Comparison of cost- and energy-efficient signal modulations for next generation passive optical networks

Extensive numerical investigations are undertaken to analyze and compare, for the first time, the performance, techno-economy, and power consumption of three-level electrical Duobinary, optical Duobinary, and PAM-4 modulation formats as candidates for high-speed next-generation PONs supporting downstream 40 Gb/s per wavelength signal transmission over standard SMFs in C-band. Optimization of transceiver bandwidths are undertaken to show the feasibility of utilizing low-cost and band-limited components to support next-generation PON transmissions. The effect of electro-absorption modulator chirp is examined for electrical Duobinary and PAM-4. Electrical Duobinary and optical Duobinary are powerefficient schemes for smaller transmission distances of 10 km SMFs and optical Duobinary offers the best receiver sensitivity albeit with a relatively high transceiver cost. PAM-4 shows the best power budget and costefficiency for larger distances of around 20 km, although it consumes more power. Electrical Duobinary shows the best trade-off between performance, cost and power dissipation.

Next generation high density three-dimensional magnetic recording systems

This work is the first work using patterned soft underlayers in multilevel three-dimensional vertical magnetic data storage systems. The motivation stems from an exponentially growing information stockpile, and a corresponding need for more efficient storage devices with higher density. The world information stockpile currently exceeds 150EB (ExaByte=1x1018Bytes); most of which is in analog form. Among the storage technologies (semiconductor, optical and magnetic), magnetic hard disk drives are posed to occupy a big role in personal, network as well as corporate storage. However; this mode suffers from a limit known as the Superparamagnetic limit; which limits achievable areal density due to fundamental quantum mechanical stability requirements. There are many viable techniques considered to defer superparamagnetism into the 100's of Gbit/in2 such as: patterned media, Heat-Assisted Magnetic Recording (HAMR), Self Organized Magnetic Arrays (SOMA), antiferromagnetically coupled structures (AFC), and perpendicular magnetic recording. Nonetheless, these techniques utilize a single magnetic layer; and can thusly be viewed as two-dimensional in nature. In this work a novel three-dimensional vertical magnetic recording approach is proposed. This approach utilizes the entire thickness of a magnetic multilayer structure to store information; with potential areal density well into the Tbit/in2 regime. ^ There are several possible implementations for 3D magnetic recording; each presenting its own set of requirements, merits and challenges. The issues and considerations pertaining to the development of such systems will be examined, and analyzed using empirical and numerical analysis techniques. Two novel key approaches are proposed and developed: (1) Patterned soft underlayer (SUL) which allows for enhanced recording of thicker media, (2) A combinatorial approach for 3D media development that facilitates concurrent investigation of various film parameters on a predefined performance metric. A case study is presented using combinatorial overcoats of Tantalum and Zirconium Oxides for corrosion protection in magnetic media. ^ Feasibility of 3D recording is demonstrated, and an emphasis on 3D media development is emphasized as a key prerequisite. Patterned SUL shows significant enhancement over conventional "un-patterned" SUL, and shows that geometry can be used as a design tool to achieve favorable field distribution where magnetic storage and magnetic phenomena are involved. ^

System design and resource management in the next-generation integrated WLAN and 3G cellular networks

Next-generation integrated wireless local area network (WLAN) and 3G cellular networks aim to take advantage of the roaming ability in a cellular network and the high data rate services of a WLAN. To ensure successful implementation of an integrated network, many issues must be carefully addressed, including network architecture design, resource management, quality-of-service (QoS), call admission control (CAC) and mobility management. ^ This dissertation focuses on QoS provisioning, CAC, and the network architecture design in the integration of WLANs and cellular networks. First, a new scheduling algorithm and a call admission control mechanism in IEEE 802.11 WLAN are presented to support multimedia services with QoS provisioning. The proposed scheduling algorithms make use of the idle system time to reduce the average packet loss of realtime (RT) services. The admission control mechanism provides long-term transmission quality for both RT and NRT services by ensuring the packet loss ratio for RT services and the throughput for non-real-time (NRT) services. ^ A joint CAC scheme is proposed to efficiently balance traffic load in the integrated environment. A channel searching and replacement algorithm (CSR) is developed to relieve traffic congestion in the cellular network by using idle channels in the WLAN. The CSR is optimized to minimize the system cost in terms of the blocking probability in the interworking environment. Specifically, it is proved that there exists an optimal admission probability for passive handoffs that minimizes the total system cost. Also, a method of searching the probability is designed based on linear-programming techniques. ^ Finally, a new integration architecture, Hybrid Coupling with Radio Access System (HCRAS), is proposed for lowering the average cost of intersystem communication (IC) and the vertical handoff latency. An analytical model is presented to evaluate the system performance of the HCRAS in terms of the intersystem communication cost function and the handoff cost function. Based on this model, an algorithm is designed to determine the optimal route for each intersystem communication. Additionally, a fast handoff algorithm is developed to reduce the vertical handoff latency.^

The Next Generation of Scientists: Examining the Experiences of Graduate Students in Network-Level Social-Ecological Science

By integrating the research and resources of hundreds of scientists from dozens of institutions, network-level science is fast becoming one scientific model of choice to address complex problems. In the pursuit to confront pressing environmental issues such as climate change, many scientists, practitioners, policy makers, and institutions are promoting network-level research that integrates the social and ecological sciences. To understand how this scientific trend is unfolding among rising scientists, we examined how graduate students experienced one such emergent social-ecological research initiative, Integrated Science for Society and Environment, within the large-scale, geographically distributed Long Term Ecological Research (LTER) Network. Through workshops, surveys, and interviews, we found that graduate students faced challenges in how they conceptualized and practiced social-ecological research within the LTER Network. We have presented these conceptual challenges at three scales: the individual/project, the LTER site, and the LTER Network. The level of student engagement with and knowledge of the LTER Network was varied, and students faced different institutional, cultural, and logistic barriers to practicing social-ecological research. These types of challenges are unlikely to be unique to LTER graduate students; thus, our findings are relevant to other scientific networks implementing new social-ecological research initiatives.

Next generation of recommender systems: Algorithms and applications

Personalized recommender systems aim to assist users in retrieving and accessing interesting items by automatically acquiring user preferences from the historical data and matching items with the preferences. In the last decade, recommendation services have gained great attention due to the problem of information overload. However, despite recent advances of personalization techniques, several critical issues in modern recommender systems have not been well studied. These issues include: (1) understanding the accessing patterns of users (i.e., how to effectively model users' accessing behaviors); (2) understanding the relations between users and other objects (i.e., how to comprehensively assess the complex correlations between users and entities in recommender systems); and (3) understanding the interest change of users (i.e., how to adaptively capture users' preference drift over time). To meet the needs of users in modern recommender systems, it is imperative to provide solutions to address the aforementioned issues and apply the solutions to real-world applications. ^ The major goal of this dissertation is to provide integrated recommendation approaches to tackle the challenges of the current generation of recommender systems. In particular, three user-oriented aspects of recommendation techniques were studied, including understanding accessing patterns, understanding complex relations and understanding temporal dynamics. To this end, we made three research contributions. First, we presented various personalized user profiling algorithms to capture click behaviors of users from both coarse- and fine-grained granularities; second, we proposed graph-based recommendation models to describe the complex correlations in a recommender system; third, we studied temporal recommendation approaches in order to capture the preference changes of users, by considering both long-term and short-term user profiles. In addition, a versatile recommendation framework was proposed, in which the proposed recommendation techniques were seamlessly integrated. Different evaluation criteria were implemented in this framework for evaluating recommendation techniques in real-world recommendation applications. ^ In summary, the frequent changes of user interests and item repository lead to a series of user-centric challenges that are not well addressed in the current generation of recommender systems. My work proposed reasonable solutions to these challenges and provided insights on how to address these challenges using a simple yet effective recommendation framework.^

Towards next generation vertical search engines

As the Web evolves unexpectedly fast, information grows explosively. Useful resources become more and more difficult to find because of their dynamic and unstructured characteristics. A vertical search engine is designed and implemented towards a specific domain. Instead of processing the giant volume of miscellaneous information distributed in the Web, a vertical search engine targets at identifying relevant information in specific domains or topics and eventually provides users with up-to-date information, highly focused insights and actionable knowledge representation. As the mobile device gets more popular, the nature of the search is changing. So, acquiring information on a mobile device poses unique requirements on traditional search engines, which will potentially change every feature they used to have. To summarize, users are strongly expecting search engines that can satisfy their individual information needs, adapt their current situation, and present highly personalized search results. ^ In my research, the next generation vertical search engine means to utilize and enrich existing domain information to close the loop of vertical search engine's system that mutually facilitate knowledge discovering, actionable information extraction, and user interests modeling and recommendation. I investigate three problems in which domain taxonomy plays an important role, including taxonomy generation using a vertical search engine, actionable information extraction based on domain taxonomy, and the use of ensemble taxonomy to catch user's interests. As the fundamental theory, ultra-metric, dendrogram, and hierarchical clustering are intensively discussed. Methods on taxonomy generation using my research on hierarchical clustering are developed. The related vertical search engine techniques are practically used in Disaster Management Domain. Especially, three disaster information management systems are developed and represented as real use cases of my research work.^

Characterizing Genetic Drivers of Lymphoma through High-Throughput Sequencing

The advent of next-generation sequencing, now nearing a decade in age, has enabled, among other capabilities, measurement of genome-wide sequence features at unprecedented scale and resolution.

In this dissertation, I describe work to understand the genetic underpinnings of non-Hodgkin’s lymphoma through exploration of the epigenetics of its cell of origin, initial characterization and interpretation of driver mutations, and finally, a larger-scale, population-level study that incorporates mutation interpretation with clinical outcome.

In the first research chapter, I describe genomic characteristics of lymphomas through the lens of their cells of origin. Just as many other cancers, such as breast cancer or lung cancer, are categorized based on their cell of origin, lymphoma subtypes can be examined through the context of their normal B Cells of origin, Naïve, Germinal Center, and post-Germinal Center. By applying integrative analysis of the epigenetics of normal B Cells of origin through chromatin-immunoprecipitation sequencing, we find that differences in normal B Cell subtypes are reflected in the mutational landscapes of the cancers that arise from them, namely Mantle Cell, Burkitt, and Diffuse Large B-Cell Lymphoma.

In the next research chapter, I describe our first endeavor into understanding the genetic heterogeneity of Diffuse Large B Cell Lymphoma, the most common form of non-Hodgkin’s lymphoma, which affects 100,000 patients in the world. Through whole-genome sequencing of 1 case as well as whole-exome sequencing of 94 cases, we characterize the most recurrent genetic features of DLBCL and lay the groundwork for a larger study.

In the last research chapter, I describe work to characterize and interpret the whole exomes of 1001 cases of DLBCL in the largest single-cancer study to date. This highly-powered study enabled sub-gene, gene-level, and gene-network level understanding of driver mutations within DLBCL. Moreover, matched genomic and clinical data enabled the connection of these driver mutations to clinical features such as treatment response or overall survival. As sequencing costs continue to drop, whole-exome sequencing will become a routine clinical assay, and another diagnostic dimension in addition to existing methods such as histology. However, to unlock the full utility of sequencing data, we must be able to interpret it. This study undertakes a first step in developing the understanding necessary to uncover the genomic signals of DLBCL hidden within its exomes. However, beyond the scope of this one disease, the experimental and analytical methods can be readily applied to other cancer sequencing studies.

Thus, this dissertation leverages next-generation sequencing analysis to understand the genetic underpinnings of lymphoma, both by examining its normal cells of origin as well as through a large-scale study to sensitively identify recurrently mutated genes and their relationship to clinical outcome.

Towards Next Generation Vertical Search Engines

As the Web evolves unexpectedly fast, information grows explosively. Useful resources become more and more difficult to find because of their dynamic and unstructured characteristics. A vertical search engine is designed and implemented towards a specific domain. Instead of processing the giant volume of miscellaneous information distributed in the Web, a vertical search engine targets at identifying relevant information in specific domains or topics and eventually provides users with up-to-date information, highly focused insights and actionable knowledge representation. As the mobile device gets more popular, the nature of the search is changing. So, acquiring information on a mobile device poses unique requirements on traditional search engines, which will potentially change every feature they used to have. To summarize, users are strongly expecting search engines that can satisfy their individual information needs, adapt their current situation, and present highly personalized search results. In my research, the next generation vertical search engine means to utilize and enrich existing domain information to close the loop of vertical search engine's system that mutually facilitate knowledge discovering, actionable information extraction, and user interests modeling and recommendation. I investigate three problems in which domain taxonomy plays an important role, including taxonomy generation using a vertical search engine, actionable information extraction based on domain taxonomy, and the use of ensemble taxonomy to catch user's interests. As the fundamental theory, ultra-metric, dendrogram, and hierarchical clustering are intensively discussed. Methods on taxonomy generation using my research on hierarchical clustering are developed. The related vertical search engine techniques are practically used in Disaster Management Domain. Especially, three disaster information management systems are developed and represented as real use cases of my research work.

Characterization of the Galactic White Dwarf Population in the Next Generation Virgo Cluster Survey

Halo white dwarfs remain one of the least studied stellar populations in the Milky Way because of their faint luminosities. Recent work has uncovered a population of hot white dwarfs which are thought to be remnants of low-mass Population II stars. This thesis uses optical data from the Next Generation Virgo Cluster Survey (NGVS) and ultravoilet data from the GALEX Ultraviolet Virgo Cluster Survey (GUViCS) to select candidates which may belong to this population of recently formed halo white dwarfs. A colour selection was used to separate white dwarfs from QSOs and main-sequence stars. Photometric distances are calculated using model colour-absolute magnitude relations. Proper motions are calculated by using the difference in positions between objects from the Sloan Digital Sky Survey and the NGVS. The proper motions are combined with the calculated photometric distances to calculate tangential velocities, as well as approximate Galactic space velocities. White dwarf candidates are characterized as belonging to either the disk or the halo using a variety of methods, including calculated scale heights (z> 1 kpc), tangential velocities (vt >200 km/s), and their location in (V,U) space. The 20 halo white dwarf candidates which were selected using Galactic space velocities are analyzed, and their colours and temperatures suggest that these objects represent some of the youngest white dwarfs in the Galactic halo.

OFDM-based schemes for next generation wireless systems

The purpose of this study is to investigate two candidate waveforms for next generation wireless systems, filtered Orthogonal Frequency Division Multiplexing (f-OFDM) and Unified Filtered Multi-Carrier (UFMC). The evaluation is done based on the power spectral density analysis of the signal and performance measurements in synchronous and asynchronous transmission. In f-OFDM we implement a soft truncated filter with length 1/3 of OFDM symbol. In UFMC we use the Dolph-Chebyshev filter, limited to the length of zero padding (ZP). The simulation results demonstrates that both waveforms have a better spectral behaviour compared with conventional OFDM. However, the induced inter-symbol interference (ISI) caused by the filter in f-OFDM, and the inter-carrier interference (ICI) induced in UFMC due to cyclic prefix (CP) reduction , should be kept under control. In addition, in a synchronous transmission case with ideal parameters, f-OFDM and UFMC appear to have similar performance with OFDM. When carrier frequency offset (CFO) is imposed in the transmission, UFMC outperforms OFDM and f-OFDM.

Next-generation technologies to develop new therapeutics in oncology and cardiology

This is an abstract of a presented talk at the European Biotechnology Conference held in Latvia during 05–07 May 2016

Domestication and the storage starch biosynthesis pathway: Signatures of selection from a whole sorghum genome sequencing strategy

Next-generation sequencing of complete genomes has given researchers unprecedented levels of information to study the multifaceted evolutionary changes that have shaped elite plant germplasm. In conjunction with population genetic analytical techniques and detailed online databases, we can more accurately capture the effects of domestication on entire biological pathways of agronomic importance. In this study, we explore the genetic diversity and signatures of selection in all predicted gene models of the storage starch synthesis pathway of Sorghum bicolor, utilizing a diversity panel containing lines categorized as either ‘Landraces’ or ‘Wild and Weedy’ genotypes. Amongst a total of 114 genes involved in starch synthesis, 71 had at least a single signal of purifying selection and 62 a signal of balancing selection and others a mix of both. This included key genes such as STARCH PHOSPHORYLASE 2 (SbPHO2, under balancing selection), PULLULANASE (SbPUL, under balancing selection) and ADP-glucose pyrophosphorylases (SHRUNKEN2, SbSH2 under purifying selection). Effectively, many genes within the primary starch synthesis pathway had a clear reduction in nucleotide diversity between the Landraces and wild and weedy lines indicating that the ancestral effects of domestication are still clearly identifiable. There was evidence of the positional rate variation within the well-characterized primary starch synthesis pathway of sorghum, particularly in the Landraces, whereby low evolutionary rates upstream and high rates downstream in the metabolic pathway were expected. This observation did not extend to the wild and weedy lines or the minor starch synthesis pathways.

Domestication and the storage starch biosynthesis pathway: signatures of selection from a whole sorghum genome sequencing strategy

Next-generation sequencing of complete genomes has given researchers unprecedented levels of information to study the multifaceted evolutionary changes that have shaped elite plant germplasm. In conjunction with population genetic analytical techniques and detailed online databases, we can more accurately capture the effects of domestication on entire biological pathways of agronomic importance. In this study, we explore the genetic diversity and signatures of selection in all predicted gene models of the storage starch synthesis pathway of Sorghum bicolor, utilizing a diversity panel containing lines categorized as either ‘Landraces’ or ‘Wild and Weedy’ genotypes. Amongst a total of 114 genes involved in starch synthesis, 71 had at least a single signal of purifying selection and 62 a signal of balancing selection and others a mix of both. This included key genes such as STARCH PHOSPHORYLASE 2 (SbPHO2, under balancing selection), PULLULANASE (SbPUL, under balancing selection) and ADP-glucose pyrophosphorylases (SHRUNKEN2, SbSH2 under purifying selection). Effectively, many genes within the primary starch synthesis pathway had a clear reduction in nucleotide diversity between the Landraces and wild and weedy lines indicating that the ancestral effects of domestication are still clearly identifiable. There was evidence of the positional rate variation within the well-characterized primary starch synthesis pathway of sorghum, particularly in the Landraces, whereby low evolutionary rates upstream and high rates downstream in the metabolic pathway were expected. This observation did not extend to the wild and weedy lines or the minor starch synthesis pathways.