The Experts below are selected from a list of 102753 Experts worldwide ranked by ideXlab platform

Jan Holmström - One of the best experts on this subject based on the ideXlab platform.

  • Wireless Product Identification: enabler for handling efficiency, customisation and information sharing
    Supply Chain Management: An International Journal, 2002
    Co-Authors: M.k. Karkkainen, Jan Holmström
    Abstract:

    More sophisticated customer demand chains and electronic business pose new challenges to supply chain management. Delivery sizes decrease as a result of more deliveries directly to the point of use. Customers are demanding Products and deliveries customised to their specific needs. Also, the information concerning small, customised deliveries has to be shared in volatile supply networks. This article analyses the opportunities of wireless Product Identification technology in transforming supply chain management. A new concept of item level supply chain management and enabling steps to achieve the benefits are proposed. Innovative companies already use wireless Product Identification with great benefits in specific functional areas, e.g. manufacturing and warehousing. However, the biggest potential is in supply chain wide solutions, i.e. item level supply chain management.

Susan J. Masten - One of the best experts on this subject based on the ideXlab platform.

  • The ozonation of benz[a]anthracene: pathway and Product Identification
    Water Research, 1998
    Co-Authors: Zhi-heng Huang, Susan J. Masten
    Abstract:

    Abstract The pathway for the ozonolysis of benz[a]anthracene (BaA) (ACS standard named), a polycyclic aromatic hydrocarbon (PAH), has been described in this paper. BaA was dissolved in a 90% acetonitrile:water (v/v) mixture to achieve an initial concentration of 1 mM. The ozonolysis of BaA was evaluated using different ozone dosages. The ozonation Products were identified by gas chromatography/mass spectrometry (GC/MS). Fifteen Products including eight pairs of isomers were identified. Ozone reacted with BaA simultaneously by bond and atom attack. Ozone attack on the carbon at the 7 and/or 12 position produced the quinone or hydroxyl functional groups. The bond attack type of reaction occurred at the 5,6 position and caused ring cleavage resulting in phenyl–naphthyl type Products. Ozonolysis of BaA in this solvent mixture occurred preferentially by bond attack rather than by the atom attack type of reaction.

  • The ozonation of pyrene: Pathway and Product Identification
    Water Research, 1998
    Co-Authors: Jehng-jyun Yao, Zhi-heng Huang, Susan J. Masten
    Abstract:

    Abstract The pathway by which ozone reacts with pyrene, a polycyclic aromatic hydrocarbon (PAH), is proposed in this paper. Pyrene was dissolved in a 90% acetonitrile:water (v/v) mixture. At this ratio, sufficient water is present to participate in the ozonolysis reaction and thereby mimic what occurs in pure water. The initial pyrene concentration was 5 mM. The ozone dosages were varied to obtain different extents of reaction. A stoichiometric ratio of 1.68 mol ozone mol −1 pyrene was required to completely destroy pyrene. The ozonation Products were tentatively identified by gas chromatography–mass spectrometry (GC–MS). Fourteen Products including aldehyde and carboxylic acid substituted phenanthrene- and biphenyl-type oxidation Products were identified. Several ring-cleavage reactions occurred sequentially: (i) ring cleavage of pyrene first occurred at the 4,5 position, with phenanthrene-type Products predominating; and (ii) once secondary ring cleavage occurred, the concentration of pyrene and the phenanthrene-type Products decreased dramatically, while the concentration of biphenyl-type Products increased. The oxidation of pyrene by hydroxyl free radicals was found to be involved in the reaction, even at pH 3.7.

Masaya Ohta - One of the best experts on this subject based on the ideXlab platform.

  • GCCE - Improved Product Identification method using CNN for mixed-reality web shopping system
    2017 IEEE 6th Global Conference on Consumer Electronics (GCCE), 2017
    Co-Authors: Kazuki Shibata, Hotaka Niwa, Masaya Ohta
    Abstract:

    E-commerce (EC) sites have become quite popular for online shopping. However, a user of an EC site must possess certain skills to search for his/her desired Product from the numerous web pages. A mixed-reality web-shopping system with panoramic views mitigates this problem. The users of this system can shop in the same manner as they do in a real shop, by viewing the panoramic photographs taken inside the shop. However, one problem with this system is the detection of a Product selected in the panoramic view by the user. Although we proposed a Product Identification system using convolutional neural networks (CNN), its performance was not satisfactory. In this research, we propose a method to improve the recognition rate of the CNN.

  • GCCE - A Product Identification method for a mixed-reality web shopping system
    2016 IEEE 5th Global Conference on Consumer Electronics, 2016
    Co-Authors: Hotaka Niwa, Masaya Ohta, Koichi Nagata, Katsumi Yamashita
    Abstract:

    On an e-commerce site, users can easily search for a desired Product by inputting the name and/or the model number of the Product into a web browser. However, they fail to find it if the query is inputted incorrectly or an ambiguous term is used. We have proposed a mixed-reality web shopping system with panoramic images photographed at the aisles of a real store. In this system, the user can move freely around the store and pick the desired Product up while viewing the panoramic images. To implement the system, the Product in the panoramic image must be recognized automatically. Because there are a huge number of Products in the image, it is not practical that all Products are recognized manually. In this paper we consider a Product Identification method for the mixed-reality web shopping system. The convolutional neural network was used to recognize Products in this method.

Albrecht Schmidt - One of the best experts on this subject based on the ideXlab platform.

  • an evaluation of Product Identification techniques for mobile phones
    International Conference on Human-Computer Interaction, 2009
    Co-Authors: Felix Von Reischach, Florian Michahelles, Dominique Guinard, Robert Adelmann, Elgar Fleisch, Albrecht Schmidt
    Abstract:

    Among others, consumer Products can be purchased in the Internet and in traditional stores. Each of the two has dedicated advantages. An online survey conducted within the frames of this work investigates these advantages. It motivates the transition of the advantages of online shopping, such as access to recommendations of other consumers, to the sales floor. Recent trends in mobile phone technology, for example the emergence of the mobile Internet, enable exactly this transition, potentially enriching the shopping experience in the real world. A key challenge though is a fast and convenient Identification of Products. This work compares five Product Identification modalities for mobile phones in a comparative study. The dependent variables evaluated are `task completion time' and `perceived ease of use'. Our study is the first that quantifies the advantage of automatic Identification. The results indicate that automatically identifying a Product scanning a tag can be up to eight times faster than entering a Product name in a text field. Surprisingly, barcode recognition using a camera phone can be conducted almost as fast and convenient as scanning an RFID tag. Our work provides a benchmark for developers having to choose appropriate Identification technology for their mobile application.

  • INTERACT (1) - An Evaluation of Product Identification Techniques for Mobile Phones
    Human-Computer Interaction – INTERACT 2009, 2009
    Co-Authors: Felix Von Reischach, Florian Michahelles, Dominique Guinard, Robert Adelmann, Elgar Fleisch, Albrecht Schmidt
    Abstract:

    Among others, consumer Products can be purchased in the Internet and in traditional stores. Each of the two has dedicated advantages. An online survey conducted within the frames of this work investigates these advantages. It motivates the transition of the advantages of online shopping, such as access to recommendations of other consumers, to the sales floor. Recent trends in mobile phone technology, for example the emergence of the mobile Internet, enable exactly this transition, potentially enriching the shopping experience in the real world. A key challenge though is a fast and convenient Identification of Products. This work compares five Product Identification modalities for mobile phones in a comparative study. The dependent variables evaluated are `task completion time' and `perceived ease of use'. Our study is the first that quantifies the advantage of automatic Identification. The results indicate that automatically identifying a Product scanning a tag can be up to eight times faster than entering a Product name in a text field. Surprisingly, barcode recognition using a camera phone can be conducted almost as fast and convenient as scanning an RFID tag. Our work provides a benchmark for developers having to choose appropriate Identification technology for their mobile application.

Hotaka Niwa - One of the best experts on this subject based on the ideXlab platform.

  • GCCE - Improved Product Identification method using CNN for mixed-reality web shopping system
    2017 IEEE 6th Global Conference on Consumer Electronics (GCCE), 2017
    Co-Authors: Kazuki Shibata, Hotaka Niwa, Masaya Ohta
    Abstract:

    E-commerce (EC) sites have become quite popular for online shopping. However, a user of an EC site must possess certain skills to search for his/her desired Product from the numerous web pages. A mixed-reality web-shopping system with panoramic views mitigates this problem. The users of this system can shop in the same manner as they do in a real shop, by viewing the panoramic photographs taken inside the shop. However, one problem with this system is the detection of a Product selected in the panoramic view by the user. Although we proposed a Product Identification system using convolutional neural networks (CNN), its performance was not satisfactory. In this research, we propose a method to improve the recognition rate of the CNN.

  • GCCE - A Product Identification method for a mixed-reality web shopping system
    2016 IEEE 5th Global Conference on Consumer Electronics, 2016
    Co-Authors: Hotaka Niwa, Masaya Ohta, Koichi Nagata, Katsumi Yamashita
    Abstract:

    On an e-commerce site, users can easily search for a desired Product by inputting the name and/or the model number of the Product into a web browser. However, they fail to find it if the query is inputted incorrectly or an ambiguous term is used. We have proposed a mixed-reality web shopping system with panoramic images photographed at the aisles of a real store. In this system, the user can move freely around the store and pick the desired Product up while viewing the panoramic images. To implement the system, the Product in the panoramic image must be recognized automatically. Because there are a huge number of Products in the image, it is not practical that all Products are recognized manually. In this paper we consider a Product Identification method for the mixed-reality web shopping system. The convolutional neural network was used to recognize Products in this method.