ResearchPad - data-processing https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Adherence to antiretroviral therapy and associated factors among Human immunodeficiency virus positive patients accessing treatment at Nekemte referral hospital, west Ethiopia, 2019]]> https://www.researchpad.co/article/elastic_article_7637 Antiretroviral therapy has a remarkable clinical effect in reducing the progress of Acquired Immune Deficiency Syndrome. The clinical outcome of Anti-Retroviral therapy depends on strict adherence. Poor adherence reduces the effectiveness of antiretroviral therapy and increases viral replication. With changes in service delivery over time and differences in socio-demographic status from region to region, it is essential to measure adherence. Therefore, this study aimed to assess adherence to antiretroviral therapy and its associated factors among HIV/AIDS patients accessing treatment at Nekemte referral hospital, West Ethiopia.MethodsInstitutional based cross-sectional study was conducted on 311 HIV/AIDS patients from March 01 to March 30, 2019. The study participants were selected by a simple random sampling method and interviewed using structured questionnaires. Bivariable logistic regression was conducted to find an association between each independent variable and adherence to antiretroviral medication. Multivariable logistic regression was used to find the independent variables which best predict adherence. The statistical significance was measured using odds ratio at a 95% confidence interval with a p-value of less than 0.05.ResultsOut of a total of 311 patients sampled, 305 were participated in the study, making a response rate of 98.07%. From these 305 study participants,73.1% (95% CI = 68.2, 78.0) were adherent to their medication. Having knowledge about HIV and its treatment (AOR = 8.24, 95% CI: 3.10, 21.92), having strong family/social support (AOR = 6.21, 95% CI: 1.39, 27.62), absence of adverse drug reaction (AOR = 5.33, 95% CI: 1.95, 14.57), absence of comorbidity of other chronic diseases (AOR = 5.72, 95% CI: 1.91, 17.16) and disclosing HIV status to the family (AOR = 5.08, 95% CI: 2.09, 12.34) were significantly associated with an increased likelihood of adherence to antiretroviral medication.ConclusionThe level of adherence to antiretroviral therapy was found low compared to WHO recommendation. The clinician should emphasize reducing adverse drug reaction, detecting and treating co-morbidities early, improving knowledge through health education, and encouraging the patients to disclose their HIV status to their families. ]]> <![CDATA[Applicability of personal laser scanning in forestry inventory]]> https://www.researchpad.co/article/5c803c6ad5eed0c484ad8913

Light Detection and Ranging (LiDAR) technology has been widely used in forestry surveys in the form of airborne laser scanning (ALS), terrestrial laser scanning (TLS), and mobile laser scanning (MLS). The acquisition of important basic tree parameters (e.g., diameter at breast height and tree position) in forest inventory did not solve the problem of low measurement efficiency or weak GNSS signal under the canopy. A personal laser scanning (PLS) device combined with SLAM technology provides an effective solution for forest inventory under complex conditions with its light weight and flexible mobility. This study proposes a new method for calculating the volume of a cylinder using point cloud data obtained by a PLS device by fitting to a polygonal cylinder to calculate the diameter of the trunk. The point cloud data of tree trunks of different thickness were modeled using different fitting methods. The rate of correct tree trunk detection was 93.3% and the total deviation of the estimations of tree diameter at breast height (DBH) was -1.26 cm. The root mean square errors (RMSEs) of the estimations of the extracted DBH and the tree position were 1.58 cm and 26 cm, respectively. The survey efficiency of the personal laser scanning (PLS) device was 30m2/min for each investigator, compared with 0.91m2/min for the field survey. The test demonstrated that the PLS device combined with the SLAM algorithm provides an efficient and convenient solution for forest inventory.

]]>
<![CDATA[Factors influencing performance of community-based health volunteers’ activities in the Kassena-Nankana Districts of Northern Ghana]]> https://www.researchpad.co/article/5c76fe2ad5eed0c484e5b61f

Background

An increasing demand for health care services and getting health care closer to doorsteps of communities has made health managers to use trained community-based health volunteers to support in providing health services to people in rural communities. Community volunteerism in Ghana has been identified as an effective strategy in the implementation of Primary Health Care activities since 1970s. However, little is known about the performance of these volunteers engaged in health interventions activities at the community level. This study assessed the level of performance and factors that affect the performance of health volunteers’ activities in Northern Ghana.

Methods

This was a cross-sectional study using quantitative method of data collection. Two hundred structured interviews were conducted with health volunteers. Data collectors visited health volunteers at home and conducted the interviews after informed consent was obtained. STATA Version 11.2 was used to analyze the data. Descriptive statistics were used to assess the level of performance of the health volunteers. Multiple logistic regression models were then used to assess factors that influence the performance of health volunteers.

Results

About 45% of volunteers scored high on performance. In the multivariate analysis, educational status [OR = 4.64 95% CI (1.22–17.45)] and ethnicity [OR = 1.85 95% CI (1.00–3.41)] were the factors that influenced the performance of health volunteers. Other intermediary factors such as incentives and means of transport also affected the performance of health volunteers engaged in health intervention activities at the community level.

Conclusion

The results suggest that higher educational status of health volunteers is more likely to increase their performance. In addition, providing non-monetary incentives and logistics such as bicycles, raincoats, torch lights and wellington boots will enhance the performance of health volunteers and also motivate them to continue to provide health services to their own people at the community level.

]]>
<![CDATA[An open source algorithm to detect natural gas leaks from mobile methane survey data]]> https://www.researchpad.co/article/5c6dc9e7d5eed0c48452a459

The data collected by mobile methane (CH4) sensors can be used to find natural gas (NG) leaks in urban distribution systems. Extracting actionable insights from the large volumes of data collected by these sensors requires several data processing steps. While these survey platforms are commercially available, the associated data processing software largely constitute a black box due to their proprietary nature. In this paper we describe a step-by-step algorithm for developing leak indications using data from mobile CH4 surveys, providing an under-the-hood look at the choices and challenges associated with data analysis. We also describe how our algorithm has evolved over time, and the data-driven insights that have prompted these changes. Applying our algorithm to data collected in 15 cities produced more than 6100 leak indications and estimates of the leaks’ size. We use these results to characterize the distribution of leak sizes in local NG distribution systems. Mobile surveys are already an effective and necessary tool for managing NG distribution systems, but improvements in the technology and software will continue to increase its value.

]]>
<![CDATA[A tactical comparison of the 4-2-3-1 and 3-5-2 formation in soccer: A theory-oriented, experimental approach based on positional data in an 11 vs. 11 game set-up]]> https://www.researchpad.co/article/5c5b52cdd5eed0c4842bd050

The presented field experiment in an 11 vs. 11 soccer game set-up is the first to examine the impact of different formations (e.g. 4-2-3-1 vs. 3-5-2) on tactical key performance indicators (KPIs) using positional data in a controlled experiment. The data were gathered using player tracking systems (1 Hz) in a standardized 11 vs. 11 soccer game. The KPIs were measured using dynamical positioning variables like Effective Playing Space, Player Length per Width ratio, Team Separateness, Space Control Gain, and Pressure Passing Efficiency. Within the experimental positional data analysis paradigm, neither of the team formations showed differences in Effective Playing Space, Team Separateness, or Space Control Gain. However, as a theory-based approach predicted, a 3-5-2 formation for the Player Length per Width ratio and Pressure Passing Efficiency exceeded the 4-2-3-1 formation. Practice task designs which manipulate team formations therefore significantly influence the emergent behavioral dynamics and need to be considered when planning and monitoring performance. Accordingly, an experimental positional data analysis paradigm is a useful approach to enable the development and validation of theory-oriented models in the area of performance analysis in sports games.

]]>
<![CDATA[Community knowledge, attitude, and perceived stigma of leprosy amongst community members living in Dhanusha and Parsa districts of Southern Central Nepal]]> https://www.researchpad.co/article/5c424369d5eed0c4845e00dc

Background

Though Nepal declared leprosy elimination in 2010, its burden is constantly rising in Terai communities for the past 2 years with 3000 new leprosy cases being diagnosed annually. Community’s perception is important for prevention and control of leprosy and enhancing quality of life of leprosy patients. Poor knowledge, unfavorable attitude and stigma create a hindrance to leprosy control. The main objective of this study was to assess the knowledge, attitude and stigma of leprosy amongst the community members living in Dhanusha and Parsa districts of Southern Central Nepal.

Methods

A total of 423 individuals were interviewed using a structured questionnaire in Dhanusha and Parsa districts. Data was analyzed using both descriptive (frequency, percentage, median) and statistical inferences (Chi-square test, Kruskal Wallis H test, Mann Whitney U test, binary logistic regression) using SPSSvs20.

Results

All respondents had heard about leprosy. Source of information on leprosy was mainly found to be health workers/hospitals (33.1%). Only 62.6% reported bacteria being its cause followed by other myths such as bad blood/curse/heredity/bad deeds (36%). Only 43.8% responded that leprosy is transmitted by prolonged close contact with leprosy patients and 25.7% reported religious rituals as the treatment. Only 42.1% had good knowledge and 40.9% had favorable attitude. Good knowledge of leprosy was highly associated with favorable attitude towards leprosy (P<0.001). The outcome variables- knowledge, attitude and EMIC score were found to have highly significant association with age, sex, ethnicity, religion, education and occupation of the respondents (P<0.001). Having knowledge on leprosy transmission was positively associated with favorable attitude towards leprosy (P<0.001).

Conclusions

Strategizing the awareness programmes according to socio-demographic characteristics for enhancing the knowledge regarding leprosy cause, symptoms, transmission, prevention and treatment, can foster the positive community attitude towards leprosy affected persons. Enhancing positive attitude towards leprosy affected persons can reduce the community stigma, thus may increase their participation in the community. Positive attitude may further increase their early health seeking behaviour including their quality of life.

]]>
<![CDATA[PAIRUP-MS: Pathway analysis and imputation to relate unknowns in profiles from mass spectrometry-based metabolite data]]> https://www.researchpad.co/article/5c466521d5eed0c48451791d

Metabolomics is a powerful approach for discovering biomarkers and for characterizing the biochemical consequences of genetic variation. While untargeted metabolite profiling can measure thousands of signals in a single experiment, many biologically meaningful signals cannot be readily identified as known metabolites nor compared across datasets, making it difficult to infer biology and to conduct well-powered meta-analyses across studies. To overcome these challenges, we developed a suite of computational methods, PAIRUP-MS, to match metabolite signals across mass spectrometry-based profiling datasets and to generate metabolic pathway annotations for these signals. To pair up signals measured in different datasets, where retention times (RT) are often not comparable or even available, we implemented an imputation-based approach that only requires mass-to-charge ratios (m/z). As validation, we treated each shared known metabolite as an unmatched signal and showed that PAIRUP-MS correctly matched 70–88% of these metabolites from among thousands of signals, equaling or outperforming a standard m/z- and RT-based approach. We performed further validation using genetic data: the most stringent set of matched signals and shared knowns showed comparable consistency of genetic associations across datasets. Next, we developed a pathway reconstitution method to annotate unknown signals using curated metabolic pathways containing known metabolites. We performed genetic validation for the generated annotations, showing that annotated signals associated with gene variants were more likely to be enriched for pathways functionally related to the genes compared to random expectation. Finally, we applied PAIRUP-MS to study associations between metabolites and genetic variants or body mass index (BMI) across multiple datasets, identifying up to ~6 times more significant signals and many more BMI-associated pathways compared to the standard practice of only analyzing known metabolites. These results demonstrate that PAIRUP-MS enables analysis of unknown signals in a robust, biologically meaningful manner and provides a path to more comprehensive, well-powered studies of untargeted metabolomics data.

]]>
<![CDATA[EMBL2checklists: A Python package to facilitate the user-friendly submission of plant and fungal DNA barcoding sequences to ENA]]> https://www.researchpad.co/article/5c40f7a5d5eed0c48438651a

Background

The submission of DNA sequences to public sequence databases is an essential, but insufficiently automated step in the process of generating and disseminating novel DNA sequence data. Despite the centrality of database submissions to biological research, the range of available software tools that facilitate the preparation of sequence data for database submissions is low, especially for sequences generated via plant and fungal DNA barcoding. Current submission procedures can be complex and prohibitively time expensive for any but a small number of input sequences. A user-friendly software tool is needed that streamlines the file preparation for database submissions of DNA sequences that are commonly generated in plant and fungal DNA barcoding.

Methods

A Python package was developed that converts DNA sequences from the common EMBL and GenBank flat file formats to submission-ready, tab-delimited spreadsheets (so-called ‘checklists’) for a subsequent upload to the annotated sequence section of the European Nucleotide Archive (ENA). The software tool, titled ‘EMBL2checklists’, automatically converts DNA sequences, their annotation features, and associated metadata into the idiosyncratic format of marker-specific ENA checklists and, thus, generates files that can be uploaded via the interactive Webin submission system of ENA.

Results

EMBL2checklists provides a simple, platform-independent tool that automates the conversion of common DNA barcoding sequences into easily editable spreadsheets that require no further processing but their upload to ENA via the interactive Webin submission system. The software is equipped with an intuitive graphical as well as an efficient command-line interface for its operation. The utility of the software is illustrated by its application in four recent investigations, including plant phylogenetic and fungal metagenomic studies.

Discussion

EMBL2checklists bridges the gap between common software suites for DNA sequence assembly and annotation and the interactive data submission process of ENA. It represents an easy-to-use solution for plant and fungal biologists without bioinformatics expertise to generate submission-ready checklists from common DNA sequence data. It allows the post-processing of checklists as well as work-sharing during the submission process and solves a critical bottleneck in the effort to increase participation in public data sharing.

]]>
<![CDATA[Validation of modified radio-frequency identification tag firmware, using an equine population case study]]> https://www.researchpad.co/article/5c3fa5fcd5eed0c484caad7f

Background

Contact networks can be used to assess disease spread potential within a population. However, the data required to generate the networks can be challenging to collect. One method of collecting this type of data is by using radio-frequency identification (RFID) tags. The OpenBeacon RFID system generally consists of tags and readers. Communicating tags should be within 10m of the readers, which are powered by an external power source. The readers are challenging to implement in agricultural settings due to the lack of a power source and the large area needed to be covered.

Methods

OpenBeacon firmware was modified to use the tag’s onboard flash memory for data storage. The tags were deployed within an equine facility for a 7-day period. Tags were attached to the horses’ halters, worn by facility staff, and placed in strategic locations around the facility to monitor which participants had contact with the specified locations during the study period. When the tags came within 2m of each other, they recorded the contact event participant IDs, and start and end times. At the end of the study period, the data were downloaded to a computer and analyzed using network analysis methods.

Results

The resulting networks were plausible given the facility schedule as described in a survey completed by the facility manager. Furthermore, changes in the daily facility operations as described in the survey were reflected in the tag-collected data. In terms of the battery life, 88% of batteries maintained a charge for at least 6 days. Lastly, no consistent trends were evident in the horses’ centrality metrics.

Discussion

This study demonstrates the utility of RFID tags for the collection of equine contact data. Future work should include the collection of contact data from multiple equine facilities to better characterize equine disease spread potential in Ontario.

]]>
<![CDATA[An improved DBSCAN algorithm based on cell-like P systems with promoters and inhibitors]]> https://www.researchpad.co/article/5c215130d5eed0c4843f9176

Density-based spatial clustering of applications with noise (DBSCAN) algorithm can find clusters of arbitrary shape, while the noise points can be removed. Membrane computing is a novel research branch of bio-inspired computing, which seeks to discover new computational models/framework from biological cells. The obtained parallel and distributed computing models are usually called P systems. In this work, DBSCAN algorithm is improved by using parallel evolution mechanism and hierarchical membrane structure in cell-like P systems with promoters and inhibitors, where promoters and inhibitors are utilized to regulate parallelism of objects evolution. Experiment results show that the proposed algorithm performs well in big cluster analysis. The time complexity is improved to O(n), in comparison with conventional DBSCAN of O(n2). The results give some hints to improve conventional algorithms by using the hierarchical framework and parallel evolution mechanism in membrane computing models.

]]>
<![CDATA[Digital Identity: The effect of trust and reputation information on user judgement in the Sharing Economy]]> https://www.researchpad.co/article/5c1c0ae2d5eed0c484426d4a

The Sharing Economy (SE) is a growing ecosystem focusing on peer-to-peer enterprise. In the SE the information available to assist individuals (users) in making decisions focuses predominantly on community-generated trust and reputation information. However, how such information impacts user judgement is still being understood. To explore such effects, we constructed an artificial SE accommodation platform where we varied the elements related to hosts’ digital identity, measuring users’ perceptions and decisions to interact. Across three studies, we find that trust and reputation information increases not only the users’ perceived trustworthiness, credibility, and sociability of hosts, but also the propensity to rent a private room in their home. This effect is seen when providing users both with complete profiles and profiles with partial user-selected information. Closer investigations reveal that three elements relating to the host’s digital identity are sufficient to produce such positive perceptions and increased rental decisions, regardless of which three elements are presented. Our findings have relevant implications for human judgment and privacy in the SE, and question its current culture of ever increasing information-sharing.

]]>
<![CDATA[Cryptanalysis and improvement of an elliptic curve based signcryption scheme for firewalls]]> https://www.researchpad.co/article/5c1c0af5d5eed0c484426fcd

In network security, firewall is a security system that observes and controls the network traffic based on some predefined rules. A firewall sets up a barrier between internal network and another outside unsecured network, such as the Internet. A number of signcryption schemes for firewall are proposed over the years, many of them are proved to have security flaws. In this paper, an elliptic curve based signcryption scheme for firewalls is analyzed. It is observed that the scheme is not secure and has many security flaws. Anyone who knows the public parameters, can modify the message without the knowledge of sender and receiver. The claimed security attributes of non-repudiation, unforgeability, integrity and authentication are compromised. After successful cryptanalysis of this scheme, we proposed a modified version of the scheme.

]]>
<![CDATA[Uterine rupture among mothers admitted for obstetrics care and associated factors in referral hospitals of Amhara regional state, institution-based cross-sectional study, Northern Ethiopia, 2013-2017]]> https://www.researchpad.co/article/5c1028c2d5eed0c484248048

Background

Maternal morbidity and mortality have been one of the most challenging health problems that concern the globe over the years. Uterine rupture is one of the peripartum complications, which cause nearly about one out of thirteen maternal deaths. This study aimed to assess the prevalence and associated factors of uterine rupture among obstetric case in referral hospitals of Amhara Regional State, Northern Ethiopia.

Methods

Institution based cross sectional study was conducted from Dec 5-2017-Jan 5–2018 on uterine rupture. During the study randomly selected 750 charts were included by using simple random sampling method. Data were checked, coded and entered into Epi info version 7.2 and then exported to SPSS Version 20 for Analysis. Binary Logistic regression was used to identify the predictors of uterine rupture and 95% Confidence Interval of odds ratio at p-value less than 0.05 was taken as a significance level.

Result

The overall prevalence of uterine rupture was 16.68% (95% CI: 14%, 19.2%). Distance from health facility >10km (Adjusted Odds Ratio (AOR) = 2.44; 95%CI:1.13,5.28), parity between II and IV (AOR = 7.26;95% (3.06,17.22)) and ≥V (AOR = 12.55;95% CI 3.64,43.20), laboring for >24hours(AO = 3.44; 95% CI:1.49,7.92), with referral paper(AOR = 2.94;95%CI:1.28,6.55) diagnosed with obstructed labor (AOR = 4.88;95%CI: 2.22,10.70), precipitated labor (AOR = 3.59;95%CI:1.10,11.77), destructive delivery (AOR = 5.18;95%: 1.22,20.08), No partograph (AOR = 5.21; 95% CI: 2.72,9.97), CPD(AOR = 4.08;95%CI:1.99,8.33), morbidly adherent placenta (AOR = 9.00;95%:2.46,27.11), gestational diabetic militias (AOR = 5.78; 95%CI:1. 12,20 .00 ), history of myomectomy(AOR = 5.00;95%CI:1.33,18.73), induction and augmentation of labor (AOR = 2.34;95%:1.15,4.72) obstetric procedure (AOR = 2.54;95%: 1.09,5.91), previous caesarian deliveries 4.90 (2.13,11.26) were found to be significantly associated with uterine rupture.

Conclusion

This finding showed that the prevalence of uterine rupture is higher. A more vigilant approach to prevent prolonged and obstructed labor, use of partograph, quick referral to a well-equipped center and prevention of other obstetrics complications need to be focused on.

]]>
<![CDATA[Magnitude and factors associated with late antenatal care booking on first visit among pregnant women in public health centers in central zone of Tigray Region, Ethiopia: A cross sectional study]]> https://www.researchpad.co/article/5c117be0d5eed0c48469ac09

Background

Antenatal care (ANC) is a care given for pregnant women and is a good opportunity to deliver maternal health interventions. Even though pregnant women should start their first antenatal care within 12 weeks of gestational age, many pregnant women start their first ANC late. So, the aim of this study is to determine magnitude of late ANC booking at first visit and factors associated with it.

Methods

Institutional based cross sectional study design was conducted in central zone of Tigray Region, Ethiopia from November 1/2017 to January 30/2018 among total of 632 pregnant women. Stratified multi stage cluster sampling method was used to select health centers and systematic random sampling technique was used during the selection of study units. Data were collected using interview administer questionnaire by face to face. The collected data were entered into EPI info-7. Later on, it was exported to STATA-14 for further analysis. Proportion was used to estimate the magnitude of late ANC booking. Bivariable and multivariable analysis were done to see factors associated with the magnitude of late ANC booking.

Results

The magnitude of late ANC booking at first visit were 85.67% (95%, CI: 82.89, 88.45). Factors that were independently associated with the late ANC booking at first visit in multivariable analysis were; having home delivery in previous delivery (AOR = 2.2, 95%, CI: 1.1, 4.49), women who had no previous ANC follow up (AOR = 3.43, 95%, CI: 1.32, 8.92) and women with poor knowledge about the advantage and service availability of ANC (AOR = 3.9, 95%, CI: 1.83, 8.29).

Conclusion

In summary, most of pregnant women were not started their first ANC at the recommended time. Home delivery and history of ANC in previous pregnancy as well as women with poor knowledge about ANC were associated with late ANC booking at first visit. Health workers should work on avoiding home delivery and increasing the knowledge of pregnant women on ANC may help on reducing late ANC booking at first visit.

]]>
<![CDATA[Cluster randomized trial of comprehensive gender-based violence programming delivered through the HIV/AIDS program platform in Mbeya Region, Tanzania: Tathmini GBV study]]> https://www.researchpad.co/article/5c12cf87d5eed0c484914876

The Tathmini GBV study was a cluster randomized trial to assess the impact of a comprehensive health facility- and community-based program delivered through the HIV/AIDS program platform on reduction in gender-based violence and improved care for survivors. Twelve health facilities and surrounding communities in the Mbeya Region of Tanzania were randomly assigned to intervention or control arms. Population-level effects were measured through two cross-sectional household surveys of women ages 15–49, at baseline (n = 1,299) and at 28 months following program scale-out (n = 1,250). Delivery of gender-based violence services was assessed through routine recording in health facility registers. Generalized linear mixed effects models and analysis of variance were used to test intervention effects on population and facility outcomes, respectively. At baseline, 52 percent of women reported experience of recent intimate partner violence. The odds of reporting experience of this violence decreased by 29 percent from baseline to follow-up in the absence of the intervention (time effect OR = 0.71, 95% CI: 0.57–0.89). While the intervention contributed an additional 15 percent reduction, the effect was not statistically significant. The program, however, was found to contribute to positive, community-wide changes including less tolerance for certain forms of violence, more gender equitable norms, better knowledge about gender-based violence, and increased community actions to address violence. The program also led to increased utilization of gender-based violence services at health facilities. Nearly three times as many client visits for gender-based violence were recorded at intervention (N = 1,427) compared to control (N = 489) facilities over a 16-month period. These visits were more likely to include provision of an HIV test (55.3% vs. 19.6%, p = .002). The study demonstrated the feasibility and impact of integrating gender-based violence and HIV programming to combat both of these major public health problems. Further opportunities to scale out GBV prevention and response strategies within HIV/AIDS service delivery platforms should be pursued.

Trial Registration: Pan African Clinical Trials Registry No. PACTR201802003124149.

]]>
<![CDATA[Privacy-preserving aggregation of personal health data streams]]> https://www.researchpad.co/article/5c24019fd5eed0c48409d6e4

Recently, as the paradigm of medical services has shifted from treatment to prevention, there is a growing interest in smart healthcare that can provide users with healthcare services anywhere, at any time, using information and communications technologies. With the development of the smart healthcare industry, there is a growing need for collecting large-scale personal health data to exploit the knowledge obtained through analyzing them for improving the smart healthcare services. Although such a considerable amount of health data can be a valuable asset to the smart healthcare fields, they may cause serious privacy problems if sensitive information of an individual user is leaked to outside users. Therefore, most individuals are reluctant to provide their health data to smart healthcare service providers for data analysis and utilization purpose, which is the biggest challenge in smart healthcare fields. Thus, in this paper, we develop a novel mechanism for privacy-preserving collection of personal health data streams that is characterized as temporal data collected at fixed intervals by leveraging local differential privacy (LDP). In particular, with the proposed approach, a data contributor uses a given privacy budget of LDP to report a small amount of salient data, which are extracted from an entire health data stream, to a data collector. Then, a data collector can effectively reconstruct a health data stream based on the noisy salient data received from a data contributor. Experimental results demonstrate that the proposed approach provides significant accuracy gains over straightforward solutions to this problem.

]]>
<![CDATA[An efficient outlier removal method for scattered point cloud data]]> https://www.researchpad.co/article/5b6da1b2463d7e4dccc5faec

Outlier removal is a fundamental data processing task to ensure the quality of scanned point cloud data (PCD), which is becoming increasing important in industrial applications and reverse engineering. Acquired scanned PCD is usually noisy, sparse and temporarily incoherent. Thus the processing of scanned data is typically an ill-posed problem. In the paper, we present a simple and effective method based on two geometrical characteristics constraints to trim the noisy points. One of the geometrical characteristics is the local density information and another is the deviation from the local fitting plane. The local density based method provides a preprocessing step, which could remove those sparse outlier and isolated outlier. The non-isolated outlier removal in this paper depends on a local projection method, which placing those points onto objects. There is no doubt that the deviation of any point from the local fitting plane should be a criterion to reduce the noisy points. The experimental results demonstrate the ability to remove the noisy point from various man-made objects consisting of complex outlier.

]]>
<![CDATA[Validation of electronic performance and tracking systems EPTS under field conditions]]> https://www.researchpad.co/article/5b603638463d7e4090b7ce26

The purpose of this study was to assess the measurement accuracy of the most commonly used tracking technologies in professional team sports (i.e., semi-automatic multiple-camera video technology (VID), radar-based local positioning system (LPS), and global positioning system (GPS)). The position, speed, acceleration and distance measures of each technology were compared against simultaneously recorded measures of a reference system (VICON motion capture system) and quantified by means of the root mean square error RMSE. Fourteen male soccer players (age: 17.4±0.4 years, height: 178.6±4.2 cm, body mass: 70.2±6.2 kg) playing for the U19 Bundesliga team FC Augsburg participated in the study. The test battery comprised a sport-specific course, shuttle runs, and small sided games on an outdoor soccer field. The validity of fundamental spatiotemporal tracking data differed significantly between all tested technologies. In particular, LPS showed higher validity for measuring an athlete’s position (23±7 cm) than both VID (56±16 cm) and GPS (96±49 cm). Considering errors of instantaneous speed measures, GPS (0.28±0.07 m⋅s-1) and LPS (0.25±0.06 m⋅s-1) achieved significantly lower error values than VID (0.41±0.08 m⋅s-1). Equivalent accuracy differences were found for instant acceleration values (GPS: 0.67±0.21 m⋅s-2, LPS: 0.68±0.14 m⋅s-2, VID: 0.91±0.19 m⋅s-2). During small-sided games, lowest deviations from reference measures have been found in the total distance category, with errors ranging from 2.2% (GPS) to 2.7% (VID) and 4.0% (LPS). All technologies had in common that the magnitude of the error increased as the speed of the tracking object increased. Especially in performance indicators that might have a high impact on practical decisions, such as distance covered with high speed, we found >40% deviations from the reference system for each of the technologies. Overall, our results revealed significant between-system differences in the validity of tracking data, implying that any comparison of results using different tracking technologies should be done with caution.

]]>
<![CDATA[Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions]]> https://www.researchpad.co/article/5b30b251463d7e0b2827fd22

Accurate and reliable forecasts of seasonal epidemics of infectious disease can assist in the design of countermeasures and increase public awareness and preparedness. This article describes two main contributions we made recently toward this goal: a novel approach to probabilistic modeling of surveillance time series based on “delta densities”, and an optimization scheme for combining output from multiple forecasting methods into an adaptively weighted ensemble. Delta densities describe the probability distribution of the change between one observation and the next, conditioned on available data; chaining together nonparametric estimates of these distributions yields a model for an entire trajectory. Corresponding distributional forecasts cover more observed events than alternatives that treat the whole season as a unit, and improve upon multiple evaluation metrics when extracting key targets of interest to public health officials. Adaptively weighted ensembles integrate the results of multiple forecasting methods, such as delta density, using weights that can change from situation to situation. We treat selection of optimal weightings across forecasting methods as a separate estimation task, and describe an estimation procedure based on optimizing cross-validation performance. We consider some details of the data generation process, including data revisions and holiday effects, both in the construction of these forecasting methods and when performing retrospective evaluation. The delta density method and an adaptively weighted ensemble of other forecasting methods each improve significantly on the next best ensemble component when applied separately, and achieve even better cross-validated performance when used in conjunction. We submitted real-time forecasts based on these contributions as part of CDC’s 2015/2016 FluSight Collaborative Comparison. Among the fourteen submissions that season, this system was ranked by CDC as the most accurate.

]]>
<![CDATA[VennPainter: A Tool for the Comparison and Identification of Candidate Genes Based on Venn Diagrams]]> https://www.researchpad.co/article/5989d9dbab0ee8fa60b679a8

VennPainter is a program for depicting unique and shared sets of genes lists and generating Venn diagrams, by using the Qt C++ framework. The software produces Classic Venn, Edwards’ Venn and Nested Venn diagrams and allows for eight sets in a graph mode and 31 sets in data processing mode only. In comparison, previous programs produce Classic Venn and Edwards’ Venn diagrams and allow for a maximum of six sets. The software incorporates user-friendly features and works in Windows, Linux and Mac OS. Its graphical interface does not require a user to have programing skills. Users can modify diagram content for up to eight datasets because of the Scalable Vector Graphics output. VennPainter can provide output results in vertical, horizontal and matrix formats, which facilitates sharing datasets as required for further identification of candidate genes. Users can obtain gene lists from shared sets by clicking the numbers on the diagram. Thus, VennPainter is an easy-to-use, highly efficient, cross-platform and powerful program that provides a more comprehensive tool for identifying candidate genes and visualizing the relationships among genes or gene families in comparative analysis.

]]>