درخت حوزه‌های تخصصی

In today’s era when a substitute for almost every product is readily available, acceptance and adoption of a new product in a market requires substantial amount of promotion. Here we formulate and analyze policies for promoting sales of a product in a market through optimal control theory problems. The market is partitioned into various segments depending upon multifarious demands of customers and promotion of the product is done segment-wise. The aim is to maximize the profits keeping in mind the demand requirements and the available budget for promotion. In order to provide a realistic model, the total available budget is taken to be imprecise. The optimal control model with fuzzy parameter is converted into crisp form using necessity and possibility constraints, and thereafter solved by using Pontryagin Maximum principle. To illustrate this technique, a numerical example is also considered by discretizing the model. The analysis also gives a deep insight of how the promotional effort should be planned by the decision makers keeping in mind the financial constrains without hindering the promotional effort at the end of the planning period. This paper mirrors the real time situation that could be faced by any industry, including that of software development, where budgets may have variable components and promotion of products may vary according to different regions and markets. The experimental data reveals that profitability can still be maximized if real-life constraints are applied in promotional planning by any industry.

Recreation and entertainment are among the major objectives and intentions of tourism. The reasons put forward by tourists include escaping quotidian life and social interactions. Relying on the Muslim mystics’ view of the real nature of human being, this article offers an analysis of escaping quotidian life and environment in the discovery of real identity and studies the role of traveling in this regard. This analysis showed that from the Muslim mystics’ viewpoint, the real nature of humans is impoverishment and desperate need for a raison d’etre. Meantime, social interactions and affiliation with minor and major social groups overshadow such identity and create obstacles in the way of self-awareness. That explains why the disciples of Islamic Sufism were recommended retreatment. Even today, traveling and tourism provide such an opportunity for humans to distance themselves from the social groups and classes they belong to for some time and gain spiritual experience through a more precise perception of their own reality

The objective of this study is to investigate the extent of spirituality in various types of tourism, and to test the hypothesis of the existence of common spiritual experiences among all types of tourists. McKercher's typology of cultural tourists and Norman's (2012) typology of tourists' spiritual experiences were applied to classify various groups of spiritual tourists participating in each type of tourism activity. The study population consisted of all individuals who have travelled with the purpose of pilgrimage, recreation, visiting cultural historical attractions, business, visiting religious sites, or participating in ecotourism and nature-based tourism. Sampling was done based on the convenience method according to the size and nature of the target population. Finally, it was concluded that most pilgrims and visitors to the religious sites were purposeful and sightseeing spiritual tourists with a deep intention to search for spiritual growth. Also, among nature-based tourists, ecotourists, business and recreational tourists, and those who had traveled to visit cultural and historical sites, a considerable number were Casual, Incidental and Serendipitous Spiritual Tourists, whilst only a small proportion had purposefully travelled for spiritual growth. Nevertheless, the research indicates the existence of at least one powerful element of spirituality in all types of tourism. 

The increase in non-performing loans considerably reduces profit in the banking systems. To solve these problems, factors influencing the collection of non-performing loans have to be examined in a hopeful attempt to reduce it to an ac-ceptable level. The present study is conducted to analyze and study factors influ-encing the collection of non-performing loans in Shahr Bank. This research is an applied study regarding its goal. It was conducted in two sections, namely the qualitative and quantitative sections. In the qualitative sections, the factors influ-encing the collection of receivables were identified using the theoretical literature and interviews with senior managers of Shahr Bank through the encoding process. In the quantitative section, data was collected by surveying the opinions of 12 experts, including senior managers of Shahr Bank in 2020 using a questionnaire. Thereafter, the factors were selected using the fuzzy Delphi technique and the relationships between them were determined using the fuzzy DEMATEL method. Finally, the factors were weighted and prioritized using the fuzzy ANP method. The research findings showed that non-performing loans can be collected through six types of factors including organizational, regulatory, customer, banking, envi-ronmental, and operational factors. The environmental factor is the most influential factor, while the operational factor is the most influenced and most important factor. In addition, behavioural, contextual, and structural sub-factors have the highest level of importance in the collection of non-performing loans in the order mentioned. These findings can help bank managers make decisions to improve the collection of receivables.

An administrator is employed to identify network security breaches in their organizations by using a Network Intrusion Detection and Prevention System (NIDPS), which is presented in this paper that can detect and preventing a wide range of well-known network attacks. It is now more important than ever to recognize different cyber-attacks and network abnormalities that build an effective intrusion detection system plays a crucial role in today's security. NSL-KDD benchmark data set is extensively used in literature, although it was created over a decade ago and will not reflect current network traffic and low-footprint attacks. Canadian Institute of Cyber security introduced a new data set, the CICIDS2017 network data set, which solved the NSL-KDD problem. With our approach, we can apply a variety of machine learning techniques like linear regression, Random Forest and ID3. The efficient IDPS is indeed implemented and tested in a network environment utilizing several machine learning methods. A model that simulates an IDS-IPS system by predicting whether a stream of network data is malicious or benign is our objective. An Enhanced ID3 is proposed in this study to identify abnormalities in network activity and classify them. For benchmark purposes, we also develop an auto encoder network, PCA, and K-Means Clustering. On CICIDS2017, a standard dataset for network intrusion, we apply Self-Taught Learning (STL), which is a deep learning approach. To compare, we looked at things like memory, Recall, Accuracy, and Precision.