Cloud computing (CC) has recently been receiving tremendous attention from the IT industry and academic researchers. CC leverages its unique services to cloud customers in a pay-as-you-go, anytime, anywhere manner. Cloud services provide dynamically scalable services through the Internet on demand. Therefore, service provisioning plays a key role in CC. The cloud customer must be able to select appropriate services according to his or her needs. Several approaches have been proposed to solve the service selection problem, including multicriteria decision analysis (MCDA). MCDA enables the user to choose from among a number of available choices. In this paper, we analyze the application of MCDA to service selection in CC. We identify and synthesize several MCDA techniques and provide a comprehensive analysis of this technology for general readers. In addition, we present a taxonomy derived from a survey of the current literature. Finally, we highlight several state-of-the-art practical aspects of MCDA implementation in cloud computing service selection. The contributions of this study are four-fold: (a) focusing on the state-of-the-art MCDA techniques, (b) highlighting the comparative analysis and suitability of several MCDA methods, (c) presenting a taxonomy through extensive literature review, and (d) analyzing and summarizing the cloud computing service selections in different scenarios.
Matched MeSH terms: Information Storage and Retrieval/methods*
The advent of web-based applications and services has created such diverse and voluminous web log data stored in web servers, proxy servers, client machines, or organizational databases. This paper attempts to investigate the effect of temporal attribute in relational rule mining for web log data. We incorporated the characteristics of time in the rule mining process and analysed the effect of various temporal parameters. The rules generated from temporal relational rule mining are then compared against the rules generated from the classical rule mining approach such as the Apriori and FP-Growth algorithms. The results showed that by incorporating the temporal attribute via time, the number of rules generated is subsequently smaller but is comparable in terms of quality.
Matched MeSH terms: Information Storage and Retrieval/methods*
The next generation of medical information system will integrate multimedia data to assist physicians in clinical decision-making, diagnoses, teaching, and research. This paper describes MIARS (Medical Image Annotation and Retrieval System). MIARS not only provides automatic annotation, but also supports text based as well as image based retrieval strategies, which play important roles in medical training, research, and diagnostics. The system utilizes three trained classifiers, which are trained using training images. The goal of these classifiers is to provide multi-level automatic annotation. Another main purpose of the MIARS system is to study image semantic retrieval strategy by which images can be retrieved according to different levels of annotation.
Matched MeSH terms: Information Storage and Retrieval*
Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques.
Matched MeSH terms: Information Storage and Retrieval*
Recently. recommender systems have become a very crucial application in the online market and e-commerce as users are often astounded by choices and preferences and they need help finding what the best they are looking for. Recommender systems have proven to overcome information overload issues in the retrieval of information, but still suffer from persistent problems related to cold-start and data sparsity. On the flip side, sentiment analysis technique has been known in translating text and expressing user preferences. It is often used to help online businesses to observe customers' feedbacks on their products as well as try to understand customer needs and preferences. However, the current solution for embedding traditional sentiment analysis in recommender solutions seems to have limitations when involving multiple domains. Therefore, an issue called domain sensitivity should be addressed. In this paper, a sentiment-based model with contextual information for recommender system was proposed. A novel solution for domain sensitivity was proposed by applying a contextual information sentiment-based model for recommender systems. In evaluating the contributions of contextual information in sentiment-based recommendations, experiments were divided into standard rating model, standard sentiment model and contextual information model. Results showed that the proposed contextual information sentiment-based model illustrates better performance as compared to the traditional collaborative filtering approach.
Matched MeSH terms: Information Storage and Retrieval/statistics & numerical data*
Wherever an impact mark is found, either on the surface or on the recovered projectile, it is important for forensic investigators to extract useful information in solving shooting-related cases. This article reviews a collection of works on examination of impact marks upon striking of projectiles on inanimate objects, emphasizing on the retrievable information from a shooting scene and their forensic significance in shooting event reconstruction. Literature suggested that impact marks on target surfaces and the degree of deformation on striking projectiles vary according to different combinations of ammunition and surface materials. It was noted that conditions in real-case scenarios further differed unpredictably in comparison with controlled studies, where forensic investigation should be treated as case-specific basis. Furthermore, the way forensic science is researched and applied operationally has to be reconsidered to reduce the gap via translational approach for more effective use of forensic evidence.
Matched MeSH terms: Information Storage and Retrieval
Mobile users have the capability of accessing information anywhere at any time with the introduction of mobile browsers and mobile web search. However, the current mobile browsers are implemented without considering the characteristics of mobile searches. As a result, mobile users need to devote time and effort in order to retrieve relevant information from the web in mobile devices. On the other hand, mobile users often request information related to their surroundings, which is also known as context. This recognizes the importance of including context in information retrieval. Besides, the availability of the embedded sensors in mobile devices has supported the recognition of context. In this study, the context acquisition and utilization for mobile information retrieval are proposed. The “just-in-time” approach is exploited in which the information that is relevant to a user is retrieved without the user requesting it. This will reduce the mobile user’s effort, time and interaction when retrieving information in mobile devices. In this paper, the context dimensions and context model are presented. Simple experiments are shown where user context is predicted using the context model.
Matched MeSH terms: Information Storage and Retrieval
Natural language interfaces to ontologies allow users to query the system using natural language queries.
These systems take natural language query as input and transform it to formal query language equivalent
to retrieve the desired information from ontologies. The existing natural language interfaces to ontologies
offer support for handling negation queries; however, they offer limited support for dealing with them.
This paper proposes a negation query handling engine which can handle relatively complex natural
language queries than the existing systems. The proposed engine effectively understands the intent of
the user query on the basis of a sophisticated algorithm, which is governed by a set of techniques and
transformation rules. The proposed engine was evaluated using the Mooney data set and AquaLog dataset,
and it manifested encouraging results.
Matched MeSH terms: Information Storage and Retrieval
Data transmission in field works especially that is related to industry, gas and chemical is paramount importance to ensure data accuracy and delivery time. A development of wireless detector system for remote data acquisition to be applied in conducting fieldwork in industry is described in this paper. A wireless communication which is applied in the project development is a viable and cost-effective method of transmitting data from the detector to the laptop on the site to facilitate data storage and analysis automatically, which can be used in various applications such as column scanning. The project involves hardware design for the detector and electronics parts besides programming for control board and user interface. A prototype of a wireless gamma scintillation detector is developed with capabilities of transmitting data to computer via radio frequency (RF) and recording the data within the 433MHz band at baud rate of 19200.
Matched MeSH terms: Information Storage and Retrieval
The rapid development of open source developmental boards incorporating microcontrollers on printed circuit boards has offered many alternatives in creating feasible, low cost indoor environment monitoring and controlling platforms. Data are collected and stored in predetermined locations throughout a series of communication activities between a network of active sensors and their processing units. However, the issue of data precision and accuracy are of real concern for generating baseline information. Therefore, with that in mind, the purpose of this paper is to accentuate an insightful trend of retrieving indoor environment data (temperature and relative humidity) for an office building in a hot and humid climate condition. The indoor parameters were monitored using a combination of a single board microcontroller with an active sensor with well calibrated thermal microclimate devices. Accordingly, it was found that proactive adjustment can be conducted in order to minimize waste.
Matched MeSH terms: Information Storage and Retrieval
In a correspondence to BMC Public Health, Dunn et al. (Dunn SE, Reed J and Neumann C. BMC Public Health (n.d)) respond to our review on the occurrence of unintentional, acute pesticide poisoning (UAPP). Based on a systematic review and further data sources we estimated that about 385 million cases of UAPP occur annually world-wide including around 11,000 fatalities (Boedeker W. et al. BMC Public Health:1875, 2020).
Matched MeSH terms: Information Storage and Retrieval
Network forensics enables investigation and identification of network attacks through the retrieved digital content. The proliferation of smartphones and the cost-effective universal data access through cloud has made Mobile Cloud Computing (MCC) a congenital target for network attacks. However, confines in carrying out forensics in MCC is interrelated with the autonomous cloud hosting companies and their policies for restricted access to the digital content in the back-end cloud platforms. It implies that existing Network Forensic Frameworks (NFFs) have limited impact in the MCC paradigm. To this end, we qualitatively analyze the adaptability of existing NFFs when applied to the MCC. Explicitly, the fundamental mechanisms of NFFs are highlighted and then analyzed using the most relevant parameters. A classification is proposed to help understand the anatomy of existing NFFs. Subsequently, a comparison is given that explores the functional similarities and deviations among NFFs. The paper concludes by discussing research challenges for progressive network forensics in MCC.
Matched MeSH terms: Information Storage and Retrieval/methods*
Due to the proliferation of handheld mobile devices, multimedia applications like Voice over IP (VoIP), video conferencing, network music, and online gaming are gaining popularity in recent years. These applications are well known to be delay sensitive and resource demanding. The mobility of mobile devices, running these applications, across different networks causes delay and service disruption. Mobile IPv6 was proposed to provide mobility support to IPv6-based mobile nodes for continuous communication when they roam across different networks. However, the Route Optimization procedure in Mobile IPv6 involves the verification of mobile node's reachability at the home address and at the care-of address (home test and care-of test) that results in higher handover delays and signalling overhead. This paper presents an enhanced procedure, time-based one-time password Route Optimization (TOTP-RO), for Mobile IPv6 Route Optimization that uses the concepts of shared secret Token, time based one-time password (TOTP) along with verification of the mobile node via direct communication and maintaining the status of correspondent node's compatibility. The TOTP-RO was implemented in network simulator (NS-2) and an analytical analysis was also made. Analysis showed that TOTP-RO has lower handover delays, packet loss, and signalling overhead with an increased level of security as compared to the standard Mobile IPv6's Return-Routability-based Route Optimization (RR-RO).
Matched MeSH terms: Information Storage and Retrieval/methods*
This paper presents a case for an intelligent agent based framework for knowledge discovery in a distributed healthcare environment comprising multiple heterogeneous healthcare data repositories. Data-mediated knowledge discovery, especially from multiple heterogeneous data resources, is a tedious process and imposes significant operational constraints on end-users. We demonstrate that autonomous, reactive and proactive intelligent agents provide an opportunity to generate end-user oriented, packaged, value-added decision-support/strategic planning services for healthcare professionals, manages and policy makers, without the need for a priori technical knowledge. Since effective healthcare is grounded in good communication, experience sharing, continuous learning and proactive actions, we use intelligent agents to implement an Agent based Data Mining Infostructure that provides a suite of healthcare-oriented decision-support/strategic planning services.
Matched MeSH terms: Information Storage and Retrieval/methods*
Cloud computing (CC) is a magnificent service-based delivery with gigantic computer processing power and data storage across connected communications channels. It imparted overwhelming technological impetus in the internet (web) mediated IT industry, where users can easily share private data for further analysis and mining. Furthermore, user affable CC services enable to deploy sundry applications economically. Meanwhile, simple data sharing impelled various phishing attacks and malware assisted security threats. Some privacy sensitive applications like health services on cloud that are built with several economic and operational benefits necessitate enhanced security. Thus, absolute cyberspace security and mitigation against phishing blitz became mandatory to protect overall data privacy. Typically, diverse applications datasets are anonymized with better privacy to owners without providing all secrecy requirements to the newly added records. Some proposed techniques emphasized this issue by re-anonymizing the datasets from the scratch. The utmost privacy protection over incremental datasets on CC is far from being achieved. Certainly, the distribution of huge datasets volume across multiple storage nodes limits the privacy preservation. In this view, we propose a new anonymization technique to attain better privacy protection with high data utility over distributed and incremental datasets on CC. The proficiency of data privacy preservation and improved confidentiality requirements is demonstrated through performance evaluation.
Matched MeSH terms: Information Storage and Retrieval*
This paper presents the evaluation of integrated partial match query in Geographic Information Retrieval (GIR). To facilitate the evaluation, Kuala Lumpur tourist related data is used as test collection and is stored in SuperWeb, a map server. Then the map server is customized to enhance its query capability to recognize word in partial or case sensitive between layers of spatial data. Query keyword is tested using the system and results are evaluated using experiments on sample data. Findings show that integrated partial match query provides more flexibility to tourist in determining search results.
Matched MeSH terms: Information Storage and Retrieval
Cloud computing is currently emerging as an ever-changing, growing paradigm that models "everything-as-a-service." Virtualised physical resources, infrastructure, and applications are supplied by service provisioning in the cloud. The evolution in the adoption of cloud computing is driven by clear and distinct promising features for both cloud users and cloud providers. However, the increasing number of cloud providers and the variety of service offerings have made it difficult for the customers to choose the best services. By employing successful service provisioning, the essential services required by customers, such as agility and availability, pricing, security and trust, and user metrics can be guaranteed by service provisioning. Hence, continuous service provisioning that satisfies the user requirements is a mandatory feature for the cloud user and vitally important in cloud computing service offerings. Therefore, we aim to review the state-of-the-art service provisioning objectives, essential services, topologies, user requirements, necessary metrics, and pricing mechanisms. We synthesize and summarize different provision techniques, approaches, and models through a comprehensive literature review. A thematic taxonomy of cloud service provisioning is presented after the systematic review. Finally, future research directions and open research issues are identified.
Matched MeSH terms: Information Storage and Retrieval/methods*; Information Storage and Retrieval/standards