درخت حوزه‌های تخصصی

The purpose of this work is to use structural analysis to create believable scenarios of Iranian food tourism. In the present study, to formulate plausible scenarios, first by reviewing the literature and interviewing experts, 37 factors affecting food tourism were extracted. The variables affecting the future of food tourism, directly and indirectly, were calculated using a questionnaire and analysis by MICMAC software. Finally, considering the two most critical factors called food festivals and sanctions/international relations, plausible scenarios for the future of Iranian food tourism were developed. Based on the results, four scenarios are presented. These scenarios include Golden Scenario, Limited Scenario, Neglected Scenario and Chaotic Scenario. In Golden scenario, which depicts the ideal conditions, as many suitable food festivals as possible are being held in a country, and sanctions are not imposed. According to Limited Scenario, holding more and better food festivals is on the officials’ agenda, but on the other hand, the country is under sanctions and pressure. In Neglected Scenario, holding festivals is the same as in the past, and the country is not sanctioned. In Chaotic Scenario, depicting the worst-case scenario, the festival process is the same as in the past and has not been developed quantitatively and qualitatively. Also, the country is in a problematic situation of sanctions. Creating Credible The industry's major players and beneficiaries greatly benefit from Iranian food tourism scenarios, which enable them to provide flexible preparation-based programmers in response to shifting circumstances. The techniques and factors that influence the growth of the business will be known to the participants and recipients of food tourism, and this will open up a multitude of opportunities for the players involved.

With the development of a new stage of the industrial revolution, the importance of digitalization of business development tools is growing. The purpose of this article is to study the applied aspects of digital marketing tools usage for business development in the B2C market. To achieve the purpose and objectives of the study general and special methods are used: comparative analysis of the results of economic and statistical surveys; method of expert assessments by questionnaires using a 5-point Likert scale. The concordance coefficient was used to determine the consistency of the experts' opinions taking into account the related ranks in method of expert assessments. According to the results of the research, it is established that the Ukrainian business of the B2C sector was actively mastering digital marketing tools. The analysis of penetration level of digital technologies in the development of trade business showed the emergence of basic conditions for updating marketing tools to influence the B2C market. There is a rapid coverage rate of multi-purpose use of the Internet among consumers and businesses; gradual growth of digital skills among practitioners; positive dynamics of development of interactive services in the trade sphere. However, the level of use of the retail businesses websites remains low in many spheres of customer service. An important trend of the current development stage of the consumer market is the usage of business Internet platforms designed for mass dissemination of information. Effective marketing channels of interaction with consumers include social media (social networks, blogs or microblogs, websites with multimedia content, knowledge sharing tools), websites, e-shops, and sales via mobile devices. According to the results of expert evaluation, foreground digital technologies, which are able to bring business to a qualitatively new level of interaction with consumers and the provision of trade services have been identified. These are artificial intelligence and cognitive technologies, BigData, Internet of Things (IoT), and cloud computing. The structural and logical scheme of research of digital marketing tools is used for business development which includes two stages is offered. In the first stage, trendwatching, benchmarking and evaluation of internal opportunities for the use of digital marketing tools are performed. In the second stage, three components of digital readiness of business are defined: technological; competence; institutional. The obtained results form the basis of further research to determine the priorities of adaptive digital business behavior for the productive use of existing digital opportunities.

Most real-time speech signals are frequently disrupted by noise such as traffic, babbling, and background noises, among other things. The goal of speech denoising is to extract the clean speech signal from as many distorted components as possible. For speech denoising, many researchers worked on sparse representation and dictionary learning algorithms. These algorithms, however, have many disadvantages, including being overcomplete, computationally expensive, and susceptible to orthogonality restrictions, as well as a lack of arithmetic precision due to the usage of double-precision. We propose a greedy technique for dictionary learning with sparse representation to overcome these concerns. In this technique, the input signal's singular value decomposition is used to exploit orthogonality, and here the ℓ1-ℓ2 norm is employed to obtain sparsity to learn the dictionary. It improves dictionary learning by overcoming the orthogonality constraint, the three-sigma rule-based number of iterations, and the overcomplete nature. And this technique has resulted in improved performance as well as reduced computing complexity. With a bit-precision of Q7 fixed-point arithmetic, this approach is also used in resource-constrained embedded systems, and the performance is considerably better than other algorithms. The greedy approach outperforms the other two in terms of SNR, Short-Time Objective Intelligibility, and computing time.