Miracle-dz/UniFAR-FTUs huggingface dataset:
Kernelized Low Rank Representation on Grassmann Manifolds

Low rank representation (LRR) has recently attracted great interest due to its pleasing efficacy in exploring low-dimensional subspace structures embedded in data. One of its successful applications is subspace clustering which means data are clustered according to the subspaces they belong to. In this paper, at a higher level, we intend to cluster subspaces into classes of subspaces. This is naturally described as a clustering problem on Grassmann manifold. The novelty of this paper is to generalize LRR on Euclidean space onto an LRR model on Grassmann manifold in a uniform kernelized framework. The new methods have many applications in computer vision tasks. Several clustering experiments are conducted on handwritten digit images, dynamic textures, human face clips and traffic scene sequences. The experimental results show that the proposed methods outperform a number of state-of-the-art subspace clustering methods.
Review and Analysis of the Impacts and Effects on Low Power VLSI Circuits Operating in Subthreshold Regime

In ultra low power portable devices set towards realizing a long battery life, low energy consumption per operation is the primary design constraint. Hence, operating the circuits in weak inversion or the sub-threshold region, with the subthreshold leakage current acting as the primary computing current, turn out to be a promising solution. Though such a methodology limits the performance in terms of speed, it exhibits a lot of benefits in terms of reduced dynamic power and leakage power, added with high transconductance gain. In the subthreshold regime, the high sensitivity of the devices to the process, voltage and temperature (PVT) variations prove to be a major challenge to be tackled, due to the exponential dependence of drain current on the threshold voltage VT. In this paper, the operational behaviours of VLSI circuits, while operating in the weak inversion region are illustrated with explicit simulation results, waveforms and discussions. Moreover, the lack of robustness of the device in the subthreshold regime is also analyzed. The elimination of the PVT variability issues by employing body biasing strategies is explored. Each of these analyses use precisely exemplified simulation methodologies. The results and discussions are depicted through ample simulation results. The impact of technology scaling on VLSI circuits in the subthreshold regime is explored. Minimum energy point, optimum Vdd and optimum VT are also evaluated. It is followed by the channel upsizing, which is considered to be the most potential circuit level technique for addressing most of the issues in the subthreshold regime. The entire analyses and study are done with the use of a 16-bit CLA adder as the benchmark circuit. PTM (Predictive Technology Models) models of 32nm, 45nm, 65nm, 90nm, 130nm and 180nm have been used in the simulations using the industry standard EDA tool.
Emotionally Charged: Exploring the Role of Emotion in Online News Information Seeking and Processing

This study examines how news stories framed in terms of discrete emotions (anger, fear, hope) influence online news message processing and information seeking. Results revealed that participants who read the approach emotion stories (anger and especially hope) spent more time on the story page than those who read the avoidant emotion (fear) story. These two emotional frames also differentially affected the information that people selected post-exposure in emotion-consistent ways. Overall, the findings deepen our understanding of the role that the emotional framing of news stories plays in determining how consumers respond to and selectively engage with online news content.
Incremental Sensorimotor Learning with Constant Update Complexity

The robotics domain is challenging from a learning perspective, since subsequent observations are dependent and the environment is typically non-stationary. Successful modeling of sensorimotor relationships therefore necessitates an open-ended learning process that continuously updates existing models when novel observations become available, while at the same time respecting strict timing constraints. These requirements can be met by combining standard Bayesian regression with an exact update rule for incremental operation and a kernel approximation for non-linearity. The resulting method is characterized by a constant update complexity, which effectively allows lifelong operation. Furthermore, an experimental validation on predicting inverse dynamics of the iCub humanoid demonstrates superior generalization and timing performance with respect to competitive methods.
The Money Metric Utility Frontier and Aggregate Index Numbers

The paper proposes the money metric utility frontier as the basic unifying concept for an applicable theory of aggregate welfare measurement. The concept is related to conventional index numbers of aggregate real consumption and the aggregate cost-of-living, as well as to consumer surplus. Current developments and controversies, related for example to the use of chain indexes in measuring CPI and GDP, as well as other issues, are discussed in relation to fundamental theory.
Software Requirements Engineering: An Overview

Software requirements engineering can be considered as the process by which the features of software systems as perceived by the user are established. Software systems are destined to be embedded into organisational settings, which impose constraints on performance and operational characteristics. Determining how the software should behave within those constraints requires a thorough understanding of the software functionalities, its attributes, the complexity of the interaction between them, and its interaction with the user environment. The primary source of information is the user (organisation). However it is often the case that users inadequately elicit software requirements and in a form inappropriate to the software developers. Software requirements have to be established by an iterative refinement process of elicitation, analysis, modelling and representation. An important but intractable issue is that of knowledge representation and management, and specially domain knowledge. Domain knowledge forms the basis for establishing a common universe of discourse (UoD) between users and analysts, for mutual understanding, reference and validation of requirements. There is an urgent need for effective support mechanism for capturing and managing such domain knowledge. Any support method must allow the interrelation between the domain knowledge and the software requirement information to be represented, so that inadequacies of the requirements can be recognised and dealt with accordingly.
Detection and Tracking of Multiple Pedestrians in Automotive Applications

We present a method for tracking an unknown and changing number of far away pedestrians in a video stream. Multiple particle filter instances are utilized which track single pedestrians independently from each other. The tracking is guided by a cascade classifier which is integrated into the particle filter framework. In order to be able to detect hardly visible pedestrians and to filter out isolated false positives of the classifier, we developed a detection criterion for particle filters which follows the track-before-detect paradigm. The system nearly works in real time.
Controllable nanoimprinting of metallic glasses: effect of pressure and interfacial properties

The quantitative model proposed here for nanoimprinting by thermoplastic compression molding is focused on bulk metallic glasses (BMGs), but it is also applicable to polymers and other thermoplastic materials. In our model the flow and pressure fields are evaluated using the lubrication theory, and the effect of molding pressure, BMG viscosity, and capillary pressure on the spatial distribution of nanoimprinted features is determined. For platinum-based BMG the theory that takes into account capillary pressure but no other surface stresses agrees very well with experimental results. For palladium-based BMG (prone to oxidation) the extended theory includes an additional threshold pressure required to break the oxide layer that forms on the BMG surface. Our analysis provides important insights into flow behavior of BMG supercooled liquids. In particular, a new method for measuring surface tension and viscosity of BMGs and evaluating the strength of the surface oxide layer is demonstrated.
Development of Microencapsulation Delivery System for Long-Term Preservation of Probiotics as Biotherapeutics Agent

The administration of probiotic bacteria for health benefit has rapidly expanded in recent years, with a global market worth $32.6 billion predicted by 2014. The oral administration of most of the probiotics results in the lack of ability to survive in a high proportion of the harsh conditions of acidity and bile concentration commonly encountered in the gastrointestinal tract of humans. Providing probiotic living cells with a physical barrier against adverse environmental conditions is therefore an approach currently receiving considerable interest. Probiotic encapsulation technology has the potential to protect microorganisms and to deliver them into the gut. However, there are still many challenges to overcome with respect to the microencapsulation process and the conditions prevailing in the gut. This review focuses mainly on the methodological approach of probiotic encapsulation including biomaterials selection and choice of appropriate technology in detailed manner.
Autonomous detection of connectivity

This paper contributes a protocol that measures underlay connectivity properties of nodes in an overlay network. The protocol autonomously assigns a unique random identifier to each subset of nodes that can communicate transitively using arbitrary underlay routing protocols (e.g., IPv4, IPv6, RFCOMM), denoted connectivity domain. We denote nodes in more than one connectivity domains relays, as they can forward messages between connectivity domains. This information is useful for overlay construction, as possible overlay neighbors must be in the same connectivity domain while relays enable communication between nodes in different connectivity domains. The general problem of identifying maximal connectivity domains is equivalent to the problem of finding all maximal cliques. We show that it can be efficiently approximated in an overlay setting with only partial knowledge of the network connectivity graph. The key observation is that in such scenario once all we discovered all relays remaining nodes can agree on a unique identifier per connectivity domain. We show by theoretical analysis and extensive simulations that the approach is accurate, scalable, resilient, and reactive to connectivity changes in the underlay network.
Automatic Human Face Detection and Tracking

With the growing interest in human-computer interaction, teleconferencing and visual surveillance, many automated human face detection and tracking system have been developed. In this project, a human face detection system is combined with tracking algorithms to form an automated human face detection and tracking system. The detection module makes use of skin color classification and segmentation to estimate the boundary of the face. Each pixel is classified as “skin” or “non-skin” colour and the largest cluster of “skin” color is labeled as a possible face candidate. In the tracking module, facial features are tracked using motionbased and model-based algorithms. A Kalman filter is employed to estimate the feature motion. Various tests are conducted and the system is shown to perform reasonably well for images in an upright and frontal view. For other orientations and views of the face, the system may lose track of some of the features. The integrated system acts as the first stage in finding the face and tracking its features’ position. Other applications can then make use of this information for human-computer interaction. Key-Words: Computer Vision, Human Face Detection, Tracking, Kalman Filters
Influence of the Presence of Tissue Expanders on Energy Deposition for Post-Mastectomy Radiotherapy

An increasing number of studies have shown that post-mastectomy radiotherapy presents benefits associated with the patients survival and a significant fraction of the treated patients makes use of tissue expanders for breast reconstruction. Some models of tissue expanders have a magnetic disk on their surface that constitutes heterogeneity in the radiation field, which can affect the dose distribution during the radiotherapy treatment. In this study, the influence of a metallic heterogeneity positioned in a breast tissue expander was evaluated by means of Monte Carlo simulations using the MCNPX code and using Eclipse treatment planning system. Deposited energy values were calculated in structures which have clinical importance for the treatment. Additionally, the effect in the absorbed energy due to backscattering and attenuation of the incident beam caused by the heterogeneity, as well as due to the expansion of the prosthesis, was evaluated in target structures for a 6 MV photon beam by simulations. The dose distributions for a breast treatment were calculated using a convolution/superposition algorithm from the Eclipse treatment planning system. When compared with the smallest breast expander volume, underdosage of 7% was found for the largest volume of breast implant, in the case of frontal irradiation of the chest wall, by Monte Carlo simulations. No significant changes were found in dose distributions for the presence of the heterogeneity during the treatment planning of irradiation with an opposed pair of beams. Even considering the limitation of the treatment planning system, the results obtained with its use confirm those ones found by Monte Carlo simulations for a tangent beam irradiation. The presence of a heterogeneity didńt alters the dose distributions on treatment structures. The underdosage of 7% observed with Monte Carlo simulations were found for irradiation at 0°, not used frequently in a clinical routine.
Severe Tuberculosis Requiring Intensive Care: A Descriptive Analysis

Background. This study aims to describe the characteristics of tuberculosis (TB) patients requiring intensive care and to determine the in-hospital mortality and the associated predictive factors. Methods. Retrospective cohort study of all TB patients admitted to the ICU of the Infectious Diseases Department of Centro Hospitalar de São João (Porto, Portugal) between January 2007 and July 2014. Comorbid diagnoses, clinical features, radiological and laboratory investigations, and outcomes were reviewed. Univariate analysis was performed to identify risk factors for death. Results. We included 39 patients: median age was 52.0 years and 74.4% were male. Twenty-one patients (53.8%) died during hospital stay (15 in the ICU). The diagnosis of isolated pulmonary TB, a positive smear for acid-fast-bacilli and a positive PCR for Mycobacterium tuberculosis in patients of pulmonary disease, severe sepsis/septic shock, acute renal failure and Multiple Organ Dysfunction Syndrome on admission, the need for mechanical ventilation or vasopressor support, hospital acquired infection, use of adjunctive corticotherapy, smoking, and alcohol abuse were significantly associated with mortality (p < 0.05). Conclusion. This cohort of TB patients requiring intensive care presented a high mortality rate. Most risk factors for mortality were related to organ failure, but others could be attributed to delay in the diagnostic and therapeutic approach, important targets for intervention.
A systematic credit scoring model based on heterogeneous classifier ensembles

Lending loans to borrowers is considered one of the main profit sources for banks and financial institutions. Thus, careful assessment and evaluation should be taken when deciding to grant credit to potential borrowers. With the rapid growth of credit industry and the massive volume of financial data, developing effective credit scoring models is very crucial. The literature in this area is very dense with models that aim to get the best predictive performance. Recent studies stressed on using ensemble models or multiple classifiers over single ones to solve credit scoring problems. Therefore, this study propose to develop and introduce a systematic credit scoring model based on homogenous and heterogeneous classifier ensembles based on three state-of-the art classifiers: logistic regression (LR), artificial neural network (ANN) and support vector machines (SVM). Results revealed that heterogeneous classifier ensembles gives better predictive performance than homogenous and single classifiers in terms of average accuracy.
Design and implementation of an Electric Differential for traction application

The use of an Electric Differential (ED) constitutes a technological advance in vehicle design along with the concept of more electric vehicles. EDs have the advantage of replacing loose and heavy mechanical differentials and transmissions with lighter and smaller electric motors directly coupled to the wheels via a single gear or an in-wheel motor. This paper deals then with an Electric Differential System (EDS) for an Electric Vehicle (EV) directly driven by dual induction motors in the rear wheels. A sensorless control technique is preferred to a position or speed encoder-based control one to reduce the overall cost and to improve the reliability. The EDS main feature is the robustness improvement against system uncertainties and road conditions. The EDS control performances are validated through experiments on a dSPACE-based test bench. The experimental results show that the proposed controller is able to track the speed reference and the curvature angle with good static and dynamic performances.
ECLECTIC ART DECO IN SURAKARTA: COMPARISON OF THREE RESIDENCES IN SURAKARTA (LAWEYAN, BALUWARTI, KAUMAN)

Art Deco emerged from the change of thinking ways of a group of people who one of them backed from the establishment of the economy. In Surakarta, there are areas that get influence Art Deco style, among others: Baluwarti, Laweyan, and Kauman. The problem is the absorption and adaptation of elements of Javanese culture and other culture that produce different art deco typology in each object of study. This study aims to compare the absorption and adaptation of elements of Javanese culture and other culture that produces different art deco typologies in three different areas in Surakarta.With different backgrounds, the absorption and adaptation of Art Deco style in residential houses in each region is different. But the common thread is the absorption of several styles, namely: Java, Art Deco, Art Nouveau, Middle East, and China which finally created the eclectic Art Deco style.
Smooth bilinear classification of EEG

The goal of this paper is to improve on single-trial classification of electro-encephalography (EEG) using linear methods. The paper proposes to combine the classification of the spatial distribution of activity with the classification of its temporal profile. The work is based on the idea that a current source in the brain has a reproducible temporal profile with a static spatial projection to the electrodes. This assumption reduces the parameter space of a linear classifier to a rank-one factorial space. The new model limits over-fitting due to the fewer number of parameters, and furthermore, it allows us to declare a prior belief of smoothness on the spatial and temporal profiles of the source. Our experiments show that the method is useful as a classifier with an area under the ROC curve of 0.93 having only 40 target trials available for training. Investigation of the trained classifier encourages us to belief that the method can also be useful as a tool to interpret the activity in the data at hand with respect to experimental events
The trade credit in the Spanish agrofood industry

Selling on credit is rather frequent in Mediterranean countries. Its generalized use can lead to excessive enlargements of the payment periods and consequently can deteriorate the profitability of firms. In spite of the relevance of this problem there are few empirical researches. This work intends to fill this gap and to shed light on the factors related to the extension of trade credit. In the theoretical and empirical literature, different motives have been proposed to explain this issue: a mechanism to reduce transaction costs, a financial alternative to the bank system and an additional tool to improve commercial activities. To contrast these ideas a panel of 388 firms of the Spanish agrofood industry has been taken, and static and dynamic regression models have been estimated by using robust methods to heteroskedasticity, autocorrelation and endogeneity of the explanatory variables. The results confirm that trade credit receivable is associated with more active firms and with cheaper bank financing. Other factors with positive relationships are short-term bank debts and accounts payable. These findings are consistent with commercial motives, rather than a pure financial view, in the sense that financial distressed producers extend trade credit as a way of promoting their products and in turn increasing their sales.
Risk prediction and clinical model building for lymph node metastasis in papillary thyroid microcarcinoma

The surgical management of papillary thyroid microcarcinoma (PTMC), especially regarding the necessity of central/lateral lymph node dissection, remains controversial. This study investigated the clinicopathologic factors predictive of lymph node metastasis (LNM) in patients diagnosed with PTMC. Multivariate logistic regression analysis was used for PTMC patients identified from the Surveillance, Epidemiology, and End Results database who were treated by surgery between 2002 and 2012, to determine the association of clinicopathologic factors with LNM. According to the results, a total of 31,017 patients met the inclusion criteria of the study. Final histology confirmed 2,135 (6.9%) cases of N1a disease and 1,684 cases (5.4%) of N1b disease. Our multivariate logistic regression analysis identified variables associated with both central LNM and lateral lymph node metastasis (LLNM), including a younger age (<45 years), male sex, non-Hispanic white and other race, classical papillary histology, larger tumor size, multifocality, and extrathyroidal extension; distant metastasis was also significantly associated with LLNM. The significant predictors identified from multivariable logistic regression were integrated into a statistical model that showed that extrathyroidal extension had maximum weight in the predictive role for LNM. LLNM was validated to be a significant risk factor for cancer-specific death in Cox regression analyses, whereas central LNM failed to predict a worse cancer-specific survival according to our data. Therefore, we suggested that central lymph node dissection could be performed in certain patients with risk factors. Given the prevalence of LLNM in PTMC, a thorough inspection of the lateral compartment is recommended in PTMC patients with risk factors for precise staging; from the viewpoint of a radical treatment for tumors, prophylactic lateral lymph node dissection that aims to remove the occult lateral lymph nodes may be an option for PTMC with risk factors. Multicenter studies with long-term follow-up are recommended to better understand the risk factors and surgical management for cervical nodes in PTMC.