Secure Data Provenance in Home Energy Monitoring Networks

Smart grid empowers home owners to efficiently manage their smart home appliances within a Home Area Network (HAN), by real time monitoring and fine-grained control. However, it offers the possibility for a malicious user to intrude into the HAN and deceive the smart metering system with fraudulent energy usage report. While most of the existing works have focused on how to prevent data tampering in HAN's communication channel, this paper looks into a relatively less studied security aspect namely data provenance. We propose a novel solution based on Shamir's secret sharing and threshold cryptography to guarantee that the reported energy usage is collected from the specific appliance as claimed at a particular location, and that it reflects the real consumption of the energy. A byproduct of the proposed security solution is a guarantee of data integrity. A prototype implementation is presented to demonstrate the feasibility and practicality of the proposed solution

Classification of Malaysian students' tendency in choosing TVET after secondary school using analytic hierarchy process and decision tree model: a case study in northern part of Malaysia

Technical and Vocational Education and Training (TVET) programme is a channel to produce skilled workers because it provides theoretical knowledge and practical skills for students. However, the current enrolment in TVET programme among secondary school leavers is still low. Therefore, this study aims to uncover the factors that affect students’ tendency in enrolling TVET programme. The perception of students, public, instructors, employers, parents, besides facility, cost and policy have been discovered as the factors in this study. In the first phase, Analytic Hierarchy Process (AHP) is used to determine the level of importance of each factor. Based on the outcome of the first phase, various Decision Tree models are developed to classify the students’ tendency in enrolling TVET programme. The respondents in this study are students from the TVET programme and secondary schools. The result of AHP shows that the factor of parents is the most important factor, followed by instructors, employers, students, cost, facility, policy and public. Then, four types of Decision Tree namely ID3, CART, C4.5 and CHAID are generated to classify the students’ tendency based on the four most important factors (parents, instructors, employers and students). The ID3 tree in 5-fold Cross Validation is selected as the best model due to its low misclassification rate (0.1355), high accuracy rate (0.8645), high precision rate (0.9143), high recall rate (0.8828), and high F-score (0.8983) with tree depth of 7 and maximum branches of 3. Hence, in the future, this model can be used to classify the students’ tendency enrolling in TVET programme. It can also assist the government to implement strategic plans such as organizing campaigns or providing on-the-job training to students in the TVET programme. Therefore, skilled workers that can adapt to new technology and innovation could be produced

Microstructure of brushite crystals prepared via high internal phase emulsion

For the first time, various microstructures of calcium phosphates were successfully synthesized using a high internal phase emulsion process. The crystals were possessed in the brushite crystalline phase. The morphology of the crystals was influenced by the variables related to the emulsion process route, which consisted of flakes, dendrites and particulates structures

Inorganic Nanostructures Decorated Graphene

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The Influence of Type 2 Diabetes and Glucose-Lowering Therapies on Cancer Risk in the Taiwanese

Objective. To investigate the association between type 2 diabetes, glucose-lowering therapies (monotherapy with either metformin, sulphonylurea or insulin) and cancer risk in Taiwan. Methods. Using Taiwan's National Health Research Institutes database of 1,000,000 random subjects from 2000–2008, we found 61777 patients with type 2 diabetes (age ≥20 years) and 677378 enrollees with no record of diabetes. Results. After adjusting for age and sex, we found patients with diabetes to have significantly higher risk of all cancers (OR: 1.176; 95% CI: 1.149–1.204, P < 0.001). Diabetic patients treated with insulin or sulfonylureas had significantly higher risk of all cancers, compared to those treated with metformin (OR: 1.583; 95% CI: 1.389–1.805, P < 0.001 and OR: 1.784; 95% CI: 1.406–2.262, P < 0.001). Metformin treatment was associated with a decreased risk of colon and liver cancer compared to sulphonylureas or insulin treatment. Sulfonylureas treatment was associated with an increased risk of breast and lung cancer compared to metformin therapy. Conclusions. Taiwanese with type 2 diabetes are at a high risk of breast, prostate, colon, lung, liver and pancreatic cancer. Those treated with insulin or sulfonylureas monotherapy are more likely to develop colon and liver cancer than those treated with metformin

Preparation of highly water dispersible functional graphene/silver nanocomposite for the detection of melamine

A stable aqueous suspension of a functional graphene/silver (FG/Ag) nanocomposite was prepared by an environmentally friendly hydrothermal method. The precursor, functional graphene oxide (FGO), was prepared by covalent functionalisation of graphene oxide (GO) with a hydrophilic organosilane, N-(trimethoxysilylpropyl) ethylenediaminetriacetic acid trisodium salt (TETA). The attachment of functional groups on the GO surface maintained the aqueous stability of the FG/Ag nanocomposite even after the hydrothermal reduction. Field emission scanning electron microscopy (FESEM) images illustrated a uniform distribution of Ag nanoparticles on the FG surface. The surface enhanced Raman spectroscopy (SERS) activity of the nanocomposite was investigated using p-aminothiophenol (p-ATP) and melamine which can be detected as low as 2 × 10−8 and 2 × 10−7 M, respectively. The impressive water stability and the high SERS sensitivity of the FG/Ag nanocomposite make it a suitable substrate for trace analysis of a variety of drugs, additives or organic contaminants in water. The nanocomposite also showed a positive inhibition effect against the growth of Escherichia coli bacteria, eliminating the possibility of bacterial contamination of the sensor, thus prolonging the shelf-life of the sensing device

One-step size-controlled synthesis of functional graphene oxide/silver nanocomposites at room temperature

A stable aqueous suspension of functional graphene oxide/silver nanocomposite (FGO/Ag) was prepared in an alkaline medium by a simple room temperature stirring method. Functional graphene oxide (FGO) served as substrate, reducing agent and stabilizer for the silver nanoparticles (Ag-NPs). The pH of the solution played a prominent role in the formation of the Ag-NPs. The morphology of the nanoparticles (NPs) could be controlled by adjusting the pH between 9.51 and 12.62 by adding NaOH solution. The aqueous stability of the nanocomposites was greatly improved by the attached functional groups. UV-visible spectroscopy, transmission electron microscopy (TEM) and field emission scanning electron microscopy (FESEM) images suggested the formation of spherical, Ag-NPs with a narrow size distribution at pH 11.40. The nanocomposites showed high bactericidal activity against Escherichia coli bacteria and also enhancement in Raman intensity due to surface enhanced Raman scattering (SERS), which was found to be dependent on the size distribution of the Ag-NPs. This work provides a simple, scalable and environmentally friendly approach to the preparation of a FGO/Ag nanocomposite with promising antibacterial and SERS properties