A low complexity SI sequence estimator for pilot-aided SLM–OFDM systems

Selected mapping (SLM) is a well-known method for reducing peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. However, as a consequence of implementing SLM, OFDM receivers often require estimation of some side information (SI) in order to achieve successful data recovery. Existing SI estimation schemes have very high computational complexities that put additional constraints on limited resources and increase system complexity. To address this problem, an alternative SLM approach that facilitates estimation of SI in the form of phase detection is presented. Simulations show that this modified SLM approach produces similar PAPR reduction performance when compared to conventional SLM. With no amplifier distortion and in the presence of non-linear power amplifier distortion, the proposed SI estimation approach achieves similar data recovery performance as both standard SLM–OFDM (with perfect SI estimation) and also when SI estimation is implemented through the use of an existing frequency-domain correlation (FDC) decision metric. In addition, the proposed method significantly reduces computational complexity compared with the FDC scheme and an ML estimation scheme

A joint OFDM PAPR reduction and data decoding scheme with no SI estimation

The need for side information (SI) estimation poses a major challenge when selected mapping (SLM) is implemented to reduce peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. Recent studies on pilot-assisted SI estimation procedures suggest that it is possible to determine the SI without the need for SI transmission. However, SI estimation adds to computational complexity and implementation challenges of practical SLM-OFDM receivers. To address these technical issues, this paper presents the use of a pilot-assisted cluster-based phase modulation and demodulation procedure called embedded coded modulation (ECM). The ECM technique uses a slightly modified SLM approach to reduce PAPR and to enable data recovery with no SI transmission and no SI estimation. In the presence of some non-linear amplifier distortion, it is shown that the ECM method achieves similar data decoding performance as conventional SLM-OFDM receiver that assumed a perfectly known SI and when the SI is estimated using a frequency-domain correlation approach. However, when the number of OFDM subcarriers is small and due to the clustering in ECM, the modified SLM produces a smaller PAPR reduction gain compared with conventional SLM

Climate Change and the Ageing Population: Enforcing the Rights to Life and Health Under Human Rights, Health and Climate Change Regimes

This article explores potential methods of protecting the ageing population from the consequences of climate change. It discusses the enforcement of the "right to life" (the right to live a life free from environmental degradation) and/or health relating to the environment in protection of the ageing population. Many countries have codified the right to life and/or health in their constitutions. In order to enjoy this right, it is essential that a clean and healthy environment be secured.Thus, this article assesses the consideration of climate change by international human rights and health regimes. It also examines whether climate obligations such as emissions reduction, climate impact assessment, mitigation and adaptation can be enforced through these regimes. The article suggests that expanding the purview of new international climate policies that address the public health of the ageing population will fill the absence of health policies under the climate regime. Finally, after proposing that climate litigation through human rights enforcement may reshape global responses to adverse effects of climate change on the ageing population, the article suggests additional ways to achieve such feats

A selective control information detection scheme for OFDM receivers

In wireless communications, both control information and payload (user-data) are concurrently transmitted and required to be successfully recovered. This paper focuses on block-level detection, which is applicable for detecting transmitted control information, particularly when this information is selected or chosen from a finite set of information that are known at both transmitting and receiving devices. Using an orthogonal frequency division multiplexing architecture, this paper investigates and evaluates the performance of a time-domain decision criterion in comparison with a form of Maximum Likelihood (ML) estimation method. Unlike the ML method, the proposed time-domain detection technique requires no channel estimation as it uses the correlation (in the time-domain) that exists between the received and the transmitted selective information as a means of detection. In comparison with the ML method, results show that the proposed method offers improved detection performance, particularly when the control information consists of at least 16. However, the implementation of the proposed method requires a slightly increased number of mathematical computations

AN OVERVIEW OF AQUIFER VULNERABILITY

Published Book ChapterAquifer vulnerability concerns assessment of risk associated with groundwater resources. Investigations are carried out based on concepts applied to assess groundwater bodies. Aquifer vulnerability concepts discussed are based on available input data (subjective, physical, and statistical); resource and source protection; intrinsic and specific approaches. The broad-based methods most vulnerability approaches follow are the hydrogeological and complex setting method, statistical method, mathematical method, parametric system method, and index method. Fifteen commonly used methods were reviewed, stating the concept, purposes, advantages, and limitations. The methods were selected based on applicability to karst topography, the basis for European vulnerability approaches, travel time concept based on physically based approaches and intrinsic vulnerability approaches. The review discusses the importance of vulnerability validation and suggests appropriate validation techniques that can be adopted. The review concludes with discussions on the challenges and directions for future contributions on aquifer vulnerability

Selective Control Information Detection in 5G Frame Transmissions

Control signalling information within wireless communication systems facilitates efficient management of limited wireless resources, plays a key role in improving system performance of 5G systems. This chapter focuses detection of one particular form of control information, namely, selective control information (SCI). Maximum-likelihood (ML) is one of the conventional SCI detection techniques. Unfortunately, it requires channel estimation, which introduces some implementation constraints and practical challenges. This chapter uses generalized frequency division multiplexing (GFDM) to evaluate and demonstrate the detection performance of a new form of SCI detection that uses a time-domain correlation (TDC) technique. Unlike the ML scheme, the TDC technique is a form of blind detection that has the capability to improve detection performance with no need for channel estimation. In comparison with the ML based receiver, results show that the TDC technique achieves improved detection performance. In addition, the detection performance of the TDC technique is improved with GFDM receivers that use the minimum mean square error (MMSE) scheme compared with the zero-forcing (ZF) technique. It is also shown that the use of a raised cosine (RC) shaped GFDM transmit filter improves detection performance comparison with filters that employ root raised cosine (RRC) pulse shape

Library Services Platform Path to Cloud Computing Adoption in Nigerian Academic Libraries: A Review

The library and Information science (LIS) profession have evolved over time taking advantage of prevailing technology. The arrival of computers and other communication technologies led to major changes in the ways library services are rendered and the profession practiced. Library Management Systems (LMS) is one of such earlier areas where ICT have been applied to the operations of the library during the library computerization era. The arrival of the renascent Cloud Computing is generating new areas of research in relation to librarians’ uptake of this new technology. Cloud computing is being leveraged by developers of library systems to facilitate the envisaged move away from ILS/LMS to a more robust system that can handle some of the shortcomings of the ILS/LMS. These new systems are called Library services platforms (LSP). While both established and new library systems vendors are turning out different products, libraries have begun to shift away to these new platforms. This paper reviews cloud computing in libraries and projects LSPs as the reliable path to its adoption in Nigerian academic libraries. Recommendations were made based on the outcomes of this study

A DEEP LEARNING MODEL FOR ELECTRICITY DEMAND FORECASTING BASED ON A TROPICAL DATA

Electricity demand forecasting is a term used for prediction of users’ consumption on the grid ahead of actual demand. It is very important to all power stakeholders across levels. The power players employ electricity demand forecasting for sundry purposes. Moreover, the government’s policy on its market deregulation has greatly amplified its essence. Despite numerous studies on the subject using certain classical approaches, there exists an opportunity for exploration of more sophisticated methods such as the deep learning (DL) techniques. Successful researches about DL applications to com¬puter vision, speech recognition, and acoustic computing problems are motivation. However, such researches are not sufficiently exploited for electricity demand forecasting using DL methods. In this paper, we considered specific DL techniques (LSTM, CNN, and MLP) to short-term load fore¬casting problems, using tropical institutional data obtained from a Transmission Company. We also test how accurate are predictions across the techniques. Our results relatively revealed models appropriateness for the problem

Lean Commercialization: A New Framework for Commercializing High Technologies

Commercializing high technologies is expensive, tedious, and resource intensive. Meanwhile, there is a need for quick diffusion of innovations due to economic pressures for companies and research institutes. Therefore, this article proposes a new framework: lean commercialization. The framework represents a transformation of new technology and knowledge to products and services through the application of the lean/agile methodology. This methodology focuses on how resources can be minimized during the development, manufacturing, and marketing of new products and services, while still being accepted by customers. The lean commercialization framework was developed from a case study of high-technology companies and by interviewing commercialization experts. This article contributes to the theory and practice of commercialization of high technologies and provides a procedure for the practical application of the lean commercialization framework.</p

Commercialization Process of High Technology: A study of Finnish University Spin-Off

This article examines commercialization process of a high technology, which is characterized by a high level of research and development activities, resources-intensive and added values. The article employed a case study approach, by observing a Finnish University Spin-off between 2013 and 2016 and making use of documentary method. In contrary to many previous studies, the findings of the article showed that the spin-off process does not necessarily to be stage-based and has to be flexible. The findings also revealed the factors responsible for successful commercialization. Similarly, the findings pinpointed that "plan is always a plan" and that plan would change during the spin-off creation process. These findings provide an in-depth knowledge for commercialization practitioners, technology entrepreneurship educators, potential entrepreneurs (engineers and scientists) and business enterprises. Therefore, this article contributes to discourse of spin-off, commercialization, technology transfer and academic and university entrepreneurship. </p