Internet of Things based Framework for Public Transportation Fleet Management in Free State, South Africa

ArticleThestudybasedonbestframeworkdesignusinginternetofthings(IoT).IoTreferstoanestablishedcommunicationbetweenidentifiedthingsthroughinternet;likesensors,tags,WirelessSensorNetwork(WSN),Radio-FrequencyIdentification(RFID),GPS.(Kopetz,2011),(Atzoriet.al.,2010)

Effect of time of harvesting and disease resistance in reducing Cassava (Manihot esculenta Crantz) yield losses by two viral diseases

Cassava mosaic disease (CMD) and cassava brown streak disease (CBSD) are two important biotic constraints for cassava (Manihot esculenta Crantz) production in Eastern and Southern Africa. CMD causes a general decline in yield in affected plants of susceptible cassava varieties but CBSD causes rotting of edible roots. Delayed harvesting can increase rotting of roots and making them unfit for consumption or marketing, and thus affecting the livelihoods of poor farmers. This study investigated the effect of interaction between time of harvesting and levels of disease resistance to identify ideal harvesting times for reducing yield losses. The resistant cassava variety Namikonga remained in the field for the duration of the study, up to 24 months after planting without incurring significant yield losses, while the tolerant varieties Kiroba and Kizimbani could only be maintained up to 21 months. Susceptible varieties Mreteta and Albert suffered significant yield losses beyond 15 months. Among the varieties, Kizimbani had the least CBSD and CMD foliar symptoms as well as farmer desirable traits including high root weight, quantity of marketable roots and dry matter content. Harvesting of cassava can depend on the resistance or susceptibility of the varieties grown. Therefore, the above harvesting times for different varieties were recommended for minimizing yield losses due to the diseases and thus maximizing yields to the farmers

Transforming South Africa’s Universities of Technology: A Roadmap Through 4IR Lenses

ArticleSince their birth in the 6thcentury, universities have undergone different forms oftransformations, especially of structural, ideological, and epistemological nature. Recently, theemergence of the fourth industrial revolution (4IR) has triggered a wave of suchtransformations and just like other industrial revolutions, university management ought to becautious as such transformations could exacerbate existing inequalities between the rich andthe poor students. To this end, a clear roadmap for such a transformation becomes critical.This is the contribution of this paper. We achieve this through a bibliometric analysis of thestate of scientific research into the ‘university transformation’ topic, with a special focus onSouth Africa’s (RSA) context. The content of the identified scientific publications on RSA wasfurther subjected to thematic analysis leading to the revelation that decolonisation,community engagement and structural transformation, are the main research themes. It alsoemerges that RSA universities have not embraced 4IR as a lens through which to pursuetransformation. On the other hand, the RSA government launched the project:“Transformation at Public Universities” during the 2017/18 planning year. Subsequently, alluniversities in the country adopted and rolled out a customised transformation agenda.Among these universities, are the six universities of technology (UoTs), which, for historicalreasons, the transformation project presents unique challenges and opportunities. Createdslightly after the millennium, UoTs are still seen as critical role players in the third missionof universities, that of “achieving economic growth and social progress”. These findings, aswells as the existence of systemic exclusion, marginalisation, and discrimination (especiallyalong racial lines) in RSA universities, defines our proposed roadmap. Using one of the UoTsand Massive Open Online Courses (MOOCs) as the reference, the proposed universitytransformation roadmap is supported by empirical data on the assessment of the readiness ofstudents to adopt 4IR technologies

Virulence of Russian Wheat Aphid, Diuraphis Noxia (Kurdjumov) (Homoptera: Aphididae) Populations in Kenya

The Russian wheat aphid (RWA) Diuraphis noxia (Kurdjumov) is a serious pest of wheat in Kenya. Development and use of RWA resistant wheat (Triticum aestivum L.) varieties, has been constrained by RWA populations evolving with differential virulence to given resistant host plants. To fully exploit host plant resistance (HPR) in management of RWA, local populations of RWA have to be evaluated for differential virulence and biotypes in order to develop and deploy cultivars that exhibit cross biotype resistance. A study was conducted at KARI-Njoro to characterize virulence of RWA populations from the endemic areas (Eldoret, Mau Narok, Njoro and Egerton) in Kenya. A factorial experiment in randomized complete block design replicated three times was set up to evaluate seedling resistance to RWA with variety and aphid collection source as main factors in the screen house. Five adult RWA aphids from each of the four collection locations were used to infest four host genotypes; PI624933-1  containing Dn4 gene, 2414-11-2  containing Dn7 gene, KRWA9 which contains an unknown Dn gene and a susceptible check, K.KWALE, for 28 days to determine virulence of the RWA aphids  to seedlings of the four wheat genotypes in the greenhouse. Data was recorded on damage scores, plant height, plant height reduction, shoot biomass and biomass reduction of test plants 28 days after infestation. Results of an analysis of variance of these plant parameters show that Egerton population was more virulent than populations selected from other areas as it caused more damage on resistant lines. Keywords: Diuraphis noxia, biotype, virulence, RWA, Wheat.

The Role of ICTs in Downscaling and Up-scaling Integrated Weather Forecasts for Farmers in Sub-Saharan Africa

Despite global advancements in technology and inter-trade volumes, Sub-Saharan Africa is the only Region where cases of hunger have increased since 1990. Rampant and frequent droughts are one of the major causes of this. Monumental and mostly donor-funded projects have been mounted to counter this but with little success. One of the latest strategies being experimented is a community-based early warning system that seeks to integrate indigenous knowledge with western climate science. This initiative is informed by the realization that, though crucial, weather forecast information provided by the national meteorological departments has little utilization amongst smallscale farmers. Though having generated promising results, the integration project still faces the challenges of scaling up across communities as well as the lack of micro-level weather data. In this paper, we describe how the adoption of mobile phones and wireless sensor networks technology is being used to address these two challenges. Use of denser wireless sensor networks to collect local weather data and mobile phones to disseminate forecasts brings information closer to the farmers that need it most. To ensure that the non-mystical aspects of indigenous knowledge are portable across communities, language technologies (part of artificial intelligence) are used in the design of our system

MobiGrid: A Middleware for Integrating Mobile Phone and Grid Computing

The popularity and the high processing power of today's smart phones have presented computer scientists with a fertile platform on which to implement grid computing for mobile phones. Such grids will not require much investment since they are designed to make use of `idle' power on already existing phones. This is because most smart phone users only use their phones for a few minutes or a few hours every day and yet, these phones are powered up 24/7. These kinds of grids are most favorable to developing countries where the penetration of mobile phone exceeds other forms of ICTs. Once in place, the grids can then be utilized to run the much-needed applications such e-health, e-education and drought prediction. In this paper, we present MobiGrid, a middleware for mobile phone grid that is part of a larger research project that aims at integrating mobile phones and sensors to come up with a drought predication tool for use in the developing countries. MobiGrid is an API on which distributed applications can be built. Unlike the rest of grid middleware solutions, the uniqueness of our approach lies in the fact that the middleware is for mobile phones environment