Featuring of Electricity Consumption Behavior towards Big-Data Applications

There is growing interest in discerning behaviors of electricity users in both the residential and commercial sectors. With the advent of high-resolution time-series power demand data through advanced metering. Large volumes of smart meter data gives opportunity for load serving entities to improve their knowledge on customers electricity consumption behavior via load profiling. This paper implements a novel approach for clustering of electricity consumption behavior dynamics.first for each individual customer symbolic aggregate approximation(SAX) to reduce the scale of the data set,and time based Markov model is applied to model the dynamics of electricity consumption, transforming the large set of load curves to several state transition matrixes. A density-based clustering technique, CFSFDP, is performed to discover the typical dynamics of electricity consumption and segment customers into different groups

Personal Assistance using Artificial Intelligence for Computers

Machine makes life easier so men always keen to develop new machine and software which makes life easier. Since the invention of computers or machines, their capability to perform various tasks went on growing exponentially. Humans have developed the power of computer systems in terms of their diverse working domains, their increasing speed, and reducing size with respect to time. So the objective of the proposed work is to control the computer in easier way that is through the voice commands. The system is based on one of the major application of artificial intelligence “Speech Recognition”. This Software “Personal assistance for computer using artificial intelligence” can be used as personal assistance to user working in personal computer. Software with cognitive abilities similar to those of the human brain so that it can understand human language thinks, infer, reason and learn. It use the android application to take the input from user and the command given by the user will sent through the Bluetooth for the MATLAB interface in computer. The command is processed and the action for specific command is executed. So in simple way through voice command we can do the work in PC

Incidence of cardiovascular diseases and associated risk factors among subjects with type 2 diabetes – An 11-year follow up study

Aims: This study was planned to assess the development of cardiovascular disease (CVD) events over an 11-year period and to identify the associated risk factors that could predict the onset of CVD among subjects with type 2 diabetes. Methods: Retrospective data of 249 patients (M:F 149:100) with type 2 diabetes, from a cohort of 7800 patients, attending a tertiary care center for diabetes from January 2000 to December 2011 were retrieved and analyzed for this study. Sociodemographic and habitual risk factors, baseline diabetes duration, HbA1c and time of onset of CVD and its risk factors were collected from case records. Person-years method was used to calculate incident rate of CVD. Binary logistic regression analyses were done to identify predictors associated with CVD and its risk factors. Results: Incidence of CVD among subjects with diabetes was 5.6 cases/1000 person-years. Nearly 60% developed hypertension and dyslipidemia or both during the 11-year period. The most common complication was neuropathy (14.4%). Smoking [OR (95%CI)] [9.26 (1.6–54.9)] (p = 0.014) and heavy alcohol consumption [8.7 (1.1–69.8)] (p = 0.04) were significantly associated with CVD. Higher BMI was significantly associated with hypertension and dyslipidemia [2.4 (1.3–4.3)] (p = 0.003). Conclusions: Smoking and heavy alcohol consumption were significantly associated with CVD, and increased BMI was significantly associated with hypertension and dyslipidemia among subjects with type 2 diabetes in this study population. These findings emphasize the need for early identification and modification of risk factors associated with CVD events in patients with diabetes