A Web Smart Space Framework for Intelligent Search Engines

A web smart space is an intelligent environment which has additional capability of searching the information smartly and efficiently. New advancements like dynamic web contents generation has increased the size of web repositories. Among so many modern software analysis requirements, one is to search information from the given repository. But useful information extraction is a troublesome hitch due to the multi-lingual; base of the web data collection. The issue of semantic based information searching has become a standoff due to the inconsistencies and variations in the characteristics of the data. In the accomplished research, a web smart space framework has been proposed which introduces front end processing for a search engine to make the information retrieval process more intelligent and accurate. In orthodox searching anatomies, searching is performed only by using pattern matching technique and consequently a large number of irrelevant results are generated. The projected framework has insightful ability to improve this drawback and returns efficient outcomes. Designed framework gets text input from the user in the form complete question, understands the input and generates the meanings. Search engine searches on the basis of the information provided

Numerical simulations for the Toda lattices Hamiltonian system : Higher order symplectic illustrative perspective

In this paper we apply some higher order symplectic numerical methods to analyze the dynamics of 3-site Toda lattices (reduced to relative coordinates). We present benchmark numerical simulations that has been generated from the HOMsPY (Higher Order Methods in Python) library. These results provide detailed information of the underlying Hamiltonian system. These numerical simulations reinforce the claim that the symplectic numerical methods are highly accurate qualitatively and quantitatively when applied not only to Hamiltonian of the Toda lattices, but also to other physical models. Excepting exactly integrable models, these symplectic numerical schemes are superior, efficient, energy preserving and suitable for a long time integrations, unlike standard non-symplectic numerical methods which lacks preservation of energy (and other constants of motion, when such exist).publishedVersio

Numerical Solutions of Quantum Mechanical Eigenvalue Problems

A large class of problems in quantum physics involve solution of the time independent Schrödinger equation in one or more space dimensions. These are boundary value problems, which in many cases only have solutions for specific (quantized) values of the total energy. In this article we describe a Python package that “automagically” transforms an analytically formulated Quantum Mechanical eigenvalue problem to a numerical form which can be handled by existing (or novel) numerical solvers. We illustrate some uses of this package. The problem is specified in terms of a small set of parameters and selectors (all provided with default values) that are easy to modify, and should be straightforward to interpret. From this the numerical details required by the solver is generated by the package, and the selected numerical solver is executed. In all cases the spatial continuum is replaced by a finite rectangular lattice. We compare common stensil discretizations of the Laplace operator with formulations involving Fast Fourier (and related trigonometric) Transforms. The numerical solutions are based on the NumPy and SciPy packages for Python 3, in particular routines from the scipy.linalg, scipy.sparse.linalg, and scipy.fftpack libraries. These, like most Python resources, are freely available for Linux, MacOS, and MSWindows. We demonstrate that some interesting problems, like the lowest eigenvalues of anharmonic oscillators, can be solved quite accurately in up to three space dimensions on a modern laptop—with some patience in the 3-dimensional case. We demonstrate that a reduction in the lattice distance, for a fixed the spatial volume, does not necessarily lead to more accurate results: A smaller lattice length increases the spectral width of the lattice Laplace operator, which in turn leads to an enhanced amplification of the numerical noise generated by round-off errors.publishedVersionUnit Licence Agreemen

Analysis of quantum coherence for localized fermionic systems in an accelerated motion

Although quantum coherence is a well known phenomenon in quantum information theory and quantum optics, it has been investigated from the resource theory perspective only recently. Furthermore, quantum coherence has important implications in relativistic quantum information where the degradation of entanglement can be attributed to decoherence. In this paper, we investigate the quantum coherence of Dirac field modes localized in a cavity as observed by two relatively accelerated observers. The acceleration is assigned very small values and its effects are investigated in a perturbative regime. For this purpose, we use parameterized two-qubit pure entangled state and a Werner state. We find that coherence shows a periodic degradation due to accelerated motion. However, this degradation can be balanced by adjusting the durations of uniform and accelerated motion. Moreover, it is found that dynamics of quantum coherence closely resembles that of entanglement under the same settings. This similarity confirms the recent attempts to relate the resource theories of coherence and entanglement in a relativistic regime.publishedVersionUnit Licence Agreemen

Optimising HYBRIDJOIN to Process Semi-Stream Data in Near-real-time Data Warehousing

Near-real-time data warehousing plays an essential role for decision making in organizations where latest data is to be fed from various data sources on near-real-time basis. The stream of sales data coming from data sources needs to be transformed to the data warehouse format using disk-based master data. This transformation process is a challenging task due to slow disk access rate as compare to the fast stream data. For this purpose, an adaptive semi-stream join algorithm called HYBRIDJOIN (Hybrid Join) is presented in the literature. The algorithm uses a single buffer to load partitions from the master data. Therefore, the algorithm has to wait until the next disk partition overwrites the existing partition in the buffer. As the cost of loading the disk partition into the buffer is a major cost in the total algorithm’s processing cost, this leaves the performance of the algorithm sub-optimal. This paper presents optimisation of existing HYBRIDJOIN by introducing another buffer. This enables the algorithm to load the second buffer while the first one is under join execution. This reduces the time that the algorithm wait for loading of master data partition and consequently, this improves the performance of the algorithm significantly

Very-high-precision solutions of a class of Schr{\"o}dinger equations

We investigate a method to solve a class of Schr{\"o}dinger equation eigenvalue problems numerically to very high precision $P$ (from thousands to a million of decimals). The memory requirement, and the number of high precision algebraic operations, of the method scale essentially linearly with $P$ when only eigenvalues are computed. However, since the algorithms for multiplying high precision numbers scale at a rate between $P^{1.6}$ and $P\,\log P\,\log\log P$, the time requirement of our method increases somewhat faster than $P^2$.Comment: 4 page contribution to proceedings of the Conference on Computational Physics, June 23rd-26th 2010 in Trondheim (submitted to Computer Physics Communications

Short stories as an innovative EFL teaching technique to improve Pakistani elementary students’ English vocabulary

Short stories are becoming very popular around the globe. Learning vocabulary, a crucial component of learning a foreign language, is at the heart of teaching a language and is important for language learners. The researchers believe that vocabulary plays a crucial part in learning any language. Therefore, it is crucial to look at the best strategies for enhancing vocabulary learning. With the aim of effectively utilizing short stories to improve vocabulary at the primary level, the current study was created to raise awareness among elementary-level teachers about how they might develop the English vocabulary of their students. The study was experimental with a pretest-posttest design. Sixty students were randomly selected from an elementary school in Bahawalpur, Pakistan. Twenty-five close-ended questions (MCQs) type questions for pre-test and post-test and the English reading assessment survey (ERAS) questionnaire were used to collect data, and the data were analyzed by using SPSS. The results show that most students spoke about three things: the value of short stories in vocabulary learning, their interest in reading short stories, and their approval of using short stories. The study implies that primary school English teachers should use short stories to increase their students' vocabulary

Regulatory Network in Plant under Abiotic Stress

Abiotic stress is one of the primary causes of crop yield loss worldwide; it contributes to a nearly 50% reduction in crop production. Anti-oxidants are produced in plants to scavenge ROS that causes cellular damage during abiotic stress. The plant stress response is a complex mechanism that involves protein initiation pathways, abscisic acid signaling, transcriptional and post-transcriptional modifications. Abiotic stress-inducible genes are divided into two groups based on protein products, one is for signal transduction and other is for expressing resistance. Transcriptional factors bind to the promoter of the target gene at specific DNA sequences thus regulating the gene expression, so different kinds of transcriptional factors known as regulons are involved in regulation of genes during drought, salinity and cold stress

Comparison Of Maternal And Perinatal Outcome Of Isolated Borderline Amniotic Fluid Index Versus Normal Amniotic Fluid In Low-Risk Pregnancies At Term

Objective: The objective of the study was to compare the maternal and perinatal outcomes in low-risk pregnancies having borderline Amniotic fluid index with normal amniotic fluid index at term. Methods: This prospective observational study, included 540 low-risk pregnant women admitted at POF Hospital Wah Cantt between 1st June 2020-31st Dec 2022. Group A had 180 women with borderline AFI having normal umbilical artery Doppler and group B had 360 women with normal AFI between 37-40 weeks, who fulfilled the inclusion criteria. The data regarding baseline characteristics and fetomaternal outcome was collected on an already designed proforma and analysis was done by using SPSS version 23. Results: The difference in overall cesarean section rate (p=0.071) and cesarean section for fetal distress (p=0.076) was not statistically significant between the two groups. The borderline AFI did not increase the risk of meconium-stained liquor (p=0.116), 5minute APGAR score <7 (p=0.218), admission to NICU (p=0.064) and low birth weight (mean birth weights p=0.278) compared to normal AFI. Conclusion: Borderline oligohydramnios does not increase the risk of cesarean section and cesarean section for fetal distress. There is no increase in the risk of meconium-stained liquor, 5-minute APGAR score<7, admission to NICU and low birth weight. Keywords: Amniotic fluid index, borderline oligohydramnios, cesarean section, fetal distress, meconium-stained liquor.