Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust GMSK Demodulation Using Demodulator Diversity and BER Estimation

This research investigates robust demodulation of Gaussian Minimum Shift Keying (GMSK) signals, using demodulator diversity and real-time bit-error-rate (BER) estimation. GMSK is particularly important because of its use in prominent wireless standards around the world (GSM, DECT, CDPD, DCS1800, and PCS1900). The dissertation begins with a literature review of GMSK demodulation techniques (coherent and noncoherent) and includes an overview of singlechannel interference rejection techniques in digital wireless communications. Various forms of GMSK demodulation are simulated, including the limiter discriminator and differential demodulator (i.e., twenty-five variations in all). Ten represent new structures and variations. The demodulator performances are evaluated in realistic wireless environments, such as additive white Gaussian noise, co-channel interference, and multipath environments modeled by COST207 and SMRCIM. Certain demodulators are superior to others for particular channel impairments, so that no demodulator is necessarily the best in every channel impairment. This research formally introduces the concept of demodulator diversity, a new idea which consists of a bank of demodulators which simultaneously demodulate the same signal and take advantage of the redundancy in the similar signals. The dissertation also proposes practical real-time BER estimation techniques which have tremendous ramifications for communications. Using Parzen’s estimator for probability density functions (pdfs) and Gram-Charlier series approximation for pdfs, BER can be estimated using short observation intervals (10 to 500 training symbols) and, in some cases, without any training sequence. We also introduce new variations of Gram-Charlier estimation using robust estimators. BER (in place of MSE) can now drive adaptive signal processing. Using a cost function and gradient for Parzen’s estimator (derived in this paper), BER estimation is applied to demodulator diversity with substantial gains of 1-10 dB in carrierto-interference ratio over individual receivers in realistic channels (with adaptive selection and weighting). With such gains, a BER-based demodulator diversity scheme can allow the employment of a frequency reuse factor of N = 4, instead of N = 7, with no degradation in performance. A lower reuse factor means more channels are available in a cell, thus increasing overall capacity. The resulting techniques are simple and easily implemented at the mobile. BER estimation techniques can also be used in BER-based equalization and dynamic allocation of resources.
(2,3,5,6-Tetrafluorophenolato)[5,10,15,20-tetrakis(4-methoxyphenyl)porphyrinato]iron(III) cyclohexane monosolvate

The title compound, [Fe(C6HF4O)(C48H36N4O4)]·C6H12, represents a five-coordinate iron(III) porphyrin complex in a square-pyramidal geometry with a tetrafluorophenolate anion as the axial ligand. The FeIII atom is displaced by 0.364 (2) Å from the 24-atom mean plane of the porphyrinate ring towards the tetrafluoro phenolate anion. The average Fe—N distance is 2.053 (2) Å and the Fe—O distance is 1.883 (2) Å. A porphyrin aryl H atom points in the general direction of the phenoxide ring. The mean plane separation between the 24-atom porphyrin planes of two adjacent porphyrin rings is ∼3.7 Å, and the lateral shift is ∼3.5 Å resu, ting in an Fe⋯Fe separation of 5.6167 (14) Å.
High-Resolution MRI Vessel Wall Imaging: Spatial and Temporal Patterns of Reversible Cerebral Vasoconstriction Syndrome and Central Nervous System Vasculitis

BACKGROUND AND PURPOSE: High-resolution MR imaging is an emerging tool for evaluating intracranial artery disease. It has an advantage of defining vessel wall characteristics of intracranial vascular diseases. We investigated high-resolution MR imaging arterial wall characteristics of CNS vasculitis and reversible cerebral vasoconstriction syndrome to determine wall pattern changes during a follow-up period. MATERIALS AND METHODS: We retrospectively reviewed 3T-high-resolution MR imaging vessel wall studies performed on 26 patients with a confirmed diagnosis of CNS vasculitis and reversible cerebral vasoconstriction syndrome during a follow-up period. Vessel wall imaging protocol included black-blood contrast-enhanced T1-weighted sequences with fat suppression and a saturation band, and time-of-flight MRA of the circle of Willis. Vessel wall characteristics including enhancement, wall thickening, and lumen narrowing were collected. RESULTS: Thirteen patients with CNS vasculitis and 13 patients with reversible cerebral vasoconstriction syndrome were included. In the CNS vasculitis group, 9 patients showed smooth, concentric wall enhancement and thickening; 3 patients had smooth, eccentric wall enhancement and thickening; and 1 patient was without wall enhancement and thickening. Six of 13 patients had follow-up imaging; 4 patients showed stable smooth, concentric enhancement and thickening; and 2 patients had resoluton of initial imaging findings. In the reversible cerebral vasoconstriction syndrome group, 10 patients showed diffuse, uniform wall thickening with negligible-to-mild enhancement. Nine patients had follow-up imaging, with 8 patients showing complete resolution of the initial findings. CONCLUSIONS: Postgadolinium 3T-high-resolution MR imaging appears to be a feasible tool in differentiating vessel wall patterns of CNS vasculitis and reversible cerebral vasoconstriction syndrome changes during a follow-up period.
HEAT: Scalable Routing in Wireless Mesh Networks Using Temperature Fields

Existing unicast routing protocols are not suited well for wireless mesh networks as in such networks, most traffic flows between a large number of mobile nodes and a few access points with Internet connectivity. In this paper, we propose HEAT, an anycast routing protocol for this type of communication that is designed to scale to the network size and to be robust to node mobility. HEAT relies on a temperature field to route data packets towards the Internet gateways, as follows. Every node is assigned a temperature value, and packets are routed along increasing temperature values until they reach any of the Internet gateways, which are modeled as heat sources. Our major contribution is a distributed protocol to establish such temperature fields. The distinguishing feature of our protocol is that it does not require flooding of control messages. Rather, every node in the network determines its temperature considering only the temperature of its direct neighbors, which renders our protocol particularly scalable to the network size. We analyze our approach and compare its performance with OLSR through simulations with Glomosim. We use realistic mobility patterns extracted from geographical data of large Swiss cities. Our results clearly show the benefit of HEAT versus OLSR in terms of scalability to the number of nodes and robustness to node mobility. The packet delivery ratio with HEAT is more than two times higher than OLSR in large mobile scenarios and we conclude that HEAT is a suitable routing protocol for city-wide wireless mesh networks.
Scaling up the Fabrication of Mechanically-Robust Carbon Nanofiber Foams

This work aimed to identify and address the main challenges associated with fabricating large samples of carbon foams composed of interwoven networks of carbon nanofibers. Solutions to two difficulties related with the process of fabricating carbon foams, maximum foam size and catalyst cost, were developed. First, a simple physical method was invented to scale-up the constrained formation of fibrous nanostructures process (CoFFiN) to fabricate relatively large foams. Specifically, a gas deflector system capable of maintaining conditions supportive of carbon nanofiber foam growth throughout a relatively large mold was developed. ANSYS CFX models were used to simulate the gas flow paths with and without deflectors; the data generated proved to be a very useful tool for the deflector design. Second, a simple method for selectively leaching the Pd catalyst material trapped in the foam during growth was successfully tested. Multiple techniques, including scanning electron microscopy, surface area measurements, and mechanical testing, were employed to characterize the foams generated in this study. All results confirmed that the larger foam samples preserve the basic characteristics: their interwoven nanofiber microstructure forms a low-density tridimensional solid with viscoelastic behavior. Fiber growth mechanisms are also discussed. Larger samples of mechanically-robust carbon nanofiber foams will enable the use of these materials as strain sensors, shock absorbers, selective absorbents for environmental remediation and electrodes for energy storage devices, among other applications.
Increased Risks of Acute Organ Dysfunction and Mortality in Intensive Care Unit Patients With Schizophrenia: A Nationwide Population-Based Study

Objective: To investigate the risks of acute organ dysfunction and death in intensive care unit (ICU) patients with schizophrenia. Methods: Using a retrospective matched cohort design, we compared 203 schizophrenic patients to 2036 demographically matched (1:10) nonschizophrenic patients with first-time ICU admission between 2005 and 2007 using the claims data of a nationally representative cohort from the Taiwan National Health Insurance Research Database. Definitions of schizophrenia and associated diagnoses were based on the codes of the International Classification of Diseases, Ninth Revision, Clinical Modification. Analyses were performed using univariate and multivariate analyses. Results: The median age of schizophrenic patients was 53 years; 61.1% were men. Schizophrenic patients were less likely to be hospitalized in a medical center and had fewer surgical conditions and principal cardiovascular diagnoses, but they had a higher prevalence of infection than nonschizophrenic patients. After controlling for the aforementioned baseline covariates, schizophrenic patients had a higher risk of acute organ dysfunction (adjusted odds ratio = 1.52, 95% confidence interval = 1.09−2.10). When individual organ systems were analyzed, they had a 47% higher risk of respiratory dysfunction, a 194% higher risk of renal dysfunction, and a 122% higher risk of neurological dysfunction than nonschizophrenic patients. Hospital mortality was also higher in schizophrenic patients than in nonschizophrenic patients (24.1% versus 14.4%, p < .001; adjusted odds ratio = 1.56, 95% confidence interval = 1.08−2.24). Conclusions: Among ICU patients, schizophrenic patients were sicker, having a higher risk of acute organ dysfunction and death.ICU = intensive care unit; NHIRD = National Health Insurance Research Database; ICD-9-CM = International Classification of Diseases, Ninth Revision, Clinical Modification; CI = confidence interval.
An Efficient Cooperative Retransmission MAC Protocol for IEEE 802.11n Wireless LANs

Recently, cooperative retransmissions have exhibited great potentials in enhancing the reliability and efficiency of wireless communications by exploring spatial diversity. With cooperative retransmissions, a cooperative node helps retransmit an overheard frame if the frame from a sender fails to reach the destination. Several cooperative retransmission schemes have been proposed for wireless local area networks (WLANs) in the literature. However, most of them require explicit coordination between the sender and the cooperative node before each retransmission, which results in a non-negligible overhead. Moreover, these schemes are not designed for the latest IEEE 802.11n standard, and are incompatible with the frame aggregation and block ACK mechanisms of 802.11n. In this paper, we propose an efficient cooperative retransmission MAC (CAR-MAC) protocol that utilizes new features of 802.11n and is compatible with standard 802.11n transmissions. In CAR-MAC, all nodes periodically broadcast a C-Beacon message to release their retransmitting capability, and each node selects a cooperative node based on received CBeacon messages. If some sub-frames in the aggregated frame from the sender fail to reach the destination, the cooperative node retransmits the failed sub-frames together with its own new sub frames, such that overhead from cooperative retransmissions is amortized by normal frame transmissions. We have theoretically analyzed the improvement on network throughput brought by CAR-MAC protocol. In addition, we have conducted extensive simulations to evaluate CAR-MAC protocol under various channel conditions. Both theoretical and simulation results show that the proposed protocol can greatly improve network throughput and reduce packet delay, compared with the 802.11n standard and existing cooperative retransmission schemes.
Design Issues and Considerations for Low-Cost 3-D TSV IC Technology

In this paper key design issues and considerations of a low-cost 3-D Cu-TSV technology are investigated. The impact of TSV on BEOL interconnect reliability is limited, no failures have been observed. The impact of TSV stress on MOS devices causes shifts, further analysis is required to understand their importance. Thermal hot spots in 3-D chip stacks cause temperature increases three times higher than in 2-D chips, necessitating a careful thermal floorplanning to avoid thermal failures. We have monitored for ESD during 3-D processing and have found no events take place, however careful further monitoring is required. The noise coupling between two tiers in a 3-D chip-stack is 20 dB lower than in a 2-D SoC, opening opportunities for increased mixed signal system performance. The impact on digital circuit performance of TSVs is accurately modeled with the presented RC model and digital gates can directly drive signals through TSVs at high speed and low power. Experimental results of a 3-D Network-on-Chip implementation demonstrate that the NoC concept can be extended from 2-D SoC to 3-D SoCs at low area (0.018 ) and power (3%) overhead.
Efficient processing of large-scale sparse matrix-matrix multiplications on a single machine

Graphs are very widely used to represent datasets in various real-world applications. Many algorithms dealing with graphs represent them in the form of sparse matrices and process them through sparse matrix operations. Recently, as the size of a graph increases rapidly, a single-machine-based graph engine has emerged as a general framework for effectively performing large-scale sparse matrix operations. Sparse matrices multiplication (SpGEMM) is a core building block for developing a variety of graph algorithms such as all source shortest paths, betweenness centrality, breadth first search from multiple sources, subgraph indexing, and graph construction. This paper addresses how to perform two sparse matrices multiplication (SpGEMM) efficiently on a single-machine-based graph engine. To effectively perform the large-scale SpGEMM, we have two issues: (1) selecting an appropriate type of matrix products (i.e., inner products, outer products, and row-row products), and (2) allocating memory space to matrices according to different types of matrix products. We first formulate the cost models for the three matrix product types by reflecting their characteristics. We observed the commonality in the processes of the matrix multiplication and the join in a relational database. Based on this observation, we propose memory allocation schemes for three matrix products by borrowing the idea of memory allocation employed in join. Finally, we show the effectiveness of our approach via extensive experiments with real-life datasets.
Domain Based Punjabi Text Document Clustering

Text Clustering is a text mining technique which is used to group similar documents into single cluster by using some sort of similarity measure & separating the dissimilar documents. Popular clustering algorithms available for text clustering treats document as conglomeration of words. The syntactic or semantic relations between words are not given any consideration. Many different algorithms were propagated to study and find connection among different words in a sentence by using different concepts. In this paper, a hybrid algorithm for clustering of Punjabi text document that uses semantic relations among words in a sentence for extracting phrases has been developed. Phrases extracted create a feature vector of the document which is used for finding similarity among all documents. Experimental results reveal that hybrid algorithm performs better with real time data sets.
Some improvements in the RGB-D SLAM system

RGB-D cameras offer both color and depth images of the surrounding environment, making them an attractive option for robot sensor. In this work, we present an RGB-D SLAM system using the Microsoft Kinect. The proposed system is a full 6DoF (Degrees of Freedom) SLAM system which can estimate camera trajectory and reconstruct a 3D model of the environment in real-time. Unlike traditional filtering-based approaches, our system optimizes the entire trajectory by the use of graph optimization. We achieve better accuracy than a previous system by employing key-frame matching instead of frame-to-frame matching. We evaluate our system on a published dataset. The results demonstrate that our system can handle unrestricted camera movements in indoor settings.
The School Environment and Adolescent Well-Being: Beyond Academics. Research Brief. Publication #2008-26.

Adolescents spend a large proportion of their day in school or pursuing school-related activities. While the primary purpose of school is the academic development of students, its effects on adolescents are far broader, also encompassing their physical and mental health, safety, civic engagement, and social development. Further, its effects on all these outcomes are produced through a variety of activities including formal pedagogy, after-school programs, caretaking activities (e.g., feeding, providing a safe environment) as well as the informal social environment created by students and staff on a daily basis.
Color filter arrays: design and performance analysis

This paper describes the design of color filter arrays (CFAs) used in the consumer-grade digital camera, and analyses their influence on the performance of the demosaicking process. Of particular interest are RGB CFAs widely used in a single-sensor imaging pipeline. Different design characteristics of various image-enabled consumer electronic devices by the different manufacturers lead to the several arrangements of the color filters in the CFA, affecting both performance and computational efficiency of the demosaicking solution. Extensive experimentation, using ten RGB CFAs and a universal demosaicking framework, reported in this paper indicates that the CFA has a great impact on both the objective and subjective (visual) quality of the demosaicked, full-color image.
Performance trends and limitations of power electronic systems

In 2003 the Roadmapping Initiative of the European Center of Power Electronics (ECPE) has been started based on a future vision of society in 2020 in order to define the future role of power electronics, and to identify technological barriers and prepare new technologies well in time. In the framework of this initiative a new mathematically supported approach for the roadmapping in power electronics has been developed. As described in this paper the procedure relies on a comprehensive mathematical modeling and subsequent multi-objective optimization of a converter system. The relationship between the technological base and the performance of the system then exists as a mathematical representation, whose optimization assures the best possible exploitation of the available degrees of freedom and technologies. Thus an objective Technology Node of a system is obtained, whereby physical limits are implicitly taken into account. Furthermore, the sensitivity of the system performance with regard to the technological base can be calculated directly and the internal interdependence of Performance Indices directly studied. Accordingly, the improvement in performance achievable by improvements in the technology base can be tested and assessed in advance. Moreover, different system concepts, i.e. circuit topologies, control procedures, etc. can be evaluated and directly compared with regard to achievable efficiency, power density and costs in the form of the associated Pareto Front which defines the boundary of the Feasible Performance Space. If the target performance lies outside the Pareto Envelope of known system concepts and state-of-the-art technologies, a new technology must be employed. The necessity of a technological leap, i.e. the introduction of a Disruptive Technology can thus be recognized at an early stage. This offers an excellent basis for effective roadmapping for various main application areas in power electronics.
Recursive Gauss-Newton based for neural network modelling of rotorcraft dynamics training algorithm an unmanned

The ability to model the time varying dynamics of an unmanned rotorcraft is an important aspect in the development of adaptive flight controller. This paper presents a recursive Gauss-Newton based training algorithm to model the attitude dynamics of a small scale rotorcraft based unmanned aerial system using the neural network (NN) modelling approach. It focuses on selection of optimised network for recursive algorithm that offers good generalisation performance with the aid of the cross validation method proposed. The recursive method is then compared with the off'-line Levenberg-Marquardt (LM) training method to evaluate the generalisation performance and adaptability ofthe model. The results indicate that the recursive Gauss-Newton (rGN) method gives slightly lower generalisation perfbrmance compared with its off-line counterpart but adapts well to the dynamic changes that occur during flight. The proposed recursive algorithm was found effective in representing helicopter dynamics with acceptable accuracy within the available computational time constraint.
The Effect of Intestinal Ischemia and Reperfusion Injury on ICAM-1 Expression, Endothelial Barrier Function, Neutrophil Tissue Influx, and Protease Inhibitor Levels in Rats

Multiple organ dysfunction syndrome (MODS) is mediated by complex mechanisms in which interactions between activated leukocytes and endothelial cells play a central role. ICAM-1 (intercellular adhesion molecule-1) mediates firm adhesion and transendothelial migration of activated leukocytes from postcapillary venules into the tissue. The present study evaluated the ICAM-1 expression in various organs after 40 min of intestinal ischemia and 1, 3, 6, 12 h of reperfusion (I/R) in the rat, using a dual monoclonal antibody technique (n = 36). Endothelial barrier permeability, using the vascular leakage of radiolabeled human serum albumin was also assessed (n = 12). Neutrophil sequestration in the lungs was quantitated by myeloperoxidase activity and plasma protease inhibitor levels were measured with electroimmunoassay. Significant regional differences were found in ICAM-1 expression between organs, both constitutively and after I/R-injury. The highest constitutive levels were observed in the liver and lungs, followed by the kidneys. The constitutive ICAM-1 expression in the intestines and in the heart was about 1/20 compared with that found in the liver and lungs. The brain and muscle had levels of about 1/150 of that in the liver and lungs. After intestinal I/R, significant increases (17–45%) were found in the lungs, intestines, brain, heart, and muscle. Albumin leakage index (ALI) in all examined organs and myeloperoxidase activity in the lungs increased after I/R-injury. Serum levels of albumin and most protease inhibitors decreased significantly after I/R challenge. Intestinal I/R results in an increase of systemic ICAM-1 expression with marked organ variability. The upregulation of ICAM-1 could represent a crucial step in the adherence- and migration process of activated leukocytes and potentially in the development of tissue injury.