Performance of SARAL/AltiKa satellite altimetry mission over the Strait of Malacca and the South China Sea

Satellite altimetry faces challenges when attempting to monitor sea surface heights (SSHs) in coastal zones due to the rapid changes in sea state and land contamination within altimeter footprints. This leads to the lack of high resolution and data quality observations, thus creating a significant gap in the data availability over the coast. A new generation of SARAL/AltiKa satellite altimetry mission with Ka-band promises a significant refinement of coastal altimetry data and provides unprecedented level of ocean SSH data as close as 10 km from the coastline. In this paper, selective passes of SARAL/AltiKa over the Strait of Malacca and the South China Sea were chosen to examine the performance of SSH data quality over the coast, and relatively compared with Jason-2 satellite altimetry mission

Credibility assessment and labelling of map mashups

The Web 2.0 revolution has changed the culture of mapping by opening it up to a wider range of users and creators. Map mashups, in particular, are being widely used to map variety of information. There is, however, no gatekeeper to validate the correctness of the information presented. The purpose of this research was to understand better what it is that influence users’ perceived credibility and trust within a map mashup presentation and to support the future implementation of automated credibility assessment and labelling of map mashup applications. This research has been conducted in three stages using mixed method approaches. The objective of the first stage was to examine the influence of metadata related to sources, specifically the map producer and map supplier, on respondents’ assessment of the credibility of map mashup information. The findings indicate a low influence of the tested metadata and a high influence of visual cue elements on users’ credibility assessment. Only half of the respondents used the metadata whilst the other half did not include it in their assessment. These findings became the basis of stage two, which was to examine the influence of colour coded traffic light (CCTL) labelling on respondents’ assessment of credibility. From the findings, the probability of respondents making informed judgements by choosing a high credibility map based on this rating label (CCTL) was three times higher than where only the metadata was presented. The third stage was to propose a conceptual framework to support the implementation of automated credibility labelling for map mashup applications. The framework was proposed on the basis of thorough reviews from the literature. The suggested parameters and approaches are not limited to assess credibility of information in the map mashup context, but could be applied to other Web GIS applications

Credibility assessment and labelling of map mashups

The Web 2.0 revolution has changed the culture of mapping by opening it up to a wider range of users and creators. Map mashups, in particular, are being widely used to map variety of information. There is, however, no gatekeeper to validate the correctness of the information presented. The purpose of this research was to understand better what it is that influence users’ perceived credibility and trust within a map mashup presentation and to support the future implementation of automated credibility assessment and labelling of map mashup applications. This research has been conducted in three stages using mixed method approaches. The objective of the first stage was to examine the influence of metadata related to sources, specifically the map producer and map supplier, on respondents’ assessment of the credibility of map mashup information. The findings indicate a low influence of the tested metadata and a high influence of visual cue elements on users’ credibility assessment. Only half of the respondents used the metadata whilst the other half did not include it in their assessment. These findings became the basis of stage two, which was to examine the influence of colour coded traffic light (CCTL) labelling on respondents’ assessment of credibility. From the findings, the probability of respondents making informed judgements by choosing a high credibility map based on this rating label (CCTL) was three times higher than where only the metadata was presented. The third stage was to propose a conceptual framework to support the implementation of automated credibility labelling for map mashup applications. The framework was proposed on the basis of thorough reviews from the literature. The suggested parameters and approaches are not limited to assess credibility of information in the map mashup context, but could be applied to other Web GIS applications

Face recognition on bag locking mechanism

With the emergent of biometric technology, people are no longer afraid to keep their important things in the safe box or room or even facility. This is because; human beings have unique features that distinguish them with other people. The scheme is based on an information theory approach that decomposes face images into a small set of characteristic feature images called ‘Eigenfaces’, which are actually the principal components of the initial training set of face images. In this report, thorough explanation on design process of face recognition on bags locking mechanism will be elucidated. The results and analysis of the proposed design prototype also presented and explained. The platform for executing the algorithm is on the Raspberry Pi. There are two artificial intelligent techniques applied to manipulate and processing data which is fuzzy logic and neural networks. Both systems are interdependent with each other, so that it can calculate and analyse data precisely. The receive image from the camera is analysed through the Eigenfaces algorithm. The algorithm is using Principal Component Analysis (PCA) method which comprise of artificial neural network paradigm and also statistical paradigm

A conceptual model of the automated credibility assessment of the volunteered geographic information

The use of Volunteered Geographic Information (VGI) in collecting, sharing and disseminating geospatially referenced information on the Web is increasingly common. The potentials of this localized and collective information have been seen to complement the maintenance process of authoritative mapping data sources and in realizing the development of Digital Earth. The main barrier to the use of this data in supporting this bottom up approach is the credibility (trust), completeness, accuracy, and quality of both the data input and outputs generated. The only feasible approach to assess these data is by relying on an automated process. This paper describes a conceptual model of indicators (parameters) and practical approaches to automated assess the credibility of information contributed through the VGI including map mashups, Geo Web and crowd-sourced based applications. There are two main components proposed to be assessed in the conceptual model-metadata and data. The metadata component comprises the indicator of the hosting (websites) and the sources of data / information. The data component comprises the indicators to assess absolute and relative data positioning, attribute, thematic, temporal and geometric correctness and consistency. This paper suggests approaches to assess the components. To assess the metadata component, automated text categorization using supervised machine learning is proposed. To assess the correctness and consistency in the data component, we suggest a matching validation approach using the current emerging technologies from Linked Data infrastructures and using third party reviews validation. This study contributes to the research domain that focuses on the credibility, trust and quality issues of data contributed by web citizen provider

The spatial epidemiology of jackfruit pest and diseases: a review

Jackfruit is identified as targeted produced for premium fruit and vegetable (EPP 7). Meanwhile in Johor, jackfruit is the third biggest fruit produced in 2016. Jackfruit contains a lot of benefits which certainly good for living things and have been used in various sector such as medicine, food, anti-bacterial and anti-oxidant, antifungal effect, immunomodulatory effect and else. However, the existence of pests and diseases have threatened the productivity of jackfruit plant particularly in tropical countries including Malaysia. There are many factors that can affect the occurrence of pests and plant diseases of jackfruit such as shoot borers, bark borers, mealy bug and scale insects, blossoms and fruit rots and bacterial die-back. Several studies have been devoted to model the plant pests and diseases epidemiology, though the contexts that focus in tropical environment and jackfruit plant are limited. Therefore, this paper aims to discuss abiotic factors and spatial methods that have been used to define dispersal pattern and relationship between abiotic factors including major climatic variables with plant pests and diseases occurrence data, particularly in tropical climate. This paper could be used as a basis to understand the epidemiological models in combating pest and plant disease and to support towards the effective management of jackfruit pests and diseases in tropical countries, particularly Malaysia

Travel Time Patterns of Students with Special Needs to Special Education Integrated Program-based Schools in Johor Bahru, Malaysia: An Initial Finding

Education for all has been a global priority to ensure that all students have equal access to high-quality education regardless of disability or minority status. In Malaysia, the special education integrated programme (SEIP) is designed to close the inequality gap by integrating special education into existing government and vernacular schools. Numerous studies examine the travel patterns of regular students to school, resulting in a dearth of research on the travel patterns of special needs students to formal school. Thus, this paper uses spatial analysis to demonstrate the travel patterns of students with special needs to SEIP schools. This paper demonstrated that the majority of SEIP schools in the Johor Bahru district can be reached within a 5 to 10 minute drive. Individual travel time analyses between origin (home) and destination (current versus ideal school) indicate that the majority of secondary school students attend their ideal neighbourhood schools, but not primary school students. The average travel time is 12 minutes, with 89 percent of them travelling by car. The travel time clustering analysis revealed that the majority of students who commute to school live within a radius of 2 to 10 km and within a time range of 10 to 20 minutes. However, a small group of these special students commutes to school for 20 to 25 minutes each day. The preliminary findings can be improved and may aid in the design of carpool and transit schedules, as the majority of these students heavily rely on their cars for transportation. The effects of the lengthy commute to school could be further investigated, as these children are vulnerable and any negative impact on their mental, emotional, or physical development must be addressed

Engaging the flood volunteers through mobile and web based neogeography platforms for efficient aid and relief coordination

The recent flood disaster that hits certain areas in Malaysia has given massive loss to the affected victims and huge damaged to certain areas. Nevertheless, the instant aid and relief supplies and supports from various sources including individuals have reduce the flood victims’ burden at some extent. However, there is an ar-gument that arises on the effectiveness of the aid and relief coordination and distribution to the affected area. This paper proposed the use of mobile and Web based Neogeography platforms to collectively centralize the aid and relief activities data among volunteers (that draw from NGOs, ad-hoc volunteer teams and individual volunteers) so that it could be shared to other volunteer teams and authority to plan for aid and relief disaster recovery activities. The proposed platforms are anticipated able to assist the authorities for effectively coor-dinating the aid and relief actions that involving various parties

Robotic arm control using internet of things (IoT)

Robotic arm is a reprogrammable and multifunctional manipulator design to assist human in various surroundings. It is able to overcome human inefficiency in performing repetitive task such as pick and place operation. Thus, industrial in assembly and manufacturing have widely integrated robotic arm into their assembling line to overcome the problem of human inefficiency. Internet of things (IoT) allow data to be exchange between devices through the connection of many devices. The integration of internet of things with robotic arm allows smart industry to be realized. The purpose of this research is to design and build a three degree of freedom robotic arm with a mechanical gripper. The robotic arm can be controlled remotely through android mobile device to perform pick and place operation while Matlab provides the graphical movement of the robotic arm as a feedback

Tweet data extractor for creating a twitter traffic map mashup

Over recent years, there has been a growth of interest in the use of social media including Facebook and Twitter by the authorities to share and updates current information to the general public. The technology has been used for a variety of purposes including traffic control and transportation planning. There is a concern that the use of new technologies, including social media will lead to data abundance that requires effective operational resources to interpret the big data. This paper proposes a tweet data extractor to extract the traffic tweet by the authority and visualise the reports and mash up on top of online map, namely Twitter map. Visualisation of traffic tweet on a map could assist a user to effectively interpret the text based Twitter report by a location based map viewer. Hence, it could ease the process of planning itinerary by the road users