Data Gathering System Research Articles

Design and deployment of a smart system for data gathering in aquaculture tanks using wireless sensor networks

SummaryThe design of monitoring systems for marine areas has increased in the last years. One of the many advantages of wireless sensor networks is the quick process in data acquisition. The information from sensors can be processed, stored, and transmitted using protocols efficiently designed to energy saving and establishing the fastest routes. The processing and storing of data can be very useful for taking intelligent decisions for improving the water quality. The monitoring of water exchange in aquaculture tanks is very important to monitor the fish welfare. Thus, this paper presents the design, deployment, and test of a smart data gathering system for monitoring several parameters in aquaculture tanks using a wireless sensor network. The system based on a server is able to request and collect data from several nodes and store them in a database. This information can be postprocessed to take efficient decisions. The paper also presents the design of a conductivity sensor and a level sensor. These sensors are installed in several aquaculture tanks. The system was implemented using Flyport modules. Finally, the data gathering system was tested in terms of consumed bandwidth and the delay Transmission Control Protocol (TCP) packets delivering data from the sensors.

Criticalities on highway maintenance yards: some suggestions to improve the effectiveness of OS&H supervision/inspection activities

Research work results on Occupational Safety and Health -OS&H- aspects of highway maintenance yards in normal operative conditions and special situations - typically potential interferences from heavy traffic - stressed the diversification of yards typologies and criticalities. The European Directive 92/57/EEC on the implementation of minimum Safety and Health requirements at temporary or mobile construction sites concentrates on the improvement of Risk Assessment and Management from the very first steps of the design, and introduces coordinators charged of a safe project preparation and of the execution phase supervising. In particular, in the case of highway maintenance yards, the Coordinator for and health matters at the project execution stage should manage both routine situations, and situations requiring high expertise and capacity of judgment. In such complex scenarios, Safety inspection activities become a demanding task also in terms of time and resources for both the Company and the National Inspectorate supervisors. The paper discusses an original approach for the optimization of supervision / inspection activities, based on the appropriate use of Fellow Supervisors to support the Coordinator in the routine activities, with the added benefit of an increased presence of safety people at the yard. The setup of an appropriate data gathering, recording and mining system, organized in interlinked cards in logical sequence, contributes to the efficiency and thoroughness of the work of the both the Coordinator and the Fellow Supervisors. The results of ex post tests on a real case -input data provided by the Prosecutor Office which proposed the study- can be considered significant.

Applied Computing in Civil Engineering

Applied Computing in Civil Engineering Behnam Neyestani Introduction The software houses have attempted to provide design software catering for the variety of infrastructure design fields in an integrated manner. However, general purpose software may be used in the same manner at a fraction of the cost of design software. When planning the construction phase, various project management methods are used to estimate factors such as cost, schedule and resourcing. Different software packages rely on different formulas and theories as the basis for these calculations. Consulting engineers also take advantage of the insight software can provide as far as crossing services are concerned. A road design may have to accommodate the presence of underground pipes for example. Civil designer is an example of a design package which forms an integrated data gathering, drawing, surface modeling and design system for civil engineering infrastructure. Computer-aided design (CAD) Computer-aided design (CAD) is the use of computer systems to assist in the creation, modification, analysis, or optimization of a design. CAD software is used to increase the productivity of the designer, improve the quality of design, improve communications through documentation, and to create a database for manufacturing. CAD output is often in the form of electronic files for print, machining, or other manufacturing operations.

Spatio Temporal Error Adaptation Model (STEAM) for Energy Efficient Wireless Data Gathering

Redundant Data communication greatly downgrades the performance and reliability of Wireless Sensor Network's (WSN). Spatial similarity and temporal similarity are the intrinsic features of sensory data. By reducing this spatio-temporal data redundancy, large amount of residual energy and bandwidth can be conserved. Very few methods use both spatial and temporal correlation to reduce data redundancy, where the system's error threshold is divided between spatial and temporal error thresholds that are fixed throughout the network's life span. In Spatio-Temporal Error Adaptation Model (STEAM), the spatio-temporal correlation between sensory data is exploited towards data reduction. The spatial redundancy is reduced by a data aware clustering and temporal redundancy is reduced by model based prediction approach. In the proposed work, the proportion of spatial and temporal error thresholds on total error is adapted based on data dynamics and spatial pattern changes of the network. The proposed work decreases considerable amount of data communication, while maintaining the data accuracy within user defined error tolerance. The proposed work follows a distributed approach, hence it is highly scalable. Since the work adapts the threshold based on network parameters, the performance is improved on diverse network conditions. The work attains up to 89% communication reduction in wireless data gathering system with an error tolerance of 0.4°C on collected data.

The Annual Report Algorithm: Retrieval of Financial Statements and Extraction of Textual Information

U.S. corporations are obligated to file financial statements with the U.S. Securities and Exchange Commission (SEC). The SEC's Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system containing millions of financial statements is one of the most important sources of corporate information available. The paper illustrates which financial statements are publicly available by analyzing the entire SEC EDGAR database since its implementation in 1993. It shows how to retrieve financial statements in a fast and efficient way from EDGAR. The key contribution however is a platform-independent algorithm for business and research purposes designed to extract textual information embedded in financial statements. The dynamic extraction algorithm capable of identifying structural changes within financial statements is applied to more than 180,000 annual reports on Form 10-K filed with the SEC for descriptive statistics and validation purposes.

A delay-aware schedule method for distributed information fusion with elastic and inelastic traffic

Information fusion is an efficient way to detect the specified events and extract useful information, especially in the context of big data. As a large-scale data-gathering system, Internet of Things (IoT) has the traffic with the mixed timing characteristics. The real-time observations with various delay constraints and the non-real-time observations are needed in information fusion. In order to guarantee the performance of Distributed Information Fusion (DIF), the paper focuses on the communication mechanism from the perspective of real-time delivery of sensing data. An online scheduling algorithm and its distributed implementation, named Delay-Guaranteed CSMA, are proposed. Both the timing constraints and the historical transmission statistics of sensors are taking into consideration. The simulation results have shown that the proposed policy achieves good delay-guaranteed satisfaction. The goal of real-time data delivery for distributed information fusion is achieved.

EDGAR, the Electronic Data Gathering, Analysis, and Retrieval system

EDGAR, the Electronic Data Gathering, Analysis, and Retrieval system

SENSE tool: easy-to-use web-based tool to calculate food product environmental impact

The purpose of the European SENSE project was to define an integral system to assess and communicate the environmental impacts of food products and to develop a web-based tool for Small and Medium size Enterprises (SMEs). The tool has been tested in salmon, beef-and-dairy, and fruit juice production sectors. The SENSE project has evaluated several existing methodologies for environmental impact assessment over the life cycle including also social aspects, in order to deliver a new integral system for the environmental and social assessment of agricultural and aquaculture food products. The system includes a standardization of a data gathering system, a selection of relevant key environmental performance indicators for food supply chains and a common methodology to perform simplified life cycle impact assessment. The results are based on collected information on the use of resources and emissions generated along the supply chain of food or drink products. The main result is a web-based software tool that is based on a summation of the partial impacts of the different steps in food supply chains. In this software, different actors in the supply chain can enter their own data and link them to the data of other companies. The results obtained in the tool could be used for at least six different approaches: (i) environmental impact assessment of the product, (ii) food chain hot spot identification, (iii) comparison of hypothetical or real improvement scenarios, (iv) assessment of the environmental impact development over the years, (v) benchmarking opportunity for the companies, and (vi) a business to business communication strategy. The scientific robustness of the tool has been tested comparing the obtained results with the same analysis with commercial software. The SENSE tool is a simplified tool designed for food and drink SMEs to assess their sustainability on their own. This cannot be fully compared to a complete LCA study. The testing with SMEs showed that they need additional support for filling in the questionnaires correctly and interpret the results. The simplified evaluation of environmental impacts based on a life cycle approach could lead to benefits to SMEs within the food industry. The future application and development of the tool will be focused on adapting the tool to the Product Environmental Footprint initiative requirements and self-assessment opportunities.

Data transparency driving frontline engagement and improving outcomes

The Affordable Care Act has increased accountability in health spending, in particular, a shift from the traditional fee-for-service model to an outcomes-based, metric driven model of reimbursement. In the US, Value Based Purchasing is established as the main pay-for-performance quality improvement mechanism. Historically, frontline care providers have not had access to “live” data on measures of quality and the practices that drive them. “Engagement” was limited to responding after the fact to top-down analysis and directives. Already burdened frontline care providers would inherit responsibility for data gathering systems and improvement programs that increased workload without necessarily increasing a sense of ownership, commitment or engagement.

Light‐weight group signatures with time‐bound membership

AbstractThis paper presents a novel privacy‐preserving cryptographic protocol for secure many‐to‐one communication systems, for example, data collection systems, data gathering systems, vehicular networks, smart‐grids, and so on. The proposed solution provides message authenticity, integrity, and non‐repudiation, while message senders are anonymous and untraceable. The protocol is based on group signatures with a time‐bound membership. The protocol is designed to achieve efficiency on the client side where restricted devices are usually employed. On the other hand, the verification of many messages is efficient as well. Common group signature schemes offer the verification phase that needs some pairing operations and employs a long revocation list. Generally, the revocation list grows until scheme parameters and keys are recomputed. However, the reinitialization of all keys and parameters is not practical in large‐scale communication systems. By applying the optimization techniques on the group signature scheme, the verification phase becomes more efficient, and the expiration of group member secret keys naturally reduces the length of a revocation list. In addition to the full cryptographic description, we implement the proposed protocol and outline the performance results. Copyright © 2015 John Wiley & Sons, Ltd.

New developments in digital dermatitis control

Recent work has provided a greater understanding of the etiopathogenesis of digital dermatitis (DD) infection within cattle populations. With enhanced lesion scoring and an understanding of the transitioning between lesion stages, coupled with improved data-gathering systems, we now understand the significance of the chronic stages of the disease in herd-infection dynamics. Herd control of DD must begin during the heifer-rearing period. Breeding resistant animals and use of in-feed organic trace mineral supplements are coupled with active surveillance for early acute stages of the disease. Combined with strategic foot bathing and hoof-trimming, when fully implemented on a farm, these strategies can reduce the incidence of the disease and provide a sustainable solution to this troublesome problem.

Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks

Wireless sensor networks are engaged in various data gathering applications. The major bottleneck in wireless data gathering systems is the finite energy of sensor nodes. By conserving the on board energy, the life span of wireless sensor network can be well extended. Data communication being the dominant energy consuming activity of wireless sensor network, data reduction can serve better in conserving the nodal energy. Spatial and temporal correlation among the sensor data is exploited to reduce the data communications. Data similar cluster formation is an effective way to exploit spatial correlation among the neighboring sensors. By sending only a subset of data and estimate the rest using this subset is the contemporary way of exploiting temporal correlation. In Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks, we construct data similar iso-clusters with minimal communication overhead. The intra-cluster communication is reduced using adaptive-normalized least mean squares based dual prediction framework. The cluster head reduces the inter-cluster data payload using a lossless compressive forwarding technique. The proposed work achieves significant data reduction in both the intra-cluster and the inter-cluster communications, with the optimal data accuracy of collected data.

Collective Prediction Exploiting Spatio Temporal Correlation (CoPeST) for Energy Efficient Wireless Sensor networks

Data redundancy has high impact on Wireless Sensor Network`s (WSN) performance and reliability. Spatial and temporal similarity is an inherent property of sensory data. By reducing this spatio-temporal data redundancy, substantial amount of nodal energy and bandwidth can be conserved. Most of the data gathering approaches use either temporal correlation or spatial correlation to minimize data redundancy. In Collective Prediction exploiting Spatio Temporal correlation (CoPeST), we exploit both the spatial and temporal correlation between sensory data. In the proposed work, the spatial redundancy of sensor data is reduced by similarity based sub clustering, where closely correlated sensor nodes are represented by a single representative node. The temporal redundancy is reduced by model based prediction approach, where only a subset of sensor data is transmitted and the rest is predicted. The proposed work reduces substantial amount of energy expensive communication, while maintaining the data within user define error threshold. Being a distributed approach, the proposed work is highly scalable. The work achieves up to 65% data reduction in a periodical data gathering system with an error tolerance of 0.6°C on collected data.

Examining trafficking statistics regarding Brazilian victims in Spain and Portugal

Despite a number of policy decisions being based upon the premise that there is a large flow of Brazilian trafficking victims to Spain and Portugal, existing statistics are not reliable enough to confirm this assertion. Due to a number of reasons, including problematic, incompatible and evolving definitions, as well as fragmented data gathering systems, the available human trafficking statistics about Brazilian trafficking victims in the Iberian Peninsula are internally and cross-comparatively inconsistent. The widely varying scenarios presented by the available numbers compromise the individual and collective responses to the phenomenon. Although a number of possible solutions can be proposed to improve the data collection, it is unlikely that the systems will change significantly as long as the figures being presented continue to support the agendas defended by the countries in question.

Doping through supplement use: a review of the available empirical data.

The potential for supplement use to result in doping infringements is likely to be of concern for anyone involved in sports nutrition. The available data indicates that between 40-70% of athletes use supplements, and that between 10-15% of supplements may contain prohibited substances. Such data indicates that there is a considerable risk of accidental or inadvertent doping through using supplements. Accordingly, this paper sets out to provide an overview of the currently available empirical evidence of accidental doping by supplement use. In carrying out this task, the authors refer to press releases and proxy measures associated with nutritional supplement use, as well as statistical data on supplement contamination rates and doping infractions. A number of different indications as to the percentage of doping cases that might be attributed to supplement use are presented, ranging from 6.4% to 8.8%. Such percentages are not comparable; instead they are provided as indications as to how difficult it is to ascertain or estimate the scale of this problem. Although some forms of estimation can be made, it is suggested that it is currently not possible to quantify the scale of the problem. By way of conclusion, it is argued that antidoping regulators may wish to review current data gathering and information provision systems so that the problem of inadvertent doping can be more directly assessed as a factor in sports doping overall.

Retrieving Financial Information in XBRL on the Next-Generation Edgar

The Securities and Exchange Commission (SEC) has upgraded the old Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system, to the Interactive Data Electronic Applications (IDEA) platform, or the Next-Generation EDGAR (New EDGAR). In January 2009, the SEC issued its final mandate for XBRL adoption and the conversion target dates for all firms. This conversion enables users to retrieve listed companies’ financial statement information at both document level and data element level. This paper reviews the basic concepts of XBRL, reports the current compliance status of the SEC XBRL conversion mandate. The main contribution of this article is to demonstrate how to retrieve data from the New EDGAR and process them with Microsoft Excel 2013.

Transport Forecasting in Slovak Regions

The transport modelling represents one of the main line of the transport engineering. The transport model of observed area is perceived in its final step. The related professions (traffic planners, ecologists, municipality officials …) need specific data such as traffic volumes, modal split, travel time, travel cost … Output data has to be exported to the different time intervals. A transport engineer must cover whole process of transport model creating. Generally it is a long term process. The transport modelers must detailed specify the conditions which are needs to transport model using. The output data must be calibrated and validated. Mentioned two steps are oftentimes underestimated mainly for financial reasons. The transport models are classified by the scale modeled data. The practical application of the transport forecast theory is not easy. The transport engineer must walk through the principled problems. The article is aimed to the description of real two transport models of bordering Slovak regions. Main part of the article describe the transport data gathering system and its implementation in to the transport forecast calculation (calibration, validation).

Nurse prescribers' experiences of recording prescribing data to the Minimum Data Set in Ireland.

This study aimed to investigate and enhance understanding of nurse prescribers' experiences of working with the Irish national data gathering system for nurse prescribing: the Minimum Data Set (MDS) in Irish clinical practice. A phenomenological research design was used, collecting data via semi-structured interviews using a purposive sample of practising nurse prescribers. The study identified three recurrent themes: communication, workload/time, and attitudes. The MDS produces only standard national reports (lists) on nurse/midwife prescribing that cannot be utilised efficiently to inform practice or understand health service needs. Nurses have reacted to this situation and evaluate the MDS in the context of their clinical setting, identifying conflicting demands and expectations and an increased workload as factors that correlated negatively with the process of collecting nurse prescribing data. Consultation and evaluation is required, particularly to analyse the nurse prescribers' views of collecting data and working with the MDS in the context of the major adjustments that the Irish health service has experienced over the past 6 years.

SpartanRPC

We describe SpartanRPC, a secure middleware technology that supports cooperation between distinct security domains in wireless sensor networks. SpartanRPC extends nesC to provide a link-layer remote procedure call (RPC) mechanism, along with an enhancement of configuration wirings that allow specification of remote, dynamic endpoints. RPC invocation is secured via an authorization logic that enables servers to specify access policies and requires clients to prove authorization. This mechanism is implemented using a combination of symmetric and public key cryptography. We report on benchmark testing of a prototype implementation and on an application of the framework that supports secure collaborative use and administration of an existing WSN data-gathering system.

Crowdseeding in Eastern Congo

Poor-quality data about conflict events can hinder humanitarian responses and bias academic research. There is increasing recognition of the role that new information technologies can play in producing more reliable data faster. We piloted a novel data-gathering system in the Democratic Republic of Congo in which villagers in a set of randomly selected communities report on events in real time via short message service. We first describe the data and assess its reliability. We then examine the usefulness of such “crowdseeded” data in two ways. First, we implement a downstream experiment on aid and conflict and find evidence that aid can lead to fewer conflict events. Second, we examine conflict diffusion in Eastern Congo and find evidence that key dynamics operate at very micro levels. Both applications highlight the benefit of collecting conflict data via cell phones in real time.