Spamming is the act of abusing an electronic messaging system by sending unsolicited bulk messages. Filtering of these messages is merely another line of defence and does not prevent spam messages from circulating in email systems. This problem causes users to distrust email systems, suspect even legitimate emails and leads to substantial investment in technologies to counter the spam problem. Spammers threaten users by abusing the lack of accountability and verification features of communicating entities. To contribute to the fight against spamming, a cloud-based system that analyses the email server logs and uses predictive analytics with machine learning to build trust identities that model the email messaging behavior of spamming and legitimate servers has been designed. The system constructs trust models for servers, updating them regularly to tune the models. This study proposed that this approach will not only minimize the circulation of spam in email messaging systems, but will also be a novel step in the direction of trust identities and accountability in email infrastructure.
Gelişen teknoloji ile birlikte, çevresel koşullar kolay bir şekilde takip edilebilmekte ve oluşabilecek tehlikeli durumlara hızlı bir şekilde müdahale edilebilmektedir. Bu gelişmeler neticesinde illerin, ilçelerin, yaşam beldelerinin yaşanabilirlik kalitesi değerlendirmesinde çevre koşulları da göz önüne alınmaktadır. Bu çalışmada, sıcaklık, nem, gürültü ve oksijen miktarları göz önünde bulundurularak bir yaşanabilirlik endeksi modeli önerilmiştir. Bu amaçla, oluşturulan devre ile Isparta ili içerisinde belirlenen çeşitli bölgelerde ölçümler yapılmış ve bir yaşanılabilirlik endeksi tabanlı haritası çıkarılmıştır. Elde edilen sonuçlar ile Isparta ilindeki insanların ikamet alanı seçimleri karşılaştırıldığında, tam bir uyum gösterdiği görülmüştür.
Artificial intelligence is widely enrolled in different types of real-world problems. In this context, developing diagnosis-based systems is one of the most popular research interests. Considering medical service purposes, using such systems has enabled doctors and other individuals taking roles in medical services to take instant, efficient expert support from computers. One cannot deny that intelligent systems are able to make diagnosis over any type of disease. That just depends on decision-making infrastructure of the formed intelligent diagnosis system. In the context of the explanations, this chapter introduces a diagnosis system formed by support vector machines (SVM) trained by vortex optimization algorithm (VOA). As a continuation of previously done works, the research considered here aims to diagnose diabetes. The chapter briefly gives information about details of the system and findings reached after using the developed system.
Creating and updating meal tags, printing them on small-sized papers raise the costs, cause workload and affect the service quality negatively at the hotels with all-you-can-eat buffet system. Over the last few years, we have seen that many hotels started to make use of tablets to improve the service quality, decrease the costs, provide customers ability to order foods, make reservations, manage their rooms, etc. Going paperless and including more features by adopting new technologies increase the quality of service, help customer's and staff's decision-making processes more effective, improve customer and service personnel experience. In this chapter, authors designed and developed a flexible, cost effective, easy-to-use, customer-friendly and staff oriented paperless buffet management system for the restaurants that have all-you-can-eat buffet. Through this system, they aimed to achieve enhanced customer service, increased efficiency and customer satisfaction; save time, paper and printing costs; provide environmental benefits and efficient buffet management.
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