Abstract

Abstract

Abstract
The most broadly perceived relative directions are right, left, up, down, backward and forward. This research paper presents a new computational technique to learn human's relative directions, where one intelligent computer can learn any human's right, left, up, down, backward and forward or different relative directions. The present paper portrays models describing the essential structures of relative direction learning process between human and intelligent machine. We developed two proficient algorithms for solving this approach. In our experiment we propose Human Relative Direction Learning (HRDL) algorithm for learning human's relative directions and Human Direction Identification (HDI) algorithm for tracking any human position and identity human's relative directions from different direction points.

Abstract
Manufacturing companies increasingly try to innovate in their offers to consumers by creating more complete solutions that combine product and service components. However, shifting from a product-centric perspective to a solution oriented perspective is challenging. The present study adopted a design research methodology and built on Service-Dominant logic, integrating the human oriented perspective of Service Design with an organizational network-oriented perspective of Product-Service System. It creates a new Integrative PSS approach, evolves design models, and provides an application in a manufacturing industry. This paper details how the application supports the design of product service system solutions from the exploration to the implementation stages, highlighting the physical evidence of service, and contributes to advance design research at the intersection of PSS and Service Design.

Abstract
The importance of e-commerce continues to grow in retail, providing companies with a critical tool to improve marketing and commercial strategies. In this context, understanding the distribution channels and the new business models becomes a fundamental issue for both researchers and business managers. This paper has two priority objectives. First is the accomplishment of a specific recent literature review survey on the theme of e-commerce platforms adoption that will support the next step. Second is to propose an adoption model that characterizes Discount and Outlet Platforms (DOP) adoption. The last contribution is distributed in the form of practical and theoretical implications, as well as future lines of action for possible investigations.

Abstract
Optical fiber tweezers have been gaining prominence in several applications in Biology and Medicine. Due to their outstanding focusing abilities, they are able to trap and manipulate microparticles, including cells, needing any physical contact and with a low degree of invasiveness to the trapped cell. Recently, we proposed a fiber tweezer configuration based on a polymeric micro-lens on the top of a single mode fiber, obtained by a self-guided photopolymerization process. This configuration is able to both trap and identify the target through the analysis of short-term portions of the back-scattered signal. In this paper, we propose a variant of this fabrication method, capable of producing more robust fiber tips, which produce stronger trapping effects on targets by as much as two to ten fold. These novel lenses maintain the capability of distinguish the different classes of trapped particles based on the back-scattered signal. This novel fabrication method consists in the introduction of a multi mode fiber section on the tip of a single mode (SM) fiber. A detailed description of how relevant fabrication parameters such as the length of the multi mode section and the photopolymerization laser power can be tuned for different purposes (e.g., microparticles trapping only, simultaneous trapping and sensing) is also provided, based on both experimental and theoretical evidences.