Miracle-dz/UniFAR-FTUs huggingface dataset:
Context ontology driven relevant search using data mining techniques (CODT)

The size of the publicly indexable World Wide Web (WWW) has probably surpassed 14.3 billion documents and as yet growth shows no sign of leveling off. Search engines encounter the problem of ambiguity in words; therefore, search engines use ontology to find pages with words that are syntactically different but semantically similar. The knowledge provided by ontology is extremely useful in defining the structure and scope for mining web content. Context-ontology is a shared vocabulary to share context information in a pervasive computing domain and include machine-interpretable definitions of basic concepts in the domain and relations among them. This paper proposes an architecture for relevant searching of web documents using data mining techniques such as clustering and association rules. These techniques together with context and ontology extract potentially useful documents from the database. Also, an algorithm has been devised which shows the working in sequence of steps. Finally, the results are compared with the prevailing approaches and with the help of an example it has been seen that CODT is better in context of relevancy.
Role of PM2.5 (particulate matter) event in the formation of a green public sphere in China

ABSTRACT A green public sphere is important for the free environmental communication in a country. However, this concept is relatively new to the public in China. Here we show that the PM2.5 event in 2011 play an important role in the formation of a green public sphere in China. First, we reviewed the PM2.5 event in China and the basic theory of green public sphere. Next, we investigated the role of the PM2.5 event in the formation of a green public sphere in China. Finally, we concluded that a green public sphere has complicated structures and is multilayered.
Extensive Modulation of the Transcription Factor Transcriptome during Somatic Embryogenesis in Arabidopsis thaliana

Molecular mechanisms controlling plant totipotency are largely unknown and studies on somatic embryogenesis (SE), the process through which already differentiated cells reverse their developmental program and become embryogenic, provide a unique means for deciphering molecular mechanisms controlling developmental plasticity of somatic cells. Among various factors essential for embryogenic transition of somatic cells transcription factors (TFs), crucial regulators of genetic programs, are believed to play a central role. Herein, we used quantitative real-time polymerase chain reaction (qRT-PCR) to identify TF genes affected during SE induced by in vitro culture in Arabidopsis thaliana. Expression profiles of 1,880 TFs were evaluated in the highly embryogenic Col-0 accession and the non-embryogenic tanmei/emb2757 mutant. Our study revealed 729 TFs whose expression changes during the 10-days incubation period of SE; 141 TFs displayed distinct differences in expression patterns in embryogenic versus non-embryogenic cultures. The embryo-induction stage of SE occurring during the first 5 days of culture was associated with a robust and dramatic change of the TF transcriptome characterized by the drastic up-regulation of the expression of a great majority (over 80%) of the TFs active during embryogenic culture. In contrast to SE induction, the advanced stage of embryo formation showed attenuation and stabilization of transcript levels of many TFs. In total, 519 of the SE-modulated TFs were functionally annotated and transcripts related with plant development, phytohormones and stress responses were found to be most abundant. The involvement of selected TFs in SE was verified using T-DNA insertion lines and a significantly reduced embryogenic response was found for the majority of them. This study provides comprehensive data focused on the expression of TF genes during SE and suggests directions for further research on functional genomics of SE.
Failure-resilient vehicular networks

Vehicular Ad-Hoc Network (VANET) has been one of the most transforming technologies for Intelligent Transportation Systems (ITS) in recent years. In particular, wireless mesh network is widely used for VANETs due to its scalability, flexibility, and low maintenance cost. When a mesh node fails, one can simply replace it with a new mesh node, and the network automatically reconfigures itself. However, due to the environment or limited resources, it may not be feasible to replace the failed node immediately. In this work, we introduce a resilient VANET that can effectively retain the coverage and capacity of the original network until the failed mesh nodes can be repaired or replaced. We give simulation results to show that this desirable property can be achieved using a virtual router concept with minimal overhead.
Achieving Energy Efficiency by Optimal Resource Utilisation in Cloud Environment

Emergence of cloud computing has provided an efficient platform for distributed utility computing. But, the huge amount of energy consumed in cloud environment has raised many environmental concerns. To solve the issue of energy consumption in cloud environment, the design of energy efficient mechanism must start to play a major role. The paper addresses this issue by proposing Energy Manager which governs activities in cloud to attain optimal energy utilization. The Energy Manager takes into account resource utilization, CPU frequency, supply voltage and effect of all these on response time. In a novel way, it uses soft scaling as a precursor to Dynamic Voltage and Frequency Scaling (DVFS) to enhance the effectiveness of DVFS in virtualized environment. It implements DVFS, Virtual Machine (VM) migration and consolidation, soft scaling, and power state switching techniques to achieve the objective.
A Study on Secure Chip for Message Authentication between a Smart Meter and Home Appliances in Smart Grid

Recently, a number of studies are underway about the smart grid for the demand what efficient power management. For these power management in smart grid environments, there are required a system that it can be safely stored and sent various information. In this paper, the user oriented side will be discussed from among the systems that it can be controlled and managed these power. There are devices of various types in the home environments which user live. And it is sent and received all power information as these modules are connected on the smart meters. In this process, it is possible an impersonation attack and a data forgery attack. In this paper, we analyze the security requirements in earlier smart grid environments and then also, propose a certification structure and a secure chip design for efficient message authentication between a smart meter and home appliances.
Phylogenetic lineages in the Capnodiales

The Capnodiales incorporates plant and human pathogens, endophytes, saprobes and epiphytes, with a wide range of nutritional modes. Several species are lichenised, or occur as parasites on fungi, or animals. The aim of the present study was to use DNA sequence data of the nuclear ribosomal small and large subunit RNA genes to test the monophyly of the Capnodiales, and resolve families within the order. We designed primers to allow the amplification and sequencing of almost the complete nuclear ribosomal small and large subunit RNA genes. Other than the Capnodiaceae (sooty moulds), and the Davidiellaceae, which contains saprobes and plant pathogens, the order presently incorporates families of major plant pathological importance such as the Mycosphaerellaceae, Teratosphaeriaceae and Schizothyriaceae. The Piedraiaceae was not supported, but resolves in the Teratosphaeriaceae. The Dissoconiaceae is introduced as a new family to accommodate Dissoconium and Ramichloridium. Lichenisation, as well as the ability to be saprobic or plant pathogenic evolved more than once in several families, though the taxa in the upper clades of the tree lead us to conclude that the strictly plant pathogenic, nectrotrophic families evolved from saprobic ancestors (Capnodiaceae), which is the more primitive state.
The Yeast Magmas Ortholog Pam16 Has an Essential Function in Fermentative Growth That Involves Sphingolipid Metabolism

Magmas is a growth factor responsive gene encoding an essential mitochondrial protein in mammalian cells. Pam16, the Magmas ortholog in Saccharomyces cerevisiae, is a component of the presequence translocase-associated motor. A temperature-sensitive allele (pam16-I61N) was used to query an array of non-essential gene-deletion strains for synthetic genetic interactions. The pam16-I61N mutation at ambient temperature caused synthetic lethal or sick phenotypes with genes involved in lipid metabolism, perixosome synthesis, histone deacetylation and mitochondrial protein import. The gene deletion array was also screened for suppressors of the pam16-I61N growth defect to identify compensatory pathways. Five suppressor genes were identified (SUR4, ISC1, IPT1, SKN1, and FEN1) and all are involved in sphingolipid metabolism. pam16-I61N cells cultured in glucose at non-permissive temperatures resulted in rapid growth inhibition and G1 cell cycle arrest, but cell viability was maintained. Altered mitochondria morphology, reduced peroxisome induction in glycerol/ethanol and oleate, and changes in the levels of several sphingolipids including C18 alpha-hydroxy-phytoceramide, were also observed in the temperature sensitive strain. Deletion of SUR4, the strongest suppressor, reversed the temperature sensitive fermentative growth defect, the morphological changes and the elevated levels of C18 alpha-hydroxy phytoceramide in pam16-I61N. Deletion of the other four suppressor genes had similar effects on C18 alpha-hydroxy-phytoceramide levels and restored proliferation to the pam16-I61N strain. In addition, pam16-I61N inhibited respiratory growth, likely by reducing cardiolipin, which is essential for mitochondrial function. Our results suggest that the pleiotropic effects caused by impaired Pam16/Magmas function are mediated in part by changes in lipid metabolism.
Serving 22 Users in Real-Time with a 128-Antenna Massive MIMO Testbed

This paper presents preliminary results for a novel 128-antenna massive Multiple-Input, Multiple-Output (MIMO) testbed developed through Bristol Is Open in collaboration with National Instruments and Lund University. We believe that the results presented here validate the adoption of massive MIMO as a key enabling technology for 5G and pave the way for further pragmatic research by the massive MIMO community. The testbed operates in real-time with a Long-Term Evolution (LTE)-like PHY in Time Division Duplex (TDD) mode and supports up to 24 spatial streams, providing an excellent basis for comparison with existing standards and complimentary testbeds. Through line-of-sight (LOS) measurements at 3.51 GHz in an indoor atrium environment with 12 user clients, an uncoded system sum-rate of 1.59 Gbps was achieved in real-time using a single 20 MHz LTE band, equating to 79.4 bits/s/Hz. In a subsequent indoor trial, 22 user clients were successfully served, which would equate to 145.6 bits/s/Hz using the same frame schedule. To the best of the author's knowledge, these are the highest spectral efficiencies achieved for any wireless system to date.
Specifying Crash Safety for Storage Systems

Software that is provably correct has been a long-time goal of computer science. Until recently this goal was realized for only small programs, but over the last decade several large systems have been built that have provable correctness properties. Examples include CompCert [21], seL4 [20], IronClad [13], CertiKOS [12], Bedrock [4, 5], Termite [32], Click’s dataplane [8], and Jitk [35]. One aspect not covered by these systems is reasoning about failures—power failures, hardware faults, or software bugs—which is well-known to be tricky in systems code. An important example of where failures matter is a file system, because developers often make subtle mistakes in recovery code, and recovery code is complex and not frequently executed. Even if such bugs are rare, they can still be costly, since they can lead to complete data loss [41]. Proving the absence of such bugs in critical software, such as a file system, is an appealing proposition. To explore what it takes to certify a file system, we are in the process of building one such file system and its machine-checked proof. Our goal is to certify a simple Unix-like file system with logging. We want to prove that our file system’s implementation is correct: it matches the specification, even if there are crashes. There are many aspects involved in implementing a certified file system, but the design choice on which everything else depends is the question of how to write specifications. We found that writing specification is surprisingly tricky. This paper summarizes what we have learned from exploring several specification strategies, including one approach that has worked well for us. Writing a precise specification assumes that you know what the specification is. Unfortunately, POSIX is not well specified: file systems have many different interpretations of what POSIX means, in particular under failures. Furthermore, file systems allow operators to configure them to have different behaviors under failure, which can result in surprising results for application writers [29]. In this paper, we adopt a simple compromise: each system call runs atomically. If there is a failure, either the system call happened completely or not all. The system call never leaves the file system in an intermediate state. There are many ways to write a specification for atomic systems calls, like there are many ways to design and implement an API, and it was initially unclear to us which one was the right choice. What criteria determine if a specification is a good one? Our three goals were (1) to prevent real bugs, (2) to enable proof automation, and (3) to allow for modularity. The rest of this paper explores this question by examining different approaches to specify the behavior of a file system under crashes. We report on what approaches we discarded and describe why an approach based on Hoare logic with an extensions for crash predicates and recovery semantics works well.
Integration of Data Mining and Operations Research

Basically, Data Mining (DM) and Operations Research (OR) are two paradigms independent of each other. OR aims at optimal solutions of decision problems with respect to a given goal. DM is concerned with secondary analysis of large amounts of data (Hand et al., 2001). However, there are some commonalities. Both paradigms are application focused (Wu et al., 2003; White, 1991). Many Data Mining approaches are within traditional OR domains like logistics, manufacturing, health care or finance. Further, both DM and OR are multidisciplinary. Since its origins, OR has been relying on fields such as mathematics, statistics, economics and computer science. In DM, most of the current textbooks show a strong bias towards one of its founding disciplines, like database management, machine learning or statistics. Being multidisciplinary and application focused, it seems to be a natural step for both paradigms to gain synergies from integration. Thus, recently an increasing number of publications of successful approaches at the intersection of DM and OR can be observed. On the one hand, efficiency of the DM process is increased by use of advanced optimization models and methods originating from OR. On the other hand, effectiveness of decision making is increased by augmentation of traditional OR approaches with DM results. Meisel and Mattfeld (in press) provide a detailed discussion of the synergies of DM and OR.
The Power of Assignment Motion Oliver R Uthing Figure 1: Expression Motion (em) Figure 2: Assignment Motion (am)

Jens Knoop Universitat Passau knoop@fmi.uni-passau.de Oliver Ruthing CAU Kiel y or@informatik.uni-kiel.d400. de Bernhard Ste en Universitat Passau y ste en@fmi.uni-passau.de Abstract Assignment motion (AM) and expression motion (EM) are the basis of powerful and at the rst sight incomparable techniques for removing partially redundant code from a program. Whereas AM aims at the elimination of complete assignments, a transformation which is always desirable, the more exible EM requires temporaries to remove partial redundancies. Based on the observation that a simple program transformation enhances AM to subsume EM, we develop an algorithm that for the rst time captures all second order e ects between AM and EM transformations. Under usual structural restrictions, the worst case time complexity of our algorithm is essentially quadratic, a fact which explains the promising experience with our implementation. Topics: data ow analysis, program optimization, partially redundant assignment and expression elimination, code motion, assignment motion, bit-vector data ow analyses. 1 Motivation A major source for improving the runtime e ciency of a program is to avoid unnecessary recomputations and reexecutions of values (expressions) and instructions (assignments), as it is illustrated in Figure 1 and 2, respectively. Fakult at f ur Mathematik und Informatik, Universit at Passau, Innstra e 33, D-94032 Passau, Germany. yInstitut f ur Informatik und Praktische Mathematik, Christian-Albrechts-Universitat, Preu erstra e 1{9, D-24105 Kiel, Germany. Figure 1 shows how to avoid the unnecessary recomputations of a + b in node 2 and 3 by initializing a new temporary h in node 1 and replacing the original occurrences of a + b by h. This is known as partially redundant expression elimination (PREE) or as expression motion (EM) for short (cf. [3, 8, 10, 15, 16, 19]).
Neuropsychological Function Schizophrenic Patients and REM Sleep in

To test the hypothesis that rapid eye movement (REM) sleep in schizophrenic patients is associated with cognitive function, we studied 18 schizophrenic inpatients by means of electroencephalograms taken during sleep in their own hospital beds after a minimum 2-wk medication withdrawal period. Patients underwent neuropsychological tests to mea. sure memory function and other aspects of cognitive performance. REM sleep measures demonstrated positive and negative correlations with cognition and memory mea~ares, depending on when REM occurred after sleep onset. Minutes of REM sleep and REM density in the first period correlated negatively with performance, while REM minutes occurring after the first REM period correlated positively with neuropsychological performance. Further work should test whether phasic REM sleep regulation at the beginning of the night plays a compensatory role for neuropsychological dysfunction in schizophrenics.
NHANCING T HE L ABELLING T ECHNIQUE OF S UFFIX T REE C LUSTERING A LGORITHM

Clustering the results of a search helps the user to overview the information returned. In this paper, we look upon the clustering task as cataloguing the search results. By catalogue we mean a structured label list that can help the user to realize the labels and search results. Labelling Cluster is crucial because meaningless or confusing labels may mislead users to check wrong clusters for the query and lose extra time. Additionally, labels should reflect the contents of documents within the cluster accurately. To be able to label clusters effectively, a new cluster labelling method is introduced. More emphasis was given to /produce comprehensible and accurate cluster labels in addition to the discovery of document clusters. We also present a new metric that employs to assess the success of cluster labelling. We adopt a comparative evaluation strategy to derive the relative performance of the proposed method with respect to the two prominent search result clustering methods: Suffix Tree Clustering and Lingo. we perform the experiments using the publicly available Datasets Ambient and ODP-239
Electronic Communications of the EASST Volume 15 ( 2008 ) Proceedings of the 8 th International Workshop on OCL Concepts and Tools ( OCL 2008 ) at MoDELS 2008 An Incremental OCL Compiler for Modeling Environments

In software engineering, reliability and development time are two of the most important aspects, therefore, modeling environments, which aide both, are widely used during software development. UML and OCL became industry standards, and are supported by many CASE tools. OCL code checking, which has to be performed by these tools, has a specialty, as not all of the information necessary for compilation is available from the code, the related model contains the types, navigations and attributes. The build time of OCL code fragments is increased if the development tool supports distributed modeling, because in this case, model element checking has to be performed in a model repository that cannot be held in memory. In this paper, we introduce a method that enables incremental OCL code building and therefore reduces the development time. Incremental builds require higher complexity than simple builds, thus balancing between the two methods is also considered.
An Embedding of Cryptol in HOL-4

In this paper we explore a shallow embedding of Cryptol in HOL-4 by providing a way to import Cryptol programs into HOL-4 so as to support reasoning about concrete Cryptol programs in higher-order logic. Since dealing with the syntax of Cryptol is a straightforward matter of applying well-established parsing technology, we focus on developing mathematical theories to model the semantics of Cryptol among which the sequence concept is the heart. Sequences are modeled as lazy lists/words in HOL-4 successfully, and various sequence operations are defined with useful properties being proven. A model is built to process sequence comprehensions over which sequences could be constructed and iterated. And, concrete cryptographic algorithms including TEA, RC6, MARS and Twofish are implemented in this model, with their functional correctness being verified by simple and effective proof methodology in the course of symbolic evaluation.
Context-aware HRV analysis system

With the availability of ubiquitous healthcare based on wireless sensor network, heart rate variability (HRV) analysis, as a valuable evaluation tool of cardiovascular mortality should be utilized more pervasively and accurately. We propose a ubiquitous HRV analysis system using people's daily life heart monitor data. The system consists of a sensor node recording electrocardiography (ECG) and acceleration signals, a processing node which does online processing and local storage, and a central server for storage, monitoring and data mining. The transmission of data between them is wireless. Data representation, storage, retrieval and processing are discussed. Planned inner/inter person data mining is also introduced. Experimental results verified the basic system functions and the research idea.
Inferring a Bayesian network for Content-based Image Classification

Bayesian networks are popular in the classification literature. The simplest kind of Bayesian network, i.e. naïve Bayesian network, has gained the interest of many researchers because of quick learning and inferring. However, when there are lots of classes to be inferred from a similar set of evidences, one may prefer to have a united network. In this paper we present a new method for merging naïve networks in order achieve a complete network and study the effect of this merging. The proposed method reduces the burden of learning a complete network. A simple measure is also introduced to assess the stability of the results after the combination of classifiers. The merging method is applied to the image classification problem. The results indicate that in addition to the reduced computation burden for learning a complete network, the total precision is increased and the precision alteration for each individual class is estimable using the measure.