Miracle-dz/UniFAR-FTUs huggingface dataset:
Physical-biological coupling at the meso scale range around South Shetland Islands ( Antarctica )-COUPLING ” View project

Phytoplankton assemblages around the South Shetland Islands (SSI) were closely related to mesoscale physical features, based on high spatial resolution sampling performed during the summer of 2010. Sampling was done in 8 transects with stations 9 km apart. Phytoplankton groups were described using flow cytometry, FlowCAM and HPLC/CHEMTAX pigment analysis. Nanophytoplankton (2–20 lm) was predominant throughout the study area, which was dominated by small diatoms. They were distributed along the stratified waters of the SSI shelf and in the centre of the Bransfield Strait where an anticyclonic eddy was detected, established between two frontal structures [Bransfield Front and Peninsula Front (PF)]. The highest concentrations correlated with mid-to-high temperatures (1.07 C) and mid-salinities (34.03) corresponding with Transitional Bellinghausen Water stations. Haptophytes distribution co-varied with small diatoms but also appeared in those vertical mixed stations with Transitional Zonal Water with Weddell Sea influence. A shift from smaller to larger diatoms was detected at the ice edge in the Antarctic Sound. Cryptophytes were restricted to stratified stations of the SSI shelf and those associated with the PF, while small prasinophytes were the only group occupying deeper and colder waters of the Drake Passage, beneath the Antarctic Surface Water, north of a narrow frontal region described here for the first time (Shetland Front). Phytoplankton assemblages around the SSI were strongly connected with the Bransfield Current System, supporting a clockwise circulation around the archipelago. The Bransfield Current System components are permanent structures during the austral summer suggesting that the distribution of phytoplankton, which responds to these structures, must also be a quasi-permanent feature.
Less Data Delivers Higher Effectiveness for KeywordQueries

As many users, such as scientists, do not know the schema and/or content of their databases, they cannot precisely formulate their information needs using formal query languages, such as SQL. To help these users, researchers have proposed keyword query interfaces over which users can submit their information need using a set of keywords without the precise knowledge about the schema or content of the database. Despite their usability, keyword query interfaces suffer from low effectiveness in answering queries. Therefore, they may return many non-relevant answers or do not return many answers related to the input queries. It is well established that the effectiveness of answering queries decreases as the size of the dataset grows, given all other conditions are the same. In this paper, we propose an approach that uses only a relatively small subset of the database to answer most queries effectively. Since this subset may not contain the relevant answers to many queries, we also propose a method that predicts whether a query can be answered more effectively using this subset or the entire database. Our comprehensive empirical studies using multiple real-world databases and query workloads indicate that our approach significantly improves both the effectiveness and efficiency of answering queries.
Enhancement of Sift algorithm to check authenticity of Indian Currency

The image analysis is a technique of image processing that helps to analyze various properties of the input image. In the recent times various application of the image analysis has come into existence. The current detection is the application of image analysis which is used to define that whether currency is fake or genuine. Various algorithms has been proposed based on SIFT algorithm to analyze external features of input currency. In the existing algorithm, only external features are analyzed that has accuracy of detection. In the proposed work, new technique has been proposed to analysis on to analyze internal features of the image for the detection. The internal features of the image are strip values of the currency. Simulation has been performed in MATLAB. Peak signal to noise ratio (PSNR), root mean square error (RMSE), fault detection rate (FDR) and accuracy values of the proposed and existing algorithm are compared to validate the proposed system.It is been found that accuracy of detection has increased up to 10 percent and fault detection rate is reduced up to 8 percent.
Accelergy: An Architecture-Level Energy Estimation Methodology for Accelerator Designs

With Moore's law slowing down and Dennard scaling ended, energy-efficient domain-specific accelerators, such as deep neural network (DNN) processors for machine learning and programmable network switches for cloud applications, have become a promising way for hardware designers to continue bringing energy efficiency improvements to data and computation-intensive applications. To ensure the fast exploration of the accelerator design space, architecture-level energy estimators, which perform energy estimations without requiring complete hardware description of the designs, are critical to designers. However, it is difficult to use existing architecture-level energy estimators to obtain accurate estimates for accelerator designs, as accelerator designs are diverse and sensitive to data patterns. This paper presents Accelergy, a generally applicable energy estimation methodology for accelerators that allows design specifications comprised of user-defined high-level compound components and user-defined low-level primitive components, which can be characterized by third-party energy estimation plug-ins. An example with primitive and compound components for DNN accelerator designs is also provided as an application of the proposed methodology. Overall, Accelergy achieves 95% accuracy on Eyeriss, a well-known DNN accelerator design, and can correctly capture the energy breakdown of components at different granularities. The Accelergy code is available at http://accelergy.mit. edu.
REGIONALIZATION OF N 2 O MEASUREMENTS FOR THE NORTH CHINA PLAIN

The Sino-German Project between the China Agricultural University and the University of Hohenheim, Germany, focused on sustainable Agriculture in the North China Plain. One major focus of the project was the establishment of an experiment field near Beijing to investigate different agricultural practices and their impact on yield and environment. The second task was to set-up a GIS based Agricultural Environmental Information System (AEIS) for the North China Plain (NCP), which exceeds almost the size of Germany. Researchers from several departments were involved in the project: Agricultural Economics, Agricultural Informatics, Vegetable Science, Landscape Ecology, Phytomedicine, Plant Nutrition, Plant Production and Soil Science. The major aim of the AEIS for the NCP is to provide information (i) about agriculture in the region, (ii) about the impact of agricultural practices on the environment and (iii) of simulation scenarios for sustainable strategies. Consequently, the AEIS for the NCP provides information for decision support and therefore could be regarded as a Decision Support System (DSS), too. In this contribution, the focus is on the importance of the linkage of measurement data with spatial data for a selected area of Beijing municipality which is a part of the North China Plain. By using the database of the AEIS, it is possible to roughly estimate the N2O emission from winter wheat / summer maize rotation which is the dominant crop rotation in the North China Plain. Furthermore, the potential of some mitigation strategies can be estimated for the regarded area. Finally, the comparison with and evaluation of available models and methods (IPCC; DNDC) for regional calculation is presented.
M ar 2 01 7 Instability of Fulde-Ferrell-Larkin-Ovchinnikov states in three and two dimensions

The exotic Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) states have been actively searched for experimentally since the mean-field based FFLO theories were put forward half a century ago. Here we investigate the stability of FFLO states against unavoidable pairing fluctuations, and conclude that FFLO superfluids cannot exist due to their intrinsic instability in three and two dimensions. This explains their absence in experimental observations in both condensed matter systems and the most recent, more promising ultracold atomic Fermi gases with a population imbalance.
Data mining with Predictive analysis for healthcare sector : An Improved weighted associative classification approach

Association mining has seen its growth right through data mining during the last few years as it has the ability to search for that entire database that could be of least constraints associated with it.Thus finding such small database sets could be done with the help of predictive analysis method. The paper enlightens the combinational classification of association and classification data mining. For this to happen a new set of constraints need to be introduced namely classification association rule( CAR). some systems like classification systems with domain experts are the ones that can be associated with. For fields like medicine where a lot many patients consult each doctor, but every patient has got different personal details not necessarily may suffer with same disease. So the doctor may look for a classifier, which could provide all details about every patient and henceforth necessary medications can be provided. However there have been many other classification methods like CMAR, CPAR MCAR and MMA and CBA.Some advance associative classifiers have also seen growth very recently with small amendments in terms of support and confidence, thereby accuracy. In this paper we proposed a HIT algorithm based automated weight calculation approach for weighted associative classifier.
Hospital Inventory Management Through Markov Decision Processes

Stock management in a hospital requires the achievement of a trade-off between conflicting criteria, with mandatory requirements on the quality of patient care as well as on purchasing and logistics costs. We address daily drug ordering in a ward of an Italian public hospital, where patient admission/discharge and drug consumption during the sojourn are subject to uncertainty. To derive optimal control policies minimizing the overall purchasing and stocking cost while avoiding drug shortages, the problem is modeled as a Markov Decision Process (MDP), fitting the statistics of hospitalization time and drug consumption through a discrete phase-type (DPH) distribution or a Hidden Markov Model (HMM). A planning algorithm that operates at run-time iteratively synthesizes and solves the MDP over a finite horizon, applies the first action of the best policy found, and then moves the horizon forward by one day. Experiments show the convenience of the proposed approach with respect to baseline inventory management policies.
Voluntary Disclosure of Disaggregated Capital Expenditures 1

Reported capital expenditures (CAPX) can be voluntarily disaggregated between maintenance (MCAPX) and growth (GCAPX) capital expenditures. Analysts have specifically requested this disaggregation because these two components provide distinctly different information useful to investors. MCAPX is the portion of investment used to prevent deterioration in performance by ensuring the longevity of plant and equipment, while, GCAPX is the portion of capital investment spent on new projects. The objectives of this study are (1) to determine if proprietary and agency cost are associated with the voluntary disclosure of disaggregated CAPX information and (2) determine whether disclosures of MCAPX and GCAPX provide different outcomes related to future performance. Regarding the first objective, we find that proprietary and agency costs are associated with the voluntary disclosure of disaggregated capital expenditures. Regarding the second objective, the findings support that the disclosures of MCAPX and GCAPX have different consequences for future firm performance. Specifically, we find GCAPX has a more positive association with future firm performance than MCAPX. Furthermore, the positive association between GCAPX and future performance is decreased by agency costs. The different associations of MCAPX and GCAPX with future firm performance suggest the disaggregation of CAPX provides important information about future earnings. Based on these findings, standard setters should give greater consideration to requiring the disclosure of disaggregated CAPX information.
MODELLING , CONTROL AND SIMULATION OF MPPT FOR WIND ENERGY CONVERSION USING MATLAB / SIMULINK

-This paper cover modeling, analysis, controland simulation of a maximum power point tracking (MPPT) for wind energy conversion. This wind energy conversion system (WECS) is grid connected and the amount of output electrical power generated from wind energy conversion system (WECS) is purely depends upon accuracy of the peak power tracked by the maximum power point tracking (MPPT) and PID controller used in WECS. A mathematical model of the system is present in this paper and it’s also provides a review of MPPT controllers used for tracking maximum power from the WECS using (PMSG). In which controllers may be divided into three main controlling methods, namely power signal feedback (PSF)control, tip speed ratio (TSR) control and hill-climb search (HCS) control. The proposed system is simulated for some operations are used in this paper to illustrate the reliability control technique in WECS. The importance of MPPT in WECS, and the effectiveness of adopted control technique.
A Comparison Study of Clustering or Classification Methods for Search Results Visualization in Web Search Context

The amount of information on the Web is steadily growing since its beginning. The number of on-line information retrieval systems has increased in parallel to this amount of information. These have been designed to help the information seeking process and to perform the user final tasks from his perspective (Wilson, 1999). As a result, web search engines are massively used to allow the accomplishment of a large range of environment-dependant and goal-ended tasks (Broder, 2002; Rose & Levinson, 2004; Toms, Freund, Kopak, & Bartlett, 2003). While information retrieval techniques (indexing, organization and ranking) and interactive features have been improved since the last twenty years (Baeza-Yates & Ribeiro-Neto, 1999; Manning, Raghavan, & Schutze, 2008; Shneiderman & Plaisant, 2005), the on-line information retrieval systems still remain hard to use (Borgman, 1996; Markey, 2007a, 2007b) and don't fit the cognitive and affective processes of the information searching tasks efficiently (Ingwersen, 1996; Ingwersen & Jarvelin, 2005; Kuhlthau, 2005; Kuhlthau, Heinstrom, & Todd, 2008).
MULTIFUNCTIONAL ANALYTIC SPACES ON PRODUCTS OF BOUNDED STRICTLY PSEUDOCONVEX DOMAINS AND EMBEDDING THEOREMS

The theory of one functional analytic spaces on pseudoconvex domains is welldeveloped by various authors during last decades (see [4–6] and various references there). One of the goals of this paper among other things is to define for the first time in literature multifunctional analytic spaces in strictly pseudoconvex domains and to establish some basic properties of these spaces. We believe this new interesting objects can serve as a base for further generalizations and investigations in this active research area. Multifunctional spaces we mentioned above are closely connected also with socalled analytic function spaces on products of strictly pseudoconvex domains D×· · ·× D. Various such connections in analytic and harmonic function spaces were found and mentioned in [3, 7, 8]. We note basic properties of last spaces on product domains are closely connected on the other hand with so-called Trace operator [7, 8]. We will add some new results related with Trace map for certain spaces of analytic functions on products of pseudoconvex domains. Next in second main part of paper we will turn to study of certain embedding theorems for some new mixed norm analytic classes in strictly pseudoconvex domains in C.We note that in this paper we extend some theorems from [3] and [30] where they can be seen in context of unit ball. Proving estimates and embedding theorems in pseudoconvex domains we heavily use
Title ODVR : A Unifying Approach to On-Demand and Proactive Loop-Free Routing in Ad-Hoc Networks Permalink

We introduce Ordered Distance Vector Routing (ODVR), which is the first approach that enables on-demand and proactive loop-free routing on a per-destination basis. ODVR establishes a strict total ordering of nodes with respect to any given destination using the distances to that destination and reference distances that nodes responding to route requests must have in order to be allowed to send responses. Destinations send gratuitous route replies to enact proactive routing. In contrast to all prior routing protocols, ODVR does not require source or destination sequence numbers, sequence numbers for messages, path information, source routing, or requiring a router to wait for replies from all its neighbors before making changes to its routing table. It is shown that loop-free on-demand routing cannot be attained simply by using destination sequence numbers and the type of signaling used in AODV (Ad-hoc On-Demand Distance Vector) if messages can be lost and nodes may lose routing state for any reason. It is also shown that ODVR provides loop-free routes at every instant. Simulation experiments using ns3 show that ODVR is more efficient than AODV and OLSR.
A Mac Protocol with Dynamic Allocation of Time Slots Based on Traffic Priority in Wireless Body Area Networks

In a wireless body area network (WBAN), wireless biomedical sensors are placed around, on, or inside the human body. Given specific requirements, WBANs can significantly improve healthcare, diagnostic monitoring, and other medical services. However, the existing standards such as IEEE 802.11 and IEEE 802.15. 4 have some limitations to meet all the requirements of WBANs. Many medium access control (MAC) protocols have been studied so far, most of which are derived from the IEEE 802.15. 4 superframe structure with some improvements and adjustments. However, the MAC protocols do not provide the required quality of service (QoS) for various types of traffic in a WBAN. In this paper, a traffic-aware MAC (TA-MAC) protocol for WBANs is proposed, in which time slots are dynamically allocated on the basis of traffic priority, providing the required QoS. According to the performance evaluation results, the proposed TA-MAC is better than IEEE 802.15. 4 MAC and the conventional priority-based MAC in terms of transmission time, system throughput, energy efficiency, and collision ratio.
Drivers of Livelihoods Diversification in Rungwe District

This paper examined the factors influencing livelihoods diversification in Rungwe district. Specifically, the study assessed the livelihoods activities in the study area and determined the drivers of livelihoods diversification. The study was carried out in six villages of Rungwe District, Mbeya Region in which about 253 households were interviewed for the study. Data was collected through documentary review, household interviews, focused group discussions (FGDs), key informant interviews (KIIs), transect walks and field observation. Quantitative data were analysed using SPSS version 20 and Excel spreadsheet. While chi-square test was conducted to determine the associations between influencing factors and livelihoods activities, content analysis was used to analyse qualitative data. The study results showed that there were various livelihoods activities in the study villages such as cash crop production, livestock keeping, trade and wage labour. Livelihoods diversification was influenced by factors like markets, climate, population, land shortages, institutions, policies, and livelihoods assets. However, agriculture has remained the main occupation of households in Rungwe District. Moreover, market appeared to be a strong factor in influencing livelihoods diversification in the area than any other factors. On that basis, this paper recommends that livelihoods activities which were environmentally friendly should be encouraged. Additionally, markets and transport services should be improved to provide equal opportunities for diversification among rural populations.
Pharmacogenetics of hepatocellular carcinoma and cholangiocarcinoma

Primary liver cancers constitute the fourth most deadly group of cancers. Their poor prognosis is due in part to the pre-existence and/or development, often during treatment, of powerful mechanisms accounting for the poor response of cancer cells to antitumor drugs. These include both impaired gene expression and the appearance of spliced variants, polymorphisms and mutations, affecting the function of genes leading to the reduction in intracellular concentrations of active agents, changes in molecular targets and survival pathways, altered tumor microenvironment and phenotypic transition. The present review summarizes available information regarding the role of germline and somatic mutations affecting drug transporters, enzymes involved in drug metabolism, organelles and signaling molecules related to liver cancer chemoresistance. A more complete picture of the actual complexity of this problem is urgently needed for carrying out further pharmacogenomic studies aimed to improve the management of patients suffering from hepatocellular carcinoma or cholangiocarcinoma.
Non-intrusive Driver Drowsiness Detection based on Face and Eye Tracking

The rate of annual road accidents attributed to drowsy driving are significantly high. Due to this, researchers have proposed several methods aimed at detecting drivers’ drowsiness. These methods include subjective, physiological, behavioral, vehicle-based, and hybrid methods. However, recent reports on road safety are still indicating drowsy driving as a major cause of road accidents. This is plausible because the current driver drowsiness detection (DDD) solutions are either intrusive or expensive, thus hindering their ubiquitous nature. This research serves to bridge this gap by providing a test-bed for achieving a non-intrusive and low-cost DDD solution. A behavioral DDD solution is proposed based on tracking the face and eye state of the driver. The aim is to make this research an inception to DDD pervasiveness. To achieve this, National Tsing Hua University (NTHU) Computer Vision Lab’s driver drowsiness detection video dataset was utilized. Several video and image processing operations were performed on the videos so as to detect the drivers’ eye state. From the eye states, three important drowsiness features were extracted: percentage of eyelid closure (PERCLOS), blink frequency (BF), and Maximum Closure Duration (MCD) of the eyes. These features were then fed as inputs into several machine learning models for drowsiness classification. Models from the K-nearest Neighbors (KNN), Support Vector Machine (SVM), Logistic Regression, and Artificial Neural Networks (ANN) machine learning algorithms were experimented. These models were evaluated by calculating their accuracy, sensitivity, specificity, miss rate, and false alarm rate values. Although these five metrics were evaluated, the focus was more on getting optimal accuracies and miss rates. The result shows that the best models were a KNN model when k = 31 and an ANN model that used an Adadelta optimizer with 3 hidden layer network of 3, 27, and 9 neurons respective. The KNN model obtained an accuracy of 72.25% with a miss rate of 16.67%, while the ANN model obtained 71.61% and 14.44% accuracy and miss rate respectively.