Miracle-dz/UniFAR-FTUs huggingface dataset:
FRAMEWORK FOR THE DESIGN AND IMPLEMENTATION OF SOFTWARE DEFINED RADIO BASED WIRELESS COMMUNICATION SYSTEM

The aim of this thesis is to design and implement a software dened radio based wireless communication system. Software dened radio is a feasible solution for recongurable radios, which can perform different functions at different times on the same hardware. The baseband section of a wireless communication system is rst simulated and then implemented in hardware. The performance of the baseband transmitter is analyzed using constellation and eye diagrams for different modulation techniques and different signal-tonoise ratios, while considering an additive white Guassian noise channel. The performance of the receiver is analyzed by comparing the input and output waveforms. The performance of the system in real time is also analyzed by implementing the system in hardware using Xilinx Spartan 2E eld programmable gate array. A comparison of the simulation results with the results obtained from implementing the system on Spartan 2E hardware is presented and discussed. It is shown that the simulation results and experimental results are similar.
Applying Constraint Logic Programming to SQL Semantic Analysis

Abstract This paper proposes the use of Constraint Logic Programming (CLP) to model SQL queries in a data-independent abstract layer by focusing on some semantic properties for signalling possible errors in such queries. First, we define a translation from SQL to Datalog, and from Datalog to CLP, so that solving this CLP program will give information about inconsistency, tautology, and possible simplifications. We use different constraint domains which are mapped to SQL types, and propose them to cooperate for improving accuracy. Our approach leverages a deductive system that includes SQL and Datalog, and we present an implementation in this system which is currently being tested in classroom, showing its advantages and differences with respect to other approaches, as well as some performance data.
Fluid dynamic optimization of HVAC-components with adjoint methods

The theory and application of continuous adjoint methods for the optimization of heating, ventilation and air-conditioning components is surveyed in this thesis. The cost functions to be optimized are related to comfort and efficiency criteria. Shape and porosity modifications are the means of control, in a CFD-based framework. The underlying physics are the incompressible, steady state Reynolds-averaged Navier-Stokes-Fourier equations. Porosity is modeled by a Darcy term. Using the adjoint method, the sensitivity is computed from the numerical solution of the primal and adjoint equation systems. The cost of the computation is independent of the number of degrees of freedom which makes the method attractive for the application to complex industrial settings. Of particular note are some specific problems related to the adjoint optimization. An essential aspect is the computation of the gradient from the sensitivity. The sensitivity is a directional derivative and for this reason not feasible for the gradient-based optimization strategy. Therefore, the gradient is computed from the Laplace-Beltrami equation, demanding the numerical solution of an additional partial differential equation of second order on the surface of the geometry. Subsequently, it is used for the design update using gradient descent in conjunction with a proper step size. The computation of the step size for the gradient method is a crucial point. It should unify efficiency and feasibility. But, established methods such as line-search based on the Armijo-rule are rather computationally expensive. Hence, a reduced Armijo approach is presented where part of the algorithm is outsourced to a coarse mesh, making the computation less expensive. Using this approach, the intensity of design modification per update step is increased and thus, the whole design cycle accelerated. However, design modifications are often limited by constraints essential for the industrial realization. Accordingly, constraints related to the porosity modification are investigated. The insertion of an approximated regularization term into the cost functional promotes a sparse distributed control which is in some cases preferred. The approaches are implemented and validated by fluid dynamic test cases. The arising framework is applied to heating, ventilation and air-conditioning components. It is shown that the adjoint method is a powerful and efficient technique to optimize heating, ventilation and air-conditioning components. However, the application to industrial cases often requires adaptations necessary for the individual requirements, making know-how and manual adjustments by the user irremissible. Therefore, future developments in the automation of the process chain offer room for improvement.
Integrin affinity modulation by Ras signalling molecules

Integrins are heterodimeric transmembrane proteins present on virtually every cell, which maintain and control cell-cell and cell-substratum adhesion. Through this adhesive property, integrins can govern aggregation, cell polarity and migration. Several human diseases demonstrate the importance of integrins in normal physiological function: inappropriate platelet integrin activation is responsible for myocardial infarctions and cerebral vascular diseases; while leucocytes require integrin activation for leucocyte migration during inflammation. The understanding of the function and regulation of integrins therefore has important therapeutic implications. Essential to the function of integrins is their ability to modulate the affinity for binding ligand through conformational change. Platelet aggregation requires prior activation of the anb(33 integrin to bind fibrinogen. This platelet integrin is a model for the understanding of the mechanisms regulating affinity modulation. A high affinity state-specific antibody, PAC1 has facilitated the analysis of oqibP3 activation. Intracellular signal transduction pathways elucidated through the use of the PAC1 antibody have shown that the integrin cytoplasmic domains are required for affinity modulation, in a process termed "inside-out signalling". In this thesis I have sought to understand the mechanism by which H-Ras and its effectors modulate integrin affinity. H-Ras is a member of the Ras superfamily of small GTP binding proteins. Expression of the constitutively active variant of H-Ras (Ras G12V) within an integrin affinity reporter system (aP-py cells) reduced integrin affinity (suppressed integrin). Ras effector mutants revealed that integrin suppression is mediated by Raf-dependent and Raf-independent signalling pathways. Rafindependent signalling pathways activated by Ral-GEFs and PI3-kinase were not responsible for integrin suppression. An active variant of R-Ras (R-Ras G38V) reversed integrin suppression by both Raf-dependent and -independent pathways, indicating that these pathways may converge at a point proximal to the integrin.
Throughput Analysis and Optimization of Multi-layer FFR-aided OFDMA Networks

In OFDMA networks, the use of universal frequency reuse plans improves cell capacity but causes very high levels of inter-cell interference (ICI), particularly affecting users located in the cell-edge regions.In order to mitigate ICI while achieving high spectral efficiencies, fractional frequency reuse (FFR) shows a good tradeoff between cell-edge throughput and overall cell spectral efficiency.Recently, multi-layer FFR-aided OFDMA-based designs, splitting the cell into inner, middle and outer layers have been proposed and studied with the aim of increasing the spectrum utilization and improving the user fairness throughout the cell.This paper presents an analytical framework allowing the performance evaluation and optimization of multi-layer FFR designs in OFDMA-based networks.Tractable mathematical expressions of the average cell throughput as well as the layer spectral efficiency have been derived for both proportional fair (PF) and round robin (RR) scheduling policies.
INDUSTRY COMPARISON OF THE PROPENSITY FOR ALLIANCE FORMATION AN EXAMINATION OF U.S. MNC'S IN JAPAN

The formation of alliances represents an increasingly visible type of strategic behavior on the part of multinational corporations. In particular, the pattern of alliance formation exhibits considerable geographic concentration. This paper estimates the relative influence of several factors identified in the related literature as important considerations in the formation of alliances. Specifically, the investigation focuses on alliances formed across different stages of the value chain and across different types of industries between U.S. and Japanese multinationals. Using a logistic regression model the paper examines the role of firm-specific, industry-specific, and country-specific factors in the choice of U.S. multinationals to form cooperative arrangements involving single and multiple type of activities in the value chain with Japanese multinationals. Preliminary findings indicate that firm size and country risk were significant influences on the nature of alliance formation. In particular, the size of a firm, the firm’s return on sales and the level of country risk act to reduce the odds (probability) that an alliance will be of a singletype form. These findings raise a number of questions about the usefulness of existing measures to adequately account for alliance formation.
Shortest Path with Dynamic Weight Implementation using Dijkstra’s Algorithm

Shortest path algorithms have been long applied to solve daily problems by selecting the most feasible route with minimum cost or time. However, some of the problems are not simple. This study applied the case using Dijkstra's algorithm on a graph representing street routes with two possible digraphs: one-way and twoway. Each cost was able to be changed anytime, representing the change in traffic condition. Results show that the usage of one way digraph in mapping the route does make the goal possible to reach, while the usage of twoway digraph may cause confusion although it is probably the possible choice in the real world. Both experiments showed that there are no additional computation stresses in re-calculating the shortest path while going halfway to reach the goal.
An Approximation Algorithm for Sharing-Aware Virtual Machine Revenue Maximization

Cloud providers face the challenge of efficiently managing their infrastructure through minimizing resource consumption while allocating service requests such that their revenue is maximized. Solutions addressing this challenge should consider the sharing of memory pages among virtual machines (VMs) and the available capacity of each type of requested resources. We provide such solution by designing a greedy approximation algorithm for solving the sharing-aware virtual machine revenue maximization (<inline-formula><tex-math notation="LaTeX">$\mathsf{SAVMRM}$</tex-math><alternatives><mml:math><mml:mi mathvariant="sans-serif">SAVMRM</mml:mi></mml:math><inline-graphic xlink:href="grosu-ieq1-2786728.gif"/></alternatives></inline-formula>) problem. The <inline-formula><tex-math notation="LaTeX">$\mathsf{SAVMRM}$</tex-math><alternatives><mml:math><mml:mi mathvariant="sans-serif">SAVMRM</mml:mi></mml:math><inline-graphic xlink:href="grosu-ieq2-2786728.gif"/></alternatives></inline-formula> problem requires determining the set of VMs that can be instantiated on a given server such that the revenue derived from hosting the VMs is maximized. In addition, we model the <inline-formula><tex-math notation="LaTeX">$\mathsf{SAVMRM}$</tex-math><alternatives><mml:math><mml:mi mathvariant="sans-serif">SAVMRM</mml:mi></mml:math><inline-graphic xlink:href="grosu-ieq3-2786728.gif"/></alternatives></inline-formula> problem as a multilinear binary program and optimally solve it, while accounting for page sharing and multiple resource constraints. We determine and analyze the approximability properties of our proposed greedy algorithm and evaluate it by performing extensive experiments using Google cluster workload traces. The experimental results show that under various scenarios, our proposed algorithm generates higher revenue than other VM allocation algorithms while achieving significant reduction of allocated memory.
GPU-accelerated CFD Simulations for Turbomachinery Design Optimization

Design optimization relies heavily on time-consuming simulations, especially when using gradient-free optimization methods. These methods require a large number of simulations in order to get a remarkable improvement over reference designs, which are nowadays based on the accumulated engineering knowledge already quite optimal. High-Performance Computing (HPC) is essential to reduce the execution time of the simulations. While parallel programming using the CPU is established since more than two decades, the use of accelerators, such as the Graphics Processing Unit (GPU), is relatively recent in design optimization. The GPU has actually a huge computational power comparable to a many-core cluster but concentrated in one device. This raw power is not easy to utilize as entire code parts have to be rewritten using a GPU programming language. Even though high-level standards (e.g. openACC) are able to bring a basic acceleration with a low development effort, it is not simple to get large speedups with these methods. Low-level programming languages are more efficient but different speedups are reported and there is a need for a deep analysis to make the GPU potential more transparent to scientists especially non-experts in HPC. In order to study the GPU acceleration for CFD steady simulations, two in-house CFD solvers have been ported to the GPU; one with explicit and the second with implicit time-stepping. After the porting and the validation of the GPU solvers, the GPU code optimization leads to the identification of a set of key parameters affecting the GPU efficiency. At the same time, both methods have been compared resulting into a performance model and a classification of the GPU acceleration of some CFD operations. The purpose is to enable scientists to take an educated decision concerning the GPU porting of their CPU applications by providing an expected GPU speedup. In addition to the two GPU CFD solvers that are now integrated into the in- house design optimization software package, this research provided key elements to reduce the ambiguity about the GPU potential, namely a qualitative analysis and a classification. These tools can help selecting the best candidate for a breakthrough in CFD acceleration. At the same time, this work identified serious limitations in the preconditioning of a linear system of equations and the limit of today iterative matrix factorization methods in terms of stability and convergence. There is a need for a paradigm shift toward inherently parallel preconditioners. The developed tools have been used for the optimization of a compressor and a turbine cascade resulting into a faster optimization process on the GPU.
Deformation monitoring of earth dams using laser scanners and digital imagery

Monitoring earth dams plays an essential role in evaluating the structural safety condition of this type of dams. Monitoring activities are related mainly with safety but also with the collection of valuable data to enhance the understanding of the behaviour of these structures. These purposes are not mutually independent but rather complementary (ICOLD, 1982). Monitoring a dam involves several activities, namely: design of the monitoring plan, installation of monitoring devices, reading those devices at some pre-established frequencies, conversion of measurements to meaningful engineering quantities, interpretation of these quantities, comparison with models, dam (visual) inspection and issuing a safety report. A monitoring plan should define which observable quantities are needed and which devices should be installed to measure those quantities. Furthermore, the plan should establish the location of the devices, their measuring procedures and monitoring frequencies depending on the age of the dam, extreme events, height, external actions, conservation conditions, available know-how and technology, human and economic losses in the case of failure, etc. The quantities involved in dam monitoring are those related both with the actions in the dam and with the dam response. Surface displacements are important quantities to be determined, especially in what concerns safety and long term behaviour (Tedd et. al, 1997). Surface displacement can be related to internal deterioration processes, such as internal erosion or slope failure or to less important phenomena as secondary consolidation or creep. In order to evaluate these displacements, surface marks should be located at regular space intervals, usually in the dam crest, at the upstream and downstream sides, in the berm or berms, and less commonly in other places in the downstream slope. Several combined terrestrial imaging systems (CTIS) have been made commercially available during the last decade and are now a reliable and proven technology. The laser component of these CTIS provide a dense set of instrumental spherical polar coordinates of any unknown point that reflects the laser radiation; the CCD photo sensors component provide the RGB intensities for those points. The polar coordinates can be easily transformed into a meaningful object Cartesian reference system. Given their high sampling frequency CTIS offer an unprecedented density of spatial information concerning an object under study. This technology has been widely used by the architectural and archaeological communities but there is enormous potential in monitoring applications where such dense data sets could provide great insight into the nature of structural deformations (Lichti et al, 2000). This paper tries to evaluate this new technology and points to a methodology for measuring surface deformations on earth dams.
COCOWA MODEL: WATCHDOG MECHANISM USED TO PROPAGATE SELFISH NODES IN CELLULAR NETWORKS OF MOVING VEHICLES

The cellular networks are used to move the rapid growth in the mobile data in the explosion on the cellular network. The offload cellular networks are dynamic in the swimming condition. The highly dynamic sector is improved by the WIFI networks the Access point is configured by the MAC and the IP address. The mobile Ad hoc network model is formatted on the selfish node behavior . The detecting selfish node is performed by the watch dog timers. The swimming performances are used to move the delay tolerant networks. The cocowa approach based on the diffusion on the selfish node propagated. The collaborative approach are reduces the time and increases the precision when detecting the selfish nodes.
Further developments on temporary cointegration

La presenza di break strutturali nelle variabili economiche e una delle ragioni per cui non sempre le procedure di analisi di cointegrazione sono in grado di rilevare l’esistenza di una relazione di lungo periodo, anche nel caso in cui quest’ultima sia avvalorata dalla teoria economica. Questo problema e particolarmente sentito nel caso in cui si voglia costruire un modello ECM a scopi previsivi. In questo lavoro verranno presentati alcuni approfondimenti al concetto di cointegrazione temporanea proposto da Granger and Siklos (1997) per modellare casi in cui, prevalentemente per il sopraggiungere di break strutturali, le serie non sono necessariamente cointegrate per tutto l’arco di tempo considerato. Sara inoltre presentata una applicazione alla serie reale dei prezzi di oro ed argento nel periodo 1971–2004.
An immersive flipped classroom for learning Mandarin Chinese: design, implementation, and outcomes

ABSTRACT Online kindergarten to twelfth grade (K-12) language learners have usually been found to hold more negative perceptions of their courses and to perform less well academically than their face-to-face counterparts, despite the well-attested benefits of computer-mediated communication in language learning. In an attempt to improve upon such outcomes, this study designed, implemented, and evaluated a 12-day immersive online high-school Chinese-language course that included daily synchronous sessions and interactive technology-enhanced tasks, with a special emphasis on engaging the students in meaningful social interactions. Based on the analysis of the 35 participants’ survey responses and their language performance, they had a very positive experience of the course, felt satisfied by it, and showed statistically significant improvement in their language skills. These findings are discussed in relation to prior studies’ findings and current online-education policies and practices.
On Centralized Scheduling and Channel Assignment Scheme for WiMAX Mesh Networks

WiMAX provides a mechanism for creating Multi-hop mesh, which can be deployed as high speed wide-area wireless network. Because multiple-access interference is a major limiting factor for the WiMAX mesh network, Multi-channel transmission can eliminate the interference and improve the throughput of the network. The efficiency of Multi-channel transmission can be affected by the scheduling and channel assignment algorithm. To reap the full performance potential of WiMAX architecture, we propose a new combined centralized scheduling and channel assignment algorithm called ALS-DSATUR (Active Link Scheduling-Degree of SATURation) for use in a Multi-channel Single-transceiver WiMAX mesh network. The proposed scheme can reduce the length of scheduling, particularly for insufficient channels with high network node density, and considerably improve the base station's ggregate throughput to improved mobile magement effacy.
Barriers and Facilitators of Adherence to Anti-Diabetic Therapy in Pregnant Women with Diabetes: Health Care Workers’ Perspectives

Global prevalence of hyperglycaemia in pregnancy in women of 20 - 49 years was estimated to be 16.9% and affecting 21.4 million live births, in 2013, 90% of which occurred in developing countries. The cornerstone of anti-diabetic therapy is diet, physical activity and medications. The study utilized a qualitative descriptive design using key informant interviews from August 2016 to November 2016 to explore challenges of adherence to anti-diabetic therapy in pregnant women with diabetes at a central hospital in Harare, Zimbabwe. Permission to conduct the study was obtained from the respective local and national ethical review boards. All participants gave verbal and written informed consent. A sample of eight key informants directly involved in the care of pregnant women with diabetes was purposively selected for key informant interviews. Key informants should have worked with diabetic pregnant women for at least one year. Sample size was determined by data saturation. Interviews followed a semi structured questionnaire that had sections on the burden of diabetes in pregnancy, challenges of adherence, challenges in management and possible solutions to challenges faced. All interviews were conducted in a private room. Detailed notes were taken during the interviews which were also being audiotaped. Trustworthiness was achieved by observing credibility, dependability, transferability and confirmability. Thematic analysis was done. Thematic analysis was done manually. The stages of data analysis followed were data organization, familiarization, transcription, coding, developing a thematic framework, indexing, displaying and reporting. Major themes identified were barriers and facilitators of adherence to anti-diabetic therapy. Categories under barriers were financial barriers, lack of health education, lack of trained personnel, shortage of staff and lack of collaboration among practitioners. Categories under facilitators of adherence were subsidization of care, formal training of professionals, promoting collaboration and establishment of a unit dedicated to the care of pregnant women with diabetes. Barriers and solutions identified should be utilized to develop frameworks to promote adherence to anti-diabetic therapy incidence of adverse perinatal outcomes.