Miracle-dz/UniFAR-FTUs huggingface dataset:
A signature-based approach for diagnosis of dynamic faults in SRAMs

This paper focuses on diagnosis of dynamic faults in SRAMs. The current techniques for fault diagnosis are mainly based on the signature method. Here, we introduce an extension of the signature scheme by taking in account additional information related to the addressing order during March test execution. A first advantage of the proposed approach is its capability to distinguish between static and dynamic faults. Another main feature is the correct identification of the location of the failure in a given memory component: the core-cell array, write drivers, sense amplifiers, address decoders and pre- charge circuits. Moreover, since this approach does not modify the March test, there is no increase of test complexity, conversely to other existing diagnosis techniques.
Wideband Voltage Controlled Oscillators for Multi-band Multi-standard Radios

In this thesis, a procedure of designing a wideband, low phase noise VCO is proposed. The sequence is presented step by step, from the frequency planning to topology selection, component selection. By exploring the advantages and disadvantages of each VCO topology and each component, the most suitable topology and components are chosen for each application. A technique for extending the tuning range of inherently narrow tuning range LC VCO is also presented. An all-PMOS wideband, low phase noise VCO is designed to demonstrate the designing procedure. Measurement results shows that the power consumption of this VCO is 8.8 mW from the 1.8 V power supply, the tuning range is from 2.85 GHz to 3.77 GHz, and the phase noise at 1 MHz from the carrier frequency of 3.76 GHz is -122.0 dBc/Hz. To reduce the amplitude variation over a wide frequency tuning range and to ensure a fast and reliable startup against process and temperature variations, combining biasing for optimum noise performance, an automatic amplitude controller is proposed. Measurement results of this
Experimental motion planning in airpath control for HCCI engine

A motion planning based control strategy is proposed for the airpath control of turbocharged diesel engines using exhaust gas recirculation (EGR). The considered model uses simple balance equations. The fully actuated dynamics are easily inverted, yielding straightforward open-loop control laws. This approach is complemented by experimentally derived lookup tables to cast the driver's requests into transients between operating points. Estimation of required variables from the intake pressure measurements is addressed and experimental tests are reported on a 4-cylinder engine in homogeneous charge compression ignition (HCCI) mode. Conclusions stress the possibility of taking into account the non-minimum phase effects of this system by a simple, yet efficient in practice, control law. Observed transients are accurate and fast
Mott-Hubbard and Anderson metal-insulator transitions in correlated lattice fermions with binary disorder

Strongly correlated fermions in a crystal or in an optical lattice in the presence of binary-alloy disorder are investigated. We employ the statistical dynamical mean-field theory, which incorporates both fluctuations due to disorder and local correlations due to interaction, to solve the Anderson-Hubbard model. Localization due to disorder is studied by means of the probability distribution function of the local density of states. We obtain a complete paramagnetic ground state phase diagram consisting of disordered correlated metal, Anderson-Mott insulator, and band insulator.
Low-Oxygen-Saturation Quantification in Human Arterial and Venous Circulation

Conventional pulse oximetry has limited accuracy in measuring blood oxygen saturation in low-saturation and -perfusion scenarios. This limits the application of pulse oximetry in patients suffering from peripheral vascular afflictions. We present a novel pulse oximetry system that proposes solutions to these low-saturation and -perfusion scenarios by inducing an artificial pulse in the detected photoplethysmograph (PPG). A novel arteriovenous hypothesis was formulated to extract arterial and venous saturation data from the artificial PPG using arterial-to-venous compliance ratios. Sensor wavelengths were selected to provide high- and low-saturation accuracy, followed by an in vitro sensor calibration procedure. System performance was validated by means of an in vivo procedure. In vivo results indicate good accuracy for high saturation, with limited accuracy in low-saturation scenarios. The arteriovenous hypothesis was validated, indicating that venous saturation can be extracted from the artificial PPG. The results indicate that the proposed system might be able to accurately monitor arterial and venous saturation in low- or no-perfusion scenarios. It is recommended that further studies into the system's performance are conducted.
Least Squares Model Averaging

This paper considers the problem of selection of weights for averaging across least squares estimates obtained from a set of models. Existing model average methods are based on exponential Akaike information criterion (AIC) and Bayesian information criterion (BIC) weights. In distinction, this paper proposes selecting the weights by minimizing a Mallows criterion, the latter an estimate of the average squared error from the model average fit. We show that our new Mallows model average (MMA) estimator is asymptotically optimal in the sense of achieving the lowest possible squared error in a class of discrete model average estimators. In a simulation experiment we show that the MMA estimator compares favorably with those based on AIC and BIC weights. The proof of the main result is an application of the work of Li (1987). Copyright The Econometric Society 2007.
Under What 1 Running head : UNDER WHAT MARKET CONDITIONS ARE AGILE METHODS Under what Market Conditions are Agile Methods the Optimal Approach to Software Development

The purpose of this document is to serve as a research proposal, which recommends a study to examine the effects of using agile methods on software project performance in dynamic and uncertain market conditions. Agile methods are an approach to software engineering, which are characterized by early customer involvement, flexible development processes, and iterative product releases. This proposal describes the research problem, research theory, literature review, and research methodology for studying the effects of using agile methods. A survey of 25 software projects from 15 Internet firms is suggested to test the hypotheses that better software project performance (e.g., fewer resources, faster time-to-market, and higher customer satisfaction) may be linked to the use of agile methods. The results of this study may help executives and managers better understand the effects of using agile methods by Internet firms on software project performance.
Mapping Cerrado physiognomies using Landsat time series based phenological profiles

Monitoring of the Brazilian Cerrado biome is crucial in order to fully understand its ecosystem functions, its response to changes, and to keep track of ongoing change processes in one of the world's biodiversity hotspots. The huge extent, heterogeneity and complex diversity of the Cerrado makes monitoring very challenging, but optical remote sensing based approaches have been shown to be valuable to tackle this task. We explored the potential of Landsat data to derive seasonal phenological profiles for the main Cerrado physiognomies, in order to use this information for classification purposes. Therefore we gathered Landsat TM, ETM+ and OLI data from the open Landsat data archive. To overcome data gaps in the time series, we applied a Gaussian kernel based convolution filter on Tasseled Cap transformed Landsat data. Thus, it was possible to derive comprehensible phenological profiles for distinct Cerrado physiognomies at Landsat spatial resolution. We used these derived seasonal profiles to train a Support Vector Machine classification model in order to map the main Cerrado physiognomies around Brasilia, DF. Although classification errors were observed between similar classes in terms of their vegetation structure and density, we were able produce an accurate map that captures the spatial patterns of the vegetation physiognomies.
Significance of formants from difference spectrum for speaker identification

In this paper, we describe a prototype speaker identification system using auto-associative neural network (AANN) and formant features. Our experiments demonstrate that formants extracted from difference spectrum perform significantly better than formants extracted from normal spectrum for the task of speaker identification. We also demonstrate that formants from difference spectrum provide comparable speaker identification performance with that of features such as weighted linear predictive Cepstral coefficients and Mel-Frequency Cepstral coefficients. Finally, we combine the results of formant based system and linear predictive Cepstral coefficients based system to achieve 100% identification performance.
BlinkToSCoAP: An end-to-end security framework for the Internet of Things

The emergence of Internet of Things and the availability of inexpensive sensor devices and platforms capable of wireless communications enable a wide range of applications such as intelligent home and building automation, mobile healthcare, smart logistics, distributed monitoring, smart grids, energy management, asset tracking to name a few. These devices are expected to employ Constrained Application Protocol for the integration of such applications with the Internet, which includes User Datagram Protocol binding with Datagram Transport Layer Security protocol to provide end-to-end security. This paper presents a framework called BlinkToSCoAP, obtained through the integration of three software libraries implementing lightweight versions of DTLS, CoAP and 6LoWPAN protocols over TinyOS. Furthermore, a detailed experimental campaign is presented that evaluates the performance of DTLS security blocks. The experiments analyze BlinkToSCoAP messages exchanged between two Zolertia Z1 devices, allowing evaluations in terms of memory footprint, energy consumption, latency and packet overhead. The results obtained indicate that securing CoAP with DTLS in Internet of Things is certainly feasible without incurring much overhead.
Synthesizing structured text from logical database subsets

In the classical database world, information access has been based on a paradigm that involves structured, schema-aware, queries and tabular answers. In the current environment, however, where information prevails in most activities of society, serving people, applications, and devices in dramatically increasing numbers, this paradigm has proved to be very limited. On the query side, much work has been done on moving towards keyword queries over structured data. In our previous work, we have touched the other side as well, and have proposed a paradigm that generates entire databases in response to keyword queries. In this paper, we continue in the same direction and propose synthesizing textual answers in response to queries of any kind over structured data. In particular, we study the transformation of a dynamically-generated logical database subset into a narrative through a customizable, extensible, and templatebased process. In doing so, we exploit the structured nature of database schemas and describe three generic translation modules for different formations in the schema, called unary, split, and join modules. We have implemented the proposed translation procedure into our own database front end and have performed several experiments evaluating the textual answers generated as several features and parameters of the system are varied. We have also conducted a set of experiments measuring the effectiveness of such answers on users. The overall results are very encouraging and indicate the promise that our approach has for several applications.
Fructose-1,6-Bisphosphatase Overexpression in Pancreatic β-Cells Results in Reduced Insulin Secretion

OBJECTIVE—Fructose-1,6-bisphosphatase (FBPase) is a gluconeogenic enzyme that is upregulated in islets or pancreatic β-cell lines exposed to high fat. However, whether specific β-cell upregulation of FBPase can impair insulin secretory function is not known. The objective of this study therefore is to determine whether a specific increase in islet β-cell FBPase can result in reduced glucose-mediated insulin secretion. RESEARCH DESIGN AND METHODS—To test this hypothesis, we have generated three transgenic mouse lines overexpressing the human FBPase (huFBPase) gene specifically in pancreatic islet β-cells. In addition, to investigate the biochemical mechanism by which elevated FBPase affects insulin secretion, we made two pancreatic β-cell lines (MIN6) stably overexpressing huFBPase. RESULTS—FBPase transgenic mice showed reduced insulin secretion in response to an intravenous glucose bolus. Compared with the untransfected parental MIN6, FBPase-overexpressing cells showed a decreased cell proliferation rate and significantly depressed glucose-induced insulin secretion. These defects were associated with a decrease in the rate of glucose utilization, resulting in reduced cellular ATP levels. CONCLUSIONS—Taken together, these results suggest that upregulation of FBPase in pancreatic islet β-cells, as occurs in states of lipid oversupply and type 2 diabetes, contributes to insulin secretory dysfunction.
Complete Solution Classification for the Perspective-Three-Point Problem

We use two approaches to solve the perspective-three-point (P3P) problem: the algebraic approach and the geometric approach. In the algebraic approach, we use Wu-Ritt's zero decomposition algorithm to give a complete triangular decomposition for the P3P equation system. This decomposition provides the first complete analytical solution to the P3P problem. We also give a complete solution classification for the P3P equation system, i.e., we give explicit criteria for the P3P problem to have one, two, three, and four solutions. Combining the analytical solutions with the criteria, we provide an algorithm, CASSC, which may be used to find complete and robust numerical solutions to the P3P problem. In the geometric approach, we give some pure geometric criteria for the number of real physical solutions.
Identification of Sun Glint Contamination in GMI Measurements Over the Global Ocean

This paper utilizes the model regression difference method to identify sun glint contamination on Global Precipitation Measurement Microwave Imager (GMI) data over the ocean based on observations from 2015 to 2016. The spatial distribution characteristics and the critical angles of the sun glint flags are analyzed in depth. It is found that the GMI measurements with horizontal and vertical polarizations at 10.65 GHz over the ocean are sometimes contaminated by the solar radiation reflected by the sea surface. The sun glint contamination has also been detected over high reflected land surface. The intensity and locations of the contamination are related to the sun glint angle. Only those GMI field of views with smaller sun glint angles are easily contaminated. The closer the sun glint angle is to 0°, the stronger the magnitude of the contamination. The GMI observations at other channels are not contaminated mainly because sun glint is most pronounced at 10 GHz. There are too strong constraints and tossing out of too many useful data in current GMI sun glint algorithms. The suggested critical angles of the sun glint flags for 10.65GHz is 20° to reduce false flagging. By applying the model regression difference method, the error in brightness temperature caused by sun glint can be corrected. The Tropical Rainfall Measuring Mission Microwave Imager (TMI) observations at 10.65 GHz are also contaminated by the reflected solar radiation from the ocean, and the intensity and locations of the contamination are similar to those of the GMI.
Üniversite Öğrencilerinin Siber Aylaklık Seviyelerini Yordayan Faktörler

Cyberloafing behavior may cause learning and discipline problems in learning environments. The purpose of this study is to investigate the reasons and factors for cyberloafing behavior. Within this regard, the Cyberloafing Behavior Scale was applied to 124 university students to examine the reasons of students’ cyberloafing behaviors. Multiple linear regression analysis and content analysis procedures were conducted to examine cyberloafing behavior of students. Findings indicate that the most observed cyberloafing behavior is sharing and messaging during the lesson time. Based on regression analysis, male students having smart phone and low GPA score; spending more time on the Internet, and using more applications are demonstrating more cyberloafing behavior. According to content analysis, reluctance to learn is found to be the main reason for cyberloafing. Besides, receiving smartphone messages, willing to communicate with others via Internet, sense of curiosity on Internet, willingness to have more enjoable time on Internet are found to be other reasons for cyberloafing. Diminishing reluctance to learn could be a significant solution for today’s educational problem – cyberloafing
MCA: Boolean Networks Control Algorithm

Control problem in a biological system is the problem of finding an interventional policy for changing the state of the biological system from an undesirable state, e.g. disease, into a desirable healthy state. Boolean networks are utilized as mathematical model for gene regulatory networks. This paper provides an algorithm to solve the control problem in Boolean networks. The proposed algorithm is implemented and applied on two biological systems: T-cell receptor network and Drosophila melanogaster network. Results show that the proposed algorithm works faster in solving the control problem over these networks, while having similar accuracy, in comparison to previous methods.
Involvement of potD in Streptococcus pneumoniae Polyamine Transport and Pathogenesis

ABSTRACT Polyamines such as putrescine, spermidine, and cadaverine are small, polycationic molecules that are required for optimal growth in all cells. The intracellular concentrations of these molecules are maintained by de novo synthesis and transport pathways. The human pathogen Streptococcus pneumoniae possesses a putative polyamine transporter (pot) operon that consists of the four pot-specific genes potABCD. The studies presented here examined the involvement of potD in polyamine transport and in pneumococcal pathogenesis. A potD-deficient mutant was created in the mouse-virulent serotype 3 strain WU2 by insertion duplication mutagenesis. The growth of the WU2ΔpotD mutant was identical to that of the wild-type strain WU2 in vitro in rich media. However, WU2ΔpotD possessed severely delayed growth compared to wild-type WU2 in the presence of the polyamine biosynthesis inhibitors DFMO (α-dimethyl-fluroornitithine) and MGBG [methylgloxal-bis (guanyl hydrazone)]. The mutant strain also showed a significant attenuation in virulence within murine models of systemic and pulmonary infection regardless of the inoculation route or location. These data suggest that potD is involved in pneumococcal polyamine transport and is important for pathogenesis within various infection models.
The relationship of stressful life events, social support, and personality to psychological and physical health /

The Relationship of Stressful Life Events, Social Support, and Personality to Psychological and Physical Health by Anthony Frank Obradovich, Ph.D. The Ohio State University, 1990 Professor Lyle D. Schmidt, Adviser The present investigation explored the relationship of stressful life events to measures of physical and psychological health. The mediating roles of social support and selected personality variables in this relationship also were investigated. Participants were 181 male college students enrolled in an electronics-related curriculum at a technical college in the midwest. Independent variables were major life events, daily irritating events ("hassles” ), social support, internal-external locus of control, optimism, sense of coherence, difficulty in seeking support, and negative affectivity. Dependent variables were number of physical and psychological symptoms. Analyses of variance, analyses of covariance, and multiple regression
Impacts of Work–Family Conflict on Female Hospitality Employees’ Job Outcomes

ABSTRACT The aims of this study were, first, to examine female hospitality employees’ perceptions of work–family conflict in both directions (work interfering with family and family interfering with work) and compare the differences between developed and developing areas; and, second, to test the mechanisms that link female hospitality employees’ work–family conflict to job satisfaction and turnover intention and examine the potential mediating effects of job satisfaction on the relationship between work–family conflict and turnover intention. A sample of 322 female hospitality employees in Guangzhou and Zhangjiajie completed the survey. Hierarchical regression analysis revealed that female employees perceived more work interfering with family (WIF) than family interfering with work (FIW). Female employees in Guangzhou perceived higher work–family conflict, both WIF and FIW, than their counterparts in Zhangjiajie. WIF was negatively related to job satisfaction and positively to turnover intention, but the effects of FIW on job outcomes were insignificant. Lastly, job satisfaction was demonstrated to partially mediate the relationship between WIF and turnover intention. Important implications and applications are provided for researchers and practitioners.
Un sitio de extracción de mármol para hacer brazaletes: la cantera neolítica de Cortijo Cevico (Ventorros de San José- Loja, Granada)

Stone bracelets of the Early Neolithic (ca. 5500-4800 cal BC) and their production workshops are well documented. Until now, extraction and primary reduction sites were not known from the Iberian Peninsula. This paper presents the survey and excavation of the first marble quarry for the knapping of bracelet preforms in this region, at Cortijo Cevico (Ventorros de San Jose-Loja, Granada). The regional geological study and raw material characterization, as well as the technological, statistical and experimental analyses, allow us to recognize how exploitation worked, and shed light on the social organization of the first farming communities.
Group sparse LMS for multiple system identification

Armed with structures, group sparsity can be exploited to extraordinarily improve the performance of adaptive estimation. In this paper, a group sparse regularized least-mean-square (LMS) algorithm is proposed to cope with the identification problems for multiple/multi-channel systems. In particular, the coefficients of impulse response function for each system are assumed to be sparse. Then, the dependencies between multiple systems are considered, where the coefficients of impulse responses of each system share the same pattern. An iterative online algorithm is proposed via proximal splitting method. At the end, simulations are carried out to verify the superiority of our proposed algorithm to the state-of-the-art algorithms.