Simple Mathematical Methods Research Articles

Development of Rule-Based Expert System for Variable Cost and Gross Profit Calculations of Agricultural Products: A Case Study

Cost and gross profit calculations of agricultural products are a comprehensive and difficult process. Many different parameters, such as soil cultivation, pruning, spraying, irrigation, storage, drying, harvesting, transportation, and marketing, need to be evaluated together. Currently, cost calculations of agricultural products are made with classical programs and simple mathematical methods. For this reason, the results vary depending on the person and organization making the evaluation. This creates some limitations, making cost planning, which is a dynamic process, unreliable. In the study, a rule-based expert system was developed for the cost and gross profit calculation of apricots. The expert system developed is called Apricot Information System (APRIS). The developed expert system aims to provide more accurate solutions by adding the precision and speed of the computer to the calculation process. The main contribution of this study is the development of a complete decision support set covering all processes from tillage to marketing and the design of rule-based user-system interaction. The designed system found the apricot variable cost calculation to be 1126.36 TL/da for 2020. This value largely overlaps with the values obtained from the field in the previous year. The developed expert system will be a platform that can be used in cost calculations of many agricultural products.

Overview of Logistics Demand Forecasting Methods

Accurate forecasting of logistics demand is of great theoretical significance and practical application value for the formulation of national policies and the satisfaction of actual demand in the logistics industry. From the modeling form, the existing logistics demand forecasting methods are divided into four categories: single traditional forecasting method, single intelligent forecasting method, combined forecasting method and mixed forecasting method. Among them, single traditional forecasting methods mainly include simple time series method, regression analysis, mathematical and statistical methods, etc.; single intelligent forecasting methods mainly involve gray forecasting method, neural network, support vector machine and their improved forms; combined forecasting methods are mainly summarized into three combined forms: linear combination of single forecasting results, nonlinear combination of single forecasting results, modified single forecasting results; mixed forecasting methods are mainly summarized into three hybrid forms: hybrid intelligent optimization algorithms with single prediction methods, hybrid data dimensionality reduction techniques with intelligent prediction methods, and hybrid data mining techniques with intelligent prediction methods. The four major types of forecasting methods are reviewed, and each forecasting model in the four major types of methods is evaluated in terms of modeling principles, advantages and disadvantages, and applicability, in order to find forecasting methods suitable for different logistics demand forecasting tasks for logistics demand researchers.

Algerian Fig Trees: Botanical and Morphometric Leaf Characterization

Leaf morphology in plants is very important in the evaluation of intraspecific variation. Indeed, the leaves of the fig tree (Ficus carica L.) present a great diversity of shape and size. The present study consists of the botanical, morphological, and morphometric characterization of the leaves of 26 local fig tree varieties cultivated in different areas of Bejaia (northeast Algeria). Our results indicate that the morphological parameters of the leaves allowed a good differentiation of the studied cultivars according to the descriptors (UPOV) among varieties and independent of their growing environment. Moreover, the method of morphometric description proposed in this paper allows the differentiation of varieties and the comparison among them in an objective way and by simple mathematical methods. This method demonstrates the existence of a very high percentage of polymorphisms within the studied varieties, but also their classification according to the number of lobes, the depth of the lateral sinuses, and the degree of openness of the angles performed by the main veins of the leaves. The Azougagh variety is characterized by wider angles, and, on the contrary, the Tassahlit variety has the least-open angles. None of the studied varieties presented “entire” leaves. The majority presented leaves with five lobes. The varieties Tilizwith, Tazarzourth, Avarkan, Tamkarkourth, and Inconnu B differed clearly from the rest by showing leaves with seven lobes and deep lateral sinuses. In contrast, the varieties Zarika, Baccor Blanc, Avarkan Lisse, and Avgaiti presented leaves with only three lobes. This is the first work on fig tree characterization using morphometric methods, which are shown to be complementary to the UPOV code and efficient in separating even the closed varieties. It will be interesting to extend these studies to larger scales and areas.

Virtual Plant of Basil (Ocimum Basillicum) by Using Functional-Structural Plant Model

Indonesia is one of the most populated and large country in south-east Asia. Its abundance of natural resources was well known. Supported by its tropical climate, made Indonesia is also among the largest tropical country in the world. However, according to the data, arable land in Indonesia has drastically decreased over the years in line with the rising demand for residency areas. This statistic shows a rather concerning fact that it is possible that even though Indonesia with this richness of natural resources one day would not fulfil its own domestic food needs. Moreover, competitions and hindrances that experienced by the Indonesian farmers might also worsen this limited food supply. In this research, the computational plant model (called virtual model) of the above-land Basil plant (Ocimum Basillicum P.) was proposed. The Basil plant that is taken as a research object is specific. It is a plant growing in a hydroponic environment. By using structural and functional plant model (FSPM) and simple mathematical and statistical methods, the constructed model was able to portray the growth pattern of each plant organ morphologically and biologically. The development and growth patterns of each plant organ (i.e., stem, petiole, leaves, etc.) are also depicted in detail and precisely. The model was quite novel. It practically can be exploited by agronomists and researchers to see the potential effort in optimizing the plant’s yield.

Secondary neurogenic prosopalgia in a neurological clinic

Annotation. Prosoplgia is one of the most common pain syndromes in the craniofacial area. In the clinic practice of the facial pain treatment, neurogenic prosopalgia accounts for 25-30% of cases. The aim of the study was to evaluate the clinical, laboratory and functional parameters of patients with secondary neurogenic prosopalgia at neurological department. The medical histories of 21 patients (17 (81.0%) women and 4 (19.0%) men) suffered from secondary neurogenic prosopalgia were analyzed retrospectively. The clinical picture, data of general blood and urine tests, biochemical blood tests, neuroimaging, electrophysiological and ultrasonic research methods were evaluated. A preliminary comparison of retrospective patients quality indicators was assessed using simple mathematical methods. A predominant lesion of the I branch of the trigeminal nerve was shown in elderly women with postherpetic neuralgia, while other reasons of secondary neuralgia of the II and III branches of the trigeminal nerve more often caused left-sided lesions. Primary diseases included: herpetic ganglionitis, malignant tumor of the bladder with herpetic complications, sinusitis, dental diseases, meningoencephalitis, atherosclerosis of the brain vessels, concussion of the brain. The features of the clinical picture of each case were evaluated, as well as the characteristic concomitant groups of symptoms, among which were determined cephalgic, asthenoneurotic, vestibulo-atactic, vegetative dystonia, pyramidal syndromes. Among the general and functional studies carries out, attention was drawn to the increase of ESR in almost half of the patients, even without exacerbation of the primary disease, as well as the presence of metabolic disorders in the myocardium according to the electrocardiogram in 47.6% of cases, including in relatively young individuals. Thus, the problem of secondary neurogenic prosopalgia, despite the modern treatment, remains relevant.

Homogenization of the macroscopic stiffness of 2D triaxially braided composites: Roles of the local stiffness model and undulating average scheme

This work investigates a two-level homogenization of the macroscopic stiffness of the 2DTBC with emphasizes on the roles of the local stiffness model and undulating average scheme. The effective elastic property of the braid yarn is rigorously derived by an energy method instead of intuitive mathematical average methods in the literature. General formulations of the compliance and stiffness undulating average schemes have been obtained, which are proven to be reduced to the simple mathematical average methods in certain cases. Validated with different experiments, it is unexpected to find out that the prediction combined with the simple rule of mixture and stiffness undulating average scheme yields the most consistent agreement with experimental results after the overall assessment of all the in-plane engineering elastic constants under various braiding conditions.

ЩОДО ОЦІНЮВАННЯ ВІДПОВІДНОСТІ МАТЕМАТИЧНОЇ МОДЕЛІ БЕЗВІДМОВНОСТІ БОЙОВИХ ЗАСОБІВ ЗЕНІТНИХ РАКЕТНИХ ВІЙСЬК ВИМОГАМ ДО МАТЕМАТИЧНИХ МОДЕЛЕЙ

The article presents a variant of the procedure for assessing the compliance of the mathematical model of the reliability of anti-aircraft missile warfare equipment with the requirements for mathematical models using the example of the Buk self-propelled fire launcher. Parameters affecting change of serviceability of self-propelled fire plant operation in conditions of combat situation are determined. The use of the Weibull distribution allows, by varying the parameter values, to increase the guarantee of the implemented self-propelled fire plant reliability indicators, stated in technical conditions, during its operation in the troops. If necessary, this model can also take into account factors that arise suddenly, for example, taking into account the staffing of the self-propelled fire plant of the anti-aircraft missile regiment to assess the possible (predicted) value of average daily losses, taking into account various measures to reduce the values of the predicted average daily losses. Values calculated using this model react markedly to changes in model parameters, are set within the specified restrictions. In addition, it is possible to determine the time between failures. The accuracy of the results of calculating certain quantities using the mathematical model was estimated by absolute and relative errors. The calculations indicate the relative simplicity of the mathematical model, because it uses simple mathematical methods. The ability to vary the parameters of scale and shape parameters (taking into account aging), the mathematical model of IED failure makes it possible to obtain individual (partial) results obtained using previously used similar models, which emphasizes the evolution of this model. The improved method of mathematical modeling quite adequately reflects the trouble-free operation of the anti-aircraft missile system "Buk" taking into account the conditions of hostilities and meets the requirements for mathematical models. Keywords: probability of failure-free operation, parameters of mathematical model, combat situation, absolute error, time between failures, average daily combat losses.

Volcanic island multi-stage construction inferred from a simple geometrical approach: Example of Réunion Island

The reconstruction of volcanic landforms is an effective way to assess the construction history and growth rates of volcanic structures and is a useful tool to estimate erosion rates. We propose a simple geometrical approach to reveal the location of the long-term eruption centers and the general shape of eroded volcanoes within the altitudinal range of the input data. This DEM-based approach consists of finding the radial topographic profile of an eroded volcanic landform from its remaining surfaces, by coupling two independent and simple mathematical methods (linear regression and Spearman rank correlation). Here we demonstrate that this simple approach is suitable for circular to elliptical (up to an ellipticity of 0.5) and to some extent for asymmetrical volcanoes, and we apply it to Réunion Island. Our results confirm previous conclusions from geological observations and data requiring more complex instrumentation. We confirm that the center of long-term volcanic activity of Piton des Neiges remained stable for the past 1.4 Myr while Piton de la Fournaise has been migrating eastward for ~300 kyr. Our approach also reveals that Piton des Neiges is the dominant volcano in Réunion and that Piton de la Fournaise is a smaller edifice built on its edge. Moreover, despite the contribution of two other volcanoes in the construction of Réunion, we suggest that the Piton des Neiges has rapidly become the main structure of the whole island and has subsumed the previous volcanic centers . Finally, we use our approach to model the magmatic activity of Piton des Neiges, and suggest a deceleration of its magma emission rate since 2Myrs.

Clinical background of cognitive disorders associated with epileptic syndrome of various genesis

Annotation. The prevalence of cognitive impairments that have not reached the degree of dementia is 15-20%. It is known that 20% of people with intellectual disabilities, due to structural changes in the brain, can be diagnosed with epilepsy. The aim of the study was to evaluate the clinical, laboratory, and functional parameters of patients diagnosed with varying degrees of cognitive disorders in the setting of an epileptic seizure in a neurological department. A retrospective assessment was made of 211 patients with cognitive decline who had a history of epileptic seizures (with consequences of traumatic brain injury, perinatal trauma with hypoxic encephalopathy, stroke, discirculatory encephalopathy, brain tumors, arteriovenous malformations, cryptogenic and due to exogenous intoxication). To assess the patient's cognitive function, rapid tests were used: a shortened test of mental abilities - 4 (AMT-4) and a simplified MMSE test. A preliminary comparison of retrospective patients quality indicators was assessed using simple mathematical methods. It was shown a significant effect on the level of cognitive impairment of exogenous intoxication, as well as atherosclerotic changes in the vessels. Brain damage due to trauma or tumor, as the cause of a convulsive attack, showed more pronounced asthenization, lethargy, decreased criticism and intelligence in the case of right hemispheric localization. More pronounced cognitive impairments occurred with lesions in the frontal and temporal localization. So, with damage to the temporal lobe, amnestic disturbances, disorientation in time and space were characteristic. With damage to the frontal lobe - decreased attention, the occurrence of asthenic-depressive syndrome, lethargy. More pronounced speech and writing disorders, disorientation in time and space, astheno-neurotic syndrome with emotional lability were revealed in the case of damage to the left carotid system in stroke. Thus, the study of cognitive impairments in a neurological clinic is one of the important interdisciplinary problems of modern medicine.

RELIABLE: Resource Allocation Mechanism for 5G Network using Mobile Edge Computing.

Technological advancement is currently focused on the miniaturization of devices, and integrated circuits allow us to observe the increase in the number of Internet of Things (IoT) devices. Most IoT services and devices require an Internet connection, which needs to provide the minimum processing, storage and networking requirements to best serve a requested service. One of the main goals of 5G networks is to comply with the user’s various Quality of Service (QoS) requirements in different application scenarios. Fifth-generation networks use Network Function Virtualization (NFV) and Mobile Edge Computing (MEC) concepts to achieve these QoS requirements. However, the computational resource allocation mechanisms required by the services are considered very complex. Thus, in this paper, we propose an allocation and management resources mechanism for 5G networks that uses MEC and simple mathematical methods to reduce the model complexity. The mechanism decides to allocate the resource in MEC to meet the requirements requested by the user. The simulation results show that the proposed mechanism provides a larger amount of services, leading to a reduction in the service lock number and as a reduction in the blocking ratio of services due to the accuracy of the approach and its load balancing in the process of resource allocation.

Deep Integration of Health Information Service System and Data Mining Analysis Technology

Abstract The scale and complexity of health information service system has increased dramatically, and its development activities and management are difficult to control. In the field of, Traditional methods and simple mathematical statistics methods are difficult to solve the problems caused by the explosive growth of data and information, which will adversely affect health information service system management finally. So, it is particularly important to find valuable information from the source code, design documents and collected software datasets and to guide the development and maintenance of software engineering. Therefore, some experts and scholars want to use mature data mining technologies to study the large amount of data generated in software engineering projects (commonly referred to as software knowledge base), and further explore the potential and valuable information inherently hidden behind the software data. This article initially gives a brief overview of the relevant knowledge of data mining technology and computer software technology, using decision tree graph mining algorithm to mine the function adjustment graph of the software system definition class, and then source code annotations are added to the relevant calling relationships. Data mining technology and computer software technology are deeply integrated, and the decision tree algorithm in data mining is used to mine the knowledge base of computer software. Potential defect changes are listed as key maintenance objects. The historical versions of source code change files with defects are found dynamically and corrected in time, to avoid the increase of maintenance cost in the future.

On COVID-19 Modelling

This is an analysis of the COVID-19 pandemic by comparably simple mathematical and numerical methods. The final goal is to predict the peak of the epidemic outbreak per country with a reliable technique. The difference to other modelling approaches is to stay extremely close to the available data, using as few hypotheses and parameters as possible.For the convenience of readers, the basic notions of modelling epidemics are collected first, focusing on the standard SIR model. Proofs of various properties of the model are included. But such models are not directly compatible with available data. Therefore a special variation of a SIR model is presented that directly works with the data provided by the Johns Hopkins University. It allows to monitor the registered part of the pandemic, but is unable to deal with the hidden part. To reconstruct data for the unregistered Infected, a second model uses current experimental values of the infection fatality rate and a data-driven estimation of a specific form of the recovery rate. All other ingredients are data-driven as well. This model allows predictions of infection peaks.Various examples of predictions are provided for illustration. They show what countries have to face that are still expecting their infection peak. Running the model on earlier data shows how closely the predictions follow the transition from an uncontrolled outbreak to the mitigation situation by non-pharmaceutical interventions like contact restrictions.

Different Mathematical Spectrophotometric Methods for Determination of Lesinurad in the Presence of its Oxidative Degradation Product

Lesinurad is a novel selective uric acid reabsorption inhibitor which has been recently approved for the treatment of the chronic gout. Four simple mathematical spectrophotometric methods have been developed for the quantitative and selective determination of lesinurad in the presence of its oxidative degradation product. Complete oxidative degradation of lesinurad to its degradation product has been done. The developed methods namely, ratio difference spectrophotometric, first derivative of the ratio spectra, mean centering of the ratio spectra and continuous wavelet transform spectrophotometric methods. These methods have been developed and optimized to resolve the existed overlapping between the zero order UV absorption spectra of lesinurad and its oxidative degradation product. The described spectrophotometric methods have achieved selective determination of lesinurad without any interference from the oxidative degradation product. Also, they have been validated and applied for quantitative analysis of the studied drug in its new pharmaceutical preparation.

Two Derivative Spectrophotometric Methods for the Simultaneous Determination of 4-AminoAntipyrine in Presence of Its Acidic Products

Simple, economic and sensitive mathematical spectrophotometric methods were developed for the estimation 4-aminoantipyrine in presence of its acidic product. The estimation of binary mixture 4-aminoantipyrine and its acidic product was achieved by first derivative and second derivative spectrophotometric methods by applying zero-crossing at (valley 255.9nm and 234.5nm) for 4-aminoantipyrine and (peak 243.3 nm and 227.3nm) for acidic product. The value of coefficient of determination for the liner graphs were not less than 0.996 and the recovery percentage were found to be in the range from 96.555 to 102.160. Normal ratio spectrophotometric method 0DD was used 50 mg/l acidic product as a divisor and then measured at 299.9 nm with correlation coefficient 0.998 and limit of detection 0.04098. ratio derivative methods 1DD and 2DD; are based on measuring the first derivative and second derivative for normal ratio spectrum at (peak 290.7 nm and valley 310 nm) for 1DD and (peak 286, valley 301 and peak 316nm) for 2DD the correlation coefficient for linearity graph not less than 0.997 and the recovery percentage were found to be in the range from 99.64 to 100.11.

The role of modelling in predicting rabies and understanding the impact of control measures.

Rabies is probably the most commonly modelled disease as both its epidemiology and host dynamics are well understood. Models are simplifications of reality and there are different approaches to achieving these representations. Over time, modelling has moved from simple mathematical methods towards more realistic biological models that incorporate spatial and individual variation. In this article, the author reviews models that have increased our understanding of actions taken to manage disease. The most developed of these focus on fox (Vulpes vulpes) rabies in Europe, where a suite of models has helped researchers to explore fox management options and the complications caused by other potential hosts, such as raccoon dogs (Nyctereutes procyonoides). Models of dog (Canis familiaris) rabies support the idea of a 70% vaccine threshold for disease elimination and are now being used to explore and optimise management methods, combining vaccination with either surgical sterilisation or the use of chemical sterilisation. Future challenges are also identified, such as the need to develop practical management models in other hosts, and to explore different Lyssavirus strains in bats.

Two Derivative Spectrophotometric Methods for the Simultaneous Determination of 4-AminoAntipyrine in Presence of Its Acidic Products

Simple, economic and sensitive mathematical spectrophotometric methods were developed for the estimation 4-aminoantipyrine in presence of its acidic product. The estimation of binary mixture 4-aminoantipyrine and its acidic product was achieved by first derivative and second derivative spectrophotometric methods by applying zero-crossing at (valley 255.9nm and 234.5nm) for 4-aminoantipyrine and (peak 243.3 nm and 227.3nm) for acidic product. The value of coefficient of determination for the liner graphs were not less than 0.996 and the recovery percentage were found to be in the range from 96.555 to 102.160. Normal ratio spectrophotometric method 0DD was used 50 mg/l acidic product as a divisor and then measured at 299.9 nm with correlation coefficient 0.998 and limit of detection 0.04098. ratio derivative methods 1DD and 2DD; are based on measuring the first derivative and second derivative for normal ratio spectrum at (peak 290.7 nm and valley 310 nm) for 1DD and(peak 286, valley 301 and peak 316nm) for 2DD the correlation coefficient for linearity graph not less than 0.997 and the recovery percentage were found to be in the range from 99.64 to 100.11.

Improvement of hydroelectric power generation using pumped storage system

Hydroelectric power is a renewable source of energy. By principle, hydroelectric power generation relies on the law of conservation of energy where kinetic energy that resulted from the movement of the mass of water from the river is translated into electr icity, the quantum of which depends on systemic variables viz: plant efficiency, volumetric water flow through the turbine and the head of the water from the water surface to the turbine. Understanding the dynamics of these variables, and the correlation b etween them are core to proper planning and management of a hydroelectric power station. In this Study, simple mathematical methods that include linear programming and statistical analysis based on simulation techniques were used to evaluate vital parameters based on the data obtained from the Hydrologic units of the Shiroro Power Stations in Nigeria. The overall aim of the study is to idealize power generation at Shiroro dam in and out of raining season so as to ensure optimum generation of electricity all year round in order to achieve energy sufficiency in Nigeria. The result of the study is encouraging as it supports the viability of the pumped storage system for generating hydroelectric power all year round. The coupling of the hydroelectric power with pumped storage system if properly harnessed could be the needed panacea for the erratic power supply in Nigeria. Keywords : hydroelectric power, pumped storage, reservoir inflows, turbine, hydrological variables, simulation techniques

Different Mathematical Processing of the Ratio Spectra for Quantification of Cefaclor in Presence of its Acid Induced Degradation Product

Three simple mathematical spectrophotometric methods based on processing the ratio spectra were developed and validated for determination of cefaclor in presence of its acid induced degradation product; namely First derivative of ratio spectra (1DD) Method (A), Ratio subtraction method (RS) Method (B) and Mean centering of ratio spectra (MCR) Method (C). The accuracy, precision and linearity ranges of the proposed methods were determined. The methods were validated and the specificity was assessed by analyzing synthetic mixtures containing the drug and its degradate. The three methods were applied for the determination of the cited drug in its pharmaceutical preparation and the obtained results were statistically compared with those of a reported method. The comparison showed that there is no significant difference between the proposed methods and the reported method regarding both accuracy and precision.

Analyzing the dynamics of cell cycle processes from fixed samples through ergodic principles

Tools to analyze cyclical cellular processes, particularly the cell cycle, are of broad value for cell biology. Cell cycle synchronization and live-cell time-lapse observation are widely used to analyze these processes but are not available for many systems. Simple mathematical methods built on the ergodic principle are a well-established, widely applicable, and powerful alternative analysis approach, although they are less widely used. These methods extract data about the dynamics of a cyclical process from a single time-point “snapshot” of a population of cells progressing through the cycle asynchronously. Here, I demonstrate application of these simple mathematical methods to analysis of basic cyclical processes—cycles including a division event, cell populations undergoing unicellular aging, and cell cycles with multiple fission (schizogony)—as well as recent advances that allow detailed mapping of the cell cycle from continuously changing properties of the cell such as size and DNA content. This includes examples using existing data from mammalian, yeast, and unicellular eukaryotic parasite cell biology. Through the ongoing advances in high-throughput cell analysis by light microscopy, electron microscopy, and flow cytometry, these mathematical methods are becoming ever more important and are a powerful complementary method to traditional synchronization and time-lapse cell cycle analysis methods.

Causes of Effects and Effects of Causes

This article summarizes a conceptual framework and simple mathematical methods of estimating the probability that one event was a necessary cause of another, as interpreted by lawmakers. We show that the fusion of observational and experimental data can yield informative bounds that, under certain circumstances, meet legal criteria of causation. We further investigate the circumstances under which such bounds can emerge, and the philosophical dilemma associated with determining individual cases from statistical data.