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Purpose – The purpose of this study was to invent morphological North Aceh durian data as germplasm information.

Methodology – The research was conducted at Langkahan and Sawang, North Aceh Region, from March to August 2014. The material used was the durian plant that should be 20 years and preferred by the local community. Exploration as the first step of experiment was done by purposive sampling. Identification was done on the source of durian germplasm. The source of durian germplasm as the experimental object was observed for its growth and morphology. Data analysis for morphological characteristics was done by using NTSYSpc (Numerical Taxonomy and Multivariate Analysis) NTSYSpc versi 2.02.

Originality – The results showed that there were 25 accessions superior durian in Langkahan and 26 accessions superior durian in Sawang. They had different characters in the vegetative parts of the plant. The durian coefficient value of similarity in Langkahan ranged from 0.33 to 0.94, while in Sawang, it ranged from 0.24 to 0.86. The diversity of the morphological character in superior durian of Langkahan and Sawang was seen from the qualitative character (surface and color of bark, crown shape, top surface color of leaves, and leaf shape) and quantitative character (plant height, stem diameter, crown diameter, length, width, and leaf area).

Semantic retrieval and discovery of datasets published as open data remains a challenging task. The datasets inherently originate in the globally distributed web jungle, lacking the luxury of centralized database administration, database schemes, shared attributes, vocabulary, structure and semantics. The existing dataset catalogs provide basic search functionality relying on keyword search in brief, incomplete or misleading textual metadata attached to the datasets. The search results are thus often insufficient. However, there exist many ways of improving the dataset discovery by employing content-based retrieval, machine learning tools, third-party (external) knowledge bases, countless feature extraction methods and description models and so forth.

In this paper, the authors propose a modular framework for rapid experimentation with methods for similarity-based dataset discovery. The framework consists of an extensible catalog of components prepared to form custom pipelines for dataset representation and discovery.

The study proposes several proof-of-concept pipelines including experimental evaluation, which showcase the usage of the framework.

To the best of authors’ knowledge, there is no similar formal framework for experimentation with various similarity methods in the context of dataset discovery. The framework has the ambition to establish a platform for reproducible and comparable research in the area of dataset discovery. The prototype implementation of the framework is available on GitHub.

The paper employs a unique online user-generated housing search dataset and introduces a novel measure for housing demand, namely “contacts per listing” as explained by hedonic, geographic and socioeconomic variables.

The authors explore housing demand by employing an extensive Internet search dataset from a German housing market platform. The authors apply state-of-the-art artificial intelligence, the eXtreme Gradient Boosting, to quantify factors that lead an apartment to be in demand.

The authors compare the results to alternative parametric models and find evidence of the superiority of the nonparametric model. The authors use eXplainable artificial intelligence (XAI) techniques to show economic meanings and inferences of the results. The results suggest that hedonic, socioeconomic and spatial aspects influence search intensity. The authors further find differences in temporal dynamics and geographical variations.

To the best of the authors’ knowledge, it is the first study of its kind. The statistical model of housing search draws on insights from decision theory, AI and qualitative studies on housing search. The econometric approach employed is new as it considers standard regression models and an eXtreme Gradient Boosting (XGB or XGBoost) approach followed by a model-agnostic interpretation of the underlying effects.

This book comprises the second volume in the recently launched New Horizons in Managerial and Organizational Cognition book series. Volume 1 (Sund, Galavan, & Huff, 2016), addressed the topic of strategic uncertainty. This second volume comprises a collection of contributions that variously report new methodological developments in managerial and organizational cognition, reflect critically on those developments, and consider the challenges that have yet to be confronted in order to further advance this exciting and dynamic interdisciplinary field. Contextualizing within an overarching framework the various contributions selected for inclusion in the present volume, in this opening chapter we reflect more broadly on what we consider the most significant developments that have occurred over recent years and the most significant challenges that lie ahead.

Purpose – The purpose of this research was to get the initial information about the phenotype diversity of avocado plants and as an information source of Acehnese avocado germplasm.

Methodology – This research was conducted at Bebesen sub-district Aceh Tengah District, from March to October 2017. Exploration was conducted using the descriptive method with purposive sampling. Plants observed in accordance with predetermined criteria namely plants that have been several times fruitful and preferred by consumers.

Originality – The research shown that the avocado plants in the Bebesen sub-district have a high degree of diversity. The diversity can be seen from canopy width, stem circumference, plant height, stem surface, tree shape, number of branches, branch shape, leaf length, leaf width, leaf area, and leaf shape. The number of superior avocado plants that were sampled was 15 accessions. The similarity level of superior avocado accession in the Bebesen sub-district ranged from 0.34 to 1.00.

The purpose of this paper is to propose a new approach to retrieve similar questions in online health communities to improve the efficiency of health information retrieval and sharing.

This paper proposes a hybrid approach to combining domain knowledge similarity and topic similarity to retrieve similar questions in online health communities. The domain knowledge similarity can evaluate the domain distance between different questions. And the topic similarity measures questions’ relationship base on the extracted latent topics.

The experiment results show that the proposed method outperforms the baseline methods.

This method conquers the problem of word mismatch and considers the named entities included in questions, which most of existing studies did not.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

This paper argues that cultures with the same climate have similar handicrafts as they have similar cultivation and identical raw materials. This study focuses on how mountainous, coastal and hot regions partaking in similar crafts and cultural heritage use palm leaves and analyses the resulting handicrafts' similarities.

A review of mapping these samples establishes this similarity in the traditional industries of some civilizations' cultural heritage from countries sharing similar climates.

The handwoven crafts using palm leaves were significant patrimonial artifacts in different societies' and communities' cultural heritage. Our studies revealed that climate plays an active role in influencing all aspects of humanity’s life. It affects the construction methods and style, agriculture and lifestyles.

Traditional handwoven palm leaf product models, especially plates and baskets, are studied from South America, Africa, Gulf Countries and Asia.

Additionally, this paper focuses on preserving these treasures as an essential part of interior elements as accessories for most inhabitants of these areas.

Cultural heritage also embraces intangible aspects such as skills passed down through generations within a particular society. The tangible and intangible elements complement each other and contribute to an overall legacy.

Cultural heritage reflects a society’s way of life carried down through the years across lands, items, customs and aesthetic concepts. People are the gatekeepers of society, as they preserve their way of life for future generations to emulate. Tangible artistic and cultural heritage comprises artifacts. It comprises all human evidence and expressions, such as traditional handicrafts, pictures, documents, books and manuscripts.

This study aims to assess the biodiversity of the study area and estimate the carbon stock of two dry deciduous forest ranges of Banka Forest Division, Bihar, India.

The phytosociological analysis was performed and C stock estimation based on volume determination through nondestructive methods was done.

Phytosociological analysis found total 18,888 [14,893 < 10 cm (diameter at breast height) dbh] and 2,855 (1,783 < 10 cm dbh) individuals at Banka and Bounsi range with basal area of 181,035.00 cm² and 32,743.76 cm², respectively. Importance value index was highest for Shorea robusta in both the ranges. Species diversity index and dominance index, 1.89 and 1.017 at Banka and 1.99 and 5.600 at Bounsi indicated the prevalence of biotic pressure. Decreased dbh and tree height resulted in a lowered growing stock volume as 59,140.40 cm³ ha⁻¹ (Banka) and 71,306.37 cm³ ha⁻¹ (Bounsi). Total C stock at Banka and Bounsi range was 51.8 t ha^-1 and 12.56 t ha⁻¹, respectively where the highest C stock is recorded for Shorea robusta in both the ranges (9.8 t ha⁻¹ and 2.54 t ha^-1, respectively). A positive correlation between volume, total biomass and basal area of tree species with C stock was observed. R² value for Banka range was 0.9269 (volume-C stock), 1 (total biomass-C stock) and 0.647 (basal area-C stock). Strong positive correlation was also established at Bounsi range with R² value of 1. Considering the total forest area enumerated, C sequestration potential was about 194.25 t CO₂ (Banka) and 45.9 t CO₂ (Bounsi). The valuation of C stock was therefore US$2,525.25 (Banka) and US$596.70 (Bounsi).

The research found the potentiality of the study area to sequester carbon. However, for future, the degraded areas would require intervention of management strategies for restoration of degraded lands and protection of planted trees to increase the carbon sequestration potential of the area.

Present study is the first attempt to assess the phytosociology and estimate the regulatory services of forest with respect to biomass and carbon stock estimation for the Banka forest division of Bihar.