% which was then reduced to 1.5% after approximately 3 minutes to avoid respiratory depression. For P27-29 and P65 animals, initial halothane concentration was 2.5% reduced to 1.8% after 3-5 minutes. Depth of anesthesia during surgery was monitored using respiratory rate and absence of foot or tail withdrawal in response to pinch. In P13-15 and P20-22 pups, respiratory rate of approximately 60 breaths per minute was found to correspond to adequate anesthetic control with minimal risk of lethal overdose. Hypothermia, especially in younger animals, was prevented by warming the rats with a 20W halogen lamp. In our experience, the lamp should be positioned no closer than 8 inches from the body to avoid halothane-related malignant hyperthermia.
KUL: Recognition and Normalization of Temporal Expressions

In this paper we describe a system for the recognition and normalization of temporal expressions (Task 13: TempEval-2, Task A). The recognition task is approached as a classification problem of sentence constituents and the normalization is implemented in a rule-based manner. One of the system features is extending positive annotations in the corpus by semantically similar words automatically obtained from a large unannotated textual corpus. The best results obtained by the system are 0.85 and 0.84 for precision and recall respectively for recognition of temporal expressions; the accuracy values of 0.91 and 0.55 were obtained for the feature values type and val respectively.
Are Youths on Income Support Less Happy? Evidence from Australia

The central research question addressed in this paper is how receipt of income support payments affects the well-being of youths. Using 1997-2004 panel data from a nationally representative survey of Australian youths, we attempt to estimate the size of the welfare stigma faced by Australian youths, where stigma is defined as the effect of welfare receipt on reported happiness levels. In analysing the determinants of happiness, we argue that it is important to control for dynamics and initial conditions. The latter arguably measures an initial setpoint of happiness which the psychological literature has found strong support for. In contrast to the general findings of the existence of a welfare stigma for adults, based on our results using dynamic panel probit models, our findings suggest that for Australian youths, there is a small negative but not statistically significant stigma associated with welfare receipt.
Can We Improve Web Accessibility for Users with Below Average Cognitive Capacity?

Previous empirical work has suggested that performance in using the Web as an information resource deteriorates when the cognitive load imposed by the content of Web pages exceeds the cognitive capacity of the user [3], [7]. This problem is particularly pronounced in users with below average cognitive capacity. The work reported in this paper describes the design, rationale and development of an adaptive interface for the use of special needs and elderly users with reduced cognitive capacity. ABEL (AccessiBility and Effective Learning) conducts an assessment of the user's cognitive capacity and then selects and directs the user to Web pages which impose an appropriate level of cognitive load. ABEL incorporates an innovative means of measuring individual variation in user working memory capacity which is suitable for special needs and elderly users. ABEL is likely to improve Web accessibility for educational and recreational purposes particularly for groups for whom Web use has previously been found to be problematic.
The effects of blocked and random practice on the learning of three variations of the golf chip shot

ABSTRACT The current study investigated the acquisition of three variations of a golf chipping task using either a blocked or random practice schedule. Twenty-four individuals performed a 5.5 m chipping task in which they practised from three different ground lies. Half were randomly assigned to a blocked practice condition in which they practised all trials of one task variation before moving on to the next variation. The other half were assigned to a random practice condition in which they practised the three tasks in a random order. Acquisition consisted of 54 total trials. Ten minutes following acquisition a six-trial blocked retention test was performed, followed by a six-trial random retention test. During acquisition, individuals significantly improved their chipping performance (p < .001) but no group differences emerged (p > .05). The random condition was significantly more accurate in chipping performance during the random retention test (p < .05) but no group differences emerged for the blocked retention test (p > .05). These results suggest that increased contextual interference during practice of a golf chip task facilitates learning. Practitioners should seek to implement increased levels of CI while instructing novice golfers.