Miracle-dz/UniFAR-FTUs huggingface dataset:
Experiences in improving the state of the practice in verification and validation of knowledge-based systems

Knowledge-based systems (KBS) are in general use in a wide variety of domains. As reliance on these types systems grows, the need to assess their quality and validity reaches critical importance. As with any software, the reliability of a KBS can be directly attributed to the application of disciplined programming and testing practices throughout the development life-cycle. However, there are some essential differences between conventional (i.e., procedural) software and knowledge-based systems, both in construction and use. The identification of these differences affect the verification and validation process and the development of techniques to handle them is the basis of considerable on-going research in this field. For the past three years IBM (Federal Systems Company - Houston) and the Software Technology Branch ( STB) of NASA~Johnson Space Center have been working to improve the "’state of the practice" in verification and validation of Knowledge-based systems. To date, the primary accomplishment has been the development and teaching of a four-day workshop on verification and validation of knowledge-based systems. With the hope of improving the impact of these workshops, we are now working directly with NASA KBS projects to employ concepts taught in the workshop. This paper describes two projects currently being assisted as part of this effort. In addition to describing each project, this paper describes problems encountered and solutions proposed in each case.
TOWARDS THE FACECODE DYNAMIC FACE SYNTHESIS BASED ON ESTIMATION IN SPEECH

The (digital) transmission of talking faces requires a high bandwidth that not every target channel is able to provide, even if powerful image compression algorithms are used. Therefore, a special face coding algorithm would be highly desirable. Unfortunately, development of such an algorithm has been hindered by the general problem of image motion estimation. In this paper we present a video-based system for face motion processing similar to the well-known voder-vocoder system for processing and coding acoustic speech signals. Like the vocoder, our ’face coder’ consists of two independent parts: an analysis part for tracking non-rigid face motion, and a synthesis part for producing face animations. Results are shown for face motion tracking and the subsequent animation derived from either the raw motion data or the outcome of Principal Component Analysis. The automatic tracking results were evaluated by comparison with a set of manually tracked points.
The Implications Of Gross Fixed Capital And Unemployment Rate General Government Deficit. Empirical Study At The European Level

In this paper we evaluate the influence of the modification of public investment level and unemployment rate on the general government deficit at the European Union level. We create a regression model that shows that a sustained and increased investment policy and the reduction of unemployment rate have a favorable effect on the objective of minimizing the budget deficit. In the last years European Union’s countries had to face a difficult problem concerning fiscal policy. They have to make public investments to stimulate economic growth and in the same time they have to meet the convergence criteria’s of public deficit. On the other hand, EU has to deal with a higher rate of unemployment. Through our model we try to see how European Union countries should implement their political strategies on unemployment and investment with the main objective of reducing the general government deficit.
Robust Speech Detection using SEM and SFN

Speech recognition, the problem of performance degradation is the difference between the model training and recognition environments. Silence features normalized using the method as a way to reduce the inconsistency of such an environment. Silence features normalized way of existing in the low signal-to-noise ratio. Increase the energy level of the silence interval for speech and non-speech classification accuracy due to the falling. There is a problem in the recognition performance is degraded. This paper proposed a robust speech detection method in noisy environments using a SFN (silence feature normalization) and SEM (speech energy maximize). In the high signal-to-noise ratio for the proposed method was used to maximize the characteristics receive less characterized the effects of noise by the speech energy. Cepstral feature distribution of speech and non-speech characteristics in the low signal-tonoise ratio and improves the recognition performance. Result of the recognition experiment, recognition performance improved compared to the conventional method.
The gene expression patterns of BMPR2, EP300, TGFβ2, and TNFAIP3 in B-Lymphoma cells

Objective The results of a previous study showed that a clear dysregulation was evident in the global gene expression of the BCL11A-suppressed B-lymphoma cells. In this study, the bone morphogenetic protein receptor, type II (BMPR2), E1A binding protein p300 (EP300), transforming growth factor-β2 (TGFβ2), and tumor necrosis factor, and alpha-induced protein 3 (TNFAIP3) gene expression patterns in B-cell malignancies were studied. Methods The relative expression levels of BMPR2, EP300, TGFβ2, and TNFAIP3 mRNA in B-lymphoma cell lines, myeloid cell lines, as well as in cells from healthy volunteers, were determined by real-time quantitative reverse transcript-polymerase chain reaction (qRT-PCR) with SYBR Green Dye. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as reference. Results The expression level of TGFβ2 mRNA in B-lymphoma cell lines was significantly higher than those in the cells from the healthy control (P<0.05). However, the expression level of TNFAIP3 mRNA in B-malignant cells was significantly lower than that of the healthy control (P<0.05). The expression levels of BMPR2 and EP300 mRNA showed no significant difference between B-malignant cell lines and the healthy group (P>0.05). In B-lymphoma cell lines, correlation analyses revealed that the expression of BMPR2 and TNFAIP3 (r=0.882, P=0.04) had significant positive relation. The expression levels of BMPR2, EP300, and TNFAIP3 mRNA in cell lines from myeloid leukemia were significantly lower than those in the cells from the healthy control (P<0.05). The expression levels of TGFβ2 mRNA showed no significant difference between myeloid leukemia cell lines and the healthy control or B-malignant cell lines (P>0.05). The expression levels of BMPR2, EP300, and TNFAIP3 mRNA in B-lymphoma cells were significantly higher than those of the myeloid leukemia cells (P<0.05). Conclusion Different expression patterns of BMPR2, EP300, TGFβ2, and TNFAIP3 genes in B-lymphoma cells exist.
Interconnecting WSNs with Fast Moving Nodes: Experiments in Real-World Scenarios

From agriculture to industry, from the office to our homes, Wireless Sensor Networks (WSNs) are becoming a part of everyday life in many application areas. In typical WSN applications, the sensor nodes are fixed and interconnected amongst each other and to the outside world on a permanent basis. However, in certain types of applications, where the area to sense is wide and sensors are sparsely distributed, a different approach can be used. A mobile node can roam in the sensor field to collect and exchange information with disconnected clusters of nodes. This paper addresses the limitations of real world sensor networks with such moving nodes. To understand the behavior of a typical WSN node in these situations, two types of experiments were conducted. To begin with, the communication performance was measured, in a static scenario, establishing the base-line behavior. Afterwards, a second set of experiments was carried out with fast moving nodes at different speeds. Finally, the results of the two experiments were compared and analyzed.
Algorithm for temporal anomaly detection in WSNs

Knowledge discovery and data analysis in resource constrained wireless sensor networks faces different challenges. One of the main challenges is to identify misbehaviors or anomalies with high accuracy while minimizing energy consumption in the network. In this paper, we extend a previous work of us and we present an algorithm for temporal anomalies detection in wireless sensor networks. Our experiments results show that our algorithm can efficiently and accurately detect anomalies in sensor measurements. It also produces low false alarm rate for slow variation time series measurements without harvesting the source of energy.
Analysing Consumer Behavior towards Social Media

ocial media allows customers and prospects to communicate directly to your brandrepresentative or about your brand with their friends. However, the obvious question is: who arethe people interacting online and how engaged are they in online activities? The aim of this paperis to conceptualize consumers' activities in social media by examining the motivations behind theactivities. By offering a more detailed description of the differences in consumer use of socialmedia, the study extends existing research on consumer activities related to user-created content.
Semisupervised learning for molecular profiling

Class prediction and feature selection are two learning tasks that are strictly paired in the search of molecular profiles from microarray data. Researchers have become aware how easy it is to incur a selection bias effect, and complex validation setups are required to avoid overly optimistic estimates of the predictive accuracy of the models and incorrect gene selections. This paper describes a semisupervised pattern discovery approach that uses the by-products of complete validation studies on experimental setups for gene profiling. In particular, we introduce the study of the patterns of single sample responses (sample-tracking profiles) to the gene selection process induced by typical supervised learning tasks in microarray studies. We originate sample-tracking profiles as the aggregated off-training evaluation of SVM models of increasing gene panel sizes. Genes are ranked by E-RFE, an entropy-based variant of the recursive feature elimination for support vector machines (RFE-SVM). A dynamic time warping (DTW) algorithm is then applied to define a metric between sample-tracking profiles. An unsupervised clustering based on the DTW metric allows automating the discovery of outliers and of subtypes of different molecular profiles. Applications are described on synthetic data and in two gene expression studies.
Generalized estimating equations for longitudinal generalized Poisson count data with regression effects on the mean and dispersion level.

Generalized estimating equations (GEE) fit parameters based on sums of weighted residuals, which may be applied for example to the Poisson distribution. We discuss Generalized Poisson (GP) response data. This distribution has a more flexible variance function than the Poisson distribution and has an additional dispersion parameter. To fit this parameter, second level estimating equations based on covariance residuals are neces- sary. This requires knowledge of variances of empirical covariances, which for most discrete distributions except the binary cannot be derived from first level GEE. We approximate them by a novel approach. We allow for regression on mean and overdispersion parame- ters. In an application we deal with the outsourcing of patent filing processes. Exploratory data analysis tools developed earlier by the authors are utilized to choose regression for the dispersion parameters. For the given data, our approach will outperform longitudinal Poisson regression and GP setups with constant dispersion.
An ASM-Based Approach for Mobile

In this work we present the use of a novel language based on Gurevich Abstract State Machiness7] to specify active mobile objects semantics. We focus on the mobility support based on the explicit interaction abstraction between units of speciication. The mobility is expressed by changing the communication topology dynamically. We provide the formal semantics of the new approach and show how the proposed method provides an adequate way to reason about a speciication based on mobile objects.
Design and Implementation of a Real-Time Wireless Sensor Network

This paper describes the development of wireless sensor network prototype that gathers biometrical data and posture information from several wearable sensor networks and sends it in real-time to a personal computer where the information is monitored and stored. The wireless sensor network is based on a low power real-time MAC protocol that was designed and implemented in the MICAz platform. This paper also presents some analytical results and several experimental results regarding the behavior of the developed system.
Image annotation using SVM

The paper describes an innovative image annotation tool for classifying image regions in one of seven classes - sky, skin, vegetation, snow, water, ground, and buildings - or as unknown. This tool could be productively applied in the management of large image and video databases where a considerable volume of images/frames there must be automatically indexed. The annotation is performed by a classification system based on a multi-class Support Vector Machine. Experimental results on a test set of 200 images are reported and discussed.
Visitors and Contributors in Wikipedia

Wikipedia continues to provide the community with a vast collection of articles tha t cover almost all the different areas of knowledge. The on-line encyclopedia is built upon altru istic contributions from individuals and organizations, which constitutes an absolutely new approach in knowledge compilation and distribution. The progression of Wikipedia to a mass phenomenon has promoted several initiatives devoted to deal with different issues concerning it, specially the quality of its contents and the authoring of its c n ributions. However, very few attention has been paid to aspects related to users’ attitudes and behavio r when browsing the information it offers. For this reason, this paper aims to find patterns that can descr ib how users interact and behave when visiting the Wikipedia’s pages. We will consider the two most common fo rms of interaction between Wikipedia and its users: visits and contributions (edits). From these observ ations we will be used obtain different metrics, such as the degree of participation or the reluctance exh ibit d by users which, in addition, will be used to perform a comparison amongst the different Wikipedia edition s. Our study is based on a sample of the requests that users submit to Wikipedia, which we receive in the form o f log lines. Its results can help to better understand the nature of the relationship between Wikipedia and its use rs, and to properly characterize the different interactions between them.
Semantic-Based Composite Document Ranking

The traditional information retrieval techniques mainly employ statistics of words in document text and/or the link structures of document sets to rank, which have been used successfully in the global web search. However, they produce unsatisfied results for Enterprise search (ES), because ES is very different from Web search. This paper proposes a novel rank approach fitting for the ES environment. With the support of an ontology describing prior knowledge about the target domain, we first mine semantic information (concepts and relations between them) from queries (documents) with which to understand the query intentions (document contents) and exploit them for evaluating the query-document relevance, and then the semantic linkages between documents are built and consumed for evaluating the document importance, finally, the above two evaluations are integrated to produce the final ranking list. Experiments show that our approach results in significant improvements over existing solutions.
The Measurement of Carried Cartons using Multiple Kinect Sensors

We propose a system to measure the dimensions of carton boxes carried on a conveyer belt with an accuracy of 5mm, required in logistic applications. Our system estimates the dimensions through a series of depth images with relatively low resolution taken by unsynchronized multiple sensors. To achieve the accuracy, we first obtain the dimensions via the distance between parallel planes instead of edge lengths, then correct errors caused by time lags among sensors using timestamps, and finally correct other measurement errors by regression analysis. We evaluated our method on three types of cartons carried on a conveyer belt in 0.9m/s, and confirmed the required accuracy.
Let’s Talk! An interactive intervention to support children’s language development

ABSTRACT This study developed, delivered and evaluated an interactive intervention, which targeted three- and four-year-old children’s oral language. The intervention was carried out over twice-weekly sessions, for ten weeks. The first weekly session was a group shared storybook reading session with a puppet and the second weekly session consisted of planning, acting out and reviewing a planned pretend play episode based on the storybook, which was read in that week’s first session. Ninety-four children were randomly assigned to a control or treatment group and were tested at pre- and post-test on a battery of vocabulary and narrative assessments. The results of a Randomised Controlled Trial showed a statistically significant effect on the receptive vocabulary and productive vocabulary of the children in the treatment group, with medium to large effect sizes. A further positive effect concerned the Mean Length of Utterance (MLU) of the children in the treatment group.
Structuring the Information Flow in Component-Based Protocol Implementations for Wireless Sensor Nodes

Protocol implementations for wireless sensor networks have particular requirements. We analyze shortcomings of existing architectures and propose the separation of packet flow and meta information as a key abstraction for a new architecture. To handle meta information, we use a publish/subscribebased, anonymous and asynchronous paradigm, for which we describe a blackboard-based implementation.
Mapping Cortical Thickness of the Patients with Unilateral End-Stage Open Angle Glaucoma on Planar Cerebral Cortex Maps

Purpose To estimate and compare cerebral cortex thickness in patients with unilateral end-stage glaucoma with that of age-matched individuals with unaffected vision. Methods 14 patients with unilateral end-stage primary open angle glaucoma (POAG) and 12 age-matched control individuals with no problems with vision were selected for the study based on detailed ophthalmic examination. For each participant 3D high-resolution structural brain T1-weighted magnetization prepared MR images were acquired on a 3.0 T scanner. Brain cortex thickness was estimated using the FreeSurfer image analysis environment. After warping of subjects' cortical surfaces to FreeSurfer common space, differences between POAG and control groups were inferred at the group analysis level with the General Linear Model. Results The analysis performed revealed local thinning in the visual cortex areas in the POAG group. Statistically significant differences form 600 mm2 clusters located in the Brodmann area BA19 in the left and right hemisphere. Conclusion Unilateral vision loss due to end-stage neuropathy from POAG is associated with significant thinning of cortical areas employed in vision.
On strongly polynomial algorithms for some classes of quadratic programming problems ⁄y

In this paper we survey some results concerning polyno- mial and/or strongly polynomial solvability of some classes of quadratic programming problems. The discussion on polynomial solvability of con- tinuous convex quadratic programming is followed by a couple of models for quadratic integer programming which, due to their special structure, allow polynomial (or even strongly polynomial) solvability. The theoret- ical merit of those results stems from the fact that a running time (i.e. the number of elementary arithmetic operations) of a strongly polyno- mial algorithm is independent of the input size of the problem.
Towards Model Checking of Simulation Models for Embedded System Development

Modeling and simulation has been widely used to develop embedded systems and cyber-physical systems, especially in safety-critical domains. While models for such systems are required to be rigidly verified, simulation offers only partial observations on them with a limited number of test cases. Model checking techniques of timed automata would not be directly applied to formal verification of simulation models due to the differences in execution semantics and model composition. In order to enable model checking of simulation models, this paper presents an algorithm to obtain region transition systems from models written in an M&S formalism. Such region transition systems could be exhaustively checked by the model checking techniques without any modification.
Near Infrared Spectroscopy based Soil Nitrogen measurement - A Review

Spectroscopy is a rapid, simple, non-destructive and analytical technique, which has been increasingly used for agricultural and food analysis processes. Soil nitrogen, being an important macronutrient of the soil, measurement of total Nitrogen (TN) content can be used as an index of crop productivity. Near infra-red (NIR) spectroscopy can accurately predict the soil nitrogen content by evaluating reflected Near Infra-red rays intensity. The need of expensive and bulky spectrometers is eliminated by use of light-emitting diode (LED) as a Near Infra-red light source, making the system cost effective and portable. The paper reviews brief study of different technologies used for the purpose and explains in detail the spectroscopy concept. A comparative study between various modern calibration methods has lead to a conclusion that, wavelet analysis can offer utmost accuracy of prediction.
A tunable light source at 1.6 [mu]m by difference-frequency mixing in cesium titanyl arsenate

An optical system is investigated to generate tunable coherent radiation at 1.6 /um by difference-frequency mixing (DFM) in cesium titanyl arsenate (CsTiOAsO4 , CTA). The input laser sources are provided by a krypton-ion laser at Ap = 530.9 nm and a Ti:sapphire ring laser whose output is tunable from As = 770 810 nm. To increase the generated output power, the CTA crystal is placed inside a cavity, forming a configuration for resonant difference-frequency mixing (RDFM). To verify the feasibility of the proposed schemes, DFM and RDFM experiments were performed. The generated output by DFM was tunable from 1566.9 nm to 1652.5 nm with output powers in the 1 uW range for a pump power of 156 mW and a signal power of 37 mW. The phase-matching angles for DFM in CTA were also experimentally measured and were compared with those calculated from the Sellmeier equations for CTA. The RDFM experiment was performed for a fixed input signal at A8 = 790.0 nm. The maximum generated output idler power at Ai = 1618.7 nm was 100 W for pump and signal powers of 230 mW and 57 mW, respectively. Thesis Supervisor: Dr. N. C. Wong Title: Research Scientist, Research Laboratory of Electronics