Trend & Mind-Set that India’s Central Science & Technology Sector & Further Need

The ability to innovate and deploy globally competitive technologies has been recognized as the next key driver of global economic change in the emerging knowledge economy. While science is scholarship driven, technology and innovation are market and competition driven, respectively. Currently, Indian Research and Development landscape is largely influenced by the character of public funded research and selection of R&D priorities is mostly supply driven. The private sector investment into R&D have been marginal. Therefore, demand driven component of R&D goals has been limited. Policy, strategy and tools are required to stimulate larger investment into demand driven R&D goals. Energy sector invests far too into R&D, although industrial turn over in the sector is extremely high. Promotion of public- private partnership into R&D and clean energy is a critical component of India’s competitiveness in global trade and industrial growth. New strategies and tools are required to stimulate engagement of private sector into R&D and enhance the share of private sector investment from the current 26% of India’s R&D spend to at least 50% during the 2012-17 period. The larger share of public investments into R&D could also be leveraged by focusing of R&D for public and social ‘good priorities of the country. There is an un-tapped opportunity for India to emerge as a global leader in affordable innovations under PPP by focusing on R&D for public and social goods in the areas of agriculture and food security, water, energy, affordable health care, education, environment, renovation of urban infrastructure, S&T inputs to rural development etc. Residual idealism among the youth and vast talent base offer an opportunity for the R&D sector in: the country to gain leadership in affordable and social innovations. Coming five years should lead to the creation of an innovation ecosystem most suited to the developmental phase of the country. Such an ecosystem should be complete with new responses to risk averse nature of the society, delivery models for innovative deployment of technologies, business models for financing deployment of innovations and adjustments in governance and management models for supporting strategic goals of innovations. The approach for R&D sector should address all’ stages of life cycles of ideas; from creation to commercialization and value creation. Thiswould call for paradigm shifts in approaches of planning for R&D in India during the Twelfth Five Year Plan period

Characterizing degradation gradients through land cover change analysis in rural Eastern Cape, South Africa

CITATION: Munch, Z., et al. 2017. Characterizing degradation gradients through land cover change analysis in rural Eastern Cape, South Africa. Geosciences, 7(1):7, doi:10.3390/geosciences7010007.The original publication is available at http://www.mdpi.comLand cover change analysis was performed for three catchments in the rural Eastern Cape, South Africa, for two time steps (2000 and 2014), to characterize landscape conversion trajectories for sustained landscape health. Land cover maps were derived: (1) from existing data (2000); and (2) through object-based image analysis (2014) of Landsat 8 imagery. Land cover change analysis was facilitated using land cover labels developed to identify landscape change trajectories. Land cover labels assigned to each intersection of the land cover maps at the two time steps provide a thematic representation of the spatial distribution of change. While land use patterns are characterized by high persistence (77%), the expansion of urban areas and agriculture has occurred predominantly at the expense of grassland. The persistence and intensification of natural or invaded wooded areas were identified as a degradation gradient within the landscape, which amounted to almost 10% of the study area. The challenge remains to determine significant signals in the landscape that are not artefacts of error in the underlying input data or scale of analysis. Systematic change analysis and accurate uncertainty reporting can potentially address these issues to produce authentic output for further modelling.http://www.mdpi.com/2076-3263/7/1/7Publisher's versio

Proceedings of a workshop on the development of a genetic improvement program for African catfish Clarias gariepinus

This proceedings include papers present at the workshop held from 5 to 9th Nov 2007 in Accra, Ghana. The areas cover 1)the present state of the catfish industry in Africa 2)Catfish reproductive management and grow out 3)Catfish nutrition and feeds 4)The application of genetic principles to catfish genetic improvement programs 5)Recommendations on how to best approach the issue of genetic improvement programs for catfish.Genetics, Biotechnology, Reproduction, Biological production, Nutrition Clarias gariepinus

Advancing Biomedicine with Graph Representation Learning: Recent Progress, Challenges, and Future Directions

Graph representation learning (GRL) has emerged as a pivotal field that has contributed significantly to breakthroughs in various fields, including biomedicine. The objective of this survey is to review the latest advancements in GRL methods and their applications in the biomedical field. We also highlight key challenges currently faced by GRL and outline potential directions for future research.Comment: Accepted by 2023 IMIA Yearbook of Medical Informatic

Building Profitable and Sustainable Community Owned Connectivity Networks

Cite:Academy of Science of South Africa (ASSAf), (2019). Building Profitable and Sustainable Community Owned Connectivity Networks. DOI 10.17159/assaf.2019/0065The IID seminar titled “Building Profitable and Sustainable Community Owned Connectivity Networks”, was hosted on 31 August 2020 on Zoom Webinar. The 2019 White Paper on science, technology and innovation (STI) recognise the pivotal enabling role of information and communication technologies (ICTs) in realising an inclusive and prosperous information society and knowledge economy. One of the Department of Science and Innovation (DSI)’s key role is to catalyse the digital ecosystem and develop scalable models for community owned connectivity networks to replicate in other areas. Rural areas provide challenging environment to implement communication infrastructure for data and Internet based services, including high cost of network implementation and lack of customer base, low-income streams, highly scattered and low population density. The DSI has thus partnered with the University of Western Cape (UWC), the Mankosi Village community, with support from the Technology Innovation Agency (TIA) to scaleup the Zenzeleni Community Owned Connectivity Networks (COCN). The Zenzeleni COCN has been in existence since 2012 and provides timely, reliable and affordable Wi-Fi connectivity to the remote rural areas of Mankosi and Zithulele in Mthatha. The webinar, facilitated by Ms Ellen Fischat from Story Room aimed to look at how rural and township wireless connectivity models, including Zenzeleni COCN can be scaled-up to increase the number of people connected in the rural settings, more so in light of the COVID-19 crisis. It is evident from the proceedings the need for community networks to provide access to connectivity and also more importantly, what connectivity enables. Subsequent discussions would need to focus on the users and owners of these community networks to understand how their lives have improved through the deployment of the technology. This will shed light of the financial feasibility and benefit. Department of Science and Innovation (DSI), South Africa.Department of Science and Innovation (DSI), South Africa

近距離MIMOシステムの通信容量に関する研究

Recently, the near field communication, abbreviated NFC, which is a form of contactless communication between devices like smartphones or tablets, is emerging quickly. Contactless communication allows a user to wave the smartphone over a NFC compatible device to send information without needing to touch the devices together or go through multiple steps setting up a connection. Fast and convenient, NFC technology is popular in parts of Europe and Asia, and is quickly spreading throughout the whole world. Over the past decade, we have witnessed the rapid evolution of Multiple-Input Multiple-Output (MIMO) systems which promise to break the frontiers of conventional architectures and deliver high throughput by employing more than one element at the transmitter (Tx) and receiver (Rx) in order to exploit the spatial domain. This is achieved by transmitting simultaneous data streams from different elements which impinge on the Rx with ideally unique spatial signatures as a result of the propagation paths‘ interactions with the surrounding environment. For exchanging massive information, for instance the videos or photos, between two devices, the future NFC systems will require higher channel capacity than current systems. Therefore, the MIMO system, which has a wider bandwidth, multi-value modulation system, and spatial multiplexing scheme, is the appropriate candidate to be employed in the high-speed NFC systems. Contrary to conventional MIMO systems, near-field MIMO communication systems transfer data in a very short range, the transmission lines are formed in parallel without multipath, and the LOS (line-of-sight) paths are the major components. The conventional MIMO works in a multipath-rich propagation environment, and is expected to achieve a high channel capacity by utilizing multipath components. The near-field MIMO, however, transfers data directly from the transmitter to the receiver, without any fading caused by multipath components. In the near-field MIMO system, a higher channel capacity results from a higher SNR and lower spatial correlation characteristics. Considering the short distance, the LOS components from each of the Tx elements arrive at the Rx array with a spherical wavefront. Therefore the beamwidth of the antenna element radiation pattern affects not only the receiving gain but also the spatial correlation characteristics. Usually, the conventional dipole antennas are used to investigate the MIMO channel capacity. However, the conventional dipoles are omni-directional in the horizontal plane. In this paper, a bi-directional element named dual-dipole element is utilized to improve the channel capacity. In the dual-dipole array, two half wave-length dipole antennas are settled parallel as only one element. By changing the internal distance between the two dipoles in one Tx element, the HPBW (half power beam width) of the element can be adjusted. Therefore, the shape of the radiation pattern can be determined by the internal distance between the two dipoles in one element. The effect of the HPBW on the channel capacity is investigated in detail. The narrower beam width of the Tx element can result for a higher SNR in the facing Rx element, however, at the meantime the power in the other sub channels will decrease. Hence, it is expected that there would be an optimum HPBW when the system could obtain the maximum channel capacity. And we find out the optimum HPBW for the near-field MIMO system with dual-dipole arrays. In addition, the improvement in the channel capacity from the conventional dipole array is considerable. Basically two factors determine the capacity of a MIMO system—the path loss and the multipath richness. The dual-dipole arrays lead to much lower path loss than the conventional dipole arrays, hence, the channel capacity improves significantly. However, the multipath richness rarely exists in the near-field MIMO. So far, all the researches on the near-field MIMO are in the free space without any obstacle. However, due to the short transfer distance of the near-field MIMO, a tiny variation of the channel will lead to a significant difference on the channel capacity. Therefore, we employ metal wire in the near-field MIMO system to increase the multipath richness and clarify the effect of obstacles in the system. The characteristics of the single metal wire are detailed investigated. And the most significant aspect is the location of the metal wire placed in the system. Generally, an object placed between two transmission antennas will decrease the channel capacity of the system. Here, we try to determine the optimal location of the object between the opposing antennas. We expect that the optimal location will alleviate the deterioration in the capacity caused by the object. However, the simulation results indicate that if the metal wire is placed in an appropriate location, a higher channel capacity can be obtained. In addition, we can set multiple metal wires in the optimum locations to achieve higher channel capacity. The different types of objects in the different types of arrays are also researched. Finally, this paper clarifies the frequency dependency of channel capacity in near-field MIMO system with metal wire. As the frequency increases, the absolute value of the channel capacity decreases. The improvement on channel capacity of using a metal wire also changes with frequency. In addition, when the frequency is very large, the effect of the metal wire is negligible. The proper location for the metal wire is found related with the corresponding wavelength of each specific frequency. Confidently, the research of the effect of the element HPBW and the objects between Tx and Rx introduced in this study can be beneficially applied in actual network preparation of future near-field MIMO wireless communications in which the improvement in the channel capacity are required

ELM ZA KLASIFIKACIJU TUMORA MOZGA KOD 3D MR SNIMAKA

Extreme Learning machine (ELM) a widely adopted algorithm in machine learning field is proposed for the use of pattern classification model using 3D MRI images for identifying tissue abnormalities in brain histology. The four class classification includes gray matter, white matter, cerebrospinal-fluid and tumor. The 3D MRI assessed by a pathologist indicates the ROI and the images are normalized. Texture features for each of the sub-regions is based on the Run-length Matrix, Co-occurence Matrix, Intensity, Euclidean distance, Gradient vector and neighbourhood statistics. Genetic Algorithm is custom designed to extract and sub-select a decisive optimal bank of features which are then used to model the ELM classifier and best selection of ELM algorithm parameters to handle sparse image data. The algorithm is explored using different activation function and the effect of number of neurons in the hidden layer by using different ratios of the number of features in the training and test data. The ELM classification outperformed in terms of accuracy, sensitivity and specificity as 93.20 %, 91.6 %, and 97.98% for discrimination of brain and pathological tumor tissue classification against state-of-the-art feature extraction methods and classifiers in the literature for publicly available SPL dataset.ELM, široko prihvaćen algoritam strojnog učenja se predlaže za korištenje u uzorkovanju pomoću klasifikacijskog modela 3D MRI slika za identifikaciju abnormalnosti tkiva u histologiji mozga. Četiri klase obuhvaćaju sive, bijele tvari, cerebrospinalne tekućine-i tumore. 3D MRI koji ocjenjuje patolog, ukazuje na ROI, a slike su normalizirane. Značajke tekstura za svaku od podregija se temelje na Run-length matrici, ponovnom pojavljivanju matrice, intenzitet, euklidska udaljenost, gradijent vektora i statistike susjedstva. Genetski algoritam je obično dizajniran za izdvajanje i sub-optimalan odabir odlučujući o značajkama koje se onda koriste za model ELM klasifikatora i najbolji izbor ELM parametra algoritama za obradu rijetkih slikovnih podataka. Algoritam se istražuje koristeći različite aktivacijske funkcije i utjecaj broja neurona u skrivenom sloju pomoću različitih omjera broja značajki kod trening i test podataka. ELM klasifikacija je nadmašila u smislu točnosti, osjetljivosti i specifičnosti, kao 93,20%, 91,6% i 97,98% za diskriminaciju mozga i patološki kod tumora i sistematizacije metode za prikupljanje podataka i klasifikatore u literaturi za javno dostupne SPL skup podataka

Joe Pawsey and the Founding of Australian Radio Astronomy

This open access book is a biography of Joseph L. Pawsey. It examines not only his life but the birth and growth of the field of radio astronomy and the state of science itself in twentieth century Australia. The book explains how an isolated continent with limited resources grew to be one of the leaders in the study of radio astronomy and the design of instruments to do so. Pawsey made a name for himself in the international astronomy community within a decade after WWII and coined the term radio astronomy. His most valuable talent was his ability to recruit and support bright young scientists who became the technical and methodological innovators of the era, building new telescopes from the Mills Cross and Chris (Christiansen) Cross to the Parkes radio telescope. The development of aperture synthesis and the controversy surrounding the cosmological interpretation of the first major survey which resulted in the Sydney research group's disagreements with Nobel laureate Martin Ryle play major roles in this story. This book also shows the connections among prominent astronomers like Oort, Minkowski, Baade, Struve, famous scientists in the UK such as J.A. Ratcliffe, Edward Appleton and Henry Tizard, and the engineers and physicists in Australia who helped develop the field of radio astronomy. Pawsey was appointed the second Director of the National Radio Astronomy Observatory (Green Bank, West Virginia) in October 1961; he died in Sydney at the age of 54 in late November 1962. Upper level students, scientists and historians will find the information, much of it from primary sources, relevant to any study of Joseph L. Pawsey or radio astronomy. This is an open access book