15437086
A framework of a visual language with dynamic specification
The behavior of complex software may be changed depending on the external environment such as user profile, available resources, input data, time, and so on. Design of such dynamic software in conventional languages needs extra effort to keep consistency among behaviors for all states. We propose an object oriented visual language for dynamic software and its visualized specification with dynamics presentation. The language supports dynamic behavior according to both time-dependent and time-independent external states based on dynamic objects. In the visualized specification, we present uniform dynamics presentation for all elements in the language based on three concepts of snapshot, overlap and sweep.
35519508
Extending Visual Languages for Multimedia
Visual languages, which let users customize iconic sentences, can be extended to accommodate multimedia objects, letting users access media dynamically. Teleaction objects, or multimedia objects with knowledge structures, can be designed using visual languages to automatically respond to events and perform tasks like "find related books" in a virtual library.
39945679
Iconic Language Design for People with Significant Speech and Multiple Impairments
34016873
Parsing 2D Languages by a Pictorial GLR Parser
17298481
Iconic language design for people with significant speech and multiple impairments
We present an approach of iconic language design for people with significant speech and multiple impairments (SSMI), based upon the theory of Icon Algebra and the theory of Conceptual Dependency (CD) to derive the meaning of iconic sentences. An interactive design environment based upon this methodology is described.
15816324
Multi-level specification and protocol design for distributed multimedia communication
The major challenge in the design of an efficient distributed multimedia system is the integration and support of a wide variety of applications. Investigating the basic issues involved in the design and specification of distributed muttimcdia systems is the focus of this paper. A basic layered network architecture is proposed as the uniform framework for the investigation of different levels of functionality typically associated with the communication network that supports multimedia communication. Within this framework, we propose to identify the communication requirements for multimedia applications and characterize a set of communication primitives which specify different qualities of scrvicc to reflect different real-time rcquircmcnts. ‘Ilis investigation is guided by an efficient and flexible multi-level specification model. We will characterize this model and show that the model can be amenable to the construction of a set of communication primitives that support synchronization and communication of multimedia applications.
15655721
The Worst-case Analysis of the MULTIFIT Algorithm for Scheduling Nonsimultaneous Parallel Machines
Abstract In this paper we consider the nonsimultaneous multiprocessor scheduling problem, or NMSP for short. The NMSP is a makespan minimization scheduling problem which involves the nonpreemptive assignment of independent jobs on m parallel machines with different starting times. It is well known that the longest processing time (LPT) algorithm and the modified LPT(MLPT) algorithm yield schedules with makespans bounded by 3 2 − 1 2m and 4/3 times the optimum makespan, respectively. In this paper, we show that the best known worst-case performance bound, 4/3 of the MLPT, is tight by constructing a worst-case example. Then, we employ the bin-packing heuristic algorithm called the MULTIFIT to solve the NMSP and show that the makespan of the schedule generated by the MULTIFIT algorithm is bounded by 9/7+2−k times the optimum makespan, where k is the selected number of the major iterations in the MULTIFIT. This worst-case bound of the MULTIFIT algorithm is, so far, the best bound for the NMSP and the tightness of the bound is still an open question.
18088728
Order Consolidation for Batch Processing
We consider the batch processing of orders where either whole or part of a single order or a specific pair of different orders may be grouped in a batch with a fixed capacity. The problem can be modelled by a graph G = (V,E), where each node v$${\in}$$V corresponds to an order, its weight w(v) corresponds to the amount of ordered quantity and a pair of orders, say u and v may be grouped in a batch if there exists the edge (u,v) $${\in}$$E. The objective is to maximize the number of batches filled up to its capacity $$\lambda$$. In this paper, we prove that the problem is NP-hard and, moreover, that no PTAS exists unless P = NP. Then, an optimal algorithm is developed with running time O(|V|log |V|) for the special case when G is a tree.
16824799
A heuristic method for self‐healing ring design in a single‐homing cluster
In this paper, we consider a SONET (Synchronous Optical NETwork) USHR (Uni‐directional Self‐Healing Ring) design problem for a single‐homing cluster, i.e., a cluster with a single designated hub. The problem is formulated as a nonlinear integer programming problem and a branch and bound heuristic method based on the Lagrangian relaxation and subgradient optimization technique is proposed to handle the problem. In solving any ring design problem, we should deal with two different aspects of the ring design, namely, the ring routing aspect and the ring loading aspect. Both of these two aspects are well integrated and represented in our model. Such an integrated formulation has not been proposed in the existing literature mainly due to its computationally intractable complexity. In order to cope with such complexity, a preprocessing technique for reducing the complexity and several branch and bound strategies are proposed. The efficiency of the proposed method is tested through computational experiments. For the computational experiments, test problems are generated using the data obtained from the actual topologies in Seoul, Korea. The computational experiments show that the proposed method yields near‐optimum designs within reasonable computation time.
33123897
Assessing users' product-specific knowledge for personalization in electronic commerce
While many electronic commerce (EC) companies are adopting one-to-one marketing approaches using various personalization technologies to make their products and services unique for the purpose of attracting and retaining customers and improving their completion edges in the EC ecosystem, which, nevertheless, has low entrance barriers for new players to join and further intensify the competition, none or few of them consider a fundamental issue-the user's product-specific knowledge. Our research proposed to add this new domain of the customer's knowledge on appropriate target products into the personalization process as a part of the overall EC strategy for businesses. In this paper, we present our initial design for assessing the user's product-specific knowledge using the proposed innovative method for detecting it directly in a non-intrusive way without asking users to answer or fill out any types of questionnaires. Our method is based on customer's on-line navigation behaviors by analyzing their navigation patterns through pre-trained artificial neural networks. An empirical study designed for a case of EC store selling digital cameras was conducted in our research to prove the concept, and a good preliminary result was derived from the study. For the purpose of comparing the performances between the conventional approach of using questionnaire and the proposed innovative approach of navigation pattern mining, a questionnaire based approach for evaluating the user's product-specific knowledge was designed and incorporated into our knowledge level assessment system (KLAS). Our study result shows that although the pure questionnaire-based KLAS is intrusive and may not be accepted by some users, for those users willing to complete the questionnaire, the proposed navigation pattern approach can be combined with the questionnaire-based approach to create a hybrid KLAS which has a significantly improved accuracy rate in detecting the customer's product knowledge level.
16514620
SIMD architecture for job shop scheduling problem solving
Job shop is a typical environment for manufacturing high-variety and low-volume discrete parts. Good scheduling is critical and challenging to the competitiveness of job shops. The Lagrangian relaxation neural network (LRNN) provides an approach of quantifiable quality and successful industrial applications. To further speed up scheduling for large-scale problems, in this paper, the parallelism of the LRNN approach is exploited for hardware implementation. New designs include a SIMD architecture, its associated instruction set and detailed circuits. Logic level simulation of the circuit design shows consistent schedules with those obtained by a software implementation. The hardware implementation is expected to have a one to two orders speed-up over the software one.