Miracle-dz/UniFAR-FTUs huggingface dataset:
Management of historical data in continuous integration systems

Continuous integration is an agile software practice where code is checked in frequently and subsequently built and tested automatically. Due to the maturity of this practice at the company Ericsson, the frequency of these automated builds is increasing at the company and as such, much more data about the development process is generated. However, the software systems that gather and present this data was not designed to scale with the current data growth. This has led to several problems surrounding the continuous integration process and the evolution of the software systems that support this process. This master’s thesis reports on the design and evaluation of two different prototypes for management of historical data in continuous integration systems. One of these prototypes uses a NoSQL database for storing historical data and one uses a relational database. The constructed prototypes where designed specifically to address problems related to scalability and performance of the current continuous integration systems in use at Ericsson. Evaluation shows that the prototypes solve scalability problems and increase performance of current systems by separating live and historical data. The value of the prototypes is further motivated by investigating how historical data in a continuous integration system can be utilized for the benefit of the company that has this data.
Optical probe pressure effects on cutaneous blood flow.

The variation of blood flow characteristics caused by the probe pressure during noninvasive studies is of particular interest within the context of fundamental and applied research. It has been shown previously that the weak local pressure induces vasodilation, whereas the increased pressure is able to stop the blood flow in the compressed area, as well as to significantly change optical signals.The blood flow oscillations measured by laser Doppler flowmetry (LDF) characterize the functional state of the microvascular system and can be used for noninvasive diagnostics of its abnormality. This study was intended to identify the patterns of the relationship between the oscillating components of blood flow registered by the LDF method under different levels of pressure applied to an optical fiber probe.For this purpose, we have developed an original optical probe capable of regulating the applied pressure. The developed protocol included six sequential records of the blood perfusion at a pressure within the 0 to 200 mmHg range with unloading at the last stage.Using wavelet analyses, we traced the variation of energy of oscillations for these records in five frequency bands associated with different vascular tone regulation mechanisms. Six young volunteers of the same age (three males and three females) were included in this preliminary study and the protocol was repeated five times in each volunteer. Accordingly, 30 LDF records were available for the analyses. As expected, the LDF signal increases at weak pressure (30 mmHg) and decreases at increased pressure. The statistically stable amplification of endothelial associated blood flow oscillations under the 90 mmHg pressure allowed us to put forward a hypothesis that the endothelial activity increases. The possible causes of this phenomenon are discussed.
Streaming Graph Analytics Framework Design

Along with the spread of the World Wide Web, social networks and the Internet of Things in the past decades, the need for systems and algorithms that can process massive graphs has been continuously increasing. There has been considerable amount of research done in distributed graph processing since the emergence of such large-scale graphs. Another steadily growing field in the past years has been stream processing. This rise of interest can be attributed to the need to process large amounts of continuously streaming data with scalability, fault tolerance and very low latency. Graph streaming, the unification of these two fields is a rather new idea, with some research already being done on it. Processing graphs that are unbounded, and so large that they cannot be stored in memory or even on the disk, is only possible with a distributed graph streaming model. Our goal is to provide a graph streaming model and API that can handle common transformations and provide statistics on streamed graphs. This graph streaming API is created on top of Flink streaming and provides similar interfaces to Gelly, which is the graph library on the batch processing part of Flink.
Real-time Detection of Between-the-Eyes with a Circle Frequency Filter

In this paper, we propose a method to extract the center point between the eyes or Between-the-Eyesin real time, which can be a good clue in detecting other face feature points. In this research, we put emphasis on real-time processing. First, a skin-color region is extracted as a face candidate. Next, a circle-frequency filter, which we proposed before, is applied to this region to extract candidate points for Between-the-Eyes and also face rotation angles in the image plane at the candidate points. Each de-rotated local pattern at a candidate is compared with a template pattern of Between-the-Eyes,which is extracted from an image database of 400 faces, and a true candidate is selected. We tested the algorithm with the face database, and the false detection rate was 1.5%. We implemented the system on a PC with a Pentium III 866MHz CPU. It ran at 27 frames/secondwithout any special hardware.
Temporal Analysis Of Adaptive Face Recognition

Abstract Aging has profound effects on facial biometrics as it causes change in shape and texture. However, aging remains an under-studied problem in comparison to facial variations due to pose, illumination and expression changes. A commonly adopted solution in the state-of-the-art is the virtual template synthesis for aging and de-aging transformations involving complex 3D modelling techniques. These methods are also prone to estimation errors in the synthesis. Another viable solution is to continuously adapt the template to the temporal variation (ageing) of the query data. Though efficacy of template update procedures has been proven for expression, lightning and pose variations, the use of template update for facial aging has not received much attention so far. Therefore, this paper first analyzes the performance of existing baseline facial representations, based on local features, under ageing effect then investigates the use of template update procedures for temporal variance due to the facial age progression process. Experimental results on FGNET and MORPH aging database using commercial VeriLook face recognition engine demonstrate that continuous template updating is an effective and simple way to adapt to variations due to the aging process.
Reconfigurable SmartComponent System

Demand for resource efficiency compliant with urging environmental regulations represents nowadays a general concern in many key fields of society. One of those main fields it is industry, where manufacturing processes occur at large scale, requiring strict control to fulfill business requirements, such as demand and cost targets. Analyzing the resource management, from a macro perspective, as happens in Industry, we face a scenario of mass production in which the waste of raw-materials and efficient management of the manufacturing resources results in a sharpened inefficiency, implying significant costs with production means and production ramp-up-time. Based in the previous statement, this work aims to create a software component that, in collaboration with several actors, members of the same system monitoring/controlling the production lines, is capable of integrating data analysis software modules in runtime. The result, will be the smart maintenance of the production machines, reduction of the ramp-up-time and the automatic calibration of production parameters; culminating in an enhanced efficiency of resources and production times. For last, this work was realized under the scope of two European projects, I-RAMP3 [1] and SelSus [2] co-founded by the European Comission Seventh Framework Programme. In colaboration with cientific and industrial partners, the working groups of these projects presented a matured knowledge that was essential to this work realization.
The assessment of posture and balance post-stroke

Physiotherapy for people with stroke has been found to be beneficial but details of the most effective interventions are unclear. Further development of the evidence base for stroke physiotherapy is limited by a lack of clinical practice models, sensitive clinically based outcome measures and effective stratification techniques to characterise homogenous groups of subjects. These issues are addressed here with regard to balance and posture. These aspects were chosen because they form a cornerstone of stroke physiotherapy as they are thought essential for the rehabilitation of functional activities. A systematic review of assessment methods in the literature revealed a lack of measurement tools which met the utility criteria: reliability, validity, sensitivity to short-term change, suitability for a wide range of abilities. ease of use and suitability for different settings. This prompted the development of a new measurement tool. Firstly, a model of the clinical assessment process was developed using an adapted focus group method with neurological physiotherapists. This informed the content of a new measurement tool which combined an ordinal scale with functional performance teststhe Brunel Balance Assessment. The tool was evaluated in a series of studies involving 92 stroke patients. It was hierarchical (coefficient of reproducibility= 0.99, coefficient of scalability = 0.69), reliable (100% agreement) and valid as a measure of balance disability (r=0.58-0.97). The psychometric properties of the individual functional performance tests were also tested and found to be reliable (ICCs =0.88-1) and valid (r=0.32-0.63). Measurement error ranged 0-40% and the minimum change needed to detect true clinical change was calculated for each test. Balance disability, measured with the Brunel Balance Assessment, is heterogeneous with sitting, standing and stepping balance forming distinct levels of ability (p<0.027). Consequently. the BBA could be used to stratify people with stroke according to balance ability. Weakness, sensation and age were significant independent contributors to balance disability (r2=82.7%). Balance ability was a strong contributor to independence in ADL (p<0.0001). The findings of this thesis address the issues that have limited research into stroke physiotherapy with regard to balance disability. In relation to clinical practice, a robust measurement and stratification tool has been developed. Table of
Fetal Pleural Effusion as A Echographic Marker of Congenital Syphilis

PURPOSE: To report a case of fetal pleural effusion with antenatal diagnosis of congenital syphilis. CASE DESCRIPTION: Patient aged 24 years, two previous vaginal deliveries, without pre-natal exams, referred to the Fetal Medicine Unit of the University Hospital of Santa Maria due to preterm labor, without gestational age. Performed obstetric ultrasound that identifies bilateral pleural effusion without fetal hemodynamic consequences plus polyhydramnios and fetal growth consistent with 32 weeks and 3 days. Maternal syphilis diagnose and started treatment for patient and the partner. Patient had premature rupture of two days after admission membranes, evolving in 24 hours for vaginal delivery for women and newborns, Apgar 8 -10, 1834 g, which had a positive VDRL and remained hospitalized for treatment of congenital syphilis and gain weight. Pleural effusion regressed spontaneously. CONCLUSIONS: pleural effusion are a complication of congenital syphilis may be part of fetal hydrops and is an unusual fetal complication of a preventable disease, an alert to public health.
Simultaneous multiple optical flow estimation

The authors propose a simultaneous closed-form estimation method for multiple optical flow from image sequences in which each image point has multiple motions. This method only requires convolution for space-time filtering and low-dimensional eigensystem analysis as an optimization process. The authors propose a mixture flow model of a multiple flow and energy integral minimization as a model fitting method. It is shown that symmetry between component flows of the mixture flow can reduce the dimension of the eigensystem and make the optimization unimodal and stable. Successful experiments on double-flow estimation of random texture patterns and natural scene images are reported. <<ETX>>
Worked Examples in Video Lessons to Reduce Cognitive Load

Worked Examples in Video Lessons to Reduce Cognitive Load by Kiera Llord-Ratcliffe MS, Walden University, 2009 BM, San Francisco Conservatory of Music, 1993 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Education Walden University December 2014
Convergence in Human Dialogues Time Series Analysis of Acoustic Feature

Convergence of acoustic/prosodic (a/p) features between two speakers is a well-known property of human dialogue. It has been suggested that this particular aspect of human interaction should be implemented in spoken dialogue systems, so that they can be perceived as more “humanlike”. This paper presents a quantitative analysis method that can provide information required for modeling the phenomenon of convergence. The analysis is a combination of TAMA, a previously introduced data extraction method, and bivariate time series analysis. Results show significant correlation of a/p features between speaker dyads in the recorded dialogues analyzed, and indicate a significant amount of feedback, which a statistical verification of bidirectional convergence.
Music Recommendation System

|The paper focuses on optimization vector content feature for the music recommendation system. For the purpose of experiments a database is created consisting of excerpts of music (cid:12)les. They are assigned to 22 classes corresponding to di(cid:11)erent music genres. Various feature vectors based on low-level signal descriptors are tested and then optimized using correlation analysis and Principal Component Analysis (PCA). Results of the experiments are shown for the variety of feature vectors. Also, a music recommendation sys-tem is presented along with its main user interfaces.
Examination of the variables predicting to solve problems in marriage

The purpose of this study is to analyze the variables predicting married individuals’problem solving skills in marriage. The working group of the research is composed of 314 married. Individuals in total, consist of 168 (%53) women and 146 (%47) men who live in Malatya and participate the research voluntarily. In Marriage Problem Solving Scale which was adapted to Turkish by Hüner(2002) and Partner Support Scale was developed by Yıldırım (2004) were used as data collection tools. The gradual regression technique was used for data analysis. In the result of the research; it was concluded that problem solving skills in marriage were predicted statistically by variables of partner support and domestic responsibility. It was found that there was not a significant relation between variables of marriage type, marriage age, duration of marriage and number of children and problem solving in marriage statistically.
Towards a Framework For Resource Allocation in Networks

of a dissertation at the University of Miami. Dissertation supervised by Professor Kamal Premaratne. No. of pages in text. (157) Network resources (such as bandwidth on a link) are not unlimited, and must be shared by all networked applications in some manner of fairness. This calls for the development and implementation of effective strategies that enable optimal utilization of these scarce network resources among the various applications that share the network. Although several rate controllers have been proposed in the literature to address the issue of optimal rate allocation, they do not appear to capture other factors that are of critical concern. For example, consider a battlefield data fusion application where a fusion center desires to allocate more bandwidth to incoming flows that are perceived to be more accurate and important. For these applications, network users should consider transmission rates of other users in the process of rate allocation. Hence, a rate controller should consider application specific rate coordination directives given by the underlying application. The work reported herein addresses this issue of how a rate controller may establish and maintain the desired application specific rate coordination directives. We identify three major challenges in meeting this objective. First, the application specific performance measures must be formulated as rate coordination directives. Second, it is necessary to incorporate these rate coordination directives into a rate controller. Of course, the resulting rate controller must co-exist with ordinary rate controllers, such as TCP Reno, in a shared network. Finally, a mechanism for identifying those flows that require the rate allocation directives must be put in place. The first challenge is addressed by means of a utility function which allows the performance of the underlying application to be maximized. The second challenge is addressed by utilizing the Network Utility Maximization (NUM) framework. The standard utility function (i.e. utility function of the standard rate controller) is augmented by inserting the application specific utility function as an additive term. Then the rate allocation problem is formulated as a constrained optimization problem, where the objective is to maximize the aggregate utility of the network. The gradient projection algorithm is used to solve the optimization problem. The resulting solution is formulated and implemented as a window update function. To address the final challenge we resort to a machine learning algorithm. We demonstrate how data features estimated utilizing only a fraction of the flow can be used as evidential input to a series of Bayesian Networks (BNs). We account for the uncertainty introduced by partial flow data through the Dempster-Shafer (DS) evidential reasoning framework.
The role of high-level and low-level features in semi-automated retrieval and generation of multimedia presentations

In this article we argue that for the automatic generation of adaptive multimedia presentations we are in need of expandable, adaptable style descriptions which provide both high-level conceptual and low-level feature extraction information. Only the combination of both facilitates the retrieval of adequate material and its user-centred presentation. We discuss the requirements for an adaptable Web-based environment for museums presenting visual artefacts. We then present the framework of our prototype multimedia generation environment which transforms a high-level user query into a concrete multimedia final-form encoding that is playable on an end-users'' platform. We describe the underlying architecture and provide a working example.
Neurocomputing approach for firearm identification

This paper is an attempt to perceive and order guns using a two-layer neural system model taking into account a feedforward backpropagation calculation. Numerical properties from the joined pictures were utilised for enhanced gun characterisation execution. Inputs of the system model were 747 pictures blackmailed from the discharging pin impression of five differing guns model, Parabellum Vector SPI 9mm. Components created from the dataset were further grouped into preparation set (523 components), testing set (112 components) and acceptance set (112 components). Under managed learning, exact results exhibited that a two-layer BPNN of 11-11-5 arrangement, with tansig/purelin exchange capacities and a “trainlm” preparing calculation, had productively delivered 87% right aftereffect of grouping. The order result serves to be progressed and contrasted with the previous works. Finally, the joined picture districts can offer some accommodating data on the grouping of gun.
Text categorization of commercial Web pages

In this paper we describe a new on-line document categorization strategy that can be integrated within Web applications. A salient aspect is the use of neural learning in both representation and classification tasks. Within text documents conceived as images, the regions of interest (RoI) containing information meaningful for categorization are identified with the support of a supervised neural network. Text within RoI is represented according to a simple solution that consider the first K words in the text and code them properly. A Kohonen Self-Organizing Map (SOM) is applied to cluster documents that are subsequently labelled by applying a simple majority voting mechanism. Solutions adopted were evaluated by conducting experiments within the context of on-line price comparison services. Results obtained demontrate that the overall classification strategy is able to categorize documents satisfectorily taking into account the high variability of Web pages.
Echinococcus granulosus Infection Results in an Increase in Eisenbergiella and Parabacteroides Genera in the Gut of Mice

Cystic echinococcosis (CE) is a chronic infectious disease caused by Echinococcus granulosus. To confirm whether the infection impacts on the gut microbiota, we established a mouse model of E. granulosus infection in this study whereby BALB/c mice were infected with micro-cysts of E. granulosus. After 4 months of infection, fecal samples were collected for high-throughput sequencing of the hypervariable regions of the 16S rRNA gene. Sequence analysis revealed a total of 13,353 operational taxonomic units (OTUs) with only 40.6% of the OTUs having genera reference information and 101 of the OTUs were significantly increased in infected mice. Bioinformatics analysis showed that the common core microbiota were not significantly changed at family level. However, two genera (Eisenbergiella and Parabacteroides) were enriched in the infected mice (PAMOV A < 0.05) at genus level. Functional analysis indicated that seven pathways were altered in the E. granulosus Infection Group compared with the Uninfected Group. Spearman correlation analysis showed strong correlations of IgG, IgG1 and IgG2a with nine major genera. E. granulosus cyst infection may change the gut microbiota which may be associated with metabolic pathways.
Video summaries and cross-referencing

A system is presented to construct a highly compact hierarchical representation of video. It is based on a tree-like representation where the bottom level is composed of frames, and the highest level represents a non-temporal segmentation of the video, and is suitable for well-structured video genres. We first propose a method to segment the video into shots, which is based on a leaky memory model, previously proposed for scene transition detection. It is unique since it presents a unified approach for shot and scene detection, and for key-frame selection. We next demonstrate the benefits of using mosaics for representing shots. A novel method for mosaic alignment and comparison is proposed, which is shown to be both efficient and effective. A scene distance measure based on mosaic comparison is then defined and used to cluster the scenes into a higher abstraction of video content, the physical settings. We demonstrate this hierarchical representation using situation comedies, in which this abstraction has a strong semantic meaning in summarizing videos. By comparing physical settings across different episodes of the same situation comedy, we determine the main plots of each episode. We conclude by demonstrating a video summary tool specialized for fast browsing of situation comedies. In another example, we apply our mosaic comparison method to detect significant events in basketball games, enabling fast forwarding from one event to the next.