A review of the Development Trend of Personalized learning Technologies and its Applications

Personalized learning tailors material and strategy to student requirements, interests, and goals in e-learning. These developments help educational institutions and other organizations to keep up with the fast pace of information technology, communications, and computing power. Studies show that self-adaptive learning and relevant learning information improve study efficiency. Compared to traditional teaching methods, the practice of online education is well in its infancy. On the other hand, the pedagogy and evaluation of students in online courses have a large gap that has to be filled, necessitating significant improvements in e-learning. We call this approach to education "personalized learning," which is a central focus of today's leading online education platforms. Several studies have been conducted on e-learning and personalized learning, but few investigated the development trend of personalized learning technologies and applications. Therefore this study examines the literature to close the gap and promote the development trend for personalized learning technologies and applications in higher education from 2010 to 2021 by analyzing related journal articles. The pivotal studies used inclusion criteria after a search generated 372 complete research articles and reduced them to 146 publications based on their proposed learning domains and research themes. Through carefully reviewing current trends and successes in numerous aspects of personalized learning, this discussion analyzes prospective future research directions in the field of personalized learning

Introduction to the Special Issue on Sustainable Solutions for the Intelligent Transportation Systems

The intelligent transportation systems improve the transportation system’s operational efficiency and enhance its safety and reliability by high-tech means such as information technology, control technology, and computer technology. In recent years, sustainable development has become an important topic in intelligent transportation’s development, including new infrastructure and energy distribution, new energy vehicles and new transportation systems, and the development of low-carbon and intelligent transportation equipment. New energy vehicles’ development is a significant part of green transportation, and its automation performance improvement is vital for smart transportation. The development of intelligent transportation and green, low-carbon, and intelligent transportation equipment needs to be promoted, a significant feature of transportation development in the future. For intelligent infrastructure and energy distribution facilities, the electricity for popular electric vehicles and renewable energy, such as nuclear power and hydrogen power, should be considered

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

An Energy Aware and Secure MAC Protocol for Tackling Denial of Sleep Attacks in Wireless Sensor Networks

Wireless sensor networks which form part of the core for the Internet of Things consist of resource constrained sensors that are usually powered by batteries. Therefore, careful energy awareness is essential when working with these devices. Indeed,the introduction of security techniques such as authentication and encryption, to ensure confidentiality and integrity of data, can place higher energy load on the sensors. However, the absence of security protection c ould give room for energy drain attacks such as denial of sleep attacks which have a higher negative impact on the life span ( of the sensors than the presence of security features. This thesis, therefore, focuses on tackling denial of sleep attacks from two perspectives A security perspective and an energy efficiency perspective. The security perspective involves evaluating and ranking a number of security based techniques to curbing denial of sleep attacks. The energy efficiency perspective, on the other hand, involves exploring duty cycling and simulating three Media Access Control ( protocols Sensor MAC, Timeout MAC andTunableMAC under different network sizes and measuring different parameters such as the Received Signal Strength RSSI) and Link Quality Indicator ( Transmit power, throughput and energy efficiency Duty cycling happens to be one of the major techniques for conserving energy in wireless sensor networks and this research aims to answer questions with regards to the effect of duty cycles on the energy efficiency as well as the throughput of three duty cycle protocols Sensor MAC ( Timeout MAC ( and TunableMAC in addition to creating a novel MAC protocol that is also more resilient to denial of sleep a ttacks than existing protocols. The main contributions to knowledge from this thesis are the developed framework used for evaluation of existing denial of sleep attack solutions and the algorithms which fuel the other contribution to knowledge a newly developed protocol tested on the Castalia Simulator on the OMNET++ platform. The new protocol has been compared with existing protocols and has been found to have significant improvement in energy efficiency and also better resilience to denial of sleep at tacks Part of this research has been published Two conference publications in IEEE Explore and one workshop paper

A compendium of Technologies, Practices, Services and Policies for Scaling Climate Smart Agriculture in Odisha (India)

Stakeholders engaged in agricultural research for development (AR4D) are increasingly tackling risks associated with climate change in smallholder systems. Accordingly, development and scaling of climate-smart agriculture (CSA) are one of the priorities for all the organizations, departments and ministries associated with the farm sector. Having a ‘one-stop-shop’ compiled in the format of a compendium for CSA technologies, practices and services would therefore serve a guide for all the stakeholders for scaling CSA in smallholder systems. Bringing out a Compendium on Climate-Smart Agriculture (CSA) for Odisha, India was therefore thought of during the workshop on ‘Scaling Climate-Smart Agriculture in Odisha’ organized at Bhubaneswar on 18-19 July 2018 by International Rice Research Institute (IRRI) in collaboration with Department of Agriculture (DoA) & Farmers’ Empowerment, Indian Council of Agricultural Research-National Rice Research Institute (ICAR-NRRI), Orissa University of Agriculture and Technology (OUAT) & International Maize and Wheat Improvement Center (CIMMYT) under the aegis of CGIAR Research program on Climate Change, Agriculture and Food Security (CCAFS). The main objectives to bring forth this compendium are: to argue the case for agriculture policies and practices that are climate-smart; to raise awareness of what can be done to make agriculture policies and practices climatesmart; and to provide practical guidance and recommendations that are well referenced and, wherever possible, based on lessons learned from practical action. CSA programmes are unlikely to be effective unless their implementation is supported by sound policies and institutions. It is therefore important to enhance institutional capacities in order to implement and replicate CSA strategies. Institutions are vital to agricultural development as well as the realisation of resilient livelihoods.They are not only a tool for farmers and decision-makers, but are also the main conduit through which CSA practices can be scaled up and sustained. The focus in this compendium is on CSA and it’s relevant aspects, i.e., (i) technologies and practices, (ii) services, (iii) technology targeting, (iv) business models, (v) capacity building, and (vi) policies. The approaches and tools available in the compendium span from face-to-face technicianfarmer dialogues to more structured exchanges of online and offline e-learning. In every scenario it is clear that tailoring to local expectations and needs is key. In particular, the voice of farmers is essential to be captured as they are the key actors to promote sustainable agriculture, and their issues need to be prioritized. CSA practices are expected to sustainably increase productivity and resilience (adaptation), reduce Greenhouse Gases (mitigation), and enhance achievement of national food security along with sustainable development goals. CSA is widely expected to contribute towards achieving these objectives and enhance climate change adaptation. CSA practices have to be included in State’s Climate Policy as a priority intervention as the state steps up efforts to tackle climate change. Furthermore, emphasis shoud be laid on CSA training for a sustainable mode to enhance CSA adoption in the state hence the relevance of developing this document. The adaption of climate related knowledge, technologies and practices to local conditions, promoting joint learning by farmers, researchers, rural advisor and widely disseminating CSA practices, is critical. This compendium brings together a collection of experiences from different stakeholders with background of agricultural extension and rural advisory services in supporting CSA. The contributions are not intended to be state-of-the art academic articles but thought and discussion pieces of work in progress. The compendium itself is a ‘living‘ document which is intended to be revised periodically