Meet User Requirements Research Articles

Estimación del tamaño de la muestra para pruebas de usabilidad

Una de las estrategias empleadas para asegurar que una interfaz satisfaga los requerimientos del usuario es la aplicación de pruebas de usabilidad. Cuando se aplican tales pruebas una de las incógnitas a despejar es el tamaño de la muestra. Dado que, realizar pruebas en forma extensiva es costoso, reducir al mínimo el número de participantes puede contribuir en gran medida a una gestión exitosa de los recursos de un proyecto. Aunque se han propuesto un número significativo de modelos para estimar el tamaño de la muestra en una prueba de usabilidad, todavía no hay consenso acerca del tamaño óptimo. Varios estudios afirman que de 3 a 5 usuarios son suficientes para descubrir el 80% de los problemas en la interfaz de un sistema. Sin embargo, otros tantos estudios cuestionan la validez de esta aseveración. El presente estudio analizó los datos obtenidos de las pruebas de usuario de una aplicación web para verificar la regla práctica conocida comúnmente como “el número mágico 5”. El resultado del análisis mostró que la regla de los 5 usuarios subestima significativamente el tamaño de la muestra requerida para conseguir niveles razonables de detección de problemas.

Hospital information system user acceptance factors: User group perspectives

ABSTRACTThis study aimed to identify and rank user acceptance factors regarding the implementation of hospital information systems (HIS) based on the views of the following user groups: doctors, nurses, hospital management, and administrative staff (operators). The results should provide guidance for hospital management and HIS developers on meeting user requirements. The study was carried out using both qualitative and quantitative methods. The authors conducted interviews and distributed questionnaires to doctors, nurses, hospital management, and administrative staff in a government-owned Indonesian public hospital. Entropy measurements were used to analyze the questionnaire data. The study identified 15 important HIS user acceptance factors, which were ranked differently by each user group. The results show that non-technological dimensions, such as human and organizational dimensions, influence HIS user acceptance to a greater extent than technological dimensions. More work should be carried out to gain a better understanding of the relationship between user acceptance factors in order to increase the success of HIS implementations.

Performance Estimation of HEVC/h.265 Decoder in a Co-Design Flow with SADF-FSM Graphs

Multiprocessor System on Chip (MPSoC) technology presents an interesting solution to reduce the computational time of complex applications such as multimedia applications. Implementing the new High Efficiency Video Coding (HEVC/h.265) codec on the MPSoC architecture becomes an interesting research point that can reduce its algorithmic complexity and resolve the real time constraints. The implementation consists of a set of steps that compose the Co-design flow of an embedded system design process. One of the first anf key steps of a Co-design flow is the modeling phase which allows designers to make best architectural choices in order to meet user requirements and platform constraints. Multimedia applications such as HEVC decoder are complex applications that demand increasing degrees of agility and flexibility. These applications are usually modeling by dataflow techniques. Several extensions with several schedules techniques of dataflow model of computation have been proposed to support dynamic behavior changes while preserving static analyzability. In this paper, the HEVC/h.265 video decoder is modeled with SADF based FSM in order to solve problems of placing and scheduling this application on an embedded architecture. In the modeling step, a high-level performance analysis is performed to find an optimal balance between the decoding efficiency and the implementation cost, thereby reducing the complexity of the system. The case study in this case works with the HEVC/h.265 decoder that runs on the Xilinx Zedboard platform, which offers a real environment of experimentation.

The Prefiltering Techniques in Emotion Based Place Recommendation Derived by User Reviews

Context-aware recommendation systems attempt to address the challenge of identifying products or items that have the greatest chance of meeting user requirements by adapting to current contextual information. Many such systems have been developed in domains such as movies, books, and music, and emotion is a contextual parameter that has already been used in those fields. This paper focuses on the use of emotion as a contextual parameter in a tourist destination recommendation system. We developed a new corpus that incorporates the emotion parameter by employing semantic analysis techniques for destination recommendation. We review the effectiveness of incorporating emotion in a recommendation process using prefiltering techniques and show that the use of emotion as a contextual parameter for location recommendation in conjunction with collaborative filtering increases user satisfaction.

Optimization of Resource Allocation and User Association for Energy Efficiency in Future Wireless Networks

The user requirements in the future wireless networks are heterogeneous. The resource allocation and user association are crucial factors to meet user requirements and save energy. In this paper, the optimization of resource allocation and user association problem in both low data and high data requirement scenario is studied. In the low data requirement scenario, a network energy consumption minimization problem which considering the signal-to-interference-plus-noise ratio coverage constraints and jointly determines the optimal density of micro base stations (mBSs) and the optimal association bias is formulated. The closed-form solution of the optimal mBSs density and association bias is derived, respectively. Optimal association bias grows like $O( {\lambda _{u}^{ - ({\alpha }/{2})}} )$ as a function of user density $\lambda _{u}$ ( $\alpha $ is path loss factor) and the optimal density of mBSs is a linearly monotone increasing function of the user density. In the high data requirement scenario, a rate coverage maximization problem by adjusting the bandwidth allocation and user association are investigated. The relationship between bandwidth allocation and user association bias is obtained and a dynamic gradient iterative algorithm is used to solve the maximization problem. Simulation results verify the relevant derivations and demonstrate the user density and requirement have an important influence on the optimal resource allocation and optimal association bias.

A QoS Aware Cloud Service Composition Algorithm for Geo-Distributed Multi Cloud Domain

Publishing the cloud services on the internet has proven to be effective for cloud providers over the internet. To meet user requirements, services should be combined through service composition from multiple cloud domains. In this paper, we proposed an algorithm which composes best QoS aware services with minimal number of cloud combinations which is an NP-hard optimization problem. The proposed algorithm will select a cloud with more number of service files and then we applied PROMETHEE a multi criteria decision making method that selects the best service based on QoS criteria (i.e. Response time, Throughput, Availability, Successability, Price) from optimal cloud combinations. Our experimental results show that the algorithm provides better QoS services with minimal number of clouds by assessing previous benchmarks.

Understanding and Promoting Effective Engagement With Digital Behavior Change Interventions.

This paper is one in a series developed through a process of expert consensus to provide an overview of questions of current importance in research into engagement with digital behavior change interventions, identifying guidance based on research to date and priority topics for future research. The first part of this paper critically reflects on current approaches to conceptualizing and measuring engagement. Next, issues relevant to promoting effective engagement are discussed, including how best to tailor to individual needs and combine digital and human support. A key conclusion with regard to conceptualizing engagement is that it is important to understand the relationship between engagement with the digital intervention and the desired behavior change. This paper argues that it may be more valuable to establish and promote "effective engagement," rather than simply more engagement, with "effective engagement" defined empirically as sufficient engagement with the intervention to achieve intended outcomes. Appraisal of the value and limitations of methods of assessing different aspects of engagement highlights the need to identify valid and efficient combinations of measures to develop and test multidimensional models of engagement. The final section of the paper reflects on how interventions can be designed to fit the user and their specific needs and context. Despite many unresolved questions posed by novel and rapidly changing technologies, there is widespread consensus that successful intervention design demands a user-centered and iterative approach to development, using mixed methods and in-depth qualitative research to progressively refine the intervention to meet user requirements.

Mass Customizing Spare Parts Support Services Based on Response Time With Inventory Pooling Strategies

Spare parts support services have received increasing management attention due to the growing number of critical systems in many business sectors. In this paper, we examine an integrated system design approach to customize spare parts support services based on response time with inventory pooling strategies. To provide customized services that meet user requirements for spare part response time, we depart from the traditional spare parts management and develop a systematic approach to design service parts support services based on axiomatic design theory. In particular, we focus on pricing discrimination decisions in service parts contracts for two-tier users under a mechanism design framework. Distinguishing between users of next-day and same-day contracts for service parts operations, we further evaluate the effect of various inventory pool structures with reserve strategies through a simulation model for the objective of cost minimization. These analytical results of this new approach provide guidance for managers in customizing spare parts support services with the holistic consideration of pricing scheme, response time, and inventory policy.

General model for boring tool optimization

Optimizing a tool (and therefore those for boring) consist in improving its performance through maximizing the objective functions chosen by the designer and/or by user. In order to define and to implement the proposed objective functions, contribute numerous features and performance required by tool users. Incorporation of new features makes the cutting tool to be competitive in the market and to meet user requirements.

SEMANTIC SIMILARITY BASED CONTEXT-AWARE WEB SERVICE DISCOVERY USING NLP TECHNIQUES

Due to the high availability and also the distributed nature of published web services on the Web, efficient discovery and retrieval of relevant services that meet user requirements can be a challenging task. In this paper, we present a semantics based web service retrieval framework that uses natural language processing techniques to extract a service’s functional information. The extracted information is used to compute the similarity between any given service pair, for generating additional metadata for each service and for classifying the services based on their functional similarity. The framework also adds natural language querying capabilities for supporting exact and approximate matching of relevant services to a given user query. We present experimental results that show that the semantic analysis & automatic tagging effectively captured the inherent functional details of a service and also the similarity between different services. Also, a significant improvement in precision and recall was observed during Web service retrieval when compared to simple keyword matching search, using the natural language querying interface provided by the proposed framework.

Hybrid Gases Brownian Motion and Gravitational Search Algorithm for Resource Scheduling

Grid computing provides efficient platform for users to access geographically distributed resources. To meet the quality requirements and timing efficiency constraints imposed by tasks running on Grid, the resources should be allocated efficiently. The plane of recent use is beyond distribution and sharing. The distributed shared resources are useful only if its resources are scheduled efficiently. Grid scheduling is mapping of incoming task to available heterogeneous resources. Here scheduling is NP-hard, henceforth a pile of effort to develop an efficient algorithm is vital to reduce makespan. Metaheuristic algorithms are simplest methods to solve efficiently complex problems. Hybridize metaheuristic algorithm is advanced; trend to improve quality of solution. In this paper Hybrid GSA-PSO (Gravitational Search Algorithm – Particle Swarm Optimization Algorithm); Hybrid GBMO-GSA (Gases Brownian Motion Optimization -Gravitational Search Algorithm) algorithms are amalgamated to provide optimal solution for task scheduling problem in computational grid. Hybrid algorithm implementation shows a significant result in minimizing makespan to meet user requirements comparatively.

Evaluation of Parameters Importance in Cloud Service Selection Using Rough Sets

With the rapid development of the cloud computing technology, it has matured enough for a lot of individuals and organizations to move their work into the cloud. Correspondingly, a variety of cloud services are emerging. It is a key issue to assess the cloud services in order to help the cloud users select the most suitable cloud service and the cloud providers offer this service with the highest quality. The criteria parameters defining the cloud services are complex which lead to cloud service deviation. In this paper, we propose an assessment method of parameters importance in cloud services using rough set theory. The method can effectively compute the importance of cloud services parameters and sort them. On the one hand, the calculation can be used as the credible reference when users choose their appropriate cloud services. On the other hand, it can help cloud service providers to meet user requirements and enhance the user experience. The simulation results show the effectiveness of the method and its relevance in the cloud context.

A Look at the Evolution of Meteorological Satellites: Advancing Capabilities and Meeting User Requirements

Abstract In this paper, the authors offer their observations from more than 30 years of involvement in the evolution of the space-based meteorological remote sensing systems. Successes and issues from the past are recalled that established meteorological satellites into their current pivotal role. Evolution of imaging and sounding satellite systems from user requirements to affordable realizations is noted; some examples from recent U.S. and European experiences in the area of operational meteorological satellites are presented. The authors discuss the importance of the balanced roles of the three partners in satellite development (government, research, and industry), the need to develop full utilization of new satellite programs quickly during their early life, and a vision for global cooperation early in the planning stages of meteorological satellite missions. The authors offer suggestions that could foster expanded international collaboration on science and applications as well as expedite more satellite observations being pursued in a sustained manner.

Simulation-based design concept evaluation for ambulance patient compartments

To address the inadequacy of ambulance design standards, the Department of Homeland Security Science and Technology Directorate, the National Institute of Standards and Technology, the National Institute for Occupational Safety and Health, and BMT Designers and Planners have collaborated to develop new design standards for ambulance patient compartments. This paper presents a simulation-based approach to evaluate and guide improving patient compartment designs that conform to developed requirements for better performance and safety of ambulance users. Those requirements address hazards stemming from (1) the inability of providers to remain safely restrained while treating patients, and (2) the musculoskeletal damage from awkward body postures. An initial design was developed through the axiomatic design approach with inputs from stakeholders such as emergency medical service providers and ambulance manufacturers. The design was imported into a human task simulation tool. It was tested for performance to identify areas for further improvements, which resulted in a second design concept. This paper shows how computer simulation was used to evaluate the effectiveness of the two successive design concepts in enabling providers to perform a range of medical care tasks while remaining seated and restrained. We also evaluated the musculoskeletal effect of these designs on the providers. The results showed that using a simulation-based evaluation produced patient compartments that better meet user requirements when compared with traditional designs. This research produced a set of requirements and recommendations that we believe will lead to better design standards and guidelines for the next generation of ambulances.

Performance evaluation of composite Web services

Composite Web service architectures are demanding much guarantee on the Quality of Service (QoS) in order to meet user requirements. Performance evaluation of these architectures has become therefore a very challenging issue, as the task is very complex due to synchronization inside the orchestrat

Critical success factors for enterprise search

Enterprise search is now an essential tool for employees. In this article, I introduce 12 factors critical to the successful implementation and sustainability of quality search applications. Ranging from content quality, the position of search in an integrated information management strategy and adequate support for users, perhaps the most important is recognizing that the process of ensuring that search is meeting user requirements never comes to an end. That few organizations have made a considered commitment to ensuring that employees can find the information they need when they need it is highlighted by large-scale surveys of the state of enterprise search. The result is confusion and inefficiency whilst ideally users want to find information that they can trust to make decisions that count. This can be removed if the introduction of a search tool is planned within an organizational information management strategy and with a clear understanding of user needs.

The Simulation of Laser Cleaning of Magnetic Head with Different Temporal Pulses

Nowadays, hard disk drives (HDD) technology are being developed continuously in order to increase the capacity, and reduce the size of HDD to meet user requirements. To increase the capacity which is equivalent to increasing read/write ability, the flying clearance must be reduced. Current new HDD models show that the fly height is lower than 0.3 μm. If the height of a particle or contamination is higher than 0.3 μm, the magnetic head will scratch the magnetic disk surface. However the process of cleaning in the HDD industry cannot remove particles with size smaller than 0.3 μm [1]. Therefore laser cleaning is selected first because this method can remove small particles [2]. and it does not damage the magnetic head. This research compares the range of temperature needed for cleaning the magnetic head between two types of heat source’s profile. The technique used is the heat transfer by finite element: FEM[3]. This technique provides an important factor of the laser cleaning method that increases the efficiency of particle removal. It is also a non-destructive method for cleaning the surface of the magnetic head slider.

An efficient refinement algorithm for multi-label image annotation with correlation model

With the explosively rising popularity of photography devices, collections of personal digital images are growing rapidly both in number and size. There is an increasing desire to effectively index and search these images to meet user requirements. The content-based image retrieval (CBIR) system facilitates effective image indexing and retrieval according to image features. However, the semantic gap between the low-level visual features and high-level semantic concepts hinders further development. Image annotation is a solution intended to resolve the CBIR system inadequacies. However, there are two problems with the annotation. (1) It is very difficult to represent an image using only a few keywords; (2) the manual annotation process is very subjective, ambiguous, and incomplete. This paper focuses on refining image annotation to cluster the most representative keywords, as the annotations to image with a small semantic gap. We propose the Hierarchical_Twin Rings algorithm to refine the quality of annotations in order to close the well-known semantic gap problem. Moreover, we present another Centroid-based Convergence method of automatically assigning relevant multi-keywords to a user specified image which could greatly improve the retrieval accuracy and fast response requirement. The key contributions of our work areas follows: (1) Weintroduce the problem of the mining of representative image keywords as the annotation for image indexing and retrieval from a large set of image collection. (2) We use Bayesian framework to integrate the image and image annotation into a unifiedframework. (3) Our formulation allows one to refine the relevant annotations of an image and remove redundant annotations. We evaluated the performance of our algorithm by means of images collected from Flickr, the photo sharing website. Our experimental results show that the Hierarchical_Twin Rings algorithm is a realistic and effective method for multi-label image annotation.

Resource management and a Best Available Concept for aggregate sustainability

Abstract Aggregates are major constituents in construction, the global demand for which approaches some 22 billion tonnes per year. Some major challenges follow: firstly, the dependency on geological conditions and the availability of resources; secondly, the traffic, emissions and energy use connected with transportation; thirdly, the technology of utilizing resources with a variety of properties to meet user requirements; and finally, the need for increased awareness, particularly over issues like land-use conflicts, environmental impact of the aggregate and quarrying industry, and the need to make these activities sustainable. Aggregate standards have primarily been written by engineers, and engineers are first of all concerned with technical requirements. However, in the future, there will be a greater focus on environmental impact and sustainability. Geological resources are non-renewable, which, for example, can be seen in the rapid depletion of natural sand/gravel deposits. This causes increasing awareness along with environmental impact, conflicts of interest concerning land use, sustainability in mass balance and – not least – increasing transport distances required to get the materials to the places of use. The principle of a Best Available Concept (BAC) for aggregate production and use is introduced, working with four essential phases: inventory and planning; quarrying and production; use of aggregates; and reclamation of mined-out areas. In order to compare alternatives and calculate environmental and economic consequences of decisions, it is recommended that new LCC (Life Cycle Cost) and LCA (Life Cycle Assessment) tools are worked with, which have been recently developed in two EU (European Union) funded research projects.

An Approach of Learning Path Sequencing Based on Revised Bloom's Taxonomy and Domain Ontologies with the Use of Genetic Algorithms

Abstract With the rapid growth of information technology, we can observe an increase amount of e-learning systems. Thus, students and teachers are exposed to a wide variety of learning resources and learning objects. They need to choose courses, lessons, and their sequence in order to obtain desired knowledge. A technique for developing an individualized learning path that meets user requirements is described in this paper. The proposed approach utilizes ontology and a revised version of Bloom's taxonomy for the purpose of creating learning paths and a genetic algorithm for choosing the most appropriate.