Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study on the Impact of Household Occupants’ Behavior on Energy Consumption Using an Integrated Computer Model

In this paper, several models are integrated into a thermal model to study the impact of occupants’ behaviors on the building energy consumption. An air flow model is developed to simulate ventilation related to the occupant’s patterns of window opening and closing. An electric consumption model is developed to simulate the usage pattern and the electricity input to household electric appliances. The thermostat setpoint temperature and window shading schemes are varied with different occupants’ behavior norms and are included in the model. The simulation was applied to a typical household located in the city of Oshawa in Ontario, Canada. The results show that the window opening has the greatest impact on the energy consumption during the heating season, and the shading scheme has the greatest impact on the A/C energy consumption during the cooling season. The electricity consumption of the A/C can be significantly reduced by appropriately applying the shading and opening schemes and resetting the thermostat setpoint temperature to a slightly higher degree. Keeping the windows closed and allowing the solar radiation to be transmitted through the window in winter help reduce the energy usage to heat the house.
1 Identifying Morphological Markers for Differential Diagnosis of Liver Lesion

1. Introduction Liver lesions stem from a variety of causes ranging from benign to malignant. The ability to efficiently and accurately differentiate these lesions as malignant or benign using non-invasive medical imaging is important to patient treatment and outcome. Contrast-enhanced computed tomography (CT) imaging is the dominant technology used for liver lesion diagnosis [1]. This modality takes advantage of the fact that the liver receives blood from two main sources, the portal vein and the hepatic artery. About 80% of blood in the liver comes from portal vein and the other 20% comes from the hepatic artery, whereas liver cancer receive all their blood from the hepatic artery [2, 3]. Injecting contrast enhancing agents into the portal vein and performing a liver CT scan shortly thereafter will cause the liver to appear brighter than the cancer because it receives the entire dosage of contrast agent. This technique is called Portal Venous Phase (PVP) imaging. Unfortunately the specificity of this method is a function of the size of the tumor and prone to a high false positive rate because other types of benign liver lesions have similar manifestation on CT images [4]. Human variability has been shown to be an issue regarding lesion differential diagnosis, and automated methods are being investigated to facilitate the diagnosis of these lesions [5]. Recent research has investigated computer-aided methods to facilitate diagnosis by providing a database of annotated images that can be retrieved by similarity [6]. It suggests that using semantic annotations and computational imaging features can lead to highly accurate diagnosis. Semantic annotations are a
Identifying Polyphonic Musical Patterns From Audio Recordings Using Music Segmentation Techniques

This paper presents a method for discovering patterns of note collections that repeatedly occur in a piece of music. We assume occurrences of these patterns must appear at least twice across a musical work and that they may contain slight differences in harmony, timbre, or rhythm. We describe an algorithm that makes use of techniques from the music information retrieval task of music segmentation, which exploits repetitive features in order to automatically identify polyphonic musical patterns from audio recordings. The novel algorithm is assessed using the recently published JKU Patterns Development Dataset, and we show how it obtains state-of-the-art results employing the standard evaluation metrics.
Fault Tolerant Topology Control for Clustered Wireless Sensor Networks

In most clustered topology control algorithms of sensor networks, all the sensor nodes are clustered and the network backbone is formed by cluster head nodes and gateway nodes, while cluster nodes keep sleeping to reduce energy cost. A fault- tolerant topology control algorithm based on clustered sensor nodes is proposed in this paper, which is termed as KCCTC (K- Connected cluster topology control protocol for wireless sensor network). The main content of the KCCTC algorithm is the procedure of the clusters forming, which includes the selection of backbone nodes, redundant nodes and sleeping scheduling of cluster nodes. In the selection of backbone nodes, energy balancing, channel quality, nodes fault and mobility are taken into account in this paper. The simulation results show that the algorithm has a better performance in network topology stability and lifetime.
Efficient Active Learning Constraints for Improved Semi-Supervised Clustering Performance

 Abstract — This paper presents a semi supervised clustering technique with incremental and decremental affinity propagation (ID-AP) that structures labeled exemplars into the AP algorithm and a new method for actively selecting informative constraints to make available of improved clustering performance. The clustering and active learning methods are both scalable to large datasets, and can hold very high dimensional data. In this paper, the active learning challenges are examined to choose the must-link and cannot-link constraints for semi-supervised clustering. The proposed active learning approach increases the neighborhoods based on selecting the informative points and querying their relationship between the neighborhoods. At this time, the classic uncertainty-based principle is designed and novel approach is presented for calculating the uncertainty associated with each data point. Further, a selection criterion is introduced that trades off the amount of uncertainty of each data point with the probable number of queries (the cost) essential to determine this uncertainty. This permits us to select queries that have the maximum information rate. Experimental results demonstrate that the proposed ID-AP technique adequately captures and takes full advantage of the intrinsic relationship between the labeled samples and unlabeled data, and produces better performance than the other considered methods Empirically evaluate the proposed method on the eight benchmark data sets against a number of competing methods. The evaluation results indicate that our method achieves consistent and substantial improvements over its competitors.
JANUS II - ADVANCES IN SPONTANEOUS SPEECH TRANSLATION

JANUS II is a research system to design and test compo nents of speech to speech translation systems as well as a research prototype for such a system. We will focus on two aspects of the system: 1) new features and recognition per formance of the speech recognition component JANUS-SR and 2) the end-to-end performance of JANUS II, including a comparison of two machine translation strategies used for JANUS-MT (PHOENIX and GLR*).
Critical Review of Authentication Mechanisms in Cloud Computing

Cloud computing is a technology, which provides low cost, scalable computation capacity and a stack of services to enterprises on demand for expansion. The complications caused by data security and privacy are the main hindrances in its acceptance. Threats in Cloud computing can be faced by adopting various security measures. One such security measure is authentication. In recent years a lot of research has been carried out throughout the world and several schemes have been proposed to improve authentication in the Cloud. Keeping in view the importance of authentication in cloud security, a survey of current cloud computing authentication trends has been conducted. On the basis of this critical review, we identify the areas of cloud computing authentication that indeed warrant further investigation.
Estimating Probabilities of Recession in Real Time Using GDP and GDI

This work estimates Markov switching models on real time data and shows that the growth rate of gross domestic income (GDI), deflated by the GDP deflator, has done a better job recognizing the start of recessions than has the growth rate of real GDP. This result suggests that placing an increased focus on GDI may be useful in assessing the current state of the economy. In addition, the paper shows that the definition of a low-growth phase in the Markov switching models has changed over the past couple of decades. The models increasingly define this phase as an extended period of around zero rather than negative growth, diverging somewhat from the traditional definition of a recession.
Myc/Max/Mad regulate the frequency but not the duration of productive cell cycles

Upregulation of the proto‐oncoprotein Myc, a basic, helix–loop–helix, leucin zipper domain transcription factor has profound consequences on cell proliferation, cell growth and apoptosis. Cell cultures of somatic c‐myc−/− rat fibroblasts show extremely prolonged doubling times of 52 h. Using time‐lapse microscopy, we show here that individual c‐myc−/− cells proceeded within ∼24 h through the cell cycle as fast as c‐myc+/+ cells. However, c‐myc−/− cells were highly sensitive to contact inhibition and readily arrested in the cell cycle already at low density. Activation of conditional MycER overcame cell cycle arrest in c‐myc−/− cells and led to continuous proliferation at the expense of increased apoptosis at high cell density. Conditional expression of Mad1, a Myc antagonist, represses proliferation of different cell types including U2OS cells. In analogy to the effect of Myc, this occurs mainly by reducing the probability of cells remaining in the cycle. Our data demonstrate that the Myc/Max/Mad network does not regulate the duration of the cell cycle, but the decision of cells to enter or exit the cell cycle.
CONSIDERING PRODUCTION UNCERTAINTY IN BLOCK LAYOUT DESIGN

Bryan A. NormanDepartment of Industrial EngineeringUniversity of Pittsburgh1048 Benedum HallPittsburgh, PA 15261banorman@engrng.pitt. edu412-624-9830412-624-9831 (fax)Alice E. SmithDepartment of Industrial and Systems EngineeringAuburn University206 Dunstan HallAuburn University, AL 36849-5346aesmith@eng.auburn. edu334-844-1400334-844-1381 (fax)Submitted to
Interest Rate Volatily, Contagion and Convergence: And Empirical Investigation of the Cases of Argentina, Chile and Mexico

Current debates on globalization have tended to focus on financial market volatility and contagion. In fact, many proponents of the imposition of some form of capital restrictions in emerging markets have argued that these would help reduce - or even eliminate -spillover across emerging market. Although this has been an old concern among developing economies, it has become more generalized after the Mexican, East Asian and Russian crises. In this paper I use high frequency data on short term nominal interest rates during the 1990s in three Latin American countries - Argentina, Chile and Mexico -- to analyze whether there has been volatility contagion from Mexico to the two South American nations. The results obtained from the estimation of augmented GARCH equations indicate, quite strongly, that while there has been volatility contagion from Mexico to Argentina, there has been no volatility contagion from Mexico to Chile. These results also indicate, however, that with the exception of a brief period in 1995, nominal interest rates have been more volatile in Chile than in Argentina. The results reported in this paper also indicate that interest rate differentials with respect to the US have tended to disappear somewhat slowly in both Chile and Argentina. Moreover, the estimation of rolling regressions for Chile indicate that after capital controls on capital inflows were imposed, interest rate differentials became more sluggish and tended to disappear more slowly than during the free capital mobility period.
At-most-once Algorithm for Linearizable RPC in Distributed Systems

In a distributed system, like RAMCloud, supporting automatic retry of RPC, it is tricky to achieve linearizability correct along with durability and liveness. Automatic retry may cause duplicate executions when a server fails after durably recording the original execution and before sending its response. We can cope with the problem by implementing at-most-once mechanism for RPC system. But in a massively distributed system, the implementation of the algorithm is not simple; correct recovery of RPC information and garbage collection for the information in cluster level are pretty challenging. In this project, I am presenting solutions to the problems and implementation in a distributed storage system, called RAMCloud.
Different Normalization Strategies Might Cause Inconsistent Variation in Circulating microRNAs in Patients with Hepatocellular Carcinoma

Background Circulating microRNA (miRNA) are promising biomarkers for diagnosing and prognosticating numerous diseases. Reports have demonstrated controversial or even contradictory conclusions in studies on circulating microRNA. This study aimed to evaluate the potential bias of using different reference genes for analyzing circulating microRNAs in the same malignant digestive diseases. Material/Methods We measured plasma concentrations of U6-snRNA, let-7a, miRNA-21, miRNA-106a, miRNA-155, miRNA-219, miRNA-221, and miRNA-16 in patients with hepatocellular carcinoma (HCC), gastric carcinoma (GC), hepatic cirrhosis, hepatitis B, and healthy volunteers using quantitative real-time polymerase chain reaction (qPCR). The GeNorm, Normfinder, BestKeeper, and Comparative ΔCq algorithms integrated in RefFinder were used to screen the most suitable reference genes from the candidates. The 4 commonly used statistical evaluation software packages provided different results regarding the stability of the candidate reference genes. Results RefFinder revealed miRNA-106a and miRNA-21 as the most stably expressed reference genes, with comprehensive stability values of 1.189 and 1.861, respectively. U6-snRNA was the most unstable nucleic acid in our data. When 5 normalization strategies were compared using U6-snRNA, serum volume, miRNA-106a, miRNA-21, or the mean value of miRNA-106a and miRNA-21, obvious expression bias was detected in almost all target microRNAs. Intriguingly, all these normalization strategies indicated that circulating miRNA-155 is greatly upregulated in patients with HCC and GC, but downregulated in benign hepatic disease. Conclusions Single reference genes used without justification in plasma microRNAs produce significant analysis bias or even erroneous results. Circulating miRNA-155 may be a promising non-invasive biomarker for discriminating malignant digestive tumors from the corresponding benign diseases.
Journal of Theoretical and Applied Information Technology on Improved Example-based Search in Digital Libraries via Term Ranking

Example-based searching, where user provides an example publication to locate similar publications to, is becoming commonplace in literature digital libraries. Two approaches to estimate similarities between publications are (i) graph based approaches where citation relationships amongst publication are used to compute similarities, and (ii) text-based approaches where observing shared terms between publications is used as indicator of similarity. In this paper we introduce a new text-based publication-similarity measuring technique that enhances existing example-based searching through utilizing term importance information. Term importance is computed via a proposed graph-based term ranking (GBTR) algorithm. The GBTR algorithm is different from previous term ranking approaches as it recursively computes term importance from the entire publication where it is observed, rather than relying only on local specific information. GBTR works well when paired with Okapi BM25. We exhaustively evaluate the performance of GBTR and compare it against the performance of existing term-ranking methods such as the Chronological Term Rank (CTR) and the Term Proximity models. Significant improvements, in terms of precision, over existing approaches are observed. GBTR achieved around 10% improvement in precision over CTR and around 2% over TP with much less computational time and space complexity than the TP approach.
Increasing the EE-SE Trade-Off in MIMO Rayleigh Fading channel

- For high speed wireless communication, data are transmitted with high spectral efficiency, high data rate and reliability. But due to Rayleigh fading, the channels suffer from lot of attenuation resulting in the reduction of Energy Efficiency (EE) and Spectral Efficiency (SE). The proposed system consists of MIMO using Closed Form Approximation (CFA) method. Multiple input Multiple Output (MIMO) systems are form of spatial diversity in which we use multiple antennas at transmitter as well as receiver. In multipath channel, deploying multiple antenna techniques at both transmitter and receiver achieves high data rate without increasing the total transmission power or bandwidth. This technology is used to reduce errors and optimize data rates. MIMO is a great technique to achieve high bandwidth and system performance. Here, energy efficiency, spectral efficiency, MIMO efficiency are the parameters that are compared using simulation. Simulation results show that when energy efficiency increases with increase in spectral efficiency. As a result, the overall efficiency of MIMO system also increases while Trade-off the EE-SE by using Closed Form Approximation (CFA) method and explicit expression method. From this CFA method gives less approximation error.
A GIS-based Framework To Model Farm And Landscape Scale Indicators For Sustainable Rural Development

Facilitation of sustainable rural development has a high priority on the European Union policy agenda and extensive research on this subject has been started. This paper presents results from the strategic EU research project MEA-scope (www.MEA-scope.org), and the development of a GIS-based framework to model farm and landscape scale indicators for rural sustainability. Problems in scaling information between the farmand the landscape levels in particular are addressed. Both aggregation and disaggregation techniques are needed to convey information between the two levels. This is demonstrated in a case study of (1) landscape level aggregation of farm level information, from statistics and from farming simulation models, and (2) disaggregation of landscape level features such as soil, climate and land use types, for farm level modelling. This interaction between farmand landscape level information sources gives the opportunity for integrated modelling of farm level indicators (e.g. nutrient balances, energy use, farmers age, employment etc.) and landscape level indicators (e.g. groundwater supply, corridors between habitats and population density). The framework developed gives valuable inputs to the discussion of which indicators are valid at farm and landscape level, respectively, and whether they have different interpretations at different scales. Whether the demonstrated aggregation and disaggregation techniques are sufficient in terms of the inclusion of linear, non-linear or other emergent effects of scale, is discussed.
包括利益の実証研究 = Empirical research on comprehensive income

第１章 本書の目的と構成 第２章 包括利益と純利益の比較 第３章 包括利益と純利益の利益特性 第４章 包括利益と純利益による投資リスクの評価 第５章 その他の包括利益の個別項目の増分情報内容に関する研究 第６章 包括利益の相対的情報内容と増分情報内容に関する研究 第７章 包括利益と純利益の価値関連性 第８章 包括利益と純利益に関する経営者の利益調整行動 第９章 利益調整行動からみた包括利益と純利益の価値関連性 第１０章 結論と展望
Hypoxia, almitrine, and peripheral neuropathy.

The chronic hypoxia seen at high altitude or induced experimentally by environmental changes has several physiological and pathological consequences. The carotid body, the principal sensor of blood oxygen tension, enlarges' and contains increased amounts of dopamine and noradrenaline.2 The hypoxic drive to ventilation diminishes.3 In the lung there is constriction of pulmonary arterioles in association with increased muscularisation of their walls, right ventricular hypertrophy, and a rise in pulmonary arterial pressure.45 In patients with severe obstructive airways disease chronic hypoxaemia when severe is associated with peripheral oedema, often inappropriately termed cor pulmonale. Although the clinical features resemble cardiac failure with a raised jugular venous pressure, hepatomegaly, and gross anasarca, cardiac output is normal or even raised and right ventricular function minimally disturbed. Renal blood flow is reduced by half or more, and this seems to be a critical physiological abnormality, closely correlated with hypoxaemia and hypercapnia, particularly the latter.67 It was hoped that many of these features in patients with hypoxaemic chronic obstructive airways disease would be improved by oxygen therapy designed to restore arterial oxygen tension to at least 8 kPa and arterial oxygen saturation to 90% or more. The benefit so far, however, has been limited. Long term domiciliary oxygen therapy was found to require administration for at least 15 hours a day for benefit to be seen, better results requiring even longer treatment-up to 24 hours a day.89 Survival is increased for some years with long term oxygen therapy but this fails to arrest the decline in airway function or the continuing pathological changes in small pulmonary vessels; benefit in the long term is limited. '" Attempts have been made to reverse the effects of hypoxia by pharmacological means as this would be considerably more convenient for the patient. Almitrine bismesylate, an orally administered triazine derivative, functions as a peripheral chemoreceptor agonist stimulating afferent carotid body nerves much as in hypoxaemia. " It causes an increase in minute ventilation and there may also be subtle ventilatory changes that are not detected as an increase in total ventilation, which increase gas flow to alveoli. Almitrine also causes pulmonary vasoconstriction, possibly more so in hypoxic areas of the lung. Whether
fCombMNZ: An Improved Data Fusion Algorithm

The data-fusion techniques have been investigated by many researchers and have been used in implementing several information retrieval systems. Fusion allows leveraging of the component systems in several ways by exploiting a number of effects, amongst them an effect called "Chorus effect"; this effect suggest that for a particular document if it is retrieved by two systems; it will be "better" than another document retrieved by only one system, and if it is retrieved by three systems it will be "better" than another document retrieved by one or two systems, and so on. "Better" means the document has higher probability to be relevant. We suggest including a new simple but effective rule called "fairness rule" within well known data-fusion algorithm called CombMNZ to allow this algorithm from leveraging the component systems in an effective way, this rule is the first attempt in the literature to manipulate the normalized score values for documents under certain circumstances to maximize the CombMNZ ability to benefit from the "chorus effect" without sacrificing its ability to benefit from another effect called "skimming effect", skimming effect; suggests that relevant documents are most likely to occur on the top of the retrieved list for any retrieval system. Our results show an improvement in the mean average precision (MAP) values over the traditional CombMNZ when we used our "fairness rule", the improvement for TREC3 groups ranged from 0.66% to 2.88%, and for TREC5 ranged from 0.2% to 3.7%.