Miracle-dz/UniFAR-FTUs huggingface dataset:
Imprecise Soft Constraint Problems

We define interval-valued soft constraints, where users can associate an interval of preference values, rather than a single value, to each instantiation of the variables of the constraints. This allows us to model a form of uncertainty and imprecision that is often found in real-life problems. We then define several notions of optimal solutions for such problems, providing algorithms to find optimals and also to test whether a solution is optimal. Besides the usefulness of the algorithms, that can be the base for an environment where to reason with uncertainty in soft constraints problems, it is important to notice that most of the times these algorithms require the solution of a soft constraint problem. This means that it is possible to handle uncertainty in soft constraints without increasing the computational effort to reason with such problems. We also show that the same results hold if users are allowed to use multiple disjoint intervals rather than a single one.
Application of the curvelet transform for pipe detection in GPR images

This paper is dedicated to the detection of buried pipes with a ground penetrating radar (GPR). The images from GPR acquisitions also called B-scan are corrupted by clutter and noise. In order to remove these undesirable items we propose to use the properties of the curvelet transform. We're using this method as a first step of the automatic detection of hyperbola in a B-scan.
Efficient Auction Mechanisms for Supply Chain Procurement

We consider multiunit Vickrey auctions for procurement in supply chain settings. This is the first paper that incorporates transportation costs into auctions in a complex supply network. We first introduce an auction mechanism that makes simultaneous production and transportation decisions so that the total supply chain cost is minimized and induces truth telling from the suppliers. Numerical study shows that considerable supply chain cost savings can be achieved if production and transportation costs are considered simultaneously. However, the buyer's payments in such auctions can be high. We then develop a new Vickrey-type auction that incorporates the buyer's reservation price function into quantity allocation and payment decision. As a result, the buyer has some control over his payments at the expense of introducing uncertainty in the quantity acquired in the auction.
The Self-Reflective Writing Scale (SRWS): a new measure to assess self-reflection following self-experiential cognitive behaviour therapy training

ABSTRACT It has been hypothesized that capacity for reflection is a key metacognitive skill in therapist development. However, the measurement of reflection in psychotherapy has proved problematic. The primary purpose of the present study has been to develop a theory-based measure of reflection, the Self-Reflective Writing Scale (SRWS). The SRWS encompasses measures of personal-self reflection (PS) and therapist-self reflection (TS). The development of the SRWS is described. Reliability and validity of the SRWS were assessed in the context of a self-practice/self-reflection (SP/SR)cognitive behavioural therapy training program where clinical psychology students practiced therapy techniques on themselves and reflected on the experience. Trainers’ co-ratings of the SRWS reached an acceptable level of inter-rater reliability. As a test of criterion-related validity, the association between students' reflective skill and an independent rating of their interpersonal skills was examined. As predicted, the level of therapist-self reflectivity was positively correlated with interpersonal skills in the therapeutic context. However, personal-self reflectivity was negatively correlated with students’ interpersonal skills. We suggest a possible explanation for this apparently surprising result. Although these tests of reliability and validity are preliminary and the results are modest, it is suggested that the SRWS holds promise as a measure of therapists' reflective ability.
Three-Phase Power Converter Stabilization via Total Energy-Shaping

The three-phase power converter mathematical model expressed in Park coordinate is represented in PCH (port controlled Hamiltonian) system form, which is able to manage so much constant load as variable; the controller design for the converter is carried out by the IDA-PBC (interconnection and damping assignment-passivity based control) technique, assigning to the closed loop dynamics to a desired energy function, modifying in a suitable form the interconnection and damping matrices. The control objectives are directed to maintain the DC regulation voltage at the output converter even with variable load, while the input power factor stays unitary; at the same time, the controller is robust to changes in the input voltage
Exploiting Query Structure and Document Structure to Improve Document Retrieval Effectiveness

In this paper we present a systematic analysis of document retrieval using unstructured and structured queries within the score region algebra (SRA) structured retrieval framework. The behavior of di®erent retrieval models, namely Boolean, tf.idf, GPX, language models, and Okapi, is tested using the transparent SRA framework in our three-level structured retrieval system called TIJAH. The retrieval models are implemented along four elementary retrieval aspects: element and term selection, element score computation, score combination, and score propagation. The analysis is performed on a numerous experiments evaluated on TREC and CLEF collections, using manually generated unstructured and structured queries. Unstructured queries range from the short title queries to long title + description + narrative queries. For generating structured queries we exploit the knowledge of the document structure and the content used to semantically describe or classify documents. We show that such structured information can be utilized in retrieval engines to give more precise answers to user queries then when using unstructured queries.
Algebraic reasoning and completeness in typed languages

We consider the following problem in proving observational congruences in functional languages: given a call-by-name language based on the simply-typed λ-calculus with algebraic operations axiomatized by algebraic equations E, is the set of observational congruences between terms exactly those provable from (β), (&eegr;), and E? We find conditions for determining whether β&eegr;E-equational reasoning is complete for proving the observational congruences between such terms. We demonstrate the power and generality of the theorems by presenting a number of easy corollaries for particular algebras.
Community Networks as lead users in online public services design

Computer professionals are used to conceive people who use the applications they develop as users, or, in the best case, as consumers. People are owner of a fundamental sovereignty right which allows them to play an active role in designing the computer-based systems shaping their working and social life. This role cannot be played in isolation: a community which converges over a shared understanding is a precious asset for designing computer-based systems and online services. The net makes this change feasible, and both the private and the public sector can effectively exploit these new perspectives.
Redescription Mining: Structure Theory and Algorithms

We introduce a new data mining problem--redescription mining--that unifies considerations of conceptual clustering, constructive induction, and logical formula discovery. Redescription mining begins with a collection of sets, views it as a propositional vocabulary, and identifies clusters of data that can be defined in at least two ways using this vocabulary. The primary contributions of this paper are conceptual and theoretical: (i) we formally study the space of redescriptions underlying a dataset and characterize their intrinsic structure, (ii) we identify impossibility as well as strong possibility results about when mining redescriptions is feasible, (iii) we present several scenarios of how we can custom-build redescription mining solutions for various biases, and (iv) we outline how many problems studied in the larger machine learning community are really special cases of redescription mining. By highlighting its broad scope and relevance. we aim to establish the importance of redescription mining and make the case for a thrust in this new line of research.
Exploiting V2G to optimize residential energy consumption with electrical vehicle (dis)charging

The potential breakthrough of pluggable (hybrid) electrical vehicles (PHEVs) will impose various challenges to the power grid, and esp. implies a significant increase of its load. Adequately dealing with such PHEVs is one of the challenges and opportunities for smart grids. In particular, intelligent control strategies for the charging process can significantly alleviate peak load increases that are to be expected from e.g. residential vehicle charging at home. In addition, the car batteries connected to the grid can also be exploited to deliver grid services, and in particular give stored energy back to the grid to help coping with peak demands stemming from e.g. household appliances. In this paper, we will address such so-called vehicle-to-grid (V2G) scenarios while considering the optimization of PHEV charging in a residential scenario. In particular, we will assess the optimal car battery (dis)charging scheduling to achieve peak shaving and reduction of the variability (over time) of the load of households connected to a local distribution grid. We compare (i) a business-as-usual (BAU) scenario, without any intelligent charging, (ii) intelligent local charging optimization without V2G, and (iii) charging optimization with V2G. To evaluate these scenarios, we make use of our simulation tool, based on OMNeT++, which combines ICT and power network models and incorporates a Matlab model that allows e.g. assessing voltage violations. In a case study on a three-feeder distribution network spanning 63 households, we observe that non-V2G optimized charging can reduce the peak demand compared to BAU with 64%. If we apply V2G to the intelligent charging, we can further cut the non-V2G peak demand with 17% (i.e., achieve a peak load which is only 30% of BAU).
Configurations structurelles et options d’extensions des systèmes de permis d’émissions négociables

La necessite d’une action mondiale pour limiter les emissions de gaz a effet de serre est reconnue par la majorite des pays, mais l’incapacite du regime climatique international a fournir une regulation globale des rejets de GES dans l’atmosphere a conduit a l’echec de l’approche top-down. Cet impossible consensus a conduit a un point de rupture dans la structure du regime climatique mondial dont temoignent notamment le developpement, avant l’Accord de Paris d’une approche bottom-up, fondee sur une gouvernance climatique polycentrique et multiniveaux. C’est dans ce contexte qu’emergent et se developpent, a differentes echelles administratives, les dix-neuf systemes de permis d’emissions negociables aujourd’hui en fonctionnement dans le monde. De fait, aucune homogeneite n’est recherchee dans la conception de ces mecanismes de reglementation. Les choix structurels sont dependants des caracteristiques et contraintes politiques et economiques de la zone geographique a laquelle ils appartiennent. Les configurations et les effets de l’elargissement des systemes de permis negociables sont encore debattus et cette these apporte des recommandations sur la maniere dont ces extensions et connexions pourraient avoir lieu. A partir d’analyses de la litterature empirique et de simulations a l’aide d’un modele d’equilibre partiel pour le secteur energetique (modele POLES), nous preconisons la mise en place de mecanismes de cloisonnement sectoriel et de restrictions aux echanges de permis. En effet, dans un contexte caracterise par des constructions heterogenes de systemes de permis d’emissions negociables, une diffusion non-universelle de ces marches et une inclusion non-integrale de tous les secteurs de l’economie, nous concluons que deux types d’ajustements sont essentiels. Premierement, nous demontrons la necessite d’une configuration et d’un cloisonnement sectoriel des marches, cela afin d’impulser une dynamique d’innovations, de limiter les impacts sur la competitivite internationale et de rendre conforme le systeme aux exigences des politiques connexes. Deuxiemement, nous justifions l’interet des mecanismes de restriction aux echanges internationaux de permis d’emissions negociables ; ils permettent en particulier une meilleure redistribution des gains lies a l’echange, tout en reduisant le cout total de la politique climatique et les quantites de GES emis par rapport a une pure segmentation des marches. Finalement, l’existence de plusieurs prix du carbone apparait incontournable dans le contexte actuel d’une gouvernance climatique mondiale heterogene et d’une multiplicite d’objectifs politiques nationaux. Encourager le developpement de prix differents par secteur et par pays permettrait, sous certaines conditions, de favoriser l’acceptabilite politique, de renforcer l’efficacite environnementale et d’ameliorer l’efficience economique des systemes de permis d’emission.
Impact of Internet Technology Usage on Job Performance of Senior Secondary School Teachers in Kaduna State Nigeria

The Internet nowadays is the twenty-four hours ’teacher, and is one of the leading sources of vital information nowadays. Therefore, this research was conceptual in nature and survey research design. It examined the contribution of the technology (internet technology) toward the enhancement of Job performance amongst secondary school teachers in central senatorial district of Kaduna State. For the purpose of this study, six (6) secondary schools were selected and the selection was based on the secondary schools that have internet facility in the senatorial zone. Both primary and secondary data sources were used by the researchers in the course of the study. The population of the study was 6000 in which the research applied the require sample size of Mark Saunder2009. The respondents were teachers, and 300 of them were involved as the sampling size. The instruments used in this study was one evaluation forms of questionnaire with two section, the first section of the questionnaire was based on teacher Perceive Internet Usage and the second segment was on measure Teacher’s Job Performance. The result of the research certainly showed the importance of internet in secondary school and the ICT would help the teachers in their various disciplines to boasting their knowledge and there is the need for encouraging teachers to utilise the bounty that in ICT. The question and the research hypothesis of the research was tested by using simple frequencies, mean and standard deviation was used and F-test (ANOVA) and (PPMR) correlation coefficient was use to retain or reject the null hypothesis. The study recommended that it is high time for the teachers to further their education and to have positive changes in their attitude towards the using internet technology for their discipline so that the achievement of the educational objectives will be achieved. Furthermore, the stakeholders of Secondary School education are called upon to ensure that only teachers who are computer literate would be employed. Attention of curriculum reviewers has also been drawn to the fact that they should design the curriculum that is relevant to the present contemporary so that it will dance to the tune of the present society.
A visual-inertial fusion based tracking system for mobile augmented reality

Recently, smart phones are usually equipped with cameras and motion sensors. This means that mobile phones have become good platforms to deploy augmented reality (AR) applications. We propose a new tracking system for AR which uses inertial measurement units (gyroscope, accelerometer and magnetic field sensor) combined with a camera to automatically detect and track a dominant plane in the scene without prior knowledge about the environment. Meanwhile, it also estimates the pose of the device, so the rendered virtual objects can be correctly overplayed on the real view. While tracking the plane and computing the camera pose with respect to the scene, the solution also needs to construct and update the map of the scene, which consists of keyframes and keypoints in our scenario. Finally, we implement our system and test its performance on Android smart phones. Our experimental results show that the system can achieve real-time and drift-free performance and the tracking is quite accurate and robust.
An interpretation of the log likelihood ratio as a measure of waveform coder performance

The log likelihood measure has been widely used in speech research for comparing speech signals. Recently, it has been proposed as a measure for assessing the quality of coded speech. In this paper we present an interpretation of the log likelihood ratio measure within the theoretical framework of a waveform coder distortion model. We then discuss the implications of this interpretation and show how it can be applied to the formulation of better objective measures of waveform coder performance.
Design issues for wireless sensor networks and smart humidity sensors for precision agriculture: A review

Precision agriculture is a process in which information and technology is used for collection of high resolution spatio-temporal data regarding atmospheric and soil conditions from farm land. With the help of farm land data and an appropriate crop-growth model, a decision support system regulates the agricultural needs precisely in order to gain maximum benefits for farmer. Application of Wireless Sensor Networks (WSN) provides a low cost and easy to implement solution for automatic data collection from farmlands. Various design issues for WSN in context of precision agriculture have been reviewed in this paper. Humidity (RH) sensors play a crucial role for WSN for precision agriculture applications. This paper also reviews various requirements of Humidity sensors characteristics in context of WSN application for precision agriculture. In the later section of the paper, in depth comparative review of recent research work done in field of design and performance modeling of humidity sensor has been given.
Speaker-independent vowel recognition: spectrograms versus cochleagrams

The ability of multilayer perceptrons (MLPs) trained with backpropagation to classify vowels excised from natural continuous speech is examined. Two spectral representations are compared: spectrograms and cochleagrams. The features used to train the MLPs include discrete Fourier transform (DFT) or cochleagram coefficients from a single frame in the middle of the vowel, or coefficients from each third of the vowel. The effects of estimates of pitch, duration, and the relative amplitude of the vowel were investigated. The experiments show that with coefficients alone, the cochleagram is superior to the spectrogram in classification performance for all experimental conditions. With the three additional features, however, the results are comparable. Perceptual experiments with trained human listeners on the same data revealed that MLPs perform much better than humans on vowels excised from context. <<ETX>>
Message Correlation for Conversation Reconstruction in Service Interaction Logs

The problem of understanding the behavior of business processes and of services is rapidly becoming a priority in medium and large companies. To this end, recently, analysis tools as well as variations of data mining techniques have been applied to process and service execution logs to perform OLAP-style analysis and to discover behavioral (process and protocol) models out of execution data. All these approaches are based on one key assumption: events describing executions and stored in process and service logs include identifiers that allow associating each event to the process or service execution they belong to (e.g., can correlate all events related to the processing of a certain purchase order or to the hiring of a given employee). In reality, however, such information rarely exists. In this paper, we present a framework for discovering correlations among messages in service logs. We characterize the problem of message correlation and propose novel algorithms and techniques based on heuristics on the characteristics of conversations and of message attributes that can act as identifier for such conversations. As we will show, there is no right or wrong way to correlate messages, and such correlation is necessarily subjective. To account for this subjectiveness, we propose an approach where algorithms suggest candidate correlators, provide measures that help users understand the implications of choosing a given correlators, and organize candidate correlators in such a way to facilitate visual exploration. The approach has been implemented and experimental results show its viability and scalability on large synthetic and real-world datasets. We believe that message correlation is a very important and challenging area of research that will witness many contributions in the near future due to the pressing industry needs for process and service execution analysis.
Interactive Conceptual Tutoring in Atlas-Andes

Atlas-Andes is a dialogue enhanced model tracing tutor (MTT) integrating the Andes Physics tutoring system (Gertner ~ VanLelm 2000) with the Atlas tutorial dialogue system (Freedman et al. 2000). Andes is a MTT that presents quantitative physics problems to students. Each problem solving action entered by students is highlighted either red or green to indicate whether it. was correct or not. This basic feedback is terlned red-greeu feedback. Furthermore, when students get stuck in the midst of problem solving and request help, Andes provides hint sequences designed to help them achieve the goal of soh’ing the problem as quickly as possible. Atlas provides Andes with the capability of leading students through directed lines of reasoning that teach basic physics conceptual knowledge, such as Newton’s Laws. The purpose of these directed lines of reasoning is to provide a solid foundation in conceptual physics to promote deep learning and to enable students to develop meaningful problem solving strategies. While students in elementary mechanics courses have demonstrated an ability to master the skills required to solve quantitative physics problems, a nmnber of studies have revealed that the same students perform very poorly when faced with qualitative physics problems (Halloun & Hestenes 1985b; 1985a; Hake 1998). Furthermore, the naive conceptions of physics that they bring with them when they begin a formal study of physics do not change significantly by the time they finish their classes (Halloun & Hestenes 1985b). Similarly, MTTs in a wide range of domains have commonly been criticized for failing to encourage deep learning (VanLehn et al. 2000). If students do not reflect upon the hints they are given, but instead simply continue guessing until they perform an action that receives positive feedback, they tend to learn the right actions for the wrong reasons (Aleveu, Koedinger, K~ Cross 1999;