Data centric trust evaluation and predication framework for IoT

Application of trust principals in internet of things (IoT) has allowed to provide more trustworthy services among the corresponding stakeholders. The most common method of assessing trust in IoT applications is to estimate trust level of the end entities (entity-centric) relative to the trustor. In these systems, trust level of the data is assumed to be the same as the trust level of the data source. However, most of the IoT based systems are data centric and operate in dynamic environments, which need immediate actions without waiting for a trust report from end entities. We address this challenge by extending our previous proposals on trust establishment for entities based on their reputation, experience and knowledge, to trust estimation of data items [1-3]. First, we present a hybrid trust framework for evaluating both data trust and entity trust, which will be enhanced as a standardization for future data driven society. The modules including data trust metric extraction, data trust aggregation, evaluation and prediction are elaborated inside the proposed framework. Finally, a possible design model is described to implement the proposed ideas

Machine Learning based Trust Computational Model for IoT Services

The Internet of Things has facilitated access to a large volume of sensitive information on each participating object in an ecosystem. This imposes many threats ranging from the risks of data management to the potential discrimination enabled by data analytics over delicate information such as locations, interests, and activities. To address these issues, the concept of trust is introduced as an important role in supporting both humans and services to overcome the perception of uncertainty and risks before making any decisions. However, establishing trust in a cyber world is a challenging task due to the volume of diversified influential factors from cyber-physical-systems. Hence, it is essential to have an intelligent trust computation model that is capable of generating accurate and intuitive trust values for prospective actors. Therefore, in this paper, a quantifiable trust assessment model is proposed. Built on this model, individual trust attributes are then calculated numerically. Moreover, a novel algorithm based on machine learning principles is devised to classify the extracted trust features and combine them to produce a final trust value to be used for decision making. Finally, our model’s effectiveness is verified through a simulation. The results show that our method has advantages over other aggregation methods

AI and Blockchain enabled Edge of Things with Privacy Preserving Computation

Recent research has brought cloud, edge, and Internet of Things (IoT) technologies together to develop integrated platforms for utilizing resource-rich clouds to support resource-constrained IoT applications. However, their success is limited, in particular, they are lack of efficient intelligence for data processing and service operations as well as dynamic and trustworthy service composition across multi-layers from IoT devices to clouds, which are important for IoT applications. This paper will thus propose an innovative platform for composing smart and trustworthy edges (ROOF (Real-time Onsite Operations Facilitation) plus Fog) of things to support applications ranging from ultra-low delay and lightweight to complex services. To achieve this goal, the research employs the microservice concept to decompose applications into lightweight services located from the edge of things to cloud data centers. Further, inspired by the artificial intelligence and blockchain technologies, this work proposes a novel approach for composing microservices that will provide prosumer-driven, decentralized and autonomous service composition while preserving the privacy of the participating stakeholders

EFFECT OF URBANIZATION ON THE ADOPTION OF AGRIENVIRONMENTAL PRACTICES BY CROP AND LIVESTOCK FARMS IN CANADA

This paper investigates the extent to which agri-environrnental practices(AEPs) adopted by Canadian crop livestock farms were adjusted to thepresence of urbanization. Seven AEPs: (1) water management; (2) wildlifeconservation; (3) pesticide management; (4) fertilizer management; (5)manure management; (6) nutrient management; (7) grazing management,were considered.It was hypothesized that farmers close to urbanized areas are more likely toadopt AEPs to minimize any conflict with their non-farm neighbors. The keyexplanatory variables included in the seven empirical models, whichcomprised of level of adoption of an AEP as the dependant variable, toexplain the degree of urbanization were: (the distance (km) "as the crowflies" from the geographical centre of each Census Sub-Division to that of thenearest Census Metropolitan Area in Canada, and (2) population density(number of persons/krrr') in the locale of each farming operation. In addition,a number of other standard control variables influencing the adoption ofAEPs (e.g. type and size of farm, age of operator, ownership, income etc.)were also included.The data from the Statistics in Canada collected through the "FarmEnvironmental Management Survey - 2001" (n=16053) were used. Theresults based on Logit Regression analysis imply that there are significantdifferences with respect to the adoption of AEPs in crop and livestock farmslocated in low versus high population density regions. The results imply inturn that farmers in urbanized areas face greater social and economicconstraints, and thus likely higher costs, than their counterparts in more ruralareas .

High-frequency Noise Removal of Audio Files using Daubechies Wavelet Transform

In general, audio signals are contaminated with various types of noise. This paper presents a novel signal processing method developed for high-frequency noise elimination using wavelet transforms. As a continuation of a previous study that used Fourier transform for noise removal in audio files, in this study Daubechies wavelets were used to reduce computational complexity and achieve better noise reduction performances. Compared to the Fourier transform, the Daubechies wavelet transform method removes the noise in each signal while preserving its vital characteristics. The suitable level of the Daubechies wavelet for noise removal in each channel was obtained using a trial-and-error approach. It was identified that the ideal range for the level of the Daubechies wavelets for noise removal is between 17 and 20. Moreover, unlike the Fourier transform, the Daubechies wavelet transform demonstrates a proficient capacity in eliminating noise from data point that lies completely outside the rest in the audio data set. Wolfram Mathematica 12.3 software package was used to complete this research. This method can be applied toconserve vintage audio recordings originally recorded in cassettes and spools. Keywords: Digital Signal Processing, Wavelet Transforms, Daubechies Wavelet Transform, Fourier Transforms, Noise Remova

An empirical investigation on factors affecting coconut growers in the Kurunegala district to adopt integrated pest management techniques

The Coconut Development Office Divisions in the Kurunegala district were in the process of introducingIntegrated Pest Management (lPM) techniques to the coconut growers in order to control the majorpest and disease outbreaks of coconut plantations in the district. This study assesses the factorsaffecting these coconut growers to be innovative in adopting these IPM techniques in the cultivation.The Choice Model used in consumer economics (McFadden 1974) was used as the theoretical baseto explain this behaviour. There were] 27 coconut growers belong to four regions, namelyDarnbadeniya, Kudagalgamuwa, Weerambugedara, and Wellawa who had received a formal educationon the use of IPM techniques in this respect from an Extension Officerls attached to the CoconutCultivation Board were selected to collect data during the April to June in 2005. The Ordered LogisticRegression techniques were used to estimate the coefficients of empirical model, in which fivedependentvariables were developed to reflect the time taken by each grower to adopt at least twoIPM techniques in the cultivation effectively, where the "least" and "most" time takers were namedas "innovators" and "laggards", respectively. The results based on Logits and Marginal Probabilitiessuggest that factors such as age, education, income, and time commitment to the land had a significantand relatively higher impact on grower to be an "innovator". It also revealed that land size, availabilityof credit and skilled labor have no significant impact 011 this behaviour.

FARMER ATTITUDES TOWARDS ADOPTION OF SUSTAINABLE PROTECTION TECHNOLOGIES: THE CASE OF INTEGRATED PEST MANAGEMENT IN VEGETABLE CULTIVATIONS IN SRI LANKA

This study examines empirically the extent to which vegetable cultivatingfarmers in Sri Lanka are willing to adopt effective, economical andsustainable crop protection technologies such as Integrated Pest Management(lPM) instead of applying solely chemical pesticides to control pests. It usesprimary data collected through a series of personnel interviews with arandomly selected sample of vegetable farmers (n = 100) that practicechemical control measures in the Kurunegala and Puttalam districts in theWayamba Province from May to July in 2005.The behavioural change in farmer attitudes and perceptions towards adoptionof environmentally-friendly IPM techniques instead of applying chemicals onthe vegetable cultivation on a regular basis were captured by means of twoindexes - Additive Index (AI) and a Multiplicative Index (MI), which usedthe scores given by participants to the survey to a set of attitudinal statements(n = 17) explaining this behaviour on a Likert scale. The outcome of AI andMI were in turn modelled with the farmer's socio economic characteristics,including the age, sex, level of education, income, managerial time,experience in farming, extent of land allocated for cultivation, crop type,availability of credit and extension facilities etc. to test significance of thesefactors on this behaviour. The results suggest that many of these have asignificant impact on the farmer's degree of responsiveness towards adoptionof sustainable agricultural practices. The outcome of analysis highlights theneed of provision of appropriate private and regulatory incentives for farmersto change their behaviour in this respect

Distribution and Abundance of the Blue Whale (Balaenoptera musculus indica) off Sri Lanka during the Southwest Monsoon 2018

Blue whales Balaenoptera musculus are the most abundant and widely distributed cetacean species in Sri Lankan waters. A vessel-based opportunistic line transect survey focusing on marine mammals was conducted in Sri Lankan waters between 24 June to 12 July 2018, while an ecosystem survey was performed by the R/V Dr. Fridtjof Nansen. The entire transect length was 2090 km within an area of 3895 km2. Overall, 72% (n = 57) of blue whale observations were group assemblages ranging between 1 and 5 individuals out of a total of 79 sightings. The largest aggregations of blue whales were recorded at the intersection of the submarine canyon off the coastline of Mirissa and busy shipping lanes between Dondra Head and Galle, where previous ship strikes were recorded. Overall, the average observed group size was 2.64 (CV, 12.34%; 95% CI, 2.07–3.38), the average group density was 0.0029 km−2 (CV, 35.96%; 95% CI, 0.00145–0.00610), and the total blue whale abundance within the survey area was 513 individuals (CV, 38.02%; 95% CI, 243–1083). These survey results fill vital knowledge gaps regarding the abundance and distribution of blue whales in Sri Lanka, which is essential for the establishment of management and conservation strategies.publishedVersio

THE ROLE OF ENVIRONMENT REGULATION ON FIRMS’ PRIVATE ACTION ON ENVIRONMENTAL QUALITY: CASE OF NON-ADOPTION OF SOLID WASTE MANAGEMENT PRACTICES BY FOOD PROCESSING SECTOR IN SRI LANKA

The purpose of this study was to examine empirically extent to which the regulatory framework and the legal system on environment have an impact on firms‟ private action on environment quality using the case of Sri Lankan food processing firms‟ non-compliance to the 9 different solid waste management practices (SWMPs) recommended by the Ministry of Environment for a firm to adopt based on the production and processing activities it undertakes. The perceptions of managers of 160 firms that did not adopt a single SWMP were assessed by means of an index – “Environment Regulation Responsiveness Index” (ERRI) of which the values reflects the relative strength of the firm in concern perceived on the environmental regulation (i.e.  -1.0 the least to 1.0 the most responsive). The outcome of analysis highlights that the magnitude of ERRI of the majority of firms was relatively low (i.e. in between -0.5 to 0.5), especially for the small scale firms, suggesting that firms did not consider the government regulation as a promising factor to act on the environment. This calls for a critical revision and adjustments to the policy on environmental quality management both at the national and provincial level in order to promote voluntary action by firms