Data | May 2021 - Browse Articles

12 pages, 335 KiB

Open AccessArticle

Recursive Genetic Micro-Aggregation Technique: Information Loss, Disclosure Risk and Scoring Index

by Ebaa Fayyoumi and Omar Alhuniti

Data 2021, 6(5), 53; https://doi.org/10.3390/data6050053 - 20 May 2021

Cited by 2 | Viewed by 2372

This research investigates the micro-aggregation problem in secure statistical databases by integrating the divide and conquer concept with a genetic algorithm. This is achieved by recursively dividing a micro-data set into two subsets based on the proximity distance similarity. On each subset the [...] Read more.

This research investigates the micro-aggregation problem in secure statistical databases by integrating the divide and conquer concept with a genetic algorithm. This is achieved by recursively dividing a micro-data set into two subsets based on the proximity distance similarity. On each subset the genetic operation “crossover” is performed until the convergence condition is satisfied. The recursion will be terminated if the size of the generated subset is satisfied. Eventually, the genetic operation “mutation” will be performed over all generated subsets that satisfied the variable group size constraint in order to maximize the objective function. Experimentally, the proposed micro-aggregation technique was applied to recommended real-life data sets. Results demonstrated a remarkable reduction in the computational time, which sometimes exceeded 70% compared to the state-of-the-art. Furthermore, a good equilibrium value of the Scoring Index

(S I)

was achieved by involving a linear combination of the General Information Loss

(G_{I L})

and the General Disclosure Risk

(G_{D R})

. Full article

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29 pages, 282 KiB

Open AccessReview

The Modern Greek Language on the Social Web: A Survey of Data Sets and Mining Applications

by Maria Nefeli Nikiforos, Yorghos Voutos, Anthi Drougani, Phivos Mylonas and Katia Lida Kermanidis

Data 2021, 6(5), 52; https://doi.org/10.3390/data6050052 - 17 May 2021

Cited by 6 | Viewed by 4392

Abstract

Mining social web text has been at the heart of the Natural Language Processing and Data Mining research community in the last 15 years. Though most of the reported work is on widely spoken languages, such as English, the significance of approaches that [...] Read more.

Mining social web text has been at the heart of the Natural Language Processing and Data Mining research community in the last 15 years. Though most of the reported work is on widely spoken languages, such as English, the significance of approaches that deal with less commonly spoken languages, such as Greek, is evident for reasons of preserving and documenting minority languages, cultural and ethnic diversity, and identifying intercultural similarities and differences. The present work aims at identifying, documenting and comparing social text data sets, as well as mining techniques and applications on social web text that target Modern Greek, focusing on the arising challenges and the potential for future research in the specific less widely spoken language. Full article

(This article belongs to the Section Featured Reviews of Data Science Research)

7 pages, 4938 KiB

Open AccessData Descriptor

LeLePhid: An Image Dataset for Aphid Detection and Infestation Severity on Lemon Leaves

by Jorge Parraga-Alava, Roberth Alcivar-Cevallos, Jéssica Morales Carrillo, Magdalena Castro, Shabely Avellán, Aaron Loor and Fernando Mendoza

Data 2021, 6(5), 51; https://doi.org/10.3390/data6050051 - 17 May 2021

Cited by 14 | Viewed by 4569

Abstract

Aphids are small insects that feed on plant sap, and they belong to a superfamily called Aphoidea. They are among the major pests causing damage to citrus crops in most parts of the world. Precise and automatic identification of aphids is needed [...] Read more.

Aphids are small insects that feed on plant sap, and they belong to a superfamily called Aphoidea. They are among the major pests causing damage to citrus crops in most parts of the world. Precise and automatic identification of aphids is needed to understand citrus pest dynamics and management. This article presents a dataset that contains 665 healthy and unhealthy lemon leaf images. The latter are leaves with the presence of aphids, and visible white spots characterize them. Moreover, each image includes a set of annotations that identify the leaf, its health state, and the infestation severity according to the percentage of the affected area on it. Images were collected manually in real-world conditions in a lemon plant field in Junín, Manabí, Ecuador, during the winter, by using a smartphone camera. The dataset is called LeLePhid: lemon (Le) leaf (Le) image dataset for aphid (Phid) detection and infestation severity. The data can facilitate evaluating models for image segmentation, detection, and classification problems related to plant disease recognition. Full article

(This article belongs to the Special Issue Machine Learning in Image Analysis and Pattern Recognition)

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6 pages, 220 KiB

Open AccessData Descriptor

Dataset on the Effects of Anti-Insect Nets of Different Porosity on Mineral and Organic Acids Profile of Cucurbita pepo L. Fruits and Leaves

by Luigi Formisano, Michele Ciriello, Christophe El-Nakhel, Stefania De Pascale and Youssef Rouphael

Data 2021, 6(5), 50; https://doi.org/10.3390/data6050050 - 13 May 2021

Cited by 17 | Viewed by 2651

Abstract

The growing interest in healthy foods has driven the agricultural sector towards eco-friendly implementation to manage biotic and abiotic factors in protected environments. In this perspective, anti-insect nets are an effective tool for controlling harmful insect populations concomitantly with reducing chemicals’ interference. However, [...] Read more.

The growing interest in healthy foods has driven the agricultural sector towards eco-friendly implementation to manage biotic and abiotic factors in protected environments. In this perspective, anti-insect nets are an effective tool for controlling harmful insect populations concomitantly with reducing chemicals’ interference. However, the low porosity of nets necessary to ensure high exclusion efficiency for a designated insect leads to reduced airflow, impacting the productivity and quality attributes of vegetables. The evidence presented in this dataset pertains to the content of total nitrogen, minerals (i.e., NO₃, K, PO₄, SO₄, Ca, Mg, Cl, and Na), and organic acids (i.e., malate and citrate) of zucchini squash (Cucurbita pepo L. cv. Zufolo F1) in leaves and fruits grown with two anti-insect nets with different porosities (Biorete^® 50 mesh and Biorete^® 50 mesh AirPlus), is and analyzed by the Kjeldahl method and ion chromatography (ICS3000), respectively. Data of total nitrogen concentration, macronutrients, and organic acids provide in-depth information about plants’ physiological response to microclimate changes induced by anti-insect nets. Full article

20 pages, 609 KiB

Open AccessArticle

Factors That Affect E-Learning Platforms after the Spread of COVID-19: Post Acceptance Study

by Rana Saeed Al-Maroof, Khadija Alhumaid, Iman Akour and Said Salloum

Data 2021, 6(5), 49; https://doi.org/10.3390/data6050049 - 12 May 2021

Cited by 24 | Viewed by 6561

Abstract

The fear of vaccines has led to population rejection due to various reasons. Students have had their own inquiries towards the effectiveness of the vaccination, which leads to vaccination hesitancy. Vaccination hesitancy can affect students’ perception, hence, acceptance of e-learning platforms. Therefore, this [...] Read more.

The fear of vaccines has led to population rejection due to various reasons. Students have had their own inquiries towards the effectiveness of the vaccination, which leads to vaccination hesitancy. Vaccination hesitancy can affect students’ perception, hence, acceptance of e-learning platforms. Therefore, this research attempts to explore the post-acceptance of e-learning platforms based on a conceptual model that has various variables. Each variable contributes differently to the post-acceptance of the e-learning platform. The research investigates the moderating role of vaccination fear on the post-acceptance of e-learning platforms among students. Thus, the study aims at exploring students’ perceptions about their post-acceptance of e-learning platforms where vaccination fear functions as a moderator. The current study depends on an online questionnaire that is composed of 29 items. The total number of respondents is 630. The collected data was implemented to test the study model and the proposed constructs and hypotheses depending on the Smart PLS Software. Fear of vaccination has a significant impact on the acceptance of e-learning platforms, and it is a strong mediator in the conceptual model. The findings indicate a positive effect of the fear of vaccination as a mediator in the variables: perceived ease of use and usefulness, perceived daily routine, perceived critical mass and perceived self-efficiency. The implication gives a deep insight to take effective steps in reducing the level of fear of vaccination, supporting the vaccination confidence among educators, teachers and students who will, in turn, affect the society as a whole. Full article

(This article belongs to the Special Issue Big Data and E-learning)

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17 pages, 1913 KiB

Open AccessArticle

Designing Knowledge Sharing System for Statistical Activities in BPS-Statistics Indonesia

by Dana Indra Sensuse, Viktor Suwiyanto, Sofian Lusa, Arfive Gandhi, Muhammad Mishbah and Damayanti Elisabeth

Data 2021, 6(5), 48; https://doi.org/10.3390/data6050048 - 12 May 2021

Cited by 7 | Viewed by 3673

Abstract

Statistics of Indonesia’s (BPS) performance are not optimal since there is a lack of integration among business processes. This has resulted in unsynchronized data, unstandardized business processes, and inefficient IT investment. To encourage more qualified and integrated business processes, BPS should optimize the [...] Read more.

Statistics of Indonesia’s (BPS) performance are not optimal since there is a lack of integration among business processes. This has resulted in unsynchronized data, unstandardized business processes, and inefficient IT investment. To encourage more qualified and integrated business processes, BPS should optimize the knowledge sharing process (KSP) among government employees in statistical areas. This study designed a Knowledge Sharing System (KSS) to facilitate KSP in BPS towards knowledge sharing improvement. The KSS manifested a hypothesis that the design of qualified knowledge management can facilitate an organization to overcome the lack of integration among business processes. Hence, BPS can avoid repetitive mistakes, improve work efficiency, and reduce the risk of failure. This study generated a business process-oriented KSS by combining soft system methodology with the B-KIDE (Business process-oriented Knowledge Infrastructure Development) Framework. It delivered research artifacts (a rich picture, CATWOE analysis (costumer, actor, transformation, weltanschauung, owner, environment), and conceptual model) to capture eight mechanisms of knowledge, map them into the knowledge process, and define the applicable technology. The KSS model has perceived a score of 0.40 using the Kappa formula that indicates the stakeholders’ acceptance. Therefore, BPS can leverage a qualified KSS towards the integrated business processes statistically while the hypothesis was accepted. Full article

(This article belongs to the Special Issue Data Governance Principles, Decision Domains and Organizational Structures)

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17 pages, 345 KiB

Open AccessArticle

Industry 4.0 and Proactive Works Council Members

by Mari Božič, Annmarie Gorenc Zoran and Matej Jevšček

Data 2021, 6(5), 47; https://doi.org/10.3390/data6050047 - 30 Apr 2021

Viewed by 2689

Abstract

Background: Integrating Industry 4.0 technologies in organizations affects employees’ workplaces and working conditions. Works Council members play an essential role in this because as intermediaries of information between employees and management, they increase mutual trust and help introduce changes in the work environment. [...] Read more.

Background: Integrating Industry 4.0 technologies in organizations affects employees’ workplaces and working conditions. Works Council members play an essential role in this because as intermediaries of information between employees and management, they increase mutual trust and help introduce changes in the work environment. This article discusses the Works Council members’ autopoietic endowments that are necessary for their proactive activity, which we discuss as building blocks for creating constructive relationships with management and quality energy in an organization. As such, we were interested in examining whether the autopoietic endowments of Works Council members influenced the type of relationship with the Works Council and management, and whether this relationship affected Works Council members’ organizational energy. Methods: A questionnaire was developed, piloted and distributed to Works Council Members, and 220 completed questionnaires were returned. Results: We found that the higher the level of self-awareness, the better the relationship between Works Council members and management. Moreover, poor energy represented poor relationships, and poor relationships signified a higher degree of resigned inertia and corrosive energy. Conclusions: Our research provides managements with insights into the relationship between employees and management, and the quality of their organizational energy. Full article

(This article belongs to the Special Issue Development of a Smart Future under Society 5.0)

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13 pages, 1463 KiB

Open AccessData Descriptor

IntelliRehabDS (IRDS)—A Dataset of Physical Rehabilitation Movements

by Alina Miron, Noureddin Sadawi, Waidah Ismail, Hafez Hussain and Crina Grosan

Data 2021, 6(5), 46; https://doi.org/10.3390/data6050046 - 30 Apr 2021

Cited by 22 | Viewed by 8404

Abstract

In this article, we present a dataset that comprises different physical rehabilitation movements. The dataset was captured as part of a research project intended to provide automatic feedback on the execution of rehabilitation exercises, even in the absence of a physiotherapist. A Kinect [...] Read more.

In this article, we present a dataset that comprises different physical rehabilitation movements. The dataset was captured as part of a research project intended to provide automatic feedback on the execution of rehabilitation exercises, even in the absence of a physiotherapist. A Kinect motion sensor camera was used to record gestures. The dataset contains repetitions of nine gestures performed by 29 subjects, out of which 15 were patients and 14 were healthy controls. The data are presented in an easily accessible format, provided as 3D coordinates of 25 body joints along with the corresponding depth map for each frame. Each movement was annotated with the gesture type, the position of the person performing the gesture (sitting or standing) as well as a correctness label. The data are publicly available and were released with to provide a comprehensive dataset that can be used for assessing the performance of different patients while performing simple movements in a rehabilitation setting and for comparing these movements with a control group of healthy individuals. Full article

(This article belongs to the Special Issue Measurements of User and Sensor Data from the Internet of Things (IoT) Devices)

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3 pages, 1991 KiB

Open AccessEditorial

Data from Smartphones and Wearables

by Joaquín Torres-Sospedra and Aleksandr Ometov

Data 2021, 6(5), 45; https://doi.org/10.3390/data6050045 - 28 Apr 2021

Cited by 1 | Viewed by 2566

Abstract

Wearables are wireless devices that we “wear” on our bodies [...] Full article

(This article belongs to the Special Issue Data from Smartphones and Wearables)

4 pages, 890 KiB

Open AccessData Descriptor

Collection of a Bacterial Community Reconstructed from Marine Metagenomes Derived from Jinhae Bay, South Korea

by Jae-Hyun Lim and Il-Nam Kim

Data 2021, 6(5), 44; https://doi.org/10.3390/data6050044 - 26 Apr 2021

Viewed by 2381

Abstract

Marine bacteria are known to play significant roles in marine biogeochemical cycles regarding the decomposition of organic matter. Despite the increasing attention paid to the study of marine bacteria, research has been too limited to fully elucidate the complex interaction between marine bacterial [...] Read more.

Marine bacteria are known to play significant roles in marine biogeochemical cycles regarding the decomposition of organic matter. Despite the increasing attention paid to the study of marine bacteria, research has been too limited to fully elucidate the complex interaction between marine bacterial communities and environmental variables. Jinhae Bay, the study area in this work, is the most anthropogenically eutrophied coastal bay in South Korea, and while its physical and biogeochemical characteristics are well described, less is known about the associated changes in microbial communities. In the present study, we reconstructed a metagenomics data based on the 16S rRNA gene to investigate temporal and vertical changes in microbial communities at three depths (surface, middle, and bottom) during a seven-month period from June to December 2016 at one sampling site (J1) in Jinhae Bay. Of all the bacterial data, Proteobacteria, Bacteroidetes, and Cyanobacteria were predominant from June to November, whereas Firmicutes were predominant in December, especially at the middle and bottom depths. These results show that the composition of the microbial community is strongly associated with temporal changes. Furthermore, the community compositions were markedly different between the surface, middle, and bottom depths in summer, when water column stratification and bottom water hypoxia (low dissolved oxygen level) were strongly developed. Metagenomics data contribute to improving our understanding of important relationships between environmental characteristics and microbial community change in eutrophication-induced and deoxygenated coastal areas. Full article

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7 pages, 1471 KiB

Open AccessData Descriptor

Data for Interaction Diagrams of Geopolymer FRC Slender Columns with Double-Layer GFRP and Steel Reinforcement

by Mohammad AlHamaydeh and Fouad Amin

Data 2021, 6(5), 43; https://doi.org/10.3390/data6050043 - 26 Apr 2021

Cited by 14 | Viewed by 3464

Abstract

This article provides data of axial load-bending moment capacities of plain and fiber-reinforced geopolymer concrete (GPC, FRGPC) columns. The columns were reinforced by double layers of longitudinal and transverse reinforcement using steel and/or glass-fiber-reinforced polymer (GFRP) bars. The concrete fiber-reinforcing materials included steel [...] Read more.

This article provides data of axial load-bending moment capacities of plain and fiber-reinforced geopolymer concrete (GPC, FRGPC) columns. The columns were reinforced by double layers of longitudinal and transverse reinforcement using steel and/or glass-fiber-reinforced polymer (GFRP) bars. The concrete fiber-reinforcing materials included steel and synthetic fibers. The columns data included different parameters like the longitudinal reinforcement ratio, the applied load eccentricity, and the columns’ slenderness ratio. The data was collected from different analysis output files then sorted and tabulated in usable formatted tables. The data can support the development of design axial load-bending moment interactions. In addition, further processing of the data can yield analytical strength curves which are useful in determining the columns stability under different structural loading configurations. Researchers and educators can make use of these data for illustrations and prospective new research suggestions. Full article

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