Accurate Bases Research Articles

Accounting Systems And Procedures Design: Supporting Business Process and Internal Control of a Small Service Business in Special Region of Yogyakarta

For businesses engaged in the service sector, the problem faced is how companies can provide output with high service quality standards to meet customer satisfaction. During the Covid-19 pandemic, accounting information systems and good procedures are very important to support management in implementing business processes and evaluating the delivery of their service products. A community service activity aims to design accounting systems and procedures for a small business in Yogyakarta so that these service businesses can have the guidelines and accurate information bases for decision making. In addition, this system can improve the financial recording process that supports the consistency of business processes, as well as the application of a good internal control system. The implementation method includes an initial survey to collect information from the business, observation, and problem identification, followed by an evaluation of the accounting aspects and the development of a system design as a solution proposed by the community service team to be implemented in target partner organizations. The system flowchart, detailed operational system guidelines, and procedures resulting from this project made a positive contribution to the organization, as shown by the results of the evaluation with the director and business management at the final stage of the activity implementation.

Detection of DNA Bases via Field Effect Transistor of Graphene Nanoribbon With a Nanopore: Semi-Empirical Modeling.

DNA sequencing techniques are critical in order to investigate genes' functions. Obtaining fast, accurate, and affordable DNA bases detection makes it possible to acquire personalized medicine. In this article, a semi-empirical technique is used to calculate the electron transport characteristics of the developed z-shaped graphene device to detect the DNA bases. The z-shaped transistor consists of a pair of zigzag graphene nanoribbon (ZGNR) connected through an armchair graphene nanoribbon (AGNR) channel with a nanopore where the DNA nucleobases are positioned. Non-equilibrium Green's function (NEGF) integrated with semi-empirical methodologies are employed to analyze the different electronic transport characteristics. The semi-empirical approach applied is an extension of the extended Hückel (EH) method integrated with self-consistent (SC) Hartree potential. By employing the NEGF+SC-EH, it is proved that each one of the four DNA nucleobases positioned within the nanopore, with the hydrogen passivated edge carbon atoms, results in a unique electrical signature. Both electrical current signal and transmission spectrum measurements of DNA nucleobases inside the device's pore are studied for the different bases with modification of their orientation and lateral translation. Moreover, the electronic noise effect of various factors is studied. The sensor sensitivity is improved by using nitrogen instead of hydrogen to passivate the nanopore and by adding a dual gate to surround the central semiconducting channel of the z-shaped graphene nanoribbon.

شیکردنەوەی نوکتەی کوردی بەپێی بنەمای هاریکاری

The study is under the title of “Kurdish Jokes Analysis According to the cooperative principle", which attempts to analyze old and new Kurdish jokes from an Assistance basis perspective. It assumes that ancient and contemporary Kurdish jokes affect the type of linguistic deviations with social changes and historical developments, which demonstrate the direction of Kurdish society´s likings and preferences. For this purpose, deviations from accurate bases of Assistance and Grice’s theory has been made the measurement to discover the rate of linguistic deviations and how they occur. The scope of the research gets benefit from jokes that derive from Kurdish culture and society. In addition, 'Ȓiştey Mirwarî for old jokes' and 'Nuktekanî ehol for modern jokes' as contemporary jokes have been chosen to prove the linguistic deviations in order to investigate an accurate comparison between two stages of Kurdish society with data and statistics.

A Decision Tree-Initialised Neuro-fuzzy Approach for Clinical Decision Support

Apart from the need for superior accuracy, healthcare applications of intelligent systems also demand the deployment of interpretable machine learning models which allow clinicians to interrogate and validate extracted medical knowledge. Fuzzy rule-based models are generally considered interpretable that are able to reflect the associations between medical conditions and associated symptoms, through the use of linguistic if-then statements. Systems built on top of fuzzy sets are of particular appealing to medical applications since they enable the tolerance of vague and imprecise concepts that are often embedded in medical entities such as symptom description and test results. They facilitate an approximate reasoning framework which mimics human reasoning and supports the linguistic delivery of medical expertise often expressed in statements such as ‘weight low’ or ‘glucose level high’ while describing symptoms. This paper proposes an approach by performing data-driven learning of accurate and interpretable fuzzy rule bases for clinical decision support. The approach starts with the generation of a crisp rule base through a decision tree learning mechanism, capable of capturing simple rule structures. The crisp rule base is then transformed into a fuzzy rule base, which forms the input to the framework of adaptive network-based fuzzy inference system (ANFIS), thereby further optimising the parameters of both rule antecedents and consequents. Experimental studies on popular medical data benchmarks demonstrate that the proposed work is able to learn compact rule bases involving simple rule antecedents, with statistically better or comparable performance to those achieved by state-of-the-art fuzzy classifiers.

Intergrating a Minimal Differentiator Expressions Approach into CBR for Linguistic Pattern reuse in Crime Relation: Proposed Method

The relation extraction of crime news can help the monitoring specialists to accelerate the crime investigation. However, constructing patterns or designing templates manually requires domain experts. Also the built patterns do not guarantee complete differentiation among different relation instances. The automatic detection of crime entities and relationship among entities can help the regulatory authorities to accelerate the crime investigation and decision support instead of being reliant on manual process. This study aims to increase the effectiveness of the extraction of crime entities and relationship among entities based on the determination of crime lingusitic pattern using Minimal Differentiator Expressions (MDEs) that represent the cases that will be used by the CBR classifier. The proposed extraction methods can help in compiling a highly accurate and machine-understandable crime knowledge bases which can support the regulatory authorities’ investigation. This paper conducted on our proposed MDEs algorithm for linguistic pattern reuse in CBR approaches.

3D non-paraxial kernel for two-point correlation modelling in optical and quantum interference at the micro and nano-scales

Optical and quantum interference at the micro and nano-scales are of growing interest. Its accurate description bases on the non-paraxial propagation of the spatial correlation, in which the physical observable, determined by the square modulus of the optical and quantum wave functions, is expressed as a modal expansion on a 3D non-paraxial geometric kernel, with the spatial correlation as coefficient. The kernel plays the main role of the model and is deduced from the optical wave equation in free-space as well as from the Schrödinger equation for particle propagation in field-free regions. Two features are analyzed in detail, i.e. the physical implications on the wave and particle interference due to the 3D spatial modulations provided by the local and non-local components of the kernel at the micro and nano-scales, and the decay of the kernel terms with the propagation distance which leads to a novel criterion for the kernel accuracy. The interference modeling is implemented on a matrix algorithm and is illustrated by some examples with nano-structured masks.

Flexure Pivot Oscillator With Intrinsically Tuned Isochronism

Abstract The most important property for accurate mechanical time bases is isochronism: the independence of period from oscillation amplitude. This paper develops a new concept in isochronism adjustment for flexure-based watch oscillators. Flexure pivot oscillators, which would advantageously replace the traditional balance wheel-spiral spring oscillator used in mechanical watches due to their significantly lower friction, exhibit nonlinear elastic properties that introduce an isochronism defect. Rather than minimizing this defect, we are interested in controlling it to compensate for external defects such as the one introduced by escapements. We show that this can be done by deriving a formula that expresses the change of frequency of the oscillator with amplitude, i.e., isochronism defect, caused by elastic nonlinearity. To adjust the isochronism, we present a new method that takes advantage of the second-order parasitic motion of flexures and embody it in a new architecture we call the co-RCC flexure pivot oscillator. In this realization, the isochronism defect of the oscillator is controlled by adjusting the stiffness of parallel flexures before fabrication through their length Lp, which has no effect on any other crucial property, including nominal frequency. We show that this method is also compatible with post-fabrication tuning by laser ablation. The advantage of our design is that isochronism tuning is an intrinsic part of the oscillator, whereas previous isochronism correctors were mechanisms added to the oscillator. The results of our previous research are also implemented in this mechanism to achieve gravity insensitivity, which is an essential property for mechanical watch time bases. We derive analytical models for the isochronism and gravity sensitivity of the oscillator and validate them by finite element simulation. We give an example of dimensioning this oscillator to reach typical practical watch specifications and show that we can tune the isochronism defect with a resolution of 1 s/day within an operating range of 10% of amplitude. We present a mock-up of the oscillator serving as a preliminary proof-of-concept.

DNA metabarcoding reveals the complex and hidden responses of chironomids to multiple stressors

BackgroundChironomids, or non-biting midges, often dominate stream invertebrate communities in terms of biomass, abundance, and species richness and play an important role in riverine food webs. Despite these clear facts, the insect family Chironomidae is often treated as a single family in ecological studies or bioassessments given the difficulty to determine specimens further. We investigated stressor responses of single chironomid operational taxonomic units (OTUs) to three globally important stressors (increased salinity, fine sediment and reduced water flow velocity) in a highly replicated mesocosm experiment using a full-factorial design (eight treatment combinations with eight replicates each).ResultsIn total, 183 chironomid OTUs (97% similarity) were obtained by applying a quantitative DNA metabarcoding approach. Whereas on the typically applied family level, chironomids responded positively to added fine sediment and reduced water velocity in the streambed and negatively to reduced velocity in the leaf litter, an OTU-level analysis revealed a total of 15 different response patterns among the 35 most common OTUs only. The response patterns ranged from (a) insensitivity to any experimental manipulation over (b) highly specific sensitivities to only one stressor to (c) additive multiple-stressor effects and even (d) complex interactions.ConclusionEven though most OTUs (> 85%) could not be assigned to a formally described species due to a lack of accurate reference data bases at present, the results indicate increased explanatory power with higher taxonomic resolution. Thus, our results highlight the potential of DNA-based approaches when studying environmental impacts, especially for this ecologically important taxon and in the context of multiple stressors.

RIFRAF: a frame-resolving consensus algorithm.

Protein coding genes can be studied using long-read next generation sequencing. However, high rates of indel sequencing errors are problematic, corrupting the reading frame. Even the consensus of multiple independent sequence reads retains indel errors. To solve this problem, we introduce Reference-Informed Frame-Resolving multiple-Alignment Free template inference algorithm (RIFRAF), a sequence consensus algorithm that takes a set of error-prone reads and a reference sequence and infers an accurate in-frame consensus. RIFRAF uses a novel structure, analogous to a two-layer hidden Markov model: the consensus is optimized to maximize alignment scores with both the set of noisy reads and with a reference. The template-to-reads component of the model encodes the preponderance of indels, and is sensitive to the per-base quality scores, giving greater weight to more accurate bases. The reference-to-template component of the model penalizes frame-destroying indels. A local search algorithm proceeds in stages to find the best consensus sequence for both objectives. Using Pacific Biosciences SMRT sequences from an HIV-1 env clone, NL4-3, we compare our approach to other consensus and frame correction methods. RIFRAF consistently finds a consensus sequence that is more accurate and in-frame, especially with small numbers of reads. It was able to perfectly reconstruct over 80% of consensus sequences from as few as three reads, whereas the best alternative required twice as many. RIFRAF is able to achieve these results and keep the consensus in-frame even with a distantly related reference sequence. Moreover, unlike other frame correction methods, RIFRAF can detect and keep true indels while removing erroneous ones. RIFRAF is implemented in Julia, and source code is publicly available at https://github.com/MurrellGroup/Rifraf.jl. Supplementary data are available at Bioinformatics online.

A note on radiation preheating of some hydrocarbons by combustion products

The aim of this paper is to provide upper bounds of the radiation emitted by hot combustion products, mainly CO2 and H2O, and absorbed by some gaseous cold hydrocarbons, or by cold CO2 and H2O. Line by line calculations with accurate spectroscopic data bases are used to compute the absorbed power under two geometrical configurations: a cold optically thin medium surrounded by spherical hot combustion products, and a thin cold slab in front of a hot combustion parallel slab. The absorbed power and the corresponding characteristic time scale are adjusted by simple and physically based formulas to provide quick estimations for various values of combustion product temperature, pressure, and the radius of the hot sphere or the hot slab thickness. The obtained time scales can be compared in a given application to hydrodynamic or diffusive time scales to decide whether it is necessary to take this preheating phenomenon into account or not.

THEORETICAL FRAMEWORK FOR SPATIAL PLANNING AND FOREST MANAGEMENT IN INDONESIA: SECURING THE BASIC RIGHTS FOR ADAT PEOPLE

Limited transparency, accountability, and participation in policy formulation as well as implementation mainly based on economic considerations, all lead to failure to attain sustainable forest management (SFM). Along with the reluctance of policy makers and lacking stakeholder capacity, less accurate data bases has also indicated a constraint in the development of appropriate action. The issues have been more complicated where they were correlated with economic imperatives, vested interest, ownership issues and the basic rights of indigenous communities living inside or adjacent the forest. Forest destruction will be no end without securing customary land and territorial rights. To cope with these issues, the concept of fair governance has been promoted as an alternative to the traditional pattern of administration. In this paper, we propose a theoretical framework for policy development in order to attain SFM while respecting the rights of the adat people. We show that adaptive governance, adaptive management, and participatory learning are strategic approaches in governance reform to achieve sustainable forest management securing the customary rights and traditional land use of forest dependent people.

BRIDGING THE GAP BETWEEN SURVEYORS AND THE GEO-SPATIAL SOCIETY

Abstract. For many years FIG, the International Association of Surveyors, has been trying to bridge the gap between surveyors and the geospatial society as a whole, with the geospatial industries in particular. Traditionally the surveying profession contributed to the good of society by creating and maintaining highly precise and accurate geospatial data bases, based on an in-depth knowledge of spatial reference frameworks. Furthermore in many countries surveyors may be entitled to make decisions about land divisions and boundaries. By managing information spatially surveyors today develop into the role of geo-data managers, the longer the more. Job assignments in this context include data entry management, data and process quality management, design of formal and informal systems, information management, consultancy, land management, all that in close cooperation with many different stakeholders. Future tasks will include the integration of geospatial information into e-government and e-commerce systems. The list of professional tasks underpins the capabilities of surveyors to contribute to a high quality geospatial data and information management. In that way modern surveyors support the needs of a geo-spatial society. The paper discusses several approaches to define the role of the surveyor within the modern geospatial society.

BRIDGING THE GAP BETWEEN SURVEYORS AND THE GEO-SPATIAL SOCIETY

For many years FIG, the International Association of Surveyors, has been trying to bridge the gap between surveyors and the geospatial society as a whole, with the geospatial industries in particular. Traditionally the surveying profession contributed to the good of society by creating and maintaining highly precise and accurate geospatial data bases, based on an in-depth knowledge of spatial reference frameworks. Furthermore in many countries surveyors may be entitled to make decisions about land divisions and boundaries. By managing information spatially surveyors today develop into the role of geo-data managers, the longer the more. Job assignments in this context include data entry management, data and process quality management, design of formal and informal systems, information management, consultancy, land management, all that in close cooperation with many different stakeholders. Future tasks will include the integration of geospatial information into e-government and e-commerce systems. The list of professional tasks underpins the capabilities of surveyors to contribute to a high quality geospatial data and information management. In that way modern surveyors support the needs of a geo-spatial society. The paper discusses several approaches to define the role of the surveyor within the modern geospatial society.

FRULER: Fuzzy Rule Learning through Evolution for Regression

The use of Takagi–Sugeno–Kang (TSK) fuzzy systems in regression problems is widely extended due to the precision of the obtained models. Moreover, the use of simple linear TSK models is usually referred as a good choice in many real problems since it provides a straightforward functional relationship between the output and input variables. In this paper we present FRULER (Fuzzy RUle Learning through Evolution for Regression), a new genetic fuzzy system for automatically learning accurate and simple linguistic TSK fuzzy rule bases for regression problems. FRULER achieves a low complexity of the learned models while keeping a high accuracy, by following three stages: instance selection, multi-granularity fuzzy discretization of the input variables, and evolutionary learning of the rule base combined with Elastic Net regularization to obtain the consequents of the rules. Each of these stages was validated using 28 real-world datasets. FRULER was also experimentally compared with three state of the art genetic fuzzy systems, showing the most accurate and simple models even when compared with approximative approaches.

THE EFFECT OF TWO PACKING TECHNIQUES ON ADAPTATION OF RESIN DENTURE BASE MATERIALS

Background: Acrylic resin denture bases undergo dimensional changes during polymerization. Injection molding techniques are reported to reduce these changes and thereby improve physical properties and adaptation of denture bases. The aim of this study was to compare denture baseadaptation processed by conventional and injection-molding techniques. Materials and Methods: Twenty one accurate denture bases with the same dimension were fabricated and divided into three groups. For the first group, sevenpolymethyl methacrylate denture bases were made using conventional compression moulding technique and for the other two groups, two different injection mouldingunits were used to produce seven polyamide bases (thermo-plasticized) and seven polymethyl-methacrylate (PMMA) bases (themo-polymerized). The adaptation accuracy was examined using universal measuring microscope. The gap between the resin base and stone cast was measured at posterior palatal area at five points, corresponding to the right and left residual ridge crests, the midline, and the right and left marginal limits of the flanges. Results: Injection molded bases showed significant lower total gap scores at the crest and the palate compared to the conventional compression molded ones. However, there was no statistically significant difference between both groups at the vestibular gap. Injection molded poly-amide resin denture bases showed significant difference compared to PMMA injected molded ones. Conclusion: Injection moulded polyamide resin has superior dimensional accuracy and adaptation compared to conventional pressure packed or injection moulded PMMA resin

Promoting low carbon sustainability through benchmarking the energy performance in public buildings in China

Two main energy performance benchmarking methods under the National Public Buildings Energy-efficiency Design Standards and the Evaluation Standard for Green Building are adopted for saving energy consumption in the public buildings in China. However, several existing barriers and weaknesses in current benchmarking systems prevent the overall energy conservation and carbon reduction from being achieved. This paper explores a new comprehensive energy performance based benchmarking method for addressing the energy saving from both technical and non-technical measures. The overlooked base load energy use is also highlighted in the new method. More importantly, the approach of establishing accurate and efficient data bases and forming sound baselines for assessing and monitoring the energy performance in different types of China’s public buildings are recommended in the paper. Governments can play a vital role in improving current benchmarking systems for promote the comprehensive low carbon sustainable development in China’s public building sector.

Global shallow water models based on multi-moment constrained finite volume method and three quasi-uniform spherical grids

This is a review article to present several accurate and computationally efficient global models for shallow water equations recently developed under a general numerical framework, the multi-moment constrained finite volume (MCV) method. The multi-moment constrained finite volume method defines the unknowns (prognostic variables) as the point values at the solution points located over each mesh element. The time evolution equations to update these unknowns are derived through the constraint conditions on different moments, e.g. the point value (PV) and the volume-integrated average (VIA). Rigorous numerical conservation is guaranteed by the constraint on the VIA moment through a finite volume formulation of flux form. The resulted numerical schemes are very simple, efficient and easy to implement for both structured and unstructured grids. We have implemented the MCV method to three major spherical grids, Yin–Yang overset grid, cubed-sphere grid and geodesic icosahedral grid, which have overall quasi-uniform grid spacings and are highly popular in the community of global modeling for atmospheric and oceanic dynamics. In this paper, we present the global shallow water models based on these three spherical grids and the third-order MCV scheme. We evaluate and compare the models by widely used benchmark tests, which show the third-order convergence rate for all models, and the numerical results are competitive to other exiting models. Using MCV method as a numerical formulation is well-balanced between solution quality and computational simplicity, the proposed models provide accurate and practical bases for developing dynamic core of general circulation models on different spherical grids.

Evaluating the performance of a Bayesian Artificial Immune System for designing fuzzy rule bases

In this paper we perform a deep investigation about the usefulness of an immune-inspired algorithm to design accurate and compact fuzzy rule bases for classification problems. The algorithm, called Bayesian Artificial Immune System BAIS, incorporates a mechanism to learn a probability graphical model from the promising solutions found so far. Thus, BAIS utilizes this model to sample new candidate solutions. The probabilistic model utilized here is a Bayesian network due to its capability of expressing the relationships among the variables of the problem, avoiding the disruption of already obtained high-quality partial solutions building blocks. Besides the capability to identify and manipulate building blocks, the algorithm maintains diversity in the population, performs multimodal optimization and adjusts the size of the population automatically according to the problem. These attributes are generally absent from alternative algorithms, and can be considered useful attributes when generating fuzzy rule bases, thus guiding to high-performance classifiers. BAIS was evaluated in thirteen well-known classification problems and its performance compares favorably with that produced by contenders.

Application of RS and GIS in Jiangsu Marine Resources Survey

Jiangsu province is a big marine province. But the development of marine economy is slow. This doesn't accord with the region advantages of Jiangsu. To make Jiangsu marine economy develop fast, persistently, steadily and harmoniously, intensifying marine resources survey is an important precondition. This paper presents the advantages of remote sensing and geographic information system in Jiangsu marine resources survey, brings forward the mode of Jiangsu marine resources survey, and brings them into practice of dynamic survey of Jiangsu sea wall and foreshore, analyzing the erosion and sedimentation of port, dock and sea\|route, surveying of land\|use/land\|cover. Combine qualitative survey and quantitative analysis, which not only improve the science and accuracy of Jiangsu marine resources survey but also provide timing and accurate bases for administrant departments concerned to realize layout and management.

Review of theories on ionization in fast ion-atom collisions with prospects for applications to hadron therapy

This study emphasizes the need for a systematic and in-depth connection between the progress in quantum theory of energetic ion collisions and applications to hadron therapy. Scattering theory for fast ion beams has reached its stage of development where accurate and robustly applicable methodologies can advantageously be exported to applied fields such as space research, fusion energy program, medicine, etc. In particular, distorted wave collision theories at high energies readily provide total, partial and fully differential cross sections for inelastic collisions of ionic projectiles with any target system. By numerous and thorough testings, such theoretical cross sections were found to exhibit excellent agreement with experimental data on atomic targets. Adequate extensions of these methods to molecular targets were also accomplished with computational efforts that are approximately comparable to that for multi-electron atomic targets. This was done by using the standard Slater-type atomic basis functions for any molecular targets, including tissue-equivalent materials (e.g. water) of relevance to hadron therapy. This expertize needs to be brought to medicine through ion transport physics, which most frequently employs the crude Bragg sum rule for obtaining molecular cross sections as linear combination of atomic cross sections. Relativistic distorted wave theories are also available, but not currently in use for modeling the passage of relativistic ions through tissue, as needed in hadron therapy of deep-seated tumors. It is high time for extensive and thorough applications of the well-established distorted wave scattering theories to fast collisions of bare and partially clothed multiple charged ions with water molecule. This type of application would provide the most accurate data bases for various cross sections (on electron capture, excitation, ionization, etc) that can be used as reliable entry data for subsequent Monte Carlo simulations of energy losses of ions during their passage through tissue. In order to gain in overall efficiency, these theoretical cross sections could be precomputed at sufficiently dense multi-variable grids, thus yielding modules for advantageous direct sampling during stochastic simulations. Such a comprehensive strategy could provide both accurate and efficient algorithms that would incorporate the state-of-the-art methodologies from high-energy atomic scattering theory involving ion beams. This is currently missing in the physics part of hadron therapy, since all the major Monte Carlo codes customarily employ atomic cross section data bases that rely almost exclusively upon the Bethe–Bloch formula and some phenomenological expressions with fitting parameters adjusted to the limited sets of experimental data. Crucially, the need is emphasized for the introduction of a still missing Monte Carlo code which could simulate transport of ions together with secondary electrons in tissue. The current main Monte Carlo codes simulate transport of either ions or electrons, but not both simultaneously. However, energetic ions produce a large number of electrons by densely ionizing the traversed tissue and many of them are δ-electrons i.e. capable on their own of ionizing various targets. Due to their light mass and considerable energy, δ-electrons undergo multiple scatterings. Because of this cumulative effect, among all the double strand breaks of DNA molecules of tissue treated by ion therapy, some 70% are produced by δ-electrons. Hence the necessity to simulate transport of δ-electrons produced by primary ion beams. Such types of computations are presently missing from the major ion transport codes. Overall, this work thoroughly analyzes conceptual and computational advances of the leading quantum-mechanical distorted wave theories for energetic ion collisions aimed at applications to medicine. Additionally, the main strategic directions are also indicated to further cross-disciplinary fertilization between medicine and basic research on collision theory of fast heavy ions of relevance to hadron therapy.