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The student dropout rate in universities is fascinating, especially among the students of Electrical Engineering. Even the most developed European countries face 40% to 50% dropout rate of engineering students during their first year, and the rate can be as high as 80% for some engineering disciplines. This problem calls attention of educators and university administration to take measures which can help in the reduction of the dropout rate and assist students in successfully completing their degree. Among many other solutions to control the student dropout rate, one is the adoption of a prediction mechanism whereby students can be warned about their potentially poor performance so that they can improve their performance resulting in better grades. Most of the existing prediction mechanisms apply various machine learning techniques on student cognitive features. In addition, non-cognitive features also have significant impact on students' performance; however, they have been sparsely applied for prediction. This research aims at improving the existing prediction mechanism by exploiting both cognitive and non-cognitive features of students for predicting their results. It has been found in the result analysis that addition of cognitive features increases prediction accuracies of decision tree; however, the addition does not play a significant role in other techniques. The study also identified the individual cognitive features that should be considered by students and universities to cater for drop outs.

ObjectivesThis research endeavours to identify the role of traditional birth attendants (TBAs) in supporting the maternal, newborn and child health (MNCH) care, partnership mechanism with a formal health system and also explored livelihood options for TBAs in the health system of Pakistan.SettingThe study was conducted in district Chitral, Khyber Pakhtunkhwa province, covering the areas where the Chitral Child Survival programme was implemented.ParticipantsA qualitative exploratory study was conducted, comprising seven key informant interviews with health managers, and four focus group discussions with community midwives (CMWs), TBAs, members of Community Based Saving Groups (CBSGs) and members of village health committees (VHCs).ResultsThe study identified that in the new scenario, after the introduction of CMWs in the health system, TBAs still have a pivotal role in health promotion activities such as breastfeeding promotion and vaccination. TBAs can assist CMWs in normal deliveries, and refer high-risk cases to the formal health system. Generally, TBAs are positive about CMWs’ introduction and welcome this addition. Yet their livelihood has suffered after CMWs’ deployment. Monetary incentives to them in recognition of referrals to CMWs could be one solution. The VHC is an active forum for strengthening co-ordination between the two service providers and to ensure an alternate and permanent livelihood support system for the TBAs.ConclusionsTBAs have assured their continued support in provision of continuum of care for pregnant women, lactating mothers and children under the age of 5 years. The district health authorities must figure out ways to foster a healthy interface vis-à-vis roles and responsibilities of TBAs and CMWs. In time it would be worthwhile to do further research to look into the CMWs’ integration in the system, as well as TBAs’ continued role for provision of MNCH care.

Abstract:The lack of adequate field measurements often hampers the construction and calibration of rainfall-runoff models over many of the world's watersheds. We adopted methodologies that rely heavily on readily available remote sensing datasets as viable alternatives for assessing, managing, and modelling of such remote and inadequately gauged regions. The Soil and Water Assessment Tool was selected for continuous (1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005) rainfall-runoff modelling of one such area, the northeast part of the Pishin Lora basin (NEPL). Input to the model included satellite-based Tropical Rainfall Measuring Mission precipitation data, and modelled runoff was calibrated against satellite-based observations, the latter included: (i) monthly estimates of the water volumes impounded by the Khushdil Khan (latitude 30°40 0 N, longitude 67°40 0 E), and the Kara Lora (latitude 30°34 0 N, longitude 66°52 0 E) reservoirs, and (ii) inferred wet versus dry conditions in streams across the NEPL. Calibrations were also conducted against observed flow reported from the Burj Aziz Khan station at the NEPL outlet (latitude 30°20 0 N; longitude 66°35 0 E). Model simulations indicate that (i) average annual precipitation (1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005), runoff and recharge in the NEPL are 1300 ð 10 6 m 3 , 148 ð 10 6 m 3 , and 361 ð 10 6 m 3 , respectively; (ii) within the NEPL watershed, precipitation and runoff are high for the northeast (precipitation: 194 mm/year; runoff: 38 ð 10 6 m 3 /year) and northwest (134 mm/year; 26 ð 10 6 m 3 /year) basins compared to the southern basin (124 mm/year; 8 ð 10 6 m 3 /year); and (3) construction of delay action dams in the northeast and northwest basins could increase recharge from 361 ð 10 6 m 3 /year up to 432 ð 10 6 m 3 /year and achieve sustainable extraction. The adopted methodologies are not a substitute for traditional approaches, but they could provide first-order estimates for rainfall, runoff, and recharge in the arid and semi-arid parts of the world that are inaccessible and/or lack adequate coverage with field data.

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