Periodicals of Engineering and Natural Sciences (PEN - International University of Sarajevo)
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Monopole antenna design with flexible frequency selective surface
Get PDFA flexible monopole antenna combined with a flexible frequency selective surface (FSS) is presented in this work. Initially, the FSS structure is examined by constructing a unit cell of the periodic FSS structure with (3x3) arrays of square loops. On a thickness of 0.13 mm, a fast film with a permittivity of 2.7 is printed, and the substrate of the monopole antenna is FR-4 with a dielectric constant of 4.3. The monopole antenna is then densely and parallelly positioned 26 mm above the FSS structure. After studying the monopole an-tenna\u27s return loss, efficiency, bandwidth, and antenna gain, the design is included in the FSS framework to obtain a steady frequency response. When the distance between both the antenna and the FSS structure is extended, the frequency response of the antenna is moved, and the return loss is determined to be less than -52 dB. Furthermore, the fractional bandwidth is extended from 62% to 103%, and the gain is increased greatly to 2.4 dB. This design structure demonstrated exceptional wireless communication performance
The effect of managers\u27 overconfidence on cash holdings in companies listed on the Baghdad stock exchange: Mathematical analysis
Get PDFOne of company managers\u27 most important financial decisions is to choose an optimal level of cash holdings so that cash deficit costs are reduced, and profit resources are directed in line with the company\u27s profitabil-ity goals. Managers\u27 overconfidence is one of the most critical factors affecting the company\u27s cash Hold-ings. The raison d\u27être of overconfidence is the peace that people get from it. In this regard, the current re-search aims to mathematically investigate the effect of managers\u27 overconfidence on cash Holdings in com-panies listed on the Baghdad Stock Exchange in the ten years between 2012 and 2022. The statistical popu-lation of this research was the companies admitted to the Baghdad Stock Exchange, and 50 companies were selected using the systematic elimination method. A multivariate regression method and combined data were used to test the hypotheses. The research findings based on mathematical analysis showed that managers\u27 overconfidence does not affect companies\u27 cash Holdings on the Baghdad Stock Exchange
A novel approach for coordinated design of TCSC controller and PSS for improving dynamic stability in power systems
Get PDFThe purpose of this article is to present a novel strategy for the coordinated design of the Thyristor Con-trolled Series Compensator (TCSC) controller and the Power System Stabilizer (PSS). A time domain objec-tive function that is based on an optimization problem has been defined. This objective function takes into account not only the influence that disturbances have on the mechanical power, but also, and this is more accurately the case, the impact that disturbances have on the reference voltage. When the objective function is minimized, potential disturbances are quickly mitigated, and the deviation of the speed of the generator\u27s rotor is limited; as a result, the system\u27s stability is ultimately improved. Particle Swarm Optimization (PSO) and the Shuffled Frog Leaping Algorithm are both components of a composite strategy that is utilized in the process of determining the optimal controller parameters. (SFLA). An independent controller design as well as a collaborative controller design utilizing PSS and TCSC are developed, which enables a direct evalua-tion of the functions performed by each. The presentation of the eigenvalue analysis and the findings of the nonlinear simulation can help to provide a better understanding of the efficacy of the outcomes. The find-ings indicate that the coordinated design is able to successfully damp low-frequency oscillations that are caused by a variety of disturbances, such as changes in the mechanical power input and the setting of the reference voltage, and significantly enhance system stability in power systems that are connected weekly
Tuning parameter selectors for bridge penalty based on particle swarm optimization method
Get PDFThe bridge penalty is widely used as a penalty for selecting and shrinking predictors in regression models. Although its effectiveness is sensitive to the parameters you decide to use for shrinking and adjusting. The shrinkage and tuning parameters of the bridge penalty are chosen concurrently, and a continuous optimization process called particle swarm optimization is proposed as a means to do this. If implemented, the proposed method will greatly facilitate regression modeling with superior prediction performance. The results show that the proposed method is effective in comparison to other well-known methods, but this varies greatly depending on the simulation setup and the real data application.
 
Comparison of Weibull and Fréchet distributions estimators to determine the best areas of rainfall in Iraq
Get PDFIn this research, an appropriate distribution of the amount of rain will be found in the Iraqi governorates for the period (2006-2014) and the researcher used two important distributions, namely, the Weibull distribution and the Fréchet distribution. Where the specific distribution was determined based on the minimum criteria (the criteria of goodness of fit) and the tests used are the Akaike Information Criterion (AIC) and the Bayesian In-formation Criterion (BIC). Rainfall in the Iraqi governorates for the stations (Mosul, Kirkuk, Tikrit, Khanaqin, Rutba, Baghdad, Karbala) is a Weibull distribution using the greatest possible estimation method, while the stations in other provinces (Najaf, Diwaniyah, Maysan, Basra) the Fréchet distribution was the distribution It is better to represent the data of these stations using the method of estimating the greatest possible as well. We also note the superiority of the method of maximum likelihood of least squares
Multi criteria decision making for optimal below knee prosthetic design
Get PDFIn manufacturing prostheses such as blow knee (BK) prostheses, the designer needs to make a proper selection of materials to achieve some requirements according to patient uses prior to fabricating the parts of the prosthesis. Some requirements are low cost, lightweight, durable and withstand the loading environment. Different methods have been used to make such selections based on the optimisation of material properties such as statistical, graphical and computer soft-ware. The selection of the optimal material for the socket, shank and foot of BK prostheses is thus considered in this work using the multi-criterion decision-making (MCDM) technique. One of the MCDM strategies is TOPSIS, which was used to choose the ideal material and make a recommendation to design BK prosthesis under different conditions. The common materials used for socket, shank and foot are collected from research works as reference data including poly-mers, composite, metal alloys, and wood. The results show that pineapple fibre-reinforced com-posite (PFRC) composite provides light and stiff sockets and PFRC composite provides elastic thought sockets. Titanium alloy (Ti-6Al-4V) provides a stiff shank, and stainless steel (SS 304) alloy provides shock resist shank. Hardwood can be used for low-cost foot, and carbon fibre for shock resistance foot.
 
A Deep learning approach for trust-untrust nodes classification problem in WBAN
Get PDFThe enormous growth in demand for WBAN services has resulted in a new set of security challenges. The capabilities of WBAN are developing to meet these needs. The complexity, heterogeneity, and instability of the mobile context make it difficult to complete these duties successfully. A more secure and flexible WBAN setting can be attained using a trust-untrust nodes classification, which is one method to satisfy the security needs of the WBAN. Considering this, we present a novel Deep Learning (DL) approach for classi-fying WBAN nodes using spatial attention based iterative DBN (SA-IDBN). Z-score normalization is used to remove repetitive entries from the input data. Then, Linear Discriminate Analysis (LDA) is employed to retrieve the features from the normalized data. In terms of accuracy, latency, recall, and f-measure, the sug-gested method\u27s performance is examined and contrasted with some other current approaches. Regarding the classification of WBAN nodes, the results are more favorable for the suggested method than for the ones already in use
Enhancing smart home energy efficiency through accurate load prediction using deep convolutional neural networks
Get PDFThe method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute parameters of electrical energy consumption. The method considers the timeseries homes of the information and offers parallelization of large-scale facts processing with magnificent operational efficiency, considering the timeseries aspects of the information and the problematic inherent correlations between variables. The exams have been done using the UCI public dataset, and the experimental findings validate the method\u27s efficacy, which has clear, sensible implications for setting up intelligent strength grid dispatching
Research of influence of different shaped charge liner materials on penetration depth using numerical simulations
Get PDFNumerical simulations, using the Ansys AUTODYN program, of Panzerfaust 30 (klein) anti-tank warhead, were performed to determine the influence of different liner materials on the penetration depth into a steel target. It has been shown that the choice of liner material can significantly affect the performance of the ammunition. Along with other methods of optimizing shaped charge ammunition (optimization of the shape, thickness and angle of the tip of the liner, use of more potent explosive and deviator, optimization of casing thickness and stand-off distance, etc.), the use of appropriate liner material is certainly one of the most im-portant parameters of shaped charge warheads to consider. Together with analytical calculations and experi-mental tests, simulations are a valuable tool. Using data obtained from numerical simulations, researchers can save both time and resources during the process of munition design and optimization
Investigating and analyzing the impact of IC on the profitability of companies listed on the Iraqi stock exchange
Get PDFCompanies need to follow a continual strategy of knowledge improvement and innovation to maintain their competitive advantage in the face of rapid technological advances and global competition. This method, known as intellectual capital (IC), aids businesses in keeping their edge in the market. Managers should pay attention to IC because of this reason. This study looked at how IC affected the bottom line of a company listed on the ISE in Iraq. The study studied data from a subset of the ISE-listed manufacturers throughout the span of ten years, from 2010 to 2019. Multivariate regression, as well as the F-Limer, Chow, and Hausman tests, were used to examine the data. It was shown that IC improved both ROA and ROE. The results also showed that the capital added value coefficient (COAV) positively impacted ROA but had no discernible impact on ROE. Moreover, ROA and ROE were found to be positively impacted by structural capital\u27s coefficient of added value COAV. And while it had little impact on ROA, the added value coefficient (AVC) of human capital (HC) had a positive and large impact on ROE