This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

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Maximum power point tracking (MPPT) is used in photovoltaic (PV) systems to enhance efficiency and maximize the output power of PV module, regardless the variation of temperature, irradiation, and the electrical characteristics of the load. A new MPPT system has been presented in this research, consisting of a synchronous DC-DC step-down Buck converter controlled by an Arduino microcontroller based unit. The MPPT process with Perturb and Observe method is performed with a DC-DC converter circuit to overcome the problem of voltage mismatch between the PV modules and the loads. The proposing system has high efficiency, lower cost and can be easily modified to handle more energy sources. The test results indicate that the u

Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

Diese Forschungsarbeit versteht sich als ein Versuch zur Bestimmung einer der neuen Unterrichtsmethoden, die den Lernenden im Fach Deutsch besonders interessant vorkommen.Der Unterricht soll in einer Atmosphäre, die frei von Zeitdruck, Angst und Zensurdruck ablaufen lassen, damit werden die Studenten ermutigt, die Nutzung von Spiel zu ihrer eigenen Sache machen, um die Spielziele Spaß, Empathie, Zusammenarbeit und Kommunikation zu realisieren. Das Hauptlernziel des Fremdsprachenunterrichts ist es, Lernenden zu ermöglichen, in der Zielsprache zu kommunizieren.

Wir konzentrieren uns in diesem Beitrag auf eine wichtige sprachliche Fertigkeit, die den rezeptiven Fertigkeiten gehört, die ist das Hörverstehen.

Das Hörvers

Growing interest in the subject of corporate governance after the repercussions of financial collapses of some of the leaders of American companies and European, and the consequent crisis of confidence in global financial lists of companies due to weak accounting disclosure and transparency, was quick from many countries and international organizations to adopt the concept in an attempt to improve the situation of companies and promote transparency and prevent further financial crises in the future. Based on this background, the present study aims to shed light on the concept of exercising the powers of governance that has become invitations for adoption in Iraq of great importance, given the increasing role of corporations both restrict

The research has  focused on accounting for marketing risks faced by banks because they are exposed to a high level of risk as a result of their great utilization of financial instruments, which may make them liable to insolvency or bankruptcy and collapse, and accordingly to major economic crises. Therefore, banks are required to manage (reduce) risks so as to prevent them. As Iraqi banks don^'t manage these risks according to modern methodology of using derivatives, as well as lack of both the standard accounting system for banks and the Iraqi accounting criterion (standard) No. 10 to an obvious methodology for these risks identification, classification, hedging and disclosure, the researchers was prompted to concentrate