Ahsan Morshed

Central Queensland University · Department of applied science

The rapid access of sensor technology provides both challenges and opportunities to authenticated spatiotemporal data. Authentication can be assured by developing related ontologies. Ontology explicitly specifies shared conceptualization and formal vocabularies. In this paper, we proposed an environmental spatio-temporal ontology (ESTO) using unifi...

Weeds are one of the most harmful agricultural pests that have a significant impact on crops. Weeds are responsible for higher production costs due to crop waste and have a significant impact on the global agricultural economy. The importance of this problem has promoted the research community in exploring the use of technology to support farmers i...

Diabetes mellitus is a serious chronic disease that affects the blood sugar levels in individuals, with current predictions estimating that nearly 578 million people will be affected by diabetes by 2030. Patients with type II diabetes usually follow a self-management regime as directed by a clinician to help regulate their blood glucose levels. Tod...

This paper explores the potential of machine learning algorithms for weed and crop classification from UAV images. The identification of weeds in crops is a challenging task that has been addressed through orthomosaicing of images, feature extraction and labelling of images to train machine learning algorithms. In this paper, the performances of se...

RDF data has been extensively deployed describing various types of resources in a structured way. Links between data elements described by RDF models stand for the core of Semantic Web. The rising amount of structured data published in public RDF repositories, also known as Linked Open Data, elucidates the success of the global and unified dataset...

Diabetes Mellitus a prevalent chronic disease that affects people from all genders and ages, continues to grow exponentially with predictions of nearly 578 million people affected by 2030. Self-management, known to be an essential aspect of any care program, can help patients with diabetics to control blood glucose and thereby, reduce the impact an...

Type II diabetes is a rapidly growing non-communicable chronic disease that is causing significant concern to healthcare systems around the world. As there is no foreseeable cure, the most effective solution is to focus on strategies to control blood glucose levels by regular monitoring of diet, exercise, and when necessary, medication management....

The advent of healthcare information management systems (HIMSs) continues to produce large volumes of healthcare data for patient care and compliance and regulatory requirements at a global scale. Analysis of this big data allows for boundless potential outcomes for discovering knowledge. Big data analytics (BDA) in healthcare can, for instance, he...

Smart farming has become imperative these days due to competition, and use of Unmanned Aerial Vehicle (UAV) imagery is becoming an integral part of the process. Machine learning techniques have been successfully applied to capture UAV imagery of various spectral bands to identify weed infestations. Identification of weeds in chilli crop is a challe...

Healthcare 4.0 is a term that has emerged recently and derived from Industry 4.0. Today, the health care sector is more digital than in past decades; for example, spreading from x‐rays and magnetic resonance imaging to computed tomography and ultrasound scans to electric medical records. With the wide spectrum of digital technologies underpinning H...

This paper focuses on facilitating state-of-the-art applications of big data analytics ( BDA ) architectures and infrastructures to telecommunications ( telecom ) industrial sector. Telecom companies are dealing with terabytes to petabytes of data on a daily basis. IoT applications in telecom are further contributing to this data deluge. Recent adv...

Open multidimensional data from social media and similar sources often carries insightful information on social issues. With the increase of high volume data and the proliferation of visual analytics platforms, it becomes easier for users to interact with and select meaningful information from large data sets. The prevention of crime is a crucial i...

Open multidimensional data from existing sources and social media often carries insightful information on social issues. With the increase of high volume data and the proliferation of visual analytics platforms, users can more easily interact with and pick out meaningful information from a large dataset. In this paper, we present VisCrime, a system...

Visual analytics is inherently multi-disciplinary in nature encompassing diverse concepts from a wide range of scientific disciplines. It is a cutting-edge technology for multi-dimensional data analysis. In this paper, we discuss the development of a Visual Analytic Ontology (VAO) that provides a standard, unified, machine-understandable representa...

Emerging availability (and varying complexity and types) of Internet of Things (IoT) devices, along with large data volumes that such devices (can potentially) generate, can have a significant impact on our lives, fuelling the development of critical next-generation services and applications in a variety of application domains (e.g. healthcare, sma...

Improving farm productivity is essential for increasing farm profitability and meeting the rapidly growing demand for food that is fuelled by rapid population growth across the world. Farm productivity can be increased by understanding and forecasting crop performance in a variety of environmental conditions. Crop recommendation is currently based...

Many underground mine void spaces are not suitable for human entry due to unprotected roofs, instability or having an unknown safety state (eg if they are many decades old). Investigations of these voids may nevertheless be important for general mine safety, for example to detect propagating collapses or water accumulation, prevent accidental intru...

In this paper an autonomous feature clustering framework has been proposed for performance and reliability evaluation of an environmental sensor network. Environmental time series were statistically preprocessed to extract multiple semantic features. A novel hybrid clustering framework was designed based on Principal Component Analysis (PCA), Guide...

Very high spatial resolution (VHSR) remote sensing imaging brings challenges and opportunities to intelligent autonomous interpretation of spatial data due to detailed information available in such images. Accurate extraction of information relies on expert knowledge which can be represented by an Ontology. Within the Geographic Object-Based Image...

In GEOBIA, segmentation is a very first task in creating image objects from very high spatial resolution (VHSR) imagery. In general, the extracted image objets are readily be used in the GIS - ready vector format. However further investigations, developments and testing of methods in extracting accurate image objects are needed. In this paper, we h...

An experiment to study the impact of supplements upon the feeding behavior of dairy cattle was conducted at the Tasmanian Institute of Agriculture (TIA) Dairy Research Facility. Collar systems with 3-axis accelerometer and magnetometer were fitted to individual cows to infer their feeding behavior. We describe the solutions applied to correct for s...

In large-scale monitoring programs, such as in agriculture and environmental management, field robots have potentially lower cost and technical overhead than multiple static sensors. Robot sensing data, however, is not generally shared during, or after deployment. This is a wasted opportunity for enhancing autonomous decision making in the robot wi...

In this paper a novel data integration approach based on three environmental Sensors - Model Networks (including the Bureau of Meteorology-SILO database, Australian Cosmic Ray Sensor Network database (CosmOz), and Australian Water Availability Project (AWAP) database) has been proposed to estimate ground water balance and average water availability...

The purpose of this research was to develop a knowledge recommendation architecture based on unsupervised machine learning and unified resource description framework (RDF) for integrated environmental sensory data sources. In developing this architecture, which is very useful for agricultural decision support systems, we considered web based large-...

Technological progress has lead the sensor network domain to an era where environmental and agricultural domain applications are completely dependent on hydrological sensor networks. Data from the sensor networks are being used for knowledge management and critical decision support system. The quality of data can, however, vary widely. Existing aut...

The rapid access of sensor technology provides both challenges and opportunities to authenticated spatiotemporal data. Authentication can be assured by developing related ontologies. Ontology explicitly specifies shared conceptualization and formal vocabularies. In this paper, we proposed an environmental spatio-temporal ontology (ESTO) using unifi...

Before using remote data sources, or those from external organisations, it is important to establish if the source is fit for purpose. We have developed an approach to automatic sensor data annotation and visualisation that evaluates overall sensor network performance and data quality. The CSIRO’s South Esk hydrological sensor web combines data rel...

With the global availability and accessibility of environmental data sources it is possible to address the water related problems. Locally, in the Australian context, the water industry is in a unique position due to the extremes with a vast experience of drought and flood conditions. Water in Australia is a national priority and there is a need to...

Introduction With the development of land based, airborne and satellite sensors and the public availability of data produced from such sensors it is now possible to acquire the data and use for intended purposes. These data are geographic and essentially observations about geographic features or phenomena referred to as "geographic reality". Howeve...

The standard terms with known meanings are often called controlled vocabulary or light weight ontologies. These play vital role in the Linked Open Data cloud. These vocabularies capture a central notion of context for a specific domain in the knowledge cloud. The extra information is co-habited with these controlled vocabularies. This short paper s...

Large scale environmental knowledge integration and development of a knowledge recommendation system for the Linked Open Data Cloud using semantic machine learning approach was the main mission of this research. This study considered five different environmental big data sources including SILO, AWAP, ASRIS, MODIS and CosmOz complementary for knowle...

Born in the early 1980's as a multilingual agricultural thesaurus, AGROVOC has steadily evolved over the last fifteen years, moving to an electronic version around the year 2000, and embracing the Semantic Web shortly thereafter. Today AGROVOC is a SKOS-XL concept scheme published as Linked Open Data, containing links (as well as backlinks) and ref...

Ongoing robotic systems are primarily under- taken by large organisations and are closed sys- tems. We describe an extension to the cloud robotics concept that encourages reuse of sen- sor data collected from robots and sensor net- works, and eases the economic and technical burden on small industry and government or- ganisations. This paper descri...

Reusing domain vocabularies in the context of developing the knowledge based Linked Open data system is the most important discipline on the web. Many editors are available for developing and managing the vocabularies or Ontologies. However, selecting the most relevant editor is very difficult since each vocabulary construction initiative requires...

A vocabulary stores words, synonyms, word sense definitions (i.e. glosses), relations between word senses and concepts; such a vocabulary is generally referred as the Controlled Vocabulary (CV) if choice or selections of terms are done by domain specialists. A facet is a distinct and dimensional feature of a concept or a term that allows taxonomy,...

In the spite of explosive growth of the Internet, information relevant to users is often unavailable even when using the latest browsers. At the same time, there is an ever-increasing number of documents that vary widely in content, format, and quality. The documents often change in content and location because they do not belong to any kind of cen...

For the users' convenience of accessing the AGRIS resources quickly and using them fully, the paper decomposes the structure of AGRIS Search net, analyzes the users' requirement met for conducting a bilingual (ZH/EN) retrieval, the system function extensions based on AGRIS English retrieval system and the key issues which the core function module s...

AGROVOC plays a significant role in setting the standards as a common data model for representing and linking multilingual information from Agriculture, Forestry, Fisheries, Food and other related domains resources unequivocally. Researchers, librarians, terminologist and information managers from international organizations leverage on AGROVOC as...

Given that existing studies for query expansion techniques for Chinese-English are relatively few and their level of standardization low, in order to improve efficiency of Chinese-English cross-language retrieval, this paper discusses the design and implementation of a SOLR plug-in for Chinese-English cross-language query expansion based on SKOS th...

The AGROVOC multilingual thesaurus maintained by the Food and Agriculture Organisation (FAO) of the United Nations is now published as linked data. In order to reach this goal AGROVOC was expressed in Simple Knowledge Organisation System (SKOS) and its concepts provided with dereferenceable URIs. AGROVOC is now aligned with ten other multilingual K...

As part of the publication of the AGROVOC thesaurus as Linked Data (LD), AGROVOC is now mapped with six well-known thesauri in the agricultural domain, i.e., EUROVOC, NALT, GEMET, STW, LCSH, RAMEAU. To find matching candidates, known matching algorithms discussed in the literature and available from public API were used. Results were evaluated by a...

The Food and Agriculture Organization of the United Nations (FAO) is recognized as an information and knowledge-base organization. FAO's activities comprise four main areas which are closely related to various aspects of information and knowledge: capture and analyze, disseminate and share, localize and provide. The goal of developing and maintaini...

The AGROVOC is multilingual structure thesaurus for Agricultural domain. It has already been mapped with several vocabularies, for example, AGROVOC-CAT, AGROVOC-NALT, and AGROVOC-SWD. Although these vocabularies already contained a good portion of non-preferred terms, the terms are collected under the literary warrant and institutional warrant prin...

A vocabulary stores words, synonyms, word sense definitions (i.e. glosses), relations between word senses and concepts; such a vocabulary is generally referred to as the Controlled Vocabulary (CV) if choice or selections of terms are done by domain specialists. A facet is a distinct and dimensional feature of a concept or a term that allows taxonom...

A vocabulary stores words, synonyms, word sense definitions (i.e. glosses), relations between word senses and concepts; such a vocabulary is generally referred to as the Controlled Vocabulary if choice or selections of terms are done by domain specialists. In our case, we create and match two controlled vocabularies by using their concept facet. Th...

There is a huge amount of information scattered on the World Wide Web. As the information flow occurs at a high speed in the WWW, there is a need to organize it in the right manner so that a user can access it very easily. Previously the organization of information was generally done manually, by matching the document contents to some pre-defined c...

The underlying idea of the Semantic Web is that web content should be expressed not only in natural language but also in a language that can be unambiguously understood, interpreted and used by software agents, thus permitting them to find, share and integrate information more easily. The central notion of the Semantic Web's syntax are ontologies,...