Miracle-dz/UniFAR-FTUs huggingface dataset:
A FIVE-FACTOR SOFTWARE ARCHITECTURE ANALYSIS BASED ON FAR FOR ATM BANKING SYSTEM 1

Software architecture represents the high level str uctu es of a software system. It can be defined as the set of structures required to explain about the softwar e system which comprise the software elements, the relations between them, and the properties of both the elements and relations. A major challenge in th e software architecture design process is the accurat e prediction and improvement of the software performance characteristics like outage frequency a nd duration. This paper proposes hybrid software architecture for an ATM banking system to overcome th difficulties of an existing architecture. The proposed system is based on the Fuzzy Association R ules (FAR). During the extraction of the FAR, a confidence index and theAprioriGen algorithm is uti lized to compute the inverse fuzzy transform. Also, this paper presents a review of some of the Softwar e Architecture Analysis Methods (SAAM). The performance of the proposed methodology is analyzed based on the metrics like reliability, flexibility , adaptability and security. The proposed software ar chitecture is compared with the various existing software architectures. The implementation results obviously proves that the proposed methodology performs better than all the other existing softwar e rchitectures.
45nm High-k+Metal Gate Strain-Enhanced Transistors

For the 45nm technology node, high-k+metal gate transistors have been introduced for the first time in a high-volume manufacturing process [1]. The introduction of a high-k gate dielectric enabled a 0.7x reduction in Tox while reducing gate leakage 1000x for the PMOS and 25x for the NMOS transistors. Dual-band edge workfunction metal gates were introduced, eliminating polysilicon gate depletion and providing compatibility with the high-k gate dielectric. In addition to the high-k+metal gate, the 35nm gate length CMOS transistors have been integrated with a third generation of strained silicon and have demonstrated the highest drive currents to date for both NMOS and PMOS. An SRAM cell size of 0. 346μ has been achieved while using 193nm dry lithography. High yield and reliability has been demonstrated on multiple single-, dual-, quad-, and six-core microprocessors. INTRODUCTION One of the key methods to enable transistor gate length scaling over the past several generations has been to scale the gate oxide. This improves the control of the gate electrode over the channel, enabling both shorter channel lengths and higher performance. As the gate oxide was scaled the gate leakage increased; this increase in gate leakage was insignificant until the 90nm technology node (Figure 1). At the 90nm and 65nm nodes, the scaling of the gate oxide slowed as a result of the power limitations from the increase in gate leakage. In order to overcome this at the 45nm technology, a gate dielectric with a higher dielectric constant (high-k) has been introduced. This enabled a >25x gate leakage reduction while scaling the Tox by 0.7x.
On Richtmyer–Meshkov instability in dilute gas-particle mixtures

Richtmyer–Meshkov instability (RMI) in gas-particle mixtures is investigated both numerically and analytically. The linear amplitude growth rate for a RMI in a two-phase mixture is derived by using a dusty gas formulation for small Stokes number (St⪡1.0), and it is shown that the problem can be characterized by mass loading and St. The model predictions are compared with numerical results under two conditions, i.e., a shock wave hitting (1) a perturbed species interface of air and SF6 surrounded by uniformly distributed particles, and (2) a perturbed shape particle cloud in uniform air. In the first case, the interaction between the instability of the species perturbation and the particles is investigated. The multiphase growth model accurately predicts the growth rates when St⪡1.0, and the amplitude growth normalized by the two-phase RMI velocity shows good agreement with the single-phase RMI growth rate as well. It is also shown that the two-phase model results are in accordance with the growth rates ob.
Full-Diversity Codes for MISO Systems Equipped With Linear or ML Detectors

In this paper, a general criterion for space-time block codes (STBC) to achieve full diversity with a linear receiver is proposed for a wireless communication system having multiple transmitter and single receiver antennas [multiple-input-single-output (MISO)]. Particularly, the STBC with Toeplitz structure satisfies this criterion, and therefore, enables full diversity. Further examination of this Toeplitz STBC reveals the following important properties: (1) the symbol transmission rate can be made to approach unity; (2) applying the Toeplitz code to any signalling scheme having nonzero distance between the nearest constellation points results in a nonvanishing determinant. In addition, if quadratic-amplitude modulation (QAM) is used as the signalling scheme, then for independent MISO flat-fading channels, the Toeplitz codes is proved to approach the optimal diversity-versus-multiplexing tradeoff with a zero-forcing (ZF) receiver when the number of channel uses is large. This is, so far, the first nonorthogonal STBC shown to achieve the optimal tradeoff for such a receiver. On the other hand, when maximum-likelihood (ML) detection is employed in a MISO system, the Toeplitz STBC achieves the maximum coding gain for independent channels. When the channel fading coefficients are correlated, the inherent transmission matrix in the Toeplitz STBC can be designed to minimize the average worst case pairwise error probability.
Openstack scheduler evaluation using design of experiment approach

Cloud computing is a computing model which is essentially characterized by an on-demand and dynamic provisioning of computing resources. In this model, a cloud is a large-scale distributed system which leverages internet and virtualization technologies to provide computing resources as a service. Efficient, flexible and dynamic resource management is among the most challenging research issues in this domain. In this context, we present a study focusing on the dynamic behavior of the scheduling functionality of an Infrastructure-as-a-Service (IaaS) cloud, namely OpenStack Scheduler. We aim, through this study at identifying the limitations of this scheduler and ultimately enabling its extension using enhanced metrics. Towards this end, we present a Design of Experiment (DOE) based approach for the evaluation of the OpenStack Scheduler behavior. In particular, we use the screening type of experiment to identify the factors with significant effects on the responses. In our context, these factors are the amount of memory and the number of CPU cores assigned to virtual machine (VM) and the amount of memory and the number of cores on physical nodes. More specifically, we present a two-level fractional factorial balanced with the resolution IV and four center points experimental design with no replication.
Generative atlases and atlas selection for C11-PIB PET-PET registration of elderly, mild cognitive impaired and Alzheimer disease patients

beta-amyloid (Abeta) plaques are one of the neuropathological hallmarks of Alzheimer's disease (AD) and can be quantified using the marker 11C PiB. The registration of 11C PIB PET images to an atlas allows spatial normalization and statistical comparisons. This generally involves a co-registration of the PET and MR which is then registered to an MR atlas. The use of PET to PET atlas registration is much less common, although important as MR scans are not always available. In this paper we present a study on using PET to PET atlas registration with the corresponding MR registration used as the reference standard. Average affine and non-rigidly aligned PET Atlases were created, as well as a principal component based generative atlases. From this work we found that the use of multiple registrations to a generative affine 11C PIB PET atlas obtains the best results, with a mean translation error of 1.67 mm, and average point to point error around the cortex of 2.77 mm. As the obtained results are almost the same as using PET-MR co-registration and propagation to an atlas, and in some cases qualitatively they can appear better, we believe this may be a suitable approach for 11C PIB PET registration, which may avoid the need for acquiring the MR and performing multimodality registration.
Clonal profile, virulence and resistance of Staphylococcus aureus isolated from sheep milk

The objective of this study was to characterize the clonal profile, virulence factors and antimicrobial resistance, particularly oxacillin resistance, of Staphylococcus aureus isolated from sheep milk. Milk samples were collected from all teats for the California Mastitis Test (CMT), somatic cell count, identification of S. aureus, investigation in these strains of genes encoding toxins (sea, seb, sec, sed, tst), biofilm (icaA, icaC, icaD, bap), leukocidin (luk-PV) oxacillin resistance by mecA gene detection and susceptibility testing (12 antibiotics). Messenger RNA expression was evaluated by RT-PCR in isolates carrying toxin and biofilm genes. Biofilm formation was also evaluated phenotypically by adherence to polystyrene plates. The clonal profile of S. aureus was investigated by pulsed-field gel electrophoresis. A total of 473 milk samples were collected from 242 animals on three farms and 20 S. aureus strains were isolated and none carried the mecA gene. The two sec gene-positive isolates and the isolates carrying the tst and luk-PV genes were positive by RT-PCR. Staphylococcus aureus isolated from the three flocks studied showed high susceptibility to the drugs tested and none was biofilm producer, indicating that biofilm formation was not a virulence factor causing infection by these strains. The typing of 17 S. aureus isolates revealed the presence of a common clone on the three farms studied, and the presence and expression of the sec and tst genes in one strain of this clone suggest the possible acquisition of virulence genes by this clone, a fact that is important for animal health and food hygiene.
Optimal Policies and Approximations for a Serial Multiechelon Inventory System with Time-Correlated Demand

Since Clark and Scarf's pioneering work, most advances in multiechelon inventory systems have been based on demand processes that are time independent. This paper revisits the serial multiechelon inventory system of Clark and Scarf and develops three key results. First, we provide a simple lower-bound approximation to the optimal echelon inventory levels and an upper bound to the total system cost for the basic model of Clark and Scarf. Second, we show that the structure of the optimal stocking policy of Clark and Scarf holds under time-correlated demand processes using a Martingale model of forecast evolution. Third, we extend the approximation to the time-correlated demand process and study, in particular for an autoregressive demand model, the impact of lead times and autocorrelation on the performance of the serial inventory system.
Standards for the formal representation of linguistic data: An exchange format for feature structures

The International Standard ISO 24610 defines a schema of how to encode feature structures and their declarations in XML. The main goal of this standard is to provide a format for the exchange of feature structures and feature system declarations between applications. This paper gives an overview of the elements of the standard and sketches its development and some of the design decisions involved. We also discuss the role of this standard in relation to other standardization proposals for language resources and we briefly address its relevance for application programming.
Stock price prediction using linear regression based on sentiment analysis

Stock price prediction is a difficult task, since it very depending on the demand of the stock, and there is no certain variable that can precisely predict the demand of one stock each day. However, Efficient Market Hypothesis (EMH) said that stock price also depends on new information significantly. One of many information sources is people's opinion in social media. People's opinion about products from certain companies may determine the company's reputation and thus affecting people's decision to buy the stock of the company. When using opinion as primary data, it is necessary to make a suitable analysis of it. A famous example using opinion as data is sentiment analysis. Sentiment analysis is a process to determine emotion/feeling within people opinion about something, in this case products of some companies. There are some researches about sentiment analysis used to predict the stock prices. Bollen on his research concludes that people opinion on social media such as Twitter can predict DJIA value with 87.6% accuracy. This shows that there is a relation between sentiment analysis and stock prices. Our purpose on this research is to predict the Indonesian stock market using simple sentiment analysis. Naive Bayes and Random Forest algorithm are used to classify tweet to calculate sentiment regarding a company. The results of sentiment analysis are used to predict the company stock price. We use linear regression method to build the prediction model. Our experiment shows that prediction models using previous stock price and hybrid feature as predictor gives the best prediction with 0.9989 and 0.9983 coefficient of determination.
Economic Viability of Polyculture of Nile Tilapia and Australian Redclaw Crayfish in Yucatan State, Mexico

Tilapia culture in rural communities of the state of Yucatan, Mexico, has been increasing in recent decades. Polyculture of tilapia with other more commercially valuable species is an opportunity to substantially improve the economic yields of rural producers. The economic viability of implementing a Nile tilapia with Australian redclaw crayfish polyculture was analyzed using profitability indicators such as internal rate of return (IRR) and net present value of the investment (NPV). A bioeconomic model was developed to simulate three production densities (33/0, 33/20, tilapia and crayfish, respectively), accounting for investment recuperation in time horizons of 5, 10 and 15 years. The model includes a biological sub-model describing the growth of both organisms, a management sub-model that influences organism development and an economic sub-model describing the main input and output variables of the economic setting of tilapia producers in the state of Yucatan. The biological sub-model was parameterized using published experimental polyculture data from Israel. A thermal correction function was integrated into Von Bertalanffy’s growth model to include the effect of temperature of Yucatan on growth in both organisms. The simulations showed a notable improvement in profitability when farms adopt the polyculture strategy, particularly over the 5-year horizon. The NPV of this horizon was -$4,855.06, $7,923.33 and $1,519.88, Mexican pesos, to the tilapia monoculture, medium crayfish density polyculture and high crayfish density polyculture, respectively. The Nile tilapia with Australian redclaw crayfish polyculture shortens investment recuperation time and it inhibits the risk related to changes in tilapia sale price. The best of the three studied combinations was the medium crayfish density polyculture (33/10) in all time horizons.
Prices of Single Family Homes Since 1970: New Indexes for Four Cities

This paper uses data on nearly a million homes sold in four metropolitan areas -- Atlanta, Chicago, Dallas and San Francisco -- to construct quarterly indexes of existing home prices between 1970 and 1986. We propose and apply a new method of constructing such indexes which we call the weighted repeat sales method (WRS). We believe the results give an accurate picture of the actual rate of appreciation in home prices in the four cities. The paper explains the construction of the index, discusses the results and compares them with the National Association of Realtors data on the median price of existing single family homes for the period 1981 - 1986.
Combination of Wavelet Multiscale Analysis and Support Vector Machines for Determination of Multicomponent

This paper suggests a novel method named DF-LS-SVM based on least squares support vector machines (LS-SVM) regression combine with multiscale wavelet transforms and data fusion (DF) to enhance the ability to extract characteristic information and improve the quality of the regression. Experimental results showed the DF-LS-SVM method was successful for simultaneous multicomponent determination even where there was severe overlap of spectra. The DF-LS-SVM method is a hybrid technique that combines the best properties of the two techniques and makes this method attractive and promising.
Optimum Wordlength Search Using Sensitivity Information

Many digital signal processing algorithms are first developed in floating point and later converted into fixed point for digital hardware implementation. During this conversion, more than 50% of the design time may be spent for complex designs, and optimum wordlengths are searched by trading off hardware complexity for arithmetic precision at system outputs. We propose a fast algorithm for searching for an optimum wordlength. This algorithm uses sensitivity information of hardware complexity and system output error with respect to the signal wordlengths, while other approaches use only one of the two sensitivities. This paper presents various optimization methods, and compares sensitivity search methods. Wordlength design case studies for a wireless demodulator show that the proposed method can find an optimum solution in one fourth of the time that the local search method takes. In addition, the optimum wordlength searched by the proposed method yields 30% lower hardware implementation costs than the sequential search method in wireless demodulators. Case studies demonstrate the proposed method is robust for searching for the optimum wordlength in a nonconvex space.
The duality of temporal encoding – the intrinsic and extrinsic representation of time

While time is well acknowledged for having a fundamental part in our perception, questions on how it is represented are still matters of great debate. One of the main issues in question is whether time is represented intrinsically at the neural level, or is it represented within dedicated brain regions. We used an fMRI block design to test if we can impose covert encoding of temporal features of faces and natural scenes stimuli within category selective neural populations by exposing subjects to four types of temporal variance, ranging from 0% up to 50% variance. We found a gradual increase in neural activation associated with the gradual increase in temporal variance within category selective areas. A second level analysis showed the same pattern of activations within known brain regions associated with time representation, such as the Cerebellum, the Caudate, and the Thalamus. We concluded that temporal features are integral to perception and are simultaneously represented within category selective regions and globally within dedicated regions. Our second conclusion, drown from our covert procedure, is that time encoding, at its basic level, is an automated process that does not require attention allocated toward the temporal features nor does it require dedicated resources.
Patient and hospital characteristics associated with recommended processes of care for elderly patients hospitalized with pneumonia: results from the medicare quality indicator system pneumonia module.

BACKGROUND Unexplained wide variability exists in the performance of key initial processes of care associated with improved survival of elderly patients (those > or =65 years) hospitalized with pneumonia. The objective of this study was to assess which patient and hospital characteristics are associated with performance of these key initial processes of care for hospitalized elderly patients with pneumonia. METHODS A retrospective cohort analysis was performed using data from the Medicare Quality Indicator System Pneumonia Module for 14 069 patients 65 years or older hospitalized with pneumonia throughout the United States. Associations were calculated using multivariate logistic regression analysis between specific patient and hospital characteristics and 2 processes of care associated with improved 30-day survival: administration of antibiotics within 8 hours of hospital arrival and blood culture collection within 24 hours of arrival. RESULTS Timely antibiotic administration was negatively associated with nonwhite race (African American: odds ratio [OR], 0.71; 95% confidence interval [CI], 0.60-0.85; and other racial minorities: OR, 0.79; 95% CI, 0.68-0.92), major hospital teaching status (OR, 0.79; 95% CI, 0.67-0.93), and larger hospital size (> or =250 beds vs. <100 beds: OR, 0.68; 95% CI, 0.59-0.80). Timely blood culture collection was positively associated with larger hospital size (OR, 1.61; 95% CI, 1.39-1.87). Performance of both processes of care were positively associated with registered nurse-bed ratios of 1.25 or higher (for antibiotic administration: OR, 1.23; 95% CI, 1.10-1.38; and for blood culture collection: OR, 1.43; 95% CI, 1.26-1.61) and fever (for antibiotic administration: OR, 1.35; 95% CI, 1.23-1.49; and for blood culture collection: OR, 3.07; 95% CI, 2.81-3.34) and were negatively associated with hospital location in the South (for antibiotic administration: OR, 0.77; 95% CI, 0.69-0.86; and for blood culture collection: OR, 0.85; 95% CI, 0.77-0.93). CONCLUSIONS Minority race, fever, nurse-bed ratio, hospital size and teaching status, and southern location are among the major patient and hospital characteristics associated, either negatively or positively, with the timeliness of performance of initial antibiotic administration and blood culture collection for patients hospitalized with pneumonia. Because performance of these processes of care is associated with improved likelihood of survival, medical providers should seek to eliminate the variations in care associated with these patient and hospital characteristics. In addition, the impact of nurse staffing changes on performance of key time-sensitive processes of care should be weighed carefully.
The Common Law in Two Voices: Language, Law, and the Postcolonial Dilemma in Hong Kong

Hong Kong is one of the very few places in the world where the common law can be practiced in a language other than English. Introduced into the courtroom over a decade ago, Cantonese has significantly altered the everyday working of the common law in China's most Westernized city. In The Common Law in Two Voices, Ng explores how English and Cantonese respectively reinforce and undermine the practice of legal formalism. This first-ever ethnographic study of Hong Kong's unique legal system in the midst of social and political transition, this book provides important insights into the social nature of language and the work of institutions. Ng contends that the dilemma of legal bilingualism in Hong Kong is emblematic of the inherent tensions of postcolonial Hong Kong. Through the legal dramas presented in the book, readers will get a fresh look at the former British colony that is now searching for its identity within a powerful China.