Low-Rank Channel Estimation for Millimeter Wave and Terahertz Hybrid MIMO Systems

Massive multiple-input multiple-output (MIMO) is one of the fundamental technologies for 5G and beyond. The increased number of antenna elements at both the transmitter and the receiver translates into a large-dimension channel matrix. In addition, the power requirements for the massive MIMO systems are high, especially when fully digital transceivers are deployed. To address this challenge, hybrid analog-digital transceivers are considered a viable alternative. However, for hybrid systems, the number of observations during each channel use is reduced. The high dimensions of the channel matrix and the reduced number of observations make the channel estimation task challenging. Thus, channel estimation may require increased training overhead and higher computational complexity. The need for high data rates is increasing rapidly, forcing a shift of wireless communication towards higher frequency bands such as millimeter Wave (mmWave) and terahertz (THz). The wireless channel at these bands is comprised of only a few dominant paths. This makes the channel sparse in the angular domain and the resulting channel matrix has a low rank. This thesis aims to provide channel estimation solutions benefiting from the low rankness and sparse nature of the channel. The motivation behind this thesis is to offer a desirable trade-off between training overhead and computational complexity while providing a desirable estimate of the channel

Assessment of Corporate Social Responsibility (CSR) awareness and practices in manufacturing sector of Pakistan

Globalization and mass communication have significantly influenced the socio-economic growth of countries and organizations are under immense pressure to develop their businesses in a more socially responsible way. Consequently, Corporate Social Responsibility (CSR) has emerged as a business development concept. CSR acknowledgement is low in south Asian countries both at state and corporate levels. Pakistan, being a developing country, is no exception and the manufacturing sector, which is the third largest contributing sector to the economy, is facing the challenge of corporate social compliance. This study explores the awareness level amongst employees in the manufacturing sector and also evaluates the practices of CSR activities in these organizations. The study is mainly focused on the textile and automobile sectors and shows greater CSR awareness in the automobile sector than the textile sector; however, there are many organizations where the concept of CSR is unknown. The findings of this research will help organizations in enhancing understanding of CSR amongst employees and will also allow manufacturing industries to improve their implementation against identified weak areas. Increased levels of social compliance will ultimately help organizations in promoting their businesses in the global market

Strengthening orthopaedic care at national level: Output of a structured residency programme at Aga Khan University

This descriptive review of the output of the orthopaedic residency programme of Aga Khan University, Karachi, comprised information regarding the number of graduated residents and their educational background which was retrieved from departmental records. Information about their work location, subspecialty, current working status, participation in medical camps and national disaster relief efforts were obtained from various sources, including fellow surgeons, and social media profiles. From 1989 to 2017, a total of 48 residents graduated from the programme, with only 2(4.2%) of them being females. Overall, 19(39.6%) residents hailed from areas outside Karachi; 28(58.3%) belonged to Karachi; 1(2%) came from Kenya; 41(85.4%) remained to serve in Pakistan working mostly in tertiary healthcare centres; and 7(14.6%) moved abroad on consultancy and teaching assignments. Subspecialty training had a general trend towards general orthopaedics and trauma 21(43.7%), followed by arthroplasty surgery 13(27%)

Ankle arthrodesis using Ilizarov ring fixator: A primary or salvage procedure?: An analysis of twenty cases

Introduction: Ankle arthrodesis using the Ilizarov technique provides high union rate with the added benefits of early weight-bearing, and the unique advantage of its ability to promote regeneration of soft tissue around the bone, including skin, muscle and neuro-vascular structures, and its versatility to allow correction of the position of the foot by adjusting the frame post-operatively as needed. We describe our experience with this technique and the functional outcomes in our patients. Materials and Methods: This retrospective study was conducted in 20 ankle fusion cases using the Ilizarov method between the years 2007 and 2017. We defined success in treatment by loss of preoperative symptoms and radiological union on plain radiographs of the ankle. Results: Fusion was achieved in all patients (100%). Immediate post-operative ambulation was with full weight bearing (FWB) in 16 (83%) of the participants and non-weight bearing (NWB) in 3 patients (17%). Post-procedure 11 patients (67%) of the participants who were full weight bearing required some form of support for walking for 2-3 weeks. Post-operatively three patients had pin tract infection requiring intravenous antibiotics. Radiological union took range of 6-12 weeks, mean union time was 8 weeks. Only one patient required bone grafting due to bone loss. Average follow-up period was 10-45 months. Conclusion:The Ilizarov technique has a high union rate and leads to general favourable clinical outcome and may be considered for any ankle arthrodesis but is especially useful in complex cases such as for revisions, soft-tissue compromise, infection and in patients with risk for non-union. Early weight bearing is an extra benefit

Infected non-union of tibia treated with ilizarov external fixator: Our experience

Introduction: Tibia is the most common long bone fractured due its vulnerable subcutaneous location and most often associated with acquired complications of delayed union or non-union due to infection. Amongst the various treatment options to treat them, the Ilizarov external fixator application is considered superior due to its multiple advantages. The objective of this study was to analyse the role of Ilizarov fixation in infected tibial non-union, as well as to assess bony union and associated functional outcomes. Materials and Methods: A retrospective review was conducted for the duration between 1st January 2005 to 31st December 2016. Total of fifty-one patients with tibial non-union associated with infection who treated with the Ilizarov fixator were included in the study. Patient records were reviewed for union of bone, bone and functional outcomes and complications. Results: The most common organism for infection was identified to be Staphylococcus Aureus. At the time of final follow-up all patients had achieved union except two, one of whom had to undergo amputation due to non-union and sepsis. Majority of the patients had an excellent score as per ASAMI grading system for bone and function results. The most common complication noted was pin track infections. Conclusion: In our experience, Ilizarov external fixator is better suited for infected non-union of tibia because it can provide a stable mechanical environment, bone transport, correct deformities, and enable weight bearing and hence we recommend its use for the same

Macroeconomic Shocks: Short-Run versus Long-Run Perspectives

Shocks that stem from goods and money markets are supposed to be influential as it takes some time for economic agents to realize their true impacts. Therefore, these shocks can induce uncertainty about key macroeconomic variables such as CPI inflation and real GDP growth. Impacts of nominal and real shocks are computed, evaluated and compared under short-run as well as under long-run restrictions for CPI inflation and real GDP. Furthermore, different countries with varying resource structures are incorporated to achieve a comprehensive and generalized analysis. Structural VAR models are employed in order to functionalize short-run and long-run restrictions. Impulse response analysis is done to analyze effects of nominal and real shocks on CPI inflation and real GDP in short-run as well as in long-run. Variance decompositions are done to locate main sources of uncertainties in CPI inflation and real GDP. Shocks from product market appeared to be more pervasive in comparison to shocks from money market

Macroeconomic Shocks: Short-Run versus Long-Run Perspectives

Shocks that stem from goods and money markets are supposed to be influential as it takes some time for economic agents to realize their true impacts. Therefore, these shocks can induce uncertainty about key macroeconomic variables such as CPI inflation and real GDP growth. Impacts of nominal and real shocks are computed, evaluated and compared under short-run as well as under long-run restrictions for CPI inflation and real GDP. Furthermore, different countries with varying resource structures are incorporated to achieve a comprehensive and generalized analysis. Structural VAR models are employed in order to functionalize short-run and long-run restrictions. Impulse response analysis is done to analyze effects of nominal and real shocks on CPI inflation and real GDP in short-run as well as in long-run. Variance decompositions are done to locate main sources of uncertainties in CPI inflation and real GDP. Shocks from product market appeared to be more pervasive in comparison to shocks from money market

Resolving data interoperability in ubiquitous health profile using semi-structured storage and processing

© 2019 Association for Computing Machinery. Advancements in the field of healthcare information management have led to the development of a plethora of software, medical devices and standards. As a consequence, the rapid growth in quantity and quality of medical data has compounded the problem of heterogeneity; thereby decreasing the effectiveness and increasing the cost of diagnostics, treatment and follow-up. However, this problem can be resolved by using a semi-structured data storage and processing engine, which can extract semantic value from a large volume of patient data, produced by a variety of data sources, at variable rates and conforming to different abstraction levels. Going beyond the traditional relational model and by re-purposing state-of-the-art tools and technologies, we present, the Ubiquitous Health Profile (UHPr), which enables a semantic solution to the data interoperability problem, in the domain of healthcare

AI-Enabled Traffic Control Prioritization in Software-Defined IoT Networks for Smart Agriculture

Smart agricultural systems have received a great deal of interest in recent years because of their potential for improving the efficiency and productivity of farming practices. These systems gather and analyze environmental data such as temperature, soil moisture, humidity, etc., using sensor networks and Internet of Things (IoT) devices. This information can then be utilized to improve crop growth, identify plant illnesses, and minimize water usage. However, dealing with data complexity and dynamism can be difficult when using traditional processing methods. As a solution to this, we offer a novel framework that combines Machine Learning (ML) with a Reinforcement Learning (RL) algorithm to optimize traffic routing inside Software-Defined Networks (SDN) through traffic classifications. ML models such as Logistic Regression (LR), Random Forest (RF), k-nearest Neighbours (KNN), Support Vector Machines (SVM), Naive Bayes (NB), and Decision Trees (DT) are used to categorize data traffic into emergency, normal, and on-demand. The basic version of RL, i.e., the Q-learning (QL) algorithm, is utilized alongside the SDN paradigm to optimize routing based on traffic classes. It is worth mentioning that RF and DT outperform the other ML models in terms of accuracy. Our results illustrate the importance of the suggested technique in optimizing traffic routing in SDN environments. Integrating ML-based data classification with the QL method improves resource allocation, reduces latency, and improves the delivery of emergency traffic. The versatility of SDN facilitates the adaption of routing algorithms depending on real-time changes in network circumstances and traffic characteristics

COMBUSTION CHARACTERISTICS OF REACTIVE NANOMATERIALS

The combustion ofmetallic particlesis analogous to the combustion of hydrocarbon particles andthe particleburn time can be related to its diametric length. The relationship is called ‘d’ law and represented astb=d2. From the physics aspect, many deviations from the established laws at the bulk scale have been reported. As the ignition temperature of energetic nanomaterials is more sensitive to the passivation layer and the external heating conditions, and the burning time of nanomaterials is deviated from the conventional d2 law. Due to the variation of certain parameters such as the particles size distribution, agglomeration, morphology, level of contamination and initial particle size,thecorrect and precise value of the exponentisdifficult to find.Consequently, there’s no universal law for the burn time and a variant of the dn law is always proposed whose exponent is less than 2 (~ 1.3-1.7).In this research, combustion experiments are performed using a Bunsen burner in a particle-laden methane stream and the relationship of particle burning time with particle diameter is found to betb ~ d1.2. The combustion process of the various particles is captured using a high speed video camera.The average values of extinction time for Si (720 nm) and Si (1000 nm) are 11.4 ms and 17.2 ms, respectively. It is also observed that the nanoparticles are more reactive than the microsized particles. The average velocity flow fields of the silicon, iron and aluminum particles are also investigatedusing PIV technique.Before and after the experiments, the particles are characterised using dynamic light scattering (DLS), scanning electron microscopy (SEM), Energy-dispersive X-ray spectroscopy (EDS) and transmission electron microscopy (TEM