Miracle-dz/UniFAR-FTUs huggingface dataset:
Language-Models for Questions

Natural-language question-answering is a promising interface for retrieving information in mobile contexts because it by-passes the problem of presenting documents and interim search results on a small screen. This paper considers language-models suitable for rapid predictive text-input and spoken input of natural-language questions. It describes a varied corpus of fact-seeking questions posed by users online and analyzes its structure. We find it to be highly constrained lexically despite its wide spectrum of topics, with a per-word perplexity less than 47 with around 2.6% of words in the test set out-of-vocabulary. One implication is that predictive interfaces can greatly speed up the input of natural-language questions with a keypad or stylus. Another is that automatic speech-recognition of such questions can be quite accurate.
Digitus: towards a platform for the characterization of the finger biomechanics in fine manipulation.

This work presents the results of the preliminary experiments performed with DIGITUS, a 2 active and 1 passive Degrees of Freedom (DoFs) fully backdrivable closed kinematics chain planar robot for finger biomechanics investigation. After a brief description of the mechanism and actuation, the paper focuses on the FPGA based control electronics. To test the platform usability two experiments were performed. The first experiment shows the DIGITUS capability to generate force disturbances at the end-effector. The second experiment shows how DIGITUS performs circular trajectories by means of appropriate force-fields at the end-effector.
Example-based plastic deformation of rigid bodies

Physics-based animation is often used to animate scenes containing destruction of near-rigid, man-made materials. For these applications, the most important visual features are plastic deformation and fracture. Methods based on continuum mechanics model these materials as elastoplastic, and must perform expensive elasticity computations even though elastic deformations are imperceptibly small for rigid materials. We introduce an example-based plasticity model based on linear blend skinning that allows artists to author simulation objects using familiar tools. Dynamics are computed using an unmodified rigid body simulator, making our method computationally efficient and easy to integrate into existing pipelines. We introduce a flexible technique for mapping impulses computed by the rigid body solver to local, example-based deformations. For completeness, our method also supports prescoring based fracture. We demonstrate the practicality of our method by animating a variety of destructive scenes.
The Prognostic Value of 18F-FDG PET/CT for Hepatocellular Carcinoma Treated with Transarterial Chemoembolization (TACE)

18F-Fluoro-deoxyglucose (FDG) PET/CT can be used to monitor the biological behavior of hepatocellular carcinoma (HCC). Baseline PET/CT has prognostic value in HCC patients, but there is litter knowledge of the PET/CT changes after treatment. We evaluated 27 HCC patients treated with transarterial chemoembolization (TACE) from June 2011 to July 2012, and we investigated the prognostic value of PET/CT. Patients were followed up with regular clinical and laboratory examinations and contrast-enhanced spiral computed tomography (CT). Furthermore, PET/CT assessments were collected and analyzed before (range 1~15 d) and after the first month of TACE (range, 27~45d). We tested the prognostic value of the tumor standardized uptake value (TSUV) and normal liver SUV(LSUV) according to the VOI (volume of interest). The SUVs were used to assess the relationship between the treatment response and survival. To assess their prognostic value, we evaluated the areas under the receiver operating characteristic (ROC) curves of different SUVs for predicting survival. Finally, the median overall survival (OS) and time to progression (TTP) for 27 patients were 15.4 months (95%CI, 3.3-27.5 months) and 11.4 months (95%CI, 6.7-16.1 months), respectively. The ΔTSUVmax%, based on the VOI, had the highest discriminative prognostic value and the cutoff PET/CT response was 0.1 with a sensitivity of 100% and a specificity of 95.2%. The OS was significantly better in the PET/CT response group than in the PET/CT non-response group (p=0.025). In conclusion, an early interim PET/CT after TACE may have prognostic value for HCC patients treated with TACE, and the ΔTSUVmax% may help in determining the HCCs viability in patients with high baseline and follow-up18F-FDG uptake.
Implementing a Storage Pattern in the OR Mapping Framework

Heading towards the next decade, a major paradigm shift has been observed in the way the software services are being provided to the enterprises and corporate sector. Corporations and enterprises are switching to www host applications being offered as a service by software vendors and on-premises LOB (Line of Business) applications are taking a toll back. SaaS (Software as a Service) is the new concept. Adapting of SaaS, however, requires that the applications which are being provided as a service should be generalized for users or groups of users and it would require a vast space to be allocated to user or user group. The users or user groups ordinarily correspond to a company or group of companies/businesses and are termed as tenants. In this regard, the architecture of SaaS applications needs to be customized to support certain characteristics — e.g., configurability, maintainability and scalability — to support high storage for hosting resources made available to diverse number of users. This paper, firstly, analyzes new trends in the present day business environment alongside the hardware and software industry that led to the development of SaaS model; and then looks into the characteristics and features that a storage pattern for multi tenant system in SaaS needs to possess in order to put this concept into practice.
A game-theoretic approach for locally detecting overlapping communities in social networks

The study of embedded structure of communities in social and information networks is an extensive studies in this domain and vast variety of community detection methods have been proposed. In this paper we proposed a distributed approach for local and overlapping community detection based on the game theory. In our method, each node is a player and there is an iterative cycle in which players can play their best action from a given set of actions periodically in their turn. Each player decides to become member of a community which has the best influence on it in order to maximize its utility function. According to players' decisions communities will be formed gradually. Therefore, when the game process reaches the Nash equilibrium, the community emerges. We evaluate our method on some common datasets to indicate the performance and sufficiency of it.
A Hybrid Artificial Neural Network-Naive Bayes for solving imbalanced dataset problems in semiconductor manufacturing test process

This paper introduces a hybrid approach, namely Hybrid Artificial Neural Network-Naive Bayes classifier, for two-class imbalanced datasets classification. An imbalanced dataset in semiconductor manufacturing test process is chosen as a case study. Outputs prediction in semiconductor manufacturing is helpful for engineer to identify good/bad products earlier and to avoid the bad units from being processed. This application shows the significance of solving the problems. The proposed hybrid approach presented in this paper uses the concept that an Artificial Neural Network (ANN) provides a guidance to Naive Bayes classifier in making better decision by providing an additional input to Naive Bayes. Several experiments are conducted as comparison to the individual classifiers, which are ANN and Naive Bayes. As a result, the proposed Hybrid approach performs better than the individual classifiers and finally overcomes the imbalanced dataset problems in semiconductor manufacturing test process.
Target detection metrics and tracking for UWB radar sensor networks

A radar sensor network (RSN) is a wireless network system, typically composed of one transmitting (TX) node and several receiving (RX) nodes, aimed at detecting and tracking an intruder (target) moving within a given surveillance area. In this paper, RSNs based on impulse radio ultra-wideband (UWB) are investigated. In the considered system, at each scanning each RX node calculates a soft image of the surveillance area based on the target-scattered UWB pulses. All images are then transferred to a fusion node where the decision about target presence or absence is taken. Optimum decision metrics and likelihood tests are developed, together with approximated metrics reducing the complexity of the detection block. Moreover, it is illustrated how the soft images produced by the RX nodes may be effectively exploited by tracking algorithms relying on Bayesian filters.
Dispersion and Line Formation in Artificial Swarm Intelligence

One of the major motifs in collective or swarm intelligence is that, even though individuals follow simple rules, the resulting global behavior can be complex and intelligent. In artificial swarm systems, such as swarm robots, the goal is to use systems that are as simple and cheap as possible, deploy many of them, and coordinate them to conduct complex tasks that each individual cannot accomplish. Shape formation in artificial intelligence systems is usually required for specific task-oriented performance, including 1) forming sensing grids, 2) exploring and mapping in space, underwater, or hazardous environments, and 3) forming a barricade for surveillance or protecting an area or a person. This paper presents a dynamic model of an artificial swarm system based on a virtual spring damper model and algorithms for dispersion without a leader and line formation with an interim leader using only the distance estimation among the neighbors.
Introduction to the symposium on ambulatory skin conductance

Ambulatory skin conductance as we see it now emerging on the market with products like the Affectiva Qsensor and the Basis B1, was promoted already in 1997 by Picard and Healey [1]. Also prototype devices such as the Empatica E3, the Smartband, and the Philips DTI-2 ([3] and figure 1) typically measure skin conductance at the base of the wrist, since this is a convenient measurement position. However, traditionally skin conductance (electrodermal activity, or galvanic skin response) is measured on the fingers, the palmar region of the palms, or on the soles of the feet. A traditional skin conductance measurement usually is also corrected with a baseline measurement, while for ambulatory measurements this needs to be self-calibrating. These differences in measurement position and procedure are among the factors that cause differences in measurement results.
Distributed Fiber Optic Sensing Technologies and Applications – An Overview

Needs for structural health monitoring in the last decades were rapidly increasing, and these needs stimulated developments of various sensing technologies. Distributed optical fiber sensing technologies have reached market maturity and opened new possibilities in structural health monitoring. Distributed strain sensor (sensing cable) is sensitive at each point of its length to strain changes and cracks. Such a sensor practically monitors one-dimensional strain field and can be installed over all the entire length of the monitored structural members, and therefore provides for integrity monitoring, i.e. for direct detection and characterization of local strain changes generated by damage (including recognition, localization, and quantification or rating). The aim of this paper is to help researchers and practitioners to get familiar with distributed sensing technologies, to understand the meaning of the distributed measurement, and to learn on best performances and limitations of these technologies. Hence, this paper briefly present light scattering as the main physical principles behind technologies, explains the spatial resolution as the important feature for interpretation of measurements, compares performances of various distributed technologies found in the market, and introduces the concept of integrity monitoring applicable to various concrete structures. Two illustrative examples are presented, including applications to pipeline and bridge.
Psychometric properties of the Persian version of Social Avoidance and Distress scale (SADS)

The aim of this study was to investigate the validity, reliability and factor structure of Persian version of social avoidance and distress scale (SADS). For this purpose, 276 students (141 males and 135 females) were selected by convenience sampling. Following by translation and back-translation of SADS, this scale was used along with Social Phobia Inventory (SPIN) and the Beck Scale for Suicidal Ideation (BSSI) to check the convergent and the divergent validities, respectively. Data were analyzed using Pearson's correlation coefficient. The factor analysis showed one factor. The reliability was calculated 0.83 using test-retest method, and the internal consistency was obtained equal to 0.83 using Kuder-Richardson approach. Furthermore, the correlations with SPIN and BSSI were measured 0.62 and 0.21, respectively. So, the reliability and validity of the Persian version of SADS among Iranian university students are acceptable.
Dynamic programming and the graphical representation of error-correcting codes

Graphical representations of codes facilitate the design of computationally efficient decoding algorithms. This is an example of a general connection between dependency graphs, as arise in the representations of Markov random fields, and the dynamic programming principle. We concentrate on two computational tasks: finding the maximum-likelihood codeword and finding its posterior probability, given a signal received through a noisy channel. These two computations lend themselves to a particularly elegant version of dynamic programming, whereby the decoding complexity is particularly transparent. We explore some codes and some graphical representations designed specifically to facilitate computation. We further explore a coarse-to-fine version of dynamic programming that can produce an exact maximum-likelihood decoding many orders of magnitude faster than ordinary dynamic programming.
WS-Advisor: A Task Memory for Service Composition Frameworks

With the proliferation of Web services, it is becoming increasingly important to support the users in selecting the most appropriate compositions of services for a task. We propose a new service discovery and selection framework that utilises the concept of task memories and a social network of task memories. A task memory captures the service composition history and their meta-data such as associated context and user rating. A network of task memories is formed to realise an effective task memory sharing platform among the users.
Fuzzy decision making using the imprecise Dirichlet model

In most applications, probabilities of states of nature in decision making are not known exactly owing to a lack of complete information. If the available information is represented by a small number of statistical data, Walley's imprecise Dirichlet model may be regarded as a tool for determining interval probabilities of states of nature. It turns out that the resulting expected utilities constitute fuzzy sets and the initial decision problem is reduced to a fuzzy-decision problem. A numerical example illustrates the proposed approach to solving decision problems under the scarce information about states of nature. The approach is compared with ? -contaminated (robust) models. This approach can also be applied for the construction of fuzzy sets on the basis of statistical observations.
A Chain-based Fast Data Aggregation Algorithm Based on Suppositional Cells for wireless sensor networks

It is important to gather sensed information with an energy efficient method in sensor networks. Although data collection may save energy and improve information accuracy, it must get this at the cost of decreasing other performances, such as the delay increment. This paper proposes a Chain-based Fast Data Aggregation Algorithm Based on Suppositional Cells (CFDASC) to solve this problem. In this algorithm, we attributed each node to one suppositional cell according to the node location information. The nodes which are in one suppositional cell act as the cluster head of data collection in turn, then the head gathers and transmits data along the cells chain to the sink node. As a result, it accelerates the data aggregation process. Simulation results also show that CFDASC algorithm performs better than PEGASIS algorithm by 50.03% in average packet transmission delay, and takes the cost of tiny energy increment, only 6.07% than that in PEGASIS.
An energy efficient coding scheme for the multiple access relay channel

In this paper, an energy efficient coding scheme for the multiple access relay channel at a fixed desired sum rate is analyzed. We first introduce a coding scheme, then, derive an optimal set of power allocation, which minimizes the network energy consumption while maintaining a desired sum rate. The results show that this scheme significantly outperforms direct and two-hop transmission. Moreover, it reduces the relay energy consumption, which is useful for the shared relays. The results also give a detailed understanding of power consumption regimes and allow a comprehensive description of the optimal message coding and resource allocation for each desired sum rate and channel realization.
Factors influencing continuance intention to use PSTN: A pilot study of an extended expectation confirmation model for legacy technology

A burden exists for many nations, telecom carriers to offer both IP and cellular phone services while still maintaining PSTN services to a small fraction of users. Previous research has focused on adoption of IP and cellular but the study of PSTN continuance usage has not been undertaken. This study identifies factors that influence continuance intention to use PSTN while newer technologies are available. The research model is based on the Expectation Confirmation Model with three additional constructs including subjective norm, fee and switching cost. The results revealed inexpensive fees and perceived usefulness influence intention for continuous use of PSTN.
Interactive Visualization of Weather and Ship Data

This paper focus on the development of a tool for Ship and Weather Information Monitoring (SWIM) visualizing weather data combined with data from ship voyages. The project was done in close collaboration with the Swedish Meteorological and Hydrological Institute (SMHI) who also evaluated the result. The goal was to implement a tool which will help shipping companies to monitor their fleet and the weather development along planned routes and provide support for decisions regarding route choice and to evade hazard. A qualitative usability study was performed to gather insight about usability issues and to aid future development. Overall the result of the study was positive and the users felt that the tool would aid them in the daily work.
Extracting Meeting Topics Using Speech and Documents

The CALO project is an ongoing effort to develop a Cognitive Assistant that Learns and Organizes. Stanford CSLI is working on the meeting assistant section of the CALO project, which involves recording a meeting, dividing the meeting into topics, and summarizing the meeting for later reference. At this point, automated speech recognition has been used to determine the word distributions of the meetings, but the topics are difficult to extract because the speech transcripts still have a high word error. Our goal is to first correlate a set of documents with their associated meetings based on their word distributions and then improve topic extraction for the meetings by using these clusters of related documents and meetings.
Surface area analysis for people number estimation

An important property of surface areas of objects as observed by a calibrated monocular camera is introduced; also improved techniques to apply the property to people number estimation are proposed. Standard surface area (SSA) is defined as the surface area of the reverse projection of an image-pixel onto a plane at specific height in the real world. SSA is calculated for each pixel according to camera calibration parameters. When the target object is bound to a certain plane, for example the floor plane, the sum of SSA along with the foreground pixels of one target object becomes constant. Therefore, simple foreground detection and SSA summation yield the number of target objects. This basic idea was proposed in a prior article, but there were two major limitations. One is that the original model could not be applied to the area directly below the camera. The other is that the silhouette of the target object was limited to a simple rectangle. In this paper we propose improved techniques that remove the limitations. Slant silhouette analysis removes the first limitation, and silhouette decomposition the second. The validity and the effectiveness of the techniques are confirmed by experiments.
A Novel Approach to Indoor RSSI Localization by Automatic Calibration of the Wireless Propagation Model

We propose a novel localization algorithm of mobile sensors based on wireless sensor networks providing RSSI measurements between the mobile and the fixed sensors (anchors) in the network. The algorithm selects and weights the RSSI measurements according to their strength, and it uses a propagation model to transform RSSI measurements into distances, in order to estimate the position of the mobile. The algorithm also uses a virtual calibration method of the propagation model that does not require human intervention. By an experimental setup we show that the localization algorithm increases the performance with respect to the commonly used least mean square algorithm showing also how to achieve a wished accuracy increasing the anchor density.
The Number of Connected Components in Graphs and Its Applications

For any given graph and an integer k, the number of connected components with k vertices in the graph is investigated. For the vertex set of size n and the maximum degree , the number is bounded above by (e ) k ( 1)k . The factor k is essential, since we give the lower bound n 2 k 1 for k < 2n . We also show that all connected components with k vertices are enumerable in O n+m+ (e ) k 1 k 2 log k time with O(n+m) space, where m is the number of edges. Thus, if k is bounded above by some polynomial of n (e.g. is xed and k = O(log n)), we can check all connected components with k vertices in polynomial time of n. Under the assumption, several intractable problems (including Topological Containment (Subgraph Isomorphism), Small Minimum Degree 4 Subgraph, Bipartite Graph Embedding, Steiner Tree, and k-Minimum Spanning Tree) are put into tractable.