The aim of this paper to find Bayes estimator under new loss function assemble between symmetric and asymmetric loss functions, namely, proposed entropy loss function, where this function that merge between entropy loss function and the squared Log error Loss function, which is quite asymmetric in nature. then comparison a the Bayes estimators of exponential distribution under the proposed function, whoever, loss functions ingredient for the proposed function the using a standard mean square error (MSE) and Bias quantity (M_bias), where the generation of the random data using the simulation for estimate exponential distribution parameters different sample sizes (n=10,50,100) and (N=1000), taking initial

Many cities suffer from the large spread of slums, especially the cities of the Middle East. The purpose of the paper is to study the reality of informal housing in Al-Barrakia and the most important problems that it suffers from. The paper also seeks to study the presence or absence of a correlation between urban safety indicators and urban containment indicators as one of the methods of developing and planning cities. This can be achieved through sustainable urban management. The slums are a source of many urban problems that threaten the security and safety of the residents and represent a focus for the concentration of crimes and drugs. The paper seeks to answer the following question: How can urban safety be improved through urban cont

To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distrib

Companies compete greatly with each other today, so they need to focus on innovation to develop their products and make them competitive. Lean product development is the ideal way to develop product, foster innovation, maximize value, and reduce time. Set-Based Concurrent Engineering (SBCE) is an approved lean product improvement mechanism that builds on the creation of a number of alternative designs at the subsystem level. These designs are simultaneously improved and tested, and the weaker choices are removed gradually until the optimum solution is reached finally. SBCE implementations have been extensively performed in the automotive industry and there are a few case studies in the aerospace industry. This research describe the use o

Developed and underdevelopment countries, on equal terms, face the problem of budget deficiency. Budget deficiency means that the public expenditure surpasses the public revenues. This, on the international level, is one of the most serious economic problems with many direct effects on the national economy, and depends, basically, on its finance chosen method. Looking for a solution to this problem, for this reason and many other ones, has been highlighted in spite of the many attempts to reduce the role of the governmental expenditure. Budget deficiency can not be attributed to a single unique cause since it is complex phenomenons the causes of which are related to many factors contribute to its occurrence, some of which refer t

This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe