Software design pattern mining using classification-based techniques

Design patterns are often used in the development of object-oriented software. It offers reusable abstract information that is helpful in solving recurring design problems. Detecting design patterns is beneficial to the comprehension and maintenance of object-oriented software systems. Several pattern detection techniques based on static analysis often encounter problems when detecting design patterns for identical structures of patterns. In this study, we attempt to detect software design patterns by using software metrics and classification-based techniques. Our study is conducted in two phases: creation of metrics-oriented dataset and detection of software design patterns. The datasets are prepared by using software metrics for the learning of classifiers. Then, pattern detection is performed by using classification-based techniques. To evaluate the proposed method, experiments are conducted using three open source software programs, JHotDraw, QuickUML, and JUnit, and the results are analyzed.     

The market for wireless electricity: The case of India

A wireless revolution has transformed telecoms in India and in other emerging markets. The electricity market, on the other hand, remains underdeveloped. We define Wireless Electricity as renewable energy produced within a few hundred meters of the point of consumption. A wireless revolution in electricity would solve the problem of electricity deficit, empower people at the bottom of the pyramid and mitigate the environmental impact of bringing hundreds of millions out of poverty as the Indian economy grows. Renewables are technically proven and economically viable in certain situations, but their use remains peripheral. The stark difference in the diffusion patterns in telecoms and electricity has been ignored by leaders in government, business and academics. We present common frameworks to explain the different directions of reform in telecoms and electricity. We explain some of the dynamics which prevent the diffusion of Wireless Electricity. We use a causal loop diagram to explain the status quo in the off-grid electricity market and propose changes which will lead to the formation of a market for Wireless Electricity. India has the entrepreneurial talent to develop this market—and the largest number of potential customers. The world will benefit as a result.     

Photovoltaic effect in arylenevinylene-co-pyrrolenevinylene (AVPV)

Arylenevinylene-co-pyrrolenevinylene (AVPV) is a promising candidate amongst the group of new photovoltaic materials. It is a low band gap organic material with a band gap of 1.84 eV and absorbs sunlight in 300-700 nm range. In this paper, we demonstrate the photovoltaic effect in an organic bulk heterojunction photovoltaic device based on the blend of AVPV as an electron donor and [6,6]-phenyl-C₆₁ butyric acid methyl ester (PCBM) as the acceptor. The short-circuit current density of the device was of the order of 0.55 μA cm⁻² with an open-circuit voltage of 0.7 V, measured under 1 sun illumination of AM 1.5 through a calibrated solar simulator. Fill factor was estimated to be 12%. Further, the tests conducted after 2 weeks showed that short-circuit current was 0.21 μA cm⁻² and open-circuit voltage was 0.5 V with a fill factor of 9.8%, suggesting the possibility of stable AVPV-based organic solar cell (OSC).     

Emission measurements from a crude oil tanker at sea

This work presents an all-inclusive set of regulated and nonregulated emission factors for the main propulsion engine (ME), auxiliary engine (AE) and an auxiliary boiler on a Suezmax class tanker while operating at sea. The data include criteria pollutants (carbon monoxide, nitrogen oxides, sulfur oxides, and particulate matter), a greenhouse gas (carbon dioxide), the principal speciated hydrocarbons needed for human health risk assessments, and a detailed analysis of the PM into its primary constituents (ions, elements, organic, and elemental carbon). Measurements followed ISO 8178-1 methods with modifications described in the paper. The vessel burned two fuels: a heavy fuel oil in the ME and boiler and a distillate fuel in the AE. The weighted NO(x) emissions for the ME and AE are 19.87 +/- 0.95 and 13.57 +/- 0.31 g/kWh, respectively. The weighted PM mass emissions factor is 1.60 +/- 0.08 g/kWh for the ME and 0.141 +/- 0.005 g/kWh for the AE, with the sulfate content of the PM being the root cause for the difference. For the ME, sulfate with associated water is about 75% of total PM mass, and the organic carbon ranges from 15 to 25% of the PM mass. A deeper analysis showed that the conversion of fuel sulfur to sulfate in the ME ranged from 1.4to 5%. This article also provides emission factors for selected polycyclic aromatic hydrocarbons, heavy alkanes, carbonyls, light hydrocarbon species, metals, and ions for the ME, AE, and the boiler.