Effective Information Management Research Articles

FEACS: A fog enhanced expressible access control scheme with secure services delegation among carers in E-health systems

The quality of health care delivery is declining with the high cost of health services. This is as a result of the delay in obtaining necessary health information from patients and/or ineffective management of health information. To avert this, a new paradigm called e-health, which fuses wearable medical devices or non-invasive measuring devices with cloud computing has been adopted to improve health care delivery. This allows medical centers and health carers to function more competently and also for patients to obtain better treatments. The adoption of wearable medical devices and cloud computing provides easy and instant access to a large volume of health information. However, it introduces some information management bottlenecks, security, and privacy challenges. In this paper, we propose a security scheme that provides effective health information management and secure access to patients’ health information in an e-health system. The approach also supports cooperative health care delivery among carers through effective information sharing techniques. A two-layer security approach is adopted using the symmetric key and modified ciphertext-policy attribute-based encryption to provide fine-grained access control, time-based attribute revocation, and cooperative health service delegation among carers. Also, fog devices are adopted to create hierarchical storage for effective health information management.

Effective Data Selection and Management Method Based on Dynamic Regulation in Opportunistic Social Networks

5G has brought a huge increase in data, and the number of nodes and types of messages are becoming more and more complex. The Internet of things has become a large and complex network. More and more devices can be used as nodes in opportunistic social networks. The attitude of nodes to messages is different and changeable. However, in the previous opportunistic network algorithm and mass data transmission environment, due to the lack of effective information selection and management means, it was easy to lead to transmission delay and high consumption. Therefore, we propose Effective Data Selection and Management (EDSM). EDSM uses the current state of the node as the basis for forwarding messages. When the cache space is insufficient, EDSM will perform cache replacement based on the message cache value and delete the information with the lowest cache value. Simulation results show that the algorithm has good performance in terms of delivery rate and latency.

Information management hits and misses in the COVID19 emergency in Brazil

Brazilian Federal Government created an emergency aid to face the COVID19 emergency. This aid provides monthly payments to low-income or unemployed citizens, informal workers, or individual micro-entrepreneurs. An intricate set of criteria made too complex the identification of all citizens eligible for emergency aid, considering there is no an integrated database to which they could apply these criteria. Consequently, lots of people who fulfilled the criteria were not able to receive the aid, and lots of people who were not supposed to get it ended up receiving it. In this context, the goal of this opinion paper is to discuss the process effectiveness and which issues related to information management hindered the positive program impact. Additionally, a less complex but relevant case of Rio Grande do Sul State is discussed. Both cases – the Federal Government and the state government – show the importance of effective information management to face very demanding situations and avoid the high social price to be paid by those who need this aid the most.

Assessing future distribution, suitability of corridors and efficiency of protected areas to conserve vulnerable ungulates under climate change

AbstractAimCentral part of Iran harbours populations of wild ungulates that are threatened or extinct over large parts of the region, and are likely to be impacted by climate change. In this study, we predicted the impact of climate change on the distribution of three vulnerable ungulates in central Iran. We then evaluated future suitability of corridors connecting the protected areas for movement of the ungulates in response to climate change.LocationCentral Iran.MethodsImpact of climate change on distribution of goitered gazelle (Gazella subgutturosa), wild sheep (Ovis spp) and wild goat (Capra aegagrus) was predicted adapting an ensemble modelling approach and under the RCP 8.5 emission scenario. We then used CIRCUITSCAPE software with current and future distribution maps to identify corridors for movement of the three ungulates, and evaluate likely changes in their suitability under climate change.ResultsOur results revealed that climate change might result in loss of 55%, 69% and 76% of suitable habitats for goitered gazelle, wild sheep and wild goat by 2070, respectively. These losses also resulted in some protected areas to become unsuitable for the ungulates. However, we identified key protected areas with the potential for future protection of these ungulates. For the three species, we also identified corridors which would persist into the future, allowing the impacted populations to move in response to climate change.Main conclusionsConservation of ungulate populations in Iran mainly depends on the protected areas. To maintain the role of the protected areas in conserving these mammals under climate change, we recommend the incorporation of their potential future distribution into conservation plans, increasing protection status of the key protected areas, and maintain critical corridors. In this regard, combining results of distribution and connectivity models provides useful information for effective management of these ungulates in the future.

The embassy of Francisco Bernardo de Quirós at The Hague: Spanish diplomatic praxis during the succession crisis*

Abstract This article analyses the Spanish diplomatic network c.1700 through a study of the correspondence generated by the embassy of The Hague held in Spanish and Belgian archives. It demonstrates how the monarchy possessed procedures and resources for the effective management of external information, allowing it to integrate and distribute the knowledge necessary for decision-making. The article closely examines the practices of ministers when handling state matters and reacting to crises, such as that of the Spanish succession.

Information credibility, disaster risk perception and evacuation willingness of rural households in China

Information credibility is important for effective disaster communication, and its strength affects the evacuation willingness of residents. However, few reports have studied the correlation of information credibility and disaster risk perception with residents’ willingness to evacuate during earthquake threats. Using survey data of 327 rural households located in four counties within earthquake-affected areas in Sichuan Province, this study systematically analyzed the credibility of public and private information about rural households, disaster risk perception and residents’ evacuation willingness. After creating an ordinary least square regression model (OLS) to investigate the correlations of the above factors, the results showed that: (1) Both positive public information and negative private information were positively correlated with residents’ evacuation willingness, and negative public information and positive private information were negatively correlated with residents’ evacuation willingness; (2) the perceived severity of disaster was significantly correlated with residents’ evacuation willingness, and the perceived probability of disaster was not significantly correlated with residents’ evacuation willingness; and (3) both positive and negative public information indirectly affected residents’ evacuation willingness through the perception of disaster severity. This study contributed to our understanding of the correlation of information credibility and disaster risk perception with evacuation willingness and provided important information for effective communication and disaster risk management.

The public health care system and primary care services in Saudi Arabia: a system in transition.

Saudi Arabia has invested heavily in its health care system by establishing health care infrastructures to improve health of the nation. However, it remains to be seen whether it is efficient and effective in providing health care services needed. Primary health care, which is the basis of universal health coverage, needs to be assessed on its performance, challenges and future opportunities to serve the Saudi Arabian population. This review aimed to identify challenges within the Saudi Arabian health care system with a focus on primary health care services, and to analyse the interrelated factors in order to suggest remedial reforms to further strengthen and improve the health care system. A narrative review of previous studies and governmental reports was undertaken to extract, analyse, synthesize and report the findings. The review found a number of key areas for improvement in the primary health care system. These areas include: the scope, structure, infrastructure, financing, increased demand, increased costs and workforce capacity. Other critical challenges include inequitable access to health services, quality and safety of services, the growing burden of chronic diseases, lack of an effective information system, management and leadership issues, and gaps in the referral system. The Saudi Arabian health care system needs comprehensive reform with a focus on primary health care.

IoT device location information storage system based on blockchain

In recent years, with the development of technologies such as the Internet, sensors and RFID, the application of the Internet of Things in various industries has deepened, resulting in a large number of new technologies, new products and new applications. There are a large number of devices in the Internet of Things. The interconnection of location information of these devices brings convenience to people’s lives, and there is also the problem of leaking location privacy. Therefore, effective management of the location information of the device is crucial to the development of the Internet of Things. At present, in the aspect of device location information supervision, the traditional encryption method or the location information is generally blurred, which improves the security of the location information, but also reduces the applicability of the location information. Aiming at these problems, based on the research on the equipment positioning of the Internet of Things and the key technologies of the blockchain, this paper designs a location chain storage system for IoT devices based on blockchain, and experiments the system. The results show that the number of transactions in the block has a significant impact on the time the system provides location services. The number of transactions in the block can be reasonably set by calculating the network nodes in the blockchain. The results show that the system can protect the device. Providing location information services to users under the premise of location privacy.

An NLP-Powered Human Rights Monitoring Platform

Effective information management has long been a problem in organisations that are not of a scale that they can afford their own department dedicated to this task. Growing information overload has made this problem even more pronounced. On the other hand we have recently witnessed the emergence of intelligent tools, packages and resources that made it possible to rapidly transfer knowledge from the academic community to industry, government and other potential beneficiaries. Here we demonstrate how adopting state-of-the-art natural language processing (NLP) and crowdsourcing methods has resulted in measurable benefits for a human rights organisation by transforming their information and knowledge management using a novel approach that supports human rights monitoring in conflict zones. More specifically, we report on mining and classifying Arabic Twitter in order to identify potential human rights abuse incidents in a continuous stream of social media data within a specified geographical region. Results show deep learning approaches such as LSTM allow us to push the precision close to 85% for this task with an F1-score of 75%. Apart from the scientific insights we also demonstrate the viability of the framework which has been deployed as the Ceasefire Iraq portal for more than three years which has already collected thousands of witness reports from within Iraq. This work is a case study of how progress in artificial intelligence has disrupted even the operation of relatively small-scale organisations.

B. IS & MIS Information Systems and Management Information Systems: The backbone, sustenance and accomplishment of modern business

Information System (IS) has always been mixed up and confused with Management Information System (MIS) by many Information Technology professionals, and even in definitions ascribed to them thereby puzzling many users of Information Technology (IT). It should however, be noted that IS deals with the generality of the process of generating information from data; and MIS is definite about information generation for the use of management to enable them to efficiently / effectively plan, organize, direct, control and govern organisations. Any organisation lacking good IS and MIS for effective management of its functions / activities would be seriously handicapped, and as such could be doomed for collapse. Many modern organisations may be culprits of possessing the needed information for effective management of their enterprise, thereby denying the establishment of achieving its goals. It is a fact that achievement of organisational goals are synonymous with success of the enterprise, and management is required to attain the goals established with the directors of the company.

Cost Effective Security Information & Event Management (SIEM) for Small and Medium-Sized Enterprises

Cost Effective Security Information & Event Management (SIEM) for Small and Medium-Sized Enterprises

Transaction costs as a barrier in the renovation decision-making process: A study of homeowners in the Netherlands

The renovation of housing stock in the Netherlands has the potential to help achieving the country’s climate change targets. However, there are non-monetary Transaction Cost (TC) factors, such as searching for information and finding a reliable professional/contractor, that present barriers to householders when making the decision to renovate or not. This study evaluates the impact of the transaction costs on the renovation decision-making process for two groups of householders, current renovators and potential renovators, and for three types of renovations, exterior renovations, interior renovations, and energy efficiency renovations. The study analyses householder renovation decisions in relation to TC barriers at different stages of the renovation processes. The data was collected from a survey of 3,776 homeowners in the Netherlands. The main identified TC barriers were found to be at the consideration, decision, and execution phases of the renovation decision-making process, and are: finding a reliable professional/contractor to do exterior renovations, determining costs for interior renovations, and finding ways to increase the energy efficiency of the house using energy-saving renovations. The main sources of information for householders are construction stores/Do It Yourself (DIY), installations and maintenance companies for exterior and energy efficiency renovations, while for interior renovations it is construction stores/DIY companies, Internet, and recommendations from family/friends. The findings from this study contribute to more effective management and distribution of both information and financial resources in relation to the renovation of housing stock.

Predictive modeling of suitable habitat for deep-sea corals offshore the Northeast United States

Deep-sea corals (DSCs) are important living marine resources, forming both oases of biodiversity and three-dimensional habitat structure for fishes and invertebrates. However, because of logistical difficulties and expense of deep-sea exploration, much less is known about the distribution of DSCs than is known for their shallow-water counterparts. Predictive modeling, therefore, is essential for estimating the extent of DSC habitat in areas that are unexplored in order to support conservation efforts, to provide information for effective management of offshore activities affecting the seafloor, and for future exploration and research. In support of research and management efforts in the U.S. Northeast (Cape Hatteras, NC north to the Canadian border), we developed a comprehensive set of habitat suitability models covering this entire geographic region for nine taxonomic groups of DSCs (Alcyonacea, gorgonian corals, non-gorgonian corals, Scleractinia, Caryophylliidae, Flabellidae, Pennatulacea, Sessiliflorae, and Subselliflorae). Maximum entropy (MaxEnt) models were fit to DSC presence records and spatially-explicit environmental predictors depicting depth and seafloor topography, surficial sediment characteristics, and oceanography. A stepwise model selection procedure was then implemented to identify the set of predictor variables that maximized predictive performance for each taxonomic group. To allow for comparisons across taxonomic groups, the standard MaxEnt logistic predictions were converted into calibrated classes of habitat suitability. Overall, model performance was high for all taxonomic groups. Model fit was best for Caryophylliidae, Sessiliflorae, and Flabellidae, whereas model stability was greatest for the three taxonomic groups of Alcyonacea. Model results reported here corroborate known distributions of corals in the region. For example, large structure-forming taxa are predicted to occur mainly in canyon environments, particularly in areas of steep slope (>30°); sea pens in softer sediments of the continental shelf and slope. Additionally, the models successfully predicted DSC locations during field testing. Despite the limitations of presence-only data, several novel extensions to the traditional MaxEnt analysis workflow improved model selection, accuracy assessment, and comparability of results across taxonomic groups. This approach, when integrated with management processes, could be a powerful tool for science-based conservation, management, and spatial planning for these marine resources.

Knowledge, beliefs, and concerns about bone health from a systematic review and metasynthesis of qualitative studies.

BackgroundPatients with low bone density or osteoporosis need information for effective prevention or disease management, respectively. However, patients may not be getting enough information from their primary care providers or other sources. Inadequate disease information leaves patients ill-informed and creates misconceptions and unnecessary concerns about the disease.ObjectiveWe systematically reviewed and synthesized the available literature to determine patient knowledge, beliefs, and concerns about osteoporosis and identify potential gaps in knowledge.MethodsA systematic search was conducted for full-text qualitative studies addressing understanding, literacy, and/or perceptions about osteoporosis and its management, using Medline, EMBASE, Web of Science, Cochrane Library, CINAHL, ERIC, PsychINFO, Psyc Behav Sci Collec, and PubMed, from inception through September 2016. Studies were selected by two reviewers, assessed for quality, and themes extracted using the Joanna Briggs Institute data extraction tool. Thematic analysis was used to identify themes and subthemes.ResultsTwenty-five studies with a total of 757 participants (including 105 men) were selected for analysis out of 1031 unique citations. Selected studies were from Australia, Canada, Denmark, Norway, the United Kingdom, and the United States. Four main themes emerged: inadequate knowledge, beliefs and misconceptions, concerns about osteoporosis, and lack of information from health care providers. Participants had inadequate knowledge about osteoporosis and were particularly uninformed about risk factors, causes, treatment, and prevention. Areas of concern for participants included diagnosis, medication side effects, and inadequate information from primary care providers.ConclusionAlthough there was general awareness of osteoporosis, many misconceptions and concerns were evident. Education on bone health needs to reinforce areas of knowledge and address deficits, misconceptions, and concerns.

Temperature dependency equation for chub mackerel (Scomber japonicus) identified by a laboratory rearing experiment and microscale analysis

In this study, juveniles of chub mackerel (Scomber japonicus) were reared from eggs in six different temperature treatments, and their otoliths were subjected to micromilling and microvolume stable oxygen isotope (δ18O) analysis. We determined the δ18O values of otoliths (δ18Ootolith) formed at mean temperatures of 16.3, 17.6, 18.3, 20.0, 24.0 and 26.5°C and identified a linear relationship between rearing water temperature (T, °C) and δ18Ootolith as follows: δ18Ootolith (VPDB) – δ18Owater (VSMOW) =–0.25 (±0.01)T+4.46 (±0.21) (R2=0.96, P<0.01), where VPDB is Vienna Peedee Belemnite, VSMOW is Vienna Standard Mean Ocean Water and the error values in parentheses are standard deviations. This species-specific temperature dependency equation for chub mackerel will enable accurate reconstruction of individual thermal histories and provide essential information for effective resource management.

Trace Elements in Human Nutrition (II) - An Update.

The dietary requirement for an essential trace element is an intake level which meets a specified criterion for adequacy and thereby minimizes risk of nutrient deficiency or excess. Disturbances in trace element homeostasis may result in the development of pathologic states and diseases. This article is an update of a review article “Trace Elements in Human Nutrition-A Review” previously published in 2013. The previous review was updated to emphasis in detail the importance of known trace elements so far in humans’ physiology and nutrition and also to implement the detailed information for practical and effective management of trace elements’ status in clinical diagnosis and health care situations. Although various classifications for trace elements have been proposed and may be controversial, this review will use World Health Organization( WHO) classification as previously done. For this review a traditional integrated review format was chosen and many recent medical and scientific literatures for the new findings on bioavailability, functions, and state of excess/deficiency of trace elements were assessed. The results indicated that for the known essential elements, essentiality and toxicity are unrelated and toxicity is a matter of dose or exposure. Little is known about the essentiality of some of the probably essential elements. In regard to toxic heavy metals, a toxic element may nevertheless be essential. In addition, the early pathological manifestations of trace elements deficiency or excess are difficult to detect until more specific pathologically relevant indicators become available. Discoveries and many refinements in the development of new techniques and continual improvement in laboratory methods have enabled researchers to detect the early pathological consequences of deficiency or excess of trace elements. They all are promises to fulfill the gaps in the present and future research and clinical diagnosis of trace elements deficiencies or intoxications. However, further investigations are needed to complete the important gaps in our knowledge on trace elements, especially probably essential trace elements’ role in health and disease status.

Effective Information Management in Virtual Organizations: an Improved Organization Analysis for Celiac Patients

Celiac disease is a disease that prevents the body from absorbing enough minerals and vitamins. In our country, the number of individuals who are struggling to deal with this unclear awareness is quite high. The study is based on an evaluation of analyses conducted in the process of establishing an information management model to improve the disease processes for those patients diagnosed with this disease. The study is based on the sharing of three of the analyzes of a doctoral study. The main aim of the study is to eliminate the lack of information that the patients and their relatives will encounter in the process after diagnosis. It is also a priority to create an effective information management model for virtual organizations from new organizational forms. Turkey actively engaged in showing celiac associations made with interviews obtained after analyzing the findings of the post-diagnosis of patients in terms of effective communication by social factors as much as they are affected, not to accept the disease process has also been found as a result to be effective more environmental factors. In social media tools that the patient used to improve his own process, virtual organizations had positive results with the effective conduct of information management process but the frequency was found to be low. 

THE SOME QUESTIONS OF AUTONOMOUS MOTION AND MANAGEMENT OF LAND-MOBILE ROBOTIC COMPLEXES FOR UKRAINIAN GROUND FORCESE

Today, more than forty countries of the world are engaged in the development of military-purpose robots. A number of unique mobile robots with a wide range of capabilities are already being used by combat and intelligence units of the Armed forces of the developed world countries to conduct battlefield intelligence and support tactical groups. At present, the issue of using the latest information technology in the field of military robotics is thoroughly investigated, and the creation of highly effective information management systems in the land-mobile robotic complexes has acquired a new phase associated with the use of distributed information and sensory systems and consists in the transition from application of separate sensors and devices to the construction of modular information subsystems, which provide the availability of various data sources and complex methods of information processing. The purpose of the article is to investigate the ways to increase the autonomy of the land-mobile robotic complexes using in a non-deterministic conditions of modern combat. Relevance of researches is connected with the necessity of creation of highly effective information and control systems in the perspective robotic means for the needs of Land Forces of Ukraine. The development of the Armed Forces of Ukraine management system based on the criteria adopted by the EU and NATO member states is one of the main directions of increasing the effectiveness of the use of forces (forces), which involves achieving the principles and standards necessary for Ukraine to become a member of the EU and NATO. The inherent features of achieving these criteria will be the transition to a reduction of tasks of the combined-arms units and the large-scale use of high-precision weapons and land remote-controlled robotic devices. According to the views of the leading specialists in the field of robotics, the automation of information subsystems and components of the land-mobile robotic complexes can increase safety, reliability, error-tolerance and the effectiveness of the use of robotic means by standardizing the necessary actions with minimal human intervention, that is, a significant increase in the autonomy of the land-mobile robotic complexes for the needs of Land Forces of Ukraine.

THE WAYS OF THE EXPANSION OF THE SITUATIONAL AWARENESS OF LAND-MOBILE ROBOTIC COMPLEXES IN THE CONDITIONS OF CONDUCT NETWORK-CENTRIC BATTLE

Today, more than forty countries of the world are engaged in the development of military-purpose robots. A number of unique mobile robots with a wide range of capabilities are already being used by combat and intelligence units of the Armed forces of the developed world countries to conduct battlefield intelligence and support tactical groups. At present, the issue of using the latest information technology in the field of military robotics is thoroughly investigated, and the creation of highly effective information management systems in the land-mobile robotic complexes has acquired a new phase associated with the use of distributed information and sensory systems and consists in the transition from application of separate sensors and devices to the construction of modular information subsystems, which provide the availability of various data sources and complex methods of information processing. The purpose of the article is to investigate the ways to increase the autonomy of the land-mobile robotic complexes using in a non-deterministic conditions of modern combat. Relevance of researches is connected with the necessity of creation of highly effective information and control systems in the perspective robotic means for the needs of Land Forces of Ukraine. The development of the Armed Forces of Ukraine management system based on the criteria adopted by the EU and NATO member states is one of the main directions of increasing the effectiveness of the use of forces (forces), which involves achieving the principles and standards necessary for Ukraine to become a member of the EU and NATO. The inherent features of achieving these criteria will be the transition to a reduction of tasks of the combined-arms units and the large-scale use of high-precision weapons and land remote-controlled robotic devices. According to the views of the leading specialists in the field of robotics, the automation of information subsystems and components of the land-mobile robotic complexes can increase safety, reliability, error-tolerance and the effectiveness of the use of robotic means by standardizing the necessary actions with minimal human intervention, that is, a significant increase in the autonomy of the land-mobile robotic complexes for the needs of Land Forces of Ukraine.

Increment-averaged kriging for 3-D modelling and mapping soil properties: Combining machine learning and geostatistical methods

Prediction and mapping of soil properties for different soil depths can provide important information for effective land management. Such predictions and maps are often built based on soil data from multiple soil surveys, and the sampled depths will rarely align with depths for which the predictions and maps are required. A recently proposed approach to deal with such datasets, termed increment-averaged kriging (IAK), fits a single model using data from all profiles and all soil depths. The approach considered several potential stumbling blocks: the effect that different widths of the sampled depth intervals has on the variances (sample support); potential non-stationarity in the covariances, depending on soil depth; the need to account for interactions between depth and the effect of covariates. In this work, we present some extensions to the original work that (i) extend the covariance model, (ii) integrate the use of a machine learning algorithm, Cubist, into the framework so that its regression parameters can be fitted while accounting for the correlation and sample support of the data, and (iii) apply a composite likelihood approximation to enable estimation and prediction with large datasets. Code to implement the method in R is also made available so that practitioners can test IAK on their own datasets.