This PDF file contains the front matter associated with SPIE Proceedings Volume 12616, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

The imbalanced data sets is an important investigation in the data science and machine learning domain. This paper is focused on providing an effective algorithm for such cases. In these cases, the number of observations is not enough to construct a machine learning model with high values of the estimated magnitudes. For example, most of the observations are labeled as one class (majority class), and the rest as the other, commonly considered as the class of interest (minority class). We propose a methodology based on the properties of the data resampling approach to systematically enhance and optimize the training dataset. The paper examines numerical experiments applying the data centric optimization methodology and compares with previously obtained results by other authors.

Organisational decisions shape individual experiences of their job relationship. Given the many contrasts between the private and public sectors, this research examines how public and private sector workers perceive their psychological contracts. Organisational Justice (OJ) separates the two sectors because the realisation of fairness is a purview of individual organisations and management capacities. The study found a positive direct impact of OJ on the breach of the psychological contract. This suggests that workers who see a decline in their views of justice within their employment connections may sense sentiments of violation and hold their organisation accountable for a significant breach of their psychological contract. The study also found a significant difference in OJ perception and employee commitment to the psychological contract. This is because the private and public sectors in the kingdom of Bahrain are different playfields. The sustenance of the OJ and psychological contract depends on several factors, such as religious beliefs, nationality, industry and background. This paper established the comparisons between the private and public sectors in Bahrain regarding OJ and commitment to psychological contracts.

Some of the novel algebraic topics explored in this paper, like Permutation Q - algebra, permutation G - part, permutation p-radical, permutation p - semisimple and permutation ideal are discussed and looked into. We show that if ( X, #, {1}) is a permutation Q - algebra, then (λ_i^β # (λ_i^β # λ_j^β)) # λ_j^β = {1}, ∀λ_i^β, λ_j^β ∈ X. Also, in the permutation G - part G(X) of X, the left cancellation law is hold and for any β - set λ_i^β in Permutation Q - algebra (X, #, {1}), we consider that λ_i^β belongs to G(X). Additionally permutation implicative, homomorphism, kernel and image of permutation Q - algebras were defined with specific results relating to our unique notions have been developed and examined.

In neutrosophic topological space (NTS), the neutrosophic setting for regular generalized b-closed set is shown as a novel kind neutrosophic closed set (NCS). Moreover, several new ideas of (NCS) are given and discussed, like neutrosophic generalized preregular closed set, neutrosophic regular generalized α-closed set, neutrosophic generalized b-closed set set, neutrosophic generalized α-closed set , neutrosophic generalized semi pre-closed set, neutrosophic generalized αb-closed set, neutrosophic semi generalized b-closed set, in neutrosophic topological spaces. Moreover, the relationships between the neutrosophic regular generalized b-closed and these new classes in (NTS) are explained and studied their characters.

In a self-evolving network, security is an essential requirement, and ensuring it in any circumstance is the most difficult task because the network is very dynamic and lacks reliable centralised monitoring. MANETs are much more vulnerable to security attacks when compared to wired networks. There are two steps in this research: the routing stage and the wormhole detection stage. Quantum walk and reinforcement learning are used to improve the results of ad hoc on-demand multipath distance vector routing technology. Quantum walk detects the moving nodes from the area and updates it to the reinforcement learning table. The proposed model is faster since the adaptive African vulture optimization is employed for path selection. This optimization creates an ideal path from source to destination using the data obtained by the routing protocol and reinforcement learning. Round trip time and packet delivery rate are key elements in the detecting phase. This parameter establishes a threshold point for classifying suspicious and normal nodes. Depending on the type of attack, the node will either be terminated or recovered if it turns malicious. Performance indicators including the proportion of packet delivery ratio (98%), end-to-end latency (23.91 sec), packet loss (4.75%), energy consumption (57J), throughput (408/sec), and average E2E delay are examined and compared with existing models to validate the efficacy of the proposed model.

Non-orthogonal multiple access (NOMA) system is one of the assuring solutions for the upcoming wireless communication systems for achieving better spectral efficiency. The NOMA based wireless communication system is mainly transformed with cognitive radio network (CRN) to improve the performance. This research work focuses on signal detection and optimal power allocation for uplink CRN-NOMA system using optimal deep learning (DL) model. This model combines the channel state estimation process and signal detection. In the proposed work, the signal detection is carried out on the basis of allocated power to the user. Initially, the power allocation process is carried out by the Bisection water filling algorithm to achieve optimal power allocation. Then, the signal detection process is enabled by the DL model ResNet-152. Then, the metaheuristic optimization using Imperialist Competitive Algorithm (ICA) is exploited to provide optimal solution for better signal detection. The noisy channel’s information like Rayleigh fading and AWGN are set for wireless transmission medium to transmit a signal. The combined model of power allocation and signal detection is carried out on MATLAB platform. The performance measures like spectral efficiency, energy efficiency, BER and average response rate of the proposed techniques are compared with the previous research works. When the value of mean harvested energy is 4.5 μJ, the energy efficiency of the proposed model, deep Q learning, conventional TDMA and conventional NOMA/ TDMA are 0.74 [bit/s/Hz], 0.71 [bit/s/Hz], 0.67 [bit/s/Hz] and 0.57 [bit/s/Hz] respectively. It has been hence proved that the performance of this methodology is accurate and effective than the existing models.

The number of brands and products competing in the market is growing in the current modern marketing period, giving consumers more options and alternative goods and services that can suit their needs, as well as the freedom to make their own decisions. Consumer decision-making is influenced by a variety of factors, which makes it particularly difficult to examine consumer purchasing behavior. Individual internal and external influences have an impact on purchasing decisions. Lifestyle, personality, and self-concept, motivation, perception, knowledge, and beliefs are examples of internal influences that affect an individual. Environmental variables and the marketing mix are examples of external influences. With 100 respondents as the research subject, this study used quantitative methodologies with the goal of conducting descriptive and causal research. The Likert scale with research data testing was the scale employed in this investigation. This test for validity and reliability is quantitative in nature. With a total of 100 respondents, sampling was carried out using the probability sampling method and the random sampling type. The method of data analysis performed is straightforward linear regression analysis straightforward linear regression analysis.

Mutual funds are companies which pool money from investors and invest it in securities such as stocks, bonds, and commodities. In this work, we apply the portfolio optimization model where an investor’s risk is measured by the exponential loss function to obtain the optimal allocation of wealth in mutual funds. We consider six correlated mutual funds investing in stocks, oil, gold, and Bitcoin. Based on parameters calibrated using the historical data, the numerical result suggests that one should go long in the funds investing in oil, gold, Thai stocks, and global stocks and go short in Bitcoin and US stocks. The biggest proportion of capital is allocated to oil. In addition, we study the effects of the modelling parameters and risk aversion factors on the optimized portfolio and the backtesting of the strategy on the historical data.

Cloud computing offer an important role in almost all online transactional activities that involve a substantial exchange of information. However, studies have revealed that despite the important roles of cloud computing, most libraries in higher educational institutions in some West African Countries have not adopted the technology. Additionally, existing empirical studies on the adoption of cloud computing in English-speaking countries of West African academic libraries are low and vary from one country to another as well as from one geo-political region to the other. This necessitates the need to explore the existing empirical studies which were carried out on the adoption of cloud computing level and its impact in academic libraries in West Africa such as Ghana, Gambia, Sierra Leone, Liberia and Nigeria. Several online academic databases were used as sources of data for this study using relevant keywords. As such, this study reviewed the existing empirical research on cloud computing acceptance within West Africa which revealed varying results concerning cloud computing acceptance in academic libraries. results revealed that the majority of the existing studies of cloud computing in academic libraries were found to be focused in Nigeria, and the findings further revealed that the Southern and Eastern parts of Nigeria have more studies compared to the other parts. Based on this outcome, this study recommends additional empirical study to be conducted on cloud computing adoption among the Anglophone Countries of West African academic libraries, as the factors for technology adoption may likely differ from one area to the other.

We consider the structure-preserving doubling algorithm (SDA) and the corresponding doubling algorithm (SDA-ss) and the improved SDA-ss algorithm for computing the minimal nonnegative solution of M-matrix algebraic Riccati equation. The performance of the considered algorithms are illustrated on some numerical experiments with examples.

After proving time values match numbers in all number lines (x_t, y_t, z_t), and time as a vector, we found the two warnings from two scientific papers about time in economic theories. Finding the causes of inaccuracy in theoretical economics was the objective of this study. Numbers, time values matching the numbers, theoretical demanded and supplied curves were used to be data. The scientific method and mathematics, such as derivatives, logic, and time equation, were used to prove the causes. The investigation found three crucial causes: (1) the nonexistence of equilibrium conditions. At the moment of exchange in price theory, supplied quantities are happening before demanded amounts. Second, the nonexistence of price adjusting to an equilibrium point was found if considering time directions in demand and supply curves. Third, an inappropriate definition of the demand curve for creating the price theory in microeconomics can be proved. After solving the causes, we found a new price model, which explains a price in the real-world market that gives economists see the different paradigms from mainstream theoretical economics and contributes to economics as a new branch of sciences in the final.

The objective of this paper is to answer economic-theory inaccuracies concerning time with demand study. Mathematics and time equations are the methodologies. Theoretical demand and supply curves are the data. The investigation found inaccuracies concerning demand: the unit of quantity demanded per time is the drawing rate while drawing the demand curve. The required amounts co-occur on many number lines with different drawing rates. Also, they are cross-section data and discontinuity. This finding supports Heilbroner and Krugman concerning poverty in economics. After solving the causes, a new price model is demonstrated, which can unite micro-and macroeconomics in one coherent picture. It gives the different paradigms concerning prices from mainstream theoretical economics and develops economics to be a new branch of science.

The Wireless Sensor Network (WSN) is a network with limited resources that uses more energy to transmit and receive data. The small sensor nodes are typically difficult to recharge after deployment so that, the routing protocol's energy consumption can have an impact on the lifespan of a WSN. In general, data aggregation is used to lower the quantity of data transferred in a WSN by minimizing and/or eliminating data redundancy at each node. This paper proposes a new energy-efficient hybrid routing protocol to enhance the network lifetime in WSN model. This protocol accomplishes the best data transmission through the selected path. The clustering approach used to distribute WSN nodes must be effective in order for the complete structure to achieve a longer network lifespan. Using the Fuzzy Density Peak Clustering (FDPC) Method, the whole network is divided into multiple clusters during clustering. Furthermore, the cluster head (CH) selection procedure requires careful consideration in order to provide effective data transfer to the sink node via the chosen CH and to improve node accessibility inside the cluster. An Adaptive Donkey Theorem Optimization (ADTO) technique is used to identify the CH necessary for effective data transfer. The data is sent to the sink node over the chosen CH using an efficient Hybrid Deep Marine Reinforcement Learning (H-DMRL) approach. The proposed hybrid routing protocol attains an improved throughput, network lifetime, and to reduce the energy consumption by nodes and CH, death of sensor nodes, routing overhead. The proposed scheme will be implemented in MATLAB platform and the performance is evaluated and compared with earlier clustering and routing scheme with respect to Quality of service parameters such as network lifetime, energy consumption, packet delivery ratio, routing overhead, packet loss, bit rate, throughput, transmission delay, and jitter.

The multiple input multiple output (MIMO) plays an integral role in improving the energy efficiency for enhancing the QoS of all users. For the 5G wireless communication (WC), NOMA strategy is used with MIMO system to improve the sum rate as well as the computational complexity of the system. This developed work mainly focuses on emphasizing deep learning based optimal power allocation and user pairing techniques in MIMO-NOMA technology to enhance the sum rate and to reduce computational complexity. Normally, NOMA system is used to improve the spectrum in 5G mobile communication. When NOMA is hybridizing with MIMO system, the spectral efficiency (SE) is highly improved. But user pairing problems arise in NOMA system. To overcome this, deep reinforcement learning approach (DRL) is established to receive data from the user equipment (UE) about CSI and position. To allocate the power in UE, cascaded attention guided refinement network (CAGR-Net) is proposed. In addition to this, tiki taka algorithm (TTA) is manipulated to perform clustering as well as to vary the power levels for optimizing the system overall performance of the proposed method. The performance measures such as energy efficiency (EE), spectral efficiency (SE), channel gain, ergodic sum capacity, MSE and error rate are evaluated. In experimental scenario, the error between user 1 and user 2 attained about 0.1044 and 0.5642 respectively with the SNR of 16dB. The performance of the developed model shows better outcome compared to other existing techniques.

Obesity is one of the major determinants of lifestyle-related chronic diseases. The advancement in diagnostic services had led to more detailed information on the understanding of this condition. The relationship between parameters between different diagnostics modalities could assist in standardizing the diagnostics requirement of this condition prior to the choice of treatment in the future. The aim of this study was to measure the intra-muscular adipose tissue (IMAT) volumes and identify its association with serum adipokines among the different categories of the obese population. A cross-sectional study was conducted to collect data on anthropometric measurement and fasting blood serum adipokines. Magnetic Resonance Imaging of the hip joint was performed. Analysis of images from the MR assessment was conducted using a semiautomatic segmentation program. Among the total 28 participants, majority were females (64%) and had Type I obesity (68%). IMAT volume was observed to be highest among participants who had Type 2 obesity (mean= 155 cm³ with SD of 31). A significant relationship was observed between serum leptin with obesity types and gender category. In conclusion, imaging of the adipose tissue could provide a more accurate fat deposition for patient with different type of obesity.

Vehicle access in restricted or protected areas of a country involves phase wise collection of vehicle data in areas like diplomatic enclave. Thus, data gathering at each street junction produces an output that forms the input to the next junction. The analysis system thus developed is intended to be used by government agencies and other special task force to provide sound reports for legal proceeding against violations. In this research, two approaches namely SOM and K-means clustering are used to generate a low-dimensional discretized representation of the vehicle data in the original feature space. The objective is to generate access control for security purposes by providing an automated vehicle analysis based upon clustered data for quicker information on vehicle movement in a particular neighborhood. Comprehensive experimental results are presented to draw conclusions.

This paper provides a contribution to the application of an innovative approach, the IBSE method, to the study of automatic control in process systems within a Chemical Engineering master course, with reference to a class of 28 students. The paper describes in detail the implementation of the five phases making up the IBSE method, from the engagement to the final evaluation, to a case study focusing the simulation of the non-linear dynamics and automatic control of a continuous polymerization reactor.

Despite being the world's fastest-growing economic region, almost half of the world's carbon emissions originate in Asia. The rising CO₂ levels over the last few decades have made energy efficiency a top priority in the fight against climate change. However, turning away from combustible organic fuels will not only reduce carbon emissions, but will also impede Asian countries' economic progress. Increasing efficiency is crucial for fostering economic growth and environmental protection. For performance analysis, this study used a two-stage Data Envelopment Analysis (DEA) model to measure energy use efficiency and economic efficiency in 35 Asian countries. First, the results show that 49% of Asian countries have energy use efficiency scores higher than the median, and only 20% have perfect energy use efficiency with a score of 1. This demonstrates that Asian countries must continue to increase their levels of energy efficiency to minimize the amount of CO₂ emissions. Second, the top ten most economically efficient countries are dominated by developed countries, while 71% of developing countries are economically inefficient. This illustrates the necessity for Asian emerging countries to accelerate their economic progress to reduce the income gap between the rich and the poor. The findings also reveal that high-income countries are not necessarily efficient, emphasizing that national economic policy should prioritize initiatives to boost economic production per capita over measures to increase aggregate economic growth.

The aim of this study is to promote a model, and an embalmment delineation for a cement factory. This research work depends on accuracy centric embalmment near to enhance a delineation and embalmment creek that involves increasing the accuracy of the releasing components system, thus involving persistent productivity. The cost-effective embalmment of the plant’s confidence rendering is the key aim of durability-based embalmment. There are seven important steps, so, performing an embalmment action depended on RCM technique is made up of 10 steps accordingly discharging from choosing units and data until performing and model updating. The calcinatory unit is the processing unit chosen for the analysis of this case as a regarding model’s effectiveness and the Travancore of Titanium Products Ltd (TTP) by using the history of a claimed data gained from the embalmment department from the aforesaid company. The results of the embalmment imitation after applying the proposed model, the present plant scheduled embalmment politics being reconsidered. Results represents the need for protective embalmment for all Class A criticality tools instead the concerted embalmment and the slump one for other techniques depends on its criticality and an FMEA statement. Respectively, the additional cost of protective embalmment would be stabilizer by the setback asset from slump embalmment for the residual tools.

Experimentation and analysis are utilized to investigate updated gaseous Jeffrey fluid throughout the container vent. An aperture and tubing link a rising nitrogen delivery container to a reduced reception. A single power container study and a cross study were utilized to anticipate pressure or extra heat in the supplies. Testing was carried out using flash PVT techniques to gather instantaneous pressures and maximum bulk temperatures, confirming the study. Research reproduces observed temporal volumes plus surplus temps in the source. Aside from the initial portion of a transmission, cooling is driven by various airflows.

Following regulating temperature testing, all insulating fabric in shipping packaging burns. This paper studies the heat transfer of the leads encapsulated in a scaling steel cube. The cuboid dimensions are 40 mm x 40 mm x 50 mm. A free convection criterion is established for the double vertical sides. Insulation is installed on both the top and bottom surfaces. The method is used to visualize the movements of a rock electrode interface, mainly during the smelting of leads. Thermal imaging is a simple and non-intrusive method for determining the melting face during the dissolving of laminates. The approach continuously and immediately exhibits dynamical capturing of the development of an electrolyte interface underneath the forces of convective heat transfer. Computational research is indeed carried out to simulate the dissolving phenomena. The results are contrasted to one wall height, and a suitable feature height is proposed.

This research presents an adaptive intelligence internet approach to the reverse heat flow issue of simultaneously identifying the thermally internal heat of vaporization and thermal diffusivity functions of a solid material. A reverse issue was created using the BICOND heat transfer characteristic measuring technique. Internal specific heat and thermal transfer vs temperature characteristics can always be calculated using the velocity and temperature histories of two devices. This work used an analytical simulation of the evet heat flow issue to construct noiseless and noisy fake observations. This reverse issue was handled using a multi-layer graze classifier with a rear method and a stochastic gradient descent type classifier using a complete historical classification algorithm. In light of the results, feedforward deep networks seem to be essential tools for non-iteratively solving component prediction opposite heat flux issues, and being extremely efficient in assessing real temperature variation past to all ascertain fluid flow specific heat and ductility as an arbitrarily defined function of pressure. Furthermore, whenever the temperature spectrum of observation changes, there is no need to retrain the networks.

Tests and computer models were used to study the liquid motion and particulate movement inside dissolving droplets subject to radioactive substances. They demonstrated in this work whether changing its free heat flux may change overall liquid fluid motion somewhere within the droplets and, therefore the depositing patterns of particles on substrates. Imaging Device Elastography (PIV) was used to evaluate the flow motion and particulate pressure gradients within its evaporation droplets. A tiny motile water droplet comprising scattered Styrofoam nanoparticles were used for the studies. Due to the picture correcting difficulty seen in previous quantitative tests using 3D drops, our test was carried out on a comparable cone 2D droplet formed by two quasi-dust particles, whereas the droplet's foot remained sealed. Emission spectra will be used to melt the droplet's upper layer. The radiative cooling of the particle was monitored using strain gauges. During the refining process, the friction factor, and particle concentration profiles, including specific absorption characteristics, were investigated. Researchers then undertook the dynamic analysis of continuous velocity, including radiative models. Its estimated torque profile via buoyant and Marangoni flow accords more with measurements in terms of quality.

Around this critical stage of working fluids, its heat transfer has not yet been exactly characterized, making assessing its actual benefit challenging. It has been demonstrated by examining its heat exchanger ability in a cylinder containing two thermal zones with a lower surface transfer coefficient. The parametric investigation of convection heat transfer of a nanoparticle’s clear liquid plus Al₂O₃ in tubing. Two different theories from the same research are utilized to represent heat capacity in particular instances of nanoparticle concentration, yielding various numerical findings in the repeating event of replacing a simple liquid with nanoparticles in a particular circumstance. During stable Nusselt number conditions, the hydrodynamic temperature difference of moisture Al2O3 nanofluid is raised by about 3.4–27.8 percentage points compared to conventional rainwater. Furthermore, for all the same mass fractions, the energy heat transfer performance is more significant than in temperature distribution. Furthermore, the impact of uncertainty in estimating nanofluids characteristics has been seen.

We study in this paper the function of development, which consists of 3 dimensions: agriculture, industry, and Human due to their strong interrelationship with each other. We will study this function in Caputo fractional non-linear model (GHD), which describe the stability relation between three dimensions. We will get the existence and uniqueness of solution and used the Banach-fixed point theorem to prove the system (GHD) has a unique fixed point and satisfies the contraction mapping. And then we get the existence equilibrium points and the stability of these points and we find the equilibrium point of (G-H) plane is locally asymptotically if R₀ < 1 , i.e. The stability satisfied with the agriculture wealth and Human population, and when the three dimensions get together the system will be asymptotically stable.

The work is focused on the acoustic guitar music note generation and validation. The music notes are recorded in the acoustic studio and the two playing styles of acoustic guitar are considered for the study. The acoustic guitar note is generated by directly using the finger or by using a small triangular shaped plectrum, known as pick. The music notes are collected on the basis of these two playing styles, finger plucked notes and plectrum plucked notes. They are termed as plucked and picked guitar notes respectively. The music notes are analyzed using digital processing technique named as cepstral domain window method. The analysis helps to separate the excitation signal of that note and the impulse response of the acoustic guitar note. The impulse response of a music note is derived and then used to generate the other music notes. The generated music notes are further classified by using machine learning algorithms. This classification of generated notes is the part of the validation of the research work. The classification of recorded music notes gives 100 % result but the generated music notes from an impulse response provides strong base for the mathematical model of the acoustic guitar note. The results are discussed in this paper.

One of the notable aspects of teacher performance evaluation is internal evaluation. This process is carried out through the cooperation of the leader of the educational institution and the staff of teachers and other school bodies to improve the quality and fulfilling the standards and competencies of the teachers' work. The educational institution uses the self-evaluation process for diagnostics or as a reference point for successful editing to become more effective in achieving its goals and the realism of its objectives. The successful implementation helps address corrective actions needed for better personal and institutional performance. In this scientific paper, with a particular focus, we will deal with some of the main aspects of the self-evaluation of teachers' performance. For the study to be as effective as possible, we surveyed 983 teachers. We obtained teachers' attitudes on the impact of self-assessment of performance on their commitment to the profession and their work with students. The findings show that over 52.1% think it affects 37% partly, 6.2% very little, and 4.8% not. Also, our focus has been to understand the attitude of teachers on the reasons why they do it and for whom they do the selfevaluation of their professional performance. The results of the study show that 10.7% of teachers do the selfevaluation "for themselves," 11.6," at the "school level," and 77.7% do the self-evaluation for the "Inspection Sector." Based on the study's findings, teachers do not do self-evaluation willingly but are necessarily obliged by the school directorate or inspection officials.

Genetically modified organisms (GMOs) created through genetic engineering have dominated the headlines since their initial scientific discovery. Humanity continues to be in awe of how biotechnological progress can help ensure human survival, primarily through food security. However, GMOs' future benefits have rarely been enough to outweigh the ethical and socio-economic concerns. These elements were not previously thought to be equally significant. This study aims to identify possible methods to incorporate ethical considerations into the decision-making process of GM technology for the protection of farmers' rights and to present indicators to aid policymakers in assessing the ethical issues in GM technology. Indicators for the ethical tools of genetically modified (GM) crops that can protect the rights of Malaysian farmers were described in this study. General ethical principles can be seen in the reverence for life and the requirement to weigh benefits and harms. Therefore, a decision-making process must consider ethical issues and scientific evidence. The results of this study revealed that despite this, farmers' rights to a living and contractual justice had been ethically ignored. This is because ethical principles are typically descriptive and challenging to implement. Therefore, its ethical implications must be carefully considered to ensure that the use of GM crops technology does not violate the fundamental rights of farmers. Hence, additional research is needed to hone and broaden this framework to ensure sustainable modern biotechnology and the protection of farmers' rights. The study's output will be a legal framework to evaluate the ethical implications of GM crops in preserving farmers' rights. Government regulators and other pertinent stakeholders can use the recommendations.

The paper considers the issues of effective direct start of high-voltage asynchronous motors of high power with the help of “thyristor voltage regulator - asynchronous motor” (TVR-AM) system. To increase the voltage and power of TVR in the work it is proposed to use series-parallel connected groups of thyristors (TG) instead of one thyristor TVR. The requirements to TG control signals, providing fail-safe thyristor commutation, have been scientifically proved and experimentally verified. In the proposed work a microprocessor device is used to monitor and control the simultaneous opening and closing of thyristors in each phase. Thyristors opening and closing instructions into microprocessor memory were compiled into C++ program.

In this paper, a novel integral transform is proposed for solving various types from differential equations, it is based on a combination of the modified Laplace transform and the generalization of Laplace-derived transformations where we study the characteristics of this transformation and apply it to some special functions and in solving linear ordinary and partial differential equations with constant coefficients.

These days, almost every piece of business and office software has data management features. Planners and coordinators are responsible for maintaining schedules and databases of contacts. E-mail clients provide a convenient way to collect, review, and organize your correspondence. When it comes to managing your papers, word processors are invaluable, especially because of the sort and outline capabilities they provide for creating structure within the text. Spreadsheets may be familiar to most people because of their widespread use in the realm of personal finance, but their versatility extends well beyond that. A large percentage of these software packages also have simple data export and import capabilities. Database software, like Microsoft® Access and Corel Paradox®, is an effective method for managing enormous amounts of data. These applications generate relational databases, which allow for sophisticated sorting and linking of information depending on their content. One common use case is the monthly distribution of membership renewal notices, which is often automated by querying a relational database. However, unless you get the hang of how they function, these complicated relational database applications maybe a real pain to understand and operate. This is partly why there are so many specialized database tools for things like book indexes and family trees.