scholarly journals Mathematical Modelling and Study of Stochastic Parameters of Computer Data Processing

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2240
Author(s):  
Radi Romansky
Keyword(s):  
Computer Processing ◽  
Software Module ◽  
Computer Data ◽  
Applied Model ◽  
Program Language ◽  
Proposed Model ◽  
Stochastic Parameters ◽  
Computer Environment ◽  
Strict Regulation ◽  
Mathematical Formalization

The main goal of dispatching strategies is to minimize the total time for processing tasks at maximum performance of the computer system, which requires strict regulation of the workload of the processing units. To achieve this, it is necessary to conduct a preliminary study of the applied model for planning. The purpose of this article is to present an approach for automating the investigation and optimization of processes in a computer environment for task planning and processing. A stochastic input flow of incoming tasks for processing is considered and mathematical formalization of some probabilistic characteristics related to the complexity of its servicing has been made. On this basis, a software module by using program language APL2 has been developed to conduct experiments for analytical study and obtaining estimates of stochastic parameters of computer processing and dispatching. The proposed model is part of a generalized environment for program investigation of the computer processing organization and expands its field of application with additional research possibilities.

Regression model of assessment of customer solvency and banking risks in the process of lending

2019 ◽  
pp. 69-73
Author(s):  
Zoryna Yurynets ◽  
Rostyslav Yurynets ◽  
Nataliya Kunanets ◽  
Ivanna Myshchyshyn
Keyword(s):  
Logistic Regression ◽  
Discriminant Analysis ◽  
Regression Model ◽  
Likelihood Ratio ◽  
Credit Scoring ◽  
Bank Loans ◽  
Management Decisions ◽  
Computer Data ◽  
Proposed Model ◽  
Loan Risk

In the current conditions of economic development, it is important to pay attention to the study of the main types of risks, effective methods of evaluation, monitoring, analysis of banking risks. One of the main approaches to quantitatively assessing the creditworthiness of borrowers is credit scoring. The objective of credit scoring is to optimize management decisions regarding the possibility of providing bank loans. In the article, the scientific and methodological provisions concerning the formation of a regression model for assessing bank risks in the process of granting loans to borrowers has been proposed. The proposed model is based on the use of logistic regression tools, discriminant analysis with the use of expert evaluation. During the formation of a regression model, the relationship between risk factors and probable magnitude of loan risk has been established. In the course of calculations, the coefficient of the individual's solvency has been calculated. Direct computer data preparation, including the calculation of the indicators selected in the process of discriminant analysis, has been carried out in the Excel package environment, followed by their import into the STATISTICA package for analysis in the “Logistic regression” sub-module of the “Nonlinear evaluation” module. The adequacy of the constructed model has been determined using the Macfaden's likelihood ratio index. The calculated value of the Macfaden's likelihood ratio index indicates the adequacy of the constructed model. The ability to issue loans to new clients has been evaluated using a regression model. The conducted calculations show the possibility of granting a loan exclusively to the second and third clients. The offered method allows to conduct assessment of client's solvency and risk prevention at different stages of lending, facilitates the possibility to independently make informed decisions on credit servicing of clients and management of a loan portfolio, optimization of management decisions in banks. In order for a loan-based model to continue to perform its functions, it must be periodically adjusted.

Offline Data Sharing Model Based on Encrypted XML Files

2012 ◽  
Vol 488-489 ◽  
pp. 1574-1581
Author(s):  
Wen Yong Weng ◽  
Jian Su ◽  
Xiao Jie Yang ◽  
Zhe Bing Wang
Keyword(s):  
Data Sharing ◽  
Software Module ◽  
Interactive Mode ◽  
Model Based ◽  
Proposed Model ◽  
Extensible Markup ◽  
Xml Signature ◽  
Data Files ◽  
Point Data ◽  
Point To Point

A confidentiality system generally needs to operate under a non-network environment. Hence, the adoption of an offline model is necessary to realize data sharing. An offline data-sharing model based on encrypted Extensible Markup Language (XML) files is designed. The combination of various techniques, such as XML mode, XML encryption, and XML signature, and the introduction of the Security Solution Support Center enable the proposed model to achieve a safe point-to-point data interactive mode and a security-based software module. The software system based on this model can ensure that data files generated from the data provider could only be identified and verified by the authorized data receiver.

scholarly journals MODULE OF PROCESSING EXPERIMENTAL THERMAL CHARACTERISTICS OF MACHINE TOOLS IN REAL-TIME MODE USING HIGH ORDER DERIVATIVES

2019 ◽  
Vol 4 (5) ◽  
pp. 155-164
Author(s):  
В. Позевалкин ◽  
Vladimir Pozevalkin ◽  
И. Парфёнов ◽  
Igor' Parfenov ◽  
А. Поляков ◽  
...  
Keyword(s):  
Real Time ◽  
Machine Tools ◽  
Thermal State ◽  
Thermal Characteristics ◽  
High Order ◽  
Automated System ◽  
Software Module ◽  
Computer Data ◽  
Characteristic Points ◽  
High Level

The article presents processing module of experimental thermal characteristics of machine tools in real time using high order derivatives. It is developed in a high level programming language. This module is a part of automated system of tests and diagnostics of machines thermal state. The module is equipped with a graphical user interface; it works in real time, allows performing procedures for smoothing experimental thermal characteristics and determining their prognostic values. This allows building curves of speed, acceleration and sharpness of temperature change over the time. The developed software module implements a new algorithm based on the Horner’s method. The practice of developing algorithmic software shows that the chosen method is very convenient and effective for machine implementation, due to the absence of a division operation at each computational step. It is experimentally confirmed that the total costs of performing the calculations of high order derivatives of an arbitrary degree polynomial using the Horner’s method according to the described algorithm are acceptable for real-time calculations on a standard personal computer. Data temperature and temperature movements of the machine working bodies can be processed using the developed algorithms. In addition, this algorithm allows calculating the value of the approximating polynomial and simultaneously obtaining the values of all its derivatives at a given point. This allows to solve the problem of "shift in time by step" of the position of characteristic points.

scholarly journals End-to-End Prediction of Buffer Overruns from Raw Source Code via Neural Memory Networks

2017 ◽  
Author(s):  
Min-je Choi ◽  
Sehun Jeong ◽  
Hakjoo Oh ◽  
Jaegul Choo
Keyword(s):  
Programming Languages ◽  
Program Analysis ◽  
Question Answering ◽  
Source Code ◽  
Source Codes ◽  
Program Language ◽  
Proposed Model ◽  
Challenging Tasks ◽  
Data Driven Approach ◽  
End To End

Detecting buffer overruns from a source code is one of the most common and yet challenging tasks in program analysis. Current approaches based on rigid rules and handcrafted features are limited in terms of flexible applicability and robustness due to diverse bug patterns and characteristics existing in sophisticated real-world software programs. In this paper, we propose a novel, data-driven approach that is completely end-to-end without requiring any hand-crafted features, thus free from any program language-specific structural limitations. In particular, our approach leverages a recently proposed neural network model called memory networks that have shown the state-of-the-art performances mainly in question-answering tasks. Our experimental results using source code samples demonstrate that our proposed model is capable of accurately detecting different types of buffer overruns. We also present in-depth analyses on how a memory network can learn to understand the semantics in programming languages solely from raw source codes, such as tracing variables of interest, identifying numerical values, and performing their quantitative comparisons.

scholarly journals Potential benefits of altering the cassava farming practices in the water shortage regions of Vietnam

2021 ◽  
Vol 23 (4) ◽  
pp. 396-401
Author(s):  
VAN HONG, NGUYEN ◽  
TRUONG AN, DANG
Keyword(s):  
Tuber Yield ◽  
Water Shortage ◽  
Crop Model ◽  
Farming Practices ◽  
Weather Factors ◽  
Applied Model ◽  
Proposed Model ◽  
Potential Benefits ◽  
Index Of Agreement ◽  
Negative Impacts

The work was proceeded to define the suitable period for planting cassava crops in Han Thuan Bac district of Binh Thuan province, Vietnam to reduce the negative impacts of weather factors. The work was deployed applying the FAO-Aqua Crop model to calculate the tuber yield of cassava plants under the cassava farming practices (CFP) to seek the suitable planting period (SPP). The applied model was appraised through the calibration and validation procedures with the index of agreement (IA), correlation coefficient (CC) and the Root Mean Square Error (RMSE) varying from 0.82 to 0.88, 0.81 to 0.89 and 0.21 to 0.29, respectively. Based on the calibrated and validated procedures it can state that the proposed model is suitable for simulating the tuber yield of cassava across the study area. The simulated results indicated that the application of the CFP on Julian days from 110 to 150 for Vu Xuan crop and from 100 to 140for Vu He crop the tuber yield of cassava can improve up to 8.9 per cent and 6.0 per cent, respectively compared to the current farming practices.

PREDICTING SOFTWARE RELIABILITY IN A FUZZY FIELD ENVIRONMENT

2013 ◽  
Vol 20 (03) ◽  
pp. 1340001 ◽  
Author(s):  
AMIR H. S. GARMABAKI ◽  
ALIREZA AHMADI ◽  
P. K. KAPUR ◽  
UDAY KUMAR
Keyword(s):  
Software Reliability ◽  
Harsh Environment ◽  
Development Phase ◽  
Operating Environment ◽  
Field Environment ◽  
Operating Environments ◽  
Development Cycle ◽  
Proposed Model ◽  
Stochastic Parameters ◽  
And Performance

The testing-development phase has been carried out in a given control environment. However, the product will be used in different operating environment by different end-users, which is unknown to the developer. The operating environment may range from a very clean one up to a harsh environment. These uncertain operating environments will impact to the reliability and performance of the software which may differ from the testing phase reliability. We consider that the effect of environment on reliability has a fuzzy nature. The fuzzy effects of the field environments can be captured by a unit-free environmental factor. To overcome this problem, the fuzzy probabilistic theory may be used in the processing of stochastic parameters, taking into account their fuzzy nature. The proposed model is based on Weibull distribution. The aim of this paper is to introduce a fuzzy field environment (FFE) reliability model that covers both the testing and operating phases in the development cycle. Illustration examples of the proposed model have been validated on data collected from two industries.

A New Model of Environment-Aware Geographic Information Services in E-navigation

2019 ◽  
Vol 73 (2) ◽  
pp. 471-484
Author(s):  
Jianan Luo ◽  
Xiaoxia Wan ◽  
Jing Duan
Keyword(s):  
River Estuary ◽  
Pearl River Estuary ◽  
Geographic Information ◽  
Information Services ◽  
Applied Model ◽  
On Demand ◽  
Proposed Model ◽  
Technical Architecture ◽  
Maritime Navigation ◽  
The Pearl River

Navigational information is of great significance to the safety of maritime navigation. To better guarantee navigator safety and improve navigation efficiency, an applied model of geographic information services (GI services) that consists of an operational architecture, several subsystems and multiple GI services is presented. This work is an e-navigation testbed that follows e-navigation technical architecture and integrates a large amount of navigation-related resources. Real-time, location-based and on-demand digital navigational information can be exchanged and applied in a standardised way. An experiment conducted in the Pearl River Estuary area of the South China Sea showed that application of GI services in e-navigation can supplement the existing methods of exchanging navigational information and better assist navigators in decision making. Furthermore, the proposed model is adaptable and could be easily applied in other areas.

scholarly journals Mechanical and thermal-expansion characteristics of Ca10(PO4)6(OH)2-Ca3(PO4)2 composites

2006 ◽  
Vol 38 (3) ◽  
pp. 245-253 ◽  
Author(s):  
G. Ruseska ◽  
E. Fidancevska ◽  
J. Bossert
Keyword(s):  
Thermal Expansion ◽  
Thermal Expansion Coefficient ◽  
Expansion Coefficient ◽  
Thermal Equilibrium ◽  
Volume Fraction ◽  
Applied Model ◽  
Proposed Model ◽  
The Subject ◽  
Model Equations ◽  
Synergism Effect

Three types of composites consisting of Ca10(PO4)6(OH)2 and Ca3(PO4)2 with composition: 75% (wt) Ca10(PO4)6(OH)2: 25%(wt) Ca3(PO4)2; 50%(wt) Ca10(PO4)6(OH)2: 50%(wt)Ca3(PO4)2 and 25 %(wt) Ca10(PO4)6(OH)2: 75%(wt) Ca3(PO4)2 were the subject of our investigation. Sintered compacts were in thermal equilibrium, which was proved by the absence of hysteresis effect of the dependence ?L/L=f(T) during heating /cooling in the temperature interval 20-1000-200C. Sintered compacts with the previously mentioned composition possess 26-50% higher values of the E-modulus, G-modulus and K-modulus indicating the presence of a synergism effect. Several proposed model equations for predicting the thermal expansion coefficient in dependence of the thermal and elastic properties of the constitutive phases and their volume fractions, given by: Turner, Kerner, Tummala and Friedberg, Thomas and Taya, were used for making correlations between mechanical and thermal-expansion characteristics of the Ca10(PO4)6(OH)2 - Ca3(PO4)2 composites. Application of the previously mentioned model equations to all kinds of composites leads to the conclusion that the experimentally obtained results for the thermal expansion coefficient are in an excellent agreement with the theoretical calculated values on account of the volume fraction of each constitutive phase and with all applied model equations, with a coefficient of correlation from 98.16-99.86 %.

scholarly journals Detection and Classification of Different Weapon Types Using Deep Learning

2021 ◽  
Vol 11 (16) ◽  
pp. 7535
Author(s):  
Volkan Kaya ◽  
Servet Tuncer ◽  
Ahmet Baran
Keyword(s):  
Deep Learning ◽  
Control Systems ◽  
Training Process ◽  
Security Forces ◽  
New Approach ◽  
New Model ◽  
Automatic Control Systems ◽  
Proposed Model ◽  
Computer Environment

Today, with the increasing number of criminal activities, automatic control systems are becoming the primary need for security forces. In this study, a new model is proposed to detect seven different weapon types using the deep learning method. This model offers a new approach to weapon classification based on the VGGNet architecture. The model is taught how to recognize assault rifles, bazookas, grenades, hunting rifles, knives, pistols, and revolvers. The proposed model is developed using the Keras library on the TensorFlow base. A new model is used to determine the method required to train, create layers, implement the training process, save training in the computer environment, determine the success rate of the training, and test the trained model. In order to train the model network proposed in this study, a new dataset consisting of seven different weapon types is constructed. Using this dataset, the proposed model is compared with the VGG-16, ResNet-50, and ResNet-101 models to determine which provides the best classification results. As a result of the comparison, the proposed model’s success accuracy of 98.40% is shown to be higher than the VGG-16 model with 89.75% success accuracy, the ResNet-50 model with 93.70% success accuracy, and the ResNet-101 model with 83.33% success accuracy.

scholarly journals Meeting Scheduling Application using Availability and Priority Attendance Heuristics

2019 ◽  
Vol 9 (2) ◽  
pp. 4302-4306
Keyword(s):  
Constraint Satisfaction ◽  
Time Slot ◽  
Dynamic Environment ◽  
Optimal Solution ◽  
Optimal Time ◽  
Scheduling Problem ◽  
Applied Model ◽  
Meeting Schedule ◽  
Proposed Model ◽  
Meeting Scheduling

Meeting scheduling is a repetitive and time consuming task for many organizations. Emails and electronic calendars has been used to help a meeting host in this process. However, it does not automate the process of searching the optimal time slot. Manual scheduling may result in suboptimal schedule. Therefore, automation is needed for meeting scheduling problem. The purpose of this research is to propose an applied model consisting of both acquiring participants’ existing schedule, and searching for an optimal time slot. Previous studies groups the solution of meeting scheduling into either constraint satisfaction or heuristics approach. Heuristics is more appropriate for a dynamic environment. The heuristics-based model is designed to consider participant availability and participant prioritization. The more participants are available, the better the time is as a candidate for optimum schedule. In the proposed model, the availability of certain key person, experts, or host may carry more weight than normal participant. An Android based application is developed as a prove of concept of the proposed model. Google Calendar API is used in this model to acquire the existing schedule, then each time slot is assigned a score based on availability weighting. The time slot with the highest score is considered the optimal solution. Evaluation is done by simulating the scheduling part for various numbers of meetings and time slots. The result shows that the model is capable of searching the optimal meeting schedule in less than one second for each of the experiment.

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