A novel predictive model for capturing threats for facilitating effective social distancing in COVID-19

Social distancing is one of the simple and effective shields for every individual to control spreading of virus in present scenario of pandemic coronavirus disease (COVID-19). However, existing application of social distancing is a basic model and it is also characterized by various pitfalls in case of dynamic monitoring of infected individual accurately. Review of existing literature shows that there has been various dedicated research attempt towards social distancing using available technologies, however, there are further scope of improvement too. This paper has introduced a novel framework which is capable of computing the level of threat with much higher degree of accuracy using distance and duration of stay as elementary parameters. Finally, the model can successfully classify the level of threats using deep learning. The study outcome shows that proposed system offers better predictive performance in contrast to other approaches.

Economic Assessment of Power Grid Development Using Artificial Bee Colony Algorithm

The electricity system is generally rapidly developing for covering various power demands with requiring a reliable and safe supply where the substructures are expanding further in generation systems, transmission systems, and distribution systems. However, the system must be run economically to access energy at a cost-effective level related to existing energy enterprises and energy consumption in the load which is represented periodically in the total costs of operations for all operating units. As a basis for its determination, the transmission of economic power within the technical limits applicable is taken into consideration. Environmental factors, on the other hand, are also an impediment to technical limitations. As a result, the operation's economic measure is expressed in the process of providing and selling energy to customers. These works use the Artificial Bees Colony algorithm to determine the scheduling of generating units using the basic principle of optimization to describe its relationship as an economic function. The IEEE-30 bus system is used as a basic model for system development. The analysis' findings show that the weighting factor scheme has an impact on the minimum total cost and that the combination of the electricity distribution process and environmental factors has implications for the operational financial condition and electricity production. The power output, in particular, is proportional to the cost of each generating unit.

R&D of the PERT basic model for project planning

The guiding principles of project implementation are planning. The discrepancy in time, cost, and quality between the plan and the actual implementation of the project requires management decisions supported by an analysis of the optimization of the duration of the project and the search for reserves to reduce the implementation time. For this purpose, a basic PERT model for a specific project was developed, early and late deadlines for work, time reserves, and a critical path were calculated. This work is aimed at applying methods of evaluation and analysis of projects to find optimal solutions and control the efficiency of time and costs in project planning, by varying the work on the project and the executors of the work. The results of this study showed that there are quite large time reserves for works 5-7, 7-9, 6-9, etc., which makes it possible to redistribute work between performers and allows you to vary performers during the implementation of several projects simultaneously.

Model design and parameter optimization of CNN for side-channel cryptanalysis

Background The side-channel cryptanalysis method based on convolutional neural network (CNNSCA) can effectively carry out cryptographic attacks. The CNNSCA network models that achieve cryptanalysis mainly include CNNSCA based on the VGG variant (VGG-CNNSCA) and CNNSCA based on the Alexnet variant (Alex-CNNSCA). The learning ability and cryptanalysis performance of these CNNSCA models are not optimal, and the trained model has low accuracy, too long training time, and takes up more computing resources. In order to improve the overall performance of CNNSCA, the paper will improve CNNSCA model design and hyperparameter optimization. Methods The paper first studied the CNN architecture composition in the SCA application scenario, and derives the calculation process of the CNN core algorithm for side-channel leakage of one-dimensional data. Secondly, a new basic model of CNNSCA was designed by comprehensively using the advantages of VGG-CNNSCA model classification and fitting efficiency and Alex-CNNSCA model occupying less computing resources, in order to better reduce the gradient dispersion problem of error back propagation in deep networks, the SE (Squeeze-and-Excitation) module is newly embedded in this basic model, this module is used for the first time in the CNNSCA model, which forms a new idea for the design of the CNNSCA model. Then apply this basic model to a known first-order masked dataset from the side-channel leak public database (ASCAD). In this application scenario, according to the model design rules and actual experimental results, exclude non-essential experimental parameters. Optimize the various hyperparameters of the basic model in the most objective experimental parameter interval to improve its cryptanalysis performance, which results in a hyper-parameter optimization scheme and a final benchmark for the determination of hyper-parameters. Results Finally, a new CNNSCA model optimized architecture for attacking unprotected encryption devices is obtained—CNNSCAnew. Through comparative experiments, CNNSCAnew’s guessing entropy evaluation results converged to 61. From model training to successful recovery of the key, the total time spent was shortened to about 30 min, and we obtained better performance than other CNNSCA models.

Do Citizens of a City that Owns a Local Public Airport Have Attachment to the Airport and Use it?

This research investigates whether passengers living in a city with a local public airport have an attachment to that airport and tend to use it. Focusing on the greater Kansai area with its three airports and Kobe, which owns one of them, Kobe Airport, as an example, an empirical analysis was conducted using a nested logit model and micro data. The result of the basic model shows that passengers living in Kobe prefer the Kobe Airport when compared to passengers living in other cities. An additional analysis based on a questionnaire survey revealed that a certain percentage of respondents choose Kobe Airport because they love it, meaning that the non-economic factor of attachment influences passengers’ decisions. The results of this research suggest that enhancing attachment to an airport might be a possible idea for policy makers of airport cities to increase their passengers.

Brand image mediation of product quality and electronic word of mouth on purchase decision

The practical implication that can be given from the findings of this study is that this study can be used as a basic model to evaluate the Samsung smartphone company's strategy for product quality, eWOM, brand image, and consumer purchase decisions. Based on the results of statistical analysis, that product quality and eWOM directly or indirectly through brand image affect consumer purchase decisions. This can be a reference for Samsung company management in making strategies to improve purchase decisions by maintaining product quality, eWOM, and brand image of Samsung smartphones. The practical implication that can be given from the findings of this study is that this study can be used as a basic model to evaluate the Samsung smartphone company's strategy for product quality, eWOM, brand image, and consumer purchase decisions. Based on the results of statistical analysis, that product quality and eWOM directly or indirectly through brand image affect consumer purchase decisions. This can be a reference for Samsung company management in making strategies to improve purchase decisions by maintaining product quality, eWOM, and brand image of Samsung smartphones. that product quality and eWOM directly or indirectly through brand image affect consumer purchase decisions.

THE FREEDOM OF CONTRACT AND ADDITIONAL CONTRACTS OF THE PARTIES TO THE EMPLOYMENT RELATIONSHIP

The issue of freedom of contract in the individual labour law is discussed in this text taking into account the additional conctracts, concluded by the employer and the employee in addition to the primary contract (i.e. employment contract). The scope of freedom of contract which is construed in the relation to the additional contracts shows deviations from the basic model. The main difference is the recognition of the rule of numerus apertus (as opposed to numerus clausus rule) of additional conctracts. The specifity of additional contracts extends the freedom of parties of an employment relationship to form the content of that legal relationship. This, however, does not prejudge a question of a regulatory model of the above-mentioned freedom.

Determination of the aerodynamic characteristics of the tiltrotor with the wingtip-mounted coaxial rotors

The article describes the study of rotor-to-wing aerodynamic interaction for the wingtip-mounted coaxial rotors configuration of the tiltrotor aircraft. The influence of the rotor slipstreams on lift-to-drag ratio characteristic was determined. Obtained results were compared with similar characteristics of the equivalent in thrust conventional single rotor slipstreams impact. Using the computational aerodynamics methods (panel-vortex method) the flow around the tiltrotor model with the wingtip-mounted single and coaxial rotors has been simulated. A study of the basic model configuration with conventional single rotors, based on the technical characteristics of the AgustaWestland AW609 tiltrotor, was conducted. Further researches were conducted for a modified model where single rotors were replaced with equivalent in thrust coaxial rotors. The influence of the rotor slipstreams on the aerodynamic characteristics of the model for both directions of rotors rotation in coaxial combination is considered. Also, the dependence of the maximum lift-to-drag characteristic due to the coaxial rotor diameters change has been determined. The results show that the coaxial rotor slipstreams-to-wing aerodynamic interaction effect is the similar to the effect of conventional single rotor, but less intensive. Comparison of the results showed that a tiltrotor equipped with wingtip-mounted single rotors has approximately 20% greater maximum lift-to-drag characteristic than one equipped with coaxial rotors with the same thrust. However, the use of coaxial rotors allows getting higher maximum speed, when conventional single rotors lose the efficiency significantly. Therefore, it is advisable to conduct further research for the possibility of using coaxial rotors for tiltrotor aircrafts. The research results are presented in graphical form. The obtained data provides a basis for further studies of the described problem, and also will be useful for new tiltrotor design works.

Prediction of Alzheimer’s Disease Based on Coordinate-Dense Attention Network

Alzheimer’s disease (AD) is a degenerative disease of the nervous system. Mild cognitive impairment (MCI) is a condition between brain aging and dementia. The prediction will be divided into stable sMCI and progressive pMCI as a binary task. Structural magnetic resonance imaging (sMRI) can describe structural changes in the brain and provide a diagnostic method for the detection and early prevention of Alzheimer’s disease. In this paper, an automatic disease prediction scheme based on MRI was designed. A dense convolutional network was used as the basic model. By adding a channel attention mechanism to the model, significant feature information in MRI images was extracted, and the unimportant features were ignored or suppressed. The proposed framework is compared with the most advanced methods, and better results are obtained.

Measuring the Return on Investment of Training Modules of Electrical Protection and Uninterruptible Power Supply (UPS) Using the Corrective and AHP Approaches

The main purpose of this study is to calculate the return on investment of two training modules of electrical protection and uninterruptible power supply (UPS) using the corrective approaches applied to the basic model presented in previous research. In this study, first, the effect points of the training were identified using open questionnaires completed by experts. Then, its content validity is ensured by Lawshe, Waltz, and Basel approaches. Data on training costs were extracted through financial documentation and estimates. Details of measures, savings, internal supply, and so on were identified and cited to convert the observed effects into financial equivalents. Using the analytic hierarchy process (AHP) approach, the role of training in comparison with other initiatives in each of the effects and achievements was determined, and the net financial achievements of the training were determined. The training return on investment for the electrical protection module was 243% and for the UPS module was 1637%.