Solar energy in asia, in Kobe, Japan, september 1989 : Reports from ISES solar world congress and from study visits in India and Pakistan

The ISES Solar World Congress Clean and Safe Energy Forever was held in Kobe, Japan, September 4-8, 1989. Short impressions from the conference and the simultaneous exhibition are given. On our (separate) ways to Kobe, Eriksson visited institutions in the Bombay, India area, and Broman one institution in Islamabad, Pakistan. Accounts of these visits are given. Three papers presented in Kobe are included in an Appendix.

Health care providers' perceptions of and attitudes towards induced abortions in sub-Saharan Africa and Southeast Asia : a systematic literature review of qualitative and quantitative data.

BACKGROUND: Unsafe abortions are a serious public health problem and a major human rights issue. In low-income countries, where restrictive abortion laws are common, safe abortion care is not always available to women in need. Health care providers have an important role in the provision of abortion services. However, the shortage of health care providers in low-income countries is critical and exacerbated by the unwillingness of some health care providers to provide abortion services. The aim of this study was to identify, summarise and synthesise available research addressing health care providers' perceptions of and attitudes towards induced abortions in sub-Saharan Africa and Southeast Asia. METHODS: A systematic literature search of three databases was conducted in November 2014, as well as a manual search of reference lists. The selection criteria included quantitative and qualitative research studies written in English, regardless of the year of publication, exploring health care providers' perceptions of and attitudes towards induced abortions in sub-Saharan Africa and Southeast Asia. The quality of all articles that met the inclusion criteria was assessed. The studies were critically appraised, and thematic analysis was used to synthesise the data. RESULTS: Thirty-six studies, published during 1977 and 2014, including data from 15 different countries, met the inclusion criteria. Nine key themes were identified as influencing the health care providers' attitudes towards induced abortions: 1) human rights, 2) gender, 3) religion, 4) access, 5) unpreparedness, 6) quality of life, 7) ambivalence 8) quality of care and 9) stigma and victimisation. CONCLUSIONS: Health care providers in sub-Saharan Africa and Southeast Asia have moral-, social- and gender-based reservations about induced abortion. These reservations influence attitudes towards induced abortions and subsequently affect the relationship between the health care provider and the pregnant woman who wishes to have an abortion. A values clarification exercise among abortion care providers is needed.

Triggering Solar-Powered Vehicle Activated Signs using Self Organising Maps with K-means

Solar-powered vehicle activated signs (VAS) are speed warning signs powered by batteries that are recharged by solar panels. These signs are more desirable than other active warning signs due to the low cost of installation and the minimal maintenance requirements. However, one problem that can affect a solar-powered VAS is the limited power capacity available to keep the sign operational. In order to be able to operate the sign more efficiently, it is proposed that the sign be appropriately triggered by taking into account the prevalent conditions. Triggering the sign depends on many factors such as the prevailing speed limit, road geometry, traffic behaviour, the weather and the number of hours of daylight. The main goal of this paper is therefore to develop an intelligent algorithm that would help optimize the trigger point to achieve the best compromise between speed reduction and power consumption. Data have been systematically collected whereby vehicle speed data were gathered whilst varying the value of the trigger speed threshold. A two stage algorithm is then utilized to extract the trigger speed value. Initially the algorithm employs a Self-Organising Map (SOM), to effectively visualize and explore the properties of the data that is then clustered in the second stage using K-means clustering method. Preliminary results achieved in the study indicate that using a SOM in conjunction with K-means method is found to perform well as opposed to direct clustering of the data by K-means alone. Using a SOM in the current case helped the algorithm determine the number of clusters in the data set, which is a frequent problem in data clustering.