A Novel Frechet-Type Probability Distribution: Its Properties and Applications

In this article, a new lifetime model, referred to as modified Frechet–Rayleigh distribution (MFRD), is developed by accommodating an additional parameter in Rayleigh distribution on the basis of the modified Frechet method. Numerous statistical properties of the suggested model are derived and discussed. The technique of maximum likelihood (ML) estimation is adopted to get estimates of the parameters. The suggested model is very flexible and has the capability to model datasets having both monotonic and nonmonotonic failure rates. The proposed model is applied on two real datasets for checking its performance in comparison with available well-known models. The suggested model has shown outclass performance in comparison with the available versions of the Rayleigh distribution used in the literature.

Using parallel pre-trained types of DCNN model to predict breast cancer with color normalization

Objective Breast cancer is the most common among women, and it causes many deaths every year. Early diagnosis increases the chance of cure through treatment. The traditional manual diagnosis requires effort and time from pathological experts, as it needs a joint experience of a number of pathologists. Diagnostic mistakes can lead to catastrophic results and endanger the lives of patients. The presence of an expert system that is able to specify whether the examined tissue is healthy or not, thus improves the quality of diagnosis and saves the time of experts. In this paper, a model capable of classifying breast cancer anatomy by making use of a pre-trained DCNN has been proposed. To build this model, first of all the image should be color stained by using Vahadane algorithm, then the model which combines three pre-trained DCNN (Xception, NASNet and Inceptoin_Resnet_V2) should be built in parallel, then the three branches should be aggregated to take advantage of each other. The suggested model was tested under different values of threshold ratios and also compared with other models. Results The proposed model on the BreaKHis dataset achieved 98% accuracy, which is better than the accuracy of other models used in this field.

Modelling and Optimisation of UHF band EW Based WTA Problem within the Scope of Threat Assessment

The classical weapon target allocation (WTA) problem has been evaluated within the scope of electronic warfare (EW) threat assessment with an electromagnetic effect-based jammer- tactical radio engagement approach. As different from the literature, optimum allocation of non-directional jammers operating at different operating UHF frequencies under constraints to RF emitters is aimed in this study. The values of the targets are modelled using an original threat assessment algorithm developed that takes into account operating frequencies, jamming distance, and weather conditions. The computed jammer-target effect matrix has been solved under different scenarios according to the efficiency and cost constraints. It is seen at the end of the simulations that the allocation results for EW applications largely depend on the effect ratio used. The better results are taken in the case of under 0.5 effect ratio. Finally, jammer-radio allocation problem specified at the suggested model is solved successfully and effectively.

Toward a Smart Organization, Integrating KM Processes and Organizational Capabilities

It is common knowledge that organizations today face the challenges of growing competition. Therefore, organizations need to develop smarter to plan for several diverse and real-time challenges. The aim of this paper is to test the impact of knowledge management (KM) processes, organizational capabilities (OC), and mediating KM mechanisms and KM technologies toward a smart organization (SO). In this paper, structural equation modeling was applied by using Smart PLS 3.3.3 software to test hypotheses and the accuracy of the suggested model. The results showed a direct impact between all constructs and are a reflection of the SO of the employees (N=225) working in three Jordanian telecommunications companies. Additionally, the outcomes provision the partial mediating role of KM mechanisms and KM technology with OC in the SO. These outcomes can support leaders in generating a consciousness in addition to favorable OC, KM mechanisms, and KM technologies inside the organization, which enables the actual implementation of SO and uses the outcomes to plan their SO strategies.

The Reality of Distance Assessment, in the Shadow of Corona Pandemic, from the Point of View of Teachers

This study sheds light on The Reality of Distance Assessment, in the Shadow of Corona Pandemic, from the Point of View of Teachers. The study sought to identify the criteria of assessing the distance learning, their requirements, and the steps of designing the distance assessment; in addition to identifying the tools and methods of distance assessment, and the characteristics of each tool. Finally, the study presented a suggested model for assessment, in the shadow of the emergent circumstances. This model depends on the philosophy of the modern educational theories and the givens of the twenty-first century and its skills. The researcher adopted the explanatory scientific method that uses knowledge to explain the phenomena and things via a group of connected concepts that are called theories. Then, adopting the descriptive method, as the researcher has designed a questionnaire that consists of (20) points, distributed on (120) male and female teachers in Lewaa Marka to know the opinions and approaches of the teaching staff about the methods and strategies of distance assessment. The responses of the study sample on the point of "to what extent the study sample knows about the methods and strategies of distance assessment" were average, while the responses of the study sample on the point of "the practical application of the distance assessment process" were weak and low.

Design and Simulation of Air-Fuel Percentage Sensors in Drone Engine Controlling

This paper presents the design and simulation of air-fuel percentage sensors in drone engine control using Matlab. The applications of sensor engineering system have been pioneer in technology development and advancement of automated machine as complex systems. The integration of drone fuel sensor system is the major series components such as injector, pumps and switches. The suggested model is tuned to interface drone fuel system with fuel flow in order to optimize efficient monitoring. The sensor system is improved and virtualized in Simulink block set by varying the parameters with high range to observe the fuel utilization curves and extract the validated results. The obtained results show that the possibility of engine operation in critical conditions such as takeoff, landing, sharp maneuver and performance is applicable to turn off the system in case of break down in the sensor to ensure the safety of drone engine. HIGHLIGHTS The drone engine fuel rate sensor is designed and examined to determine the air-to-fuel ratio The suggested model is tuned to interface drone fuel system with fuel flow in order to optimize efficient monitoring The obtained results show that the possibility of using engine with different failure mode and fault considerations The represented control structure is simple, efficient and provides the required air-to-fuel ratio

M-Learning and Learning Autonomy - Needs Analysis and Suggested Model

In this 4.0 era, where technology has been a part of our daily lives, the integration of smart devices into education is an indispensable movement that we are striving for. Hence, the application of mobile devices into learning, M-learning is becoming a trendy approach and a quality assurance’s measurement for almost every academic institution. Technology makes education available for students almost anywhere, anytime, and offers unlimited access to learning resources. Furthermore, M-learning is also reported to have a positive impact on students’ learning autonomy. Hence, this paper aims at validating possibilities to amplify this aspect of M-learning and suggesting an appropriate M-learning model at Nguyen Tat Thanh university (NTTU). The paper investigates students’ needs, requirements, ability to adapt to the new trend of M-learning plus the external elements affecting their learning autonomy to come up with the learning model. Surveys were collected from students in the Faculty of Foreign Languages and analyzed using a qualitative method to provide educators and teachers at NTTU with insightful information and careful preparation before launching new approaches to M-learning.

Analysis of Flexible Batch Service Queueing System to Constrict Waiting Time of Customers

When the required number of customers is available in the general bulk service (GBS) queueing system, the server begins service. Otherwise, the server will remain inactive until the number of consumers in the queue reaches that minimum required number. Customers that have already come must wait throughout this time, regardless of their arrival time. In some circumstances, like specimens awaiting testing in a clinical laboratory or perishable commodities awaiting delivery, it is necessary to finish services before the expiration date. It might only be achievable if consumers’ waiting times are kept under control. As a result, the flexible general bulk service (FGBS) rule is developed in this article to provide flexibility in batching. The effectiveness of FGBS implementation has been demonstrated using two examples: a clinical laboratory and a distribution center. To justify the suggested model, a simulation study and numerical illustration are provided.

MalSEIRS: Forecasting Malware Spread Based on Compartmental Models in Epidemiology

Over the last few decades, the Internet has brought about a myriad of benefits to almost every aspect of our daily lives. However, malware attacks have also widely proliferated, mainly aiming at legitimate network users, resulting in millions of dollars in damages if proper protection and response measures are not settled and enforced. In this context, the paper at hand proposes MalSEIRS, a novel dynamic model, to predict malware distribution in a network based on the SEIRS epidemiological model. As a result, the time-dependent rates of infection, recovery, and loss of immunity enable us to capture the complex dynamism of malware spreading behavior, which is influenced by a variety of external circumstances. In addition, we describe both offensive and defensive techniques, based on the proposed MalSEIRS model, through extensive experimentation, as well as disclosing real-life malware campaigns that can be better understood by using the suggested model.