Miracle-dz/UniFAR-FTUs huggingface dataset:
Analisis Perbandingan Teknologi 3-Liquid Crystal Display & Digital Light Processing Pada Proyektor

Seiring dengan perkembangan zaman, manusia berhasil menemukan berbagai macam teknologi yang berguna untuk kehidupan sehari-hari. Penggunaan Proyektor adalah salah satu dari perkembangan teknologi saat ini. Ada dua tipe teknologi proyektor yang sangat populer pada saat ini yaitu teknologi Digital Light Processing (DLP) proyektor dan teknologi 3-Liquid Crystal Display (3LCD) proyektor. Teknologi manakah yang terbaik di antara keduanya? Penelitian ini melakukan pencarian data dari sumber yang dapat dipercaya berupa buku petunjuk manual dari ke dua teknologi proyektor yang akan di bandingakan. Selain itu peneliti juga menyebarkan kuisioner untuk mengumpulkan data untuk mencari perbandingan antara ke dua teknologi tersebut, serta melakukan Observasi dalam rangka melihat langsung perbedaan dari kedua Proyektor tersebut. Kelebihan yang dimiliki oleh teknologi DLP ini antara lain video lebih halus, kotak kecil atau piksel yang kurang terlihat, visi /tampilan seperti film di HDTV, menghasilkan kulit hitam yang lebih hitam, Kontras lebih tinggi, dan ukuran proyektor yang portable. Kelebihan dari LCD adalah penggunaan cahaya yang lebih efisien sehingga dapat memproduksi “ansi lumens” yang lebih tinggi dibandingkan proyektor dengan teknologi DLP. Teknologi 3LCD dan DLP pada proyektor adalah teknologi yang memiliki perbedaan dari segi proses pencahayaan, mulai dari input cahaya sampai di proses atau dirpoyeksikan menjadi gambar atau video. Masing-masing memiliki kelebihan dan kelemahan.
Journal of Graph Algorithms and Applications Confluent Drawings: Visualizing Non-planar Diagrams in a Planar Way

We introduce a new approach for drawing diagrams. Our approach is to use a technique we call confluent drawing for visualizing non-planar graphs in a planar way. This approach allows us to draw, in a crossing-free manner, graphs—such as software interaction diagrams—that would normally have many crossings. The main idea of this approach is quite simple: we allow groups of edges to be merged together and drawn as " tracks " (similar to train tracks). Producing such confluent drawings automatically from a graph with many crossings is quite challenging, however, we offer a heuristic algorithm (one version for undirected graphs and one version for directed ones) to test if a non-planar graph can be drawn efficiently in a confluent way. In addition, we identify several large classes of graphs that can be completely categorized as being either confluently drawable or confluently non-drawable.
An Electro-Magnetic Energy Harvesting System With 190 nW Idle Mode Power Consumption for a BAW Based Wireless Sensor Node

State-of-the-art wireless sensor nodes are mostly supplied by batteries. Such systems have the disadvantage that they are not maintenance free because of the limited lifetime of batteries. Instead, wireless sensor nodes or related devices can be remotely powered. To increase the operating range and applicability of these remotely powered devices an electro-magnetic energy harvester iPs developed in a 0.13 μ m low cost CMOS technology. This paper presents an energy harvesting system that converts RF power to DC power to supply wireless sensor nodes, active transmitters or related systems with a power consumption up to the mW range. This energy harvesting system is used to power a wireless sensor node from the 900 MHz RF field. The wireless sensor node includes an on-chip temperature sensor and a bulk acoustic wave (BAW) based transmitter. The BAW resonator reduces the startup time of the transmitter to about 2 μs which reduces the amount of energy needed in one transmission cycle. The maximum output power of the transmitter is 5.4 dBm. The chip contains an ultra-low-power control unit and consumes only 190 nW in idle mode. The required input power is -19.7 dBm.
Formal Automatic Verification of Cache Coherence in Multiprocessors with Relaxed Memory Models

State-based, formal methods have been successfully applied to the automatic verification of cache coherence in sequentially consistent systems. However, coherence in shared memory multiprocessors under a relaxed memory model is much more complex to verify automatically. With relaxed memory models, incoming invalidations and outgoing updates can be delayed in each cache while processors are allowed to race ahead. This buffering of memory accesses considerably increases the amount of state in each cache and the complexity of protocol interactions. Moreover, because caches can hold inconsistent copies of the same data for long periods of time, coherence cannot be verified by simply checking that cached copies are identical at all times. This paper makes two major contributions. First, we demonstrate how to model and verify cache coherence under a relaxed memory model in the context of state-based verification methods. Frameworks for modeling the hardware and for generating correct memory access sequences driving the hardware model are developed. We also show correctness properties which must be verified on the hardware model. Second, we demonstrate a successful application of a state-based verification tool called SSM for the verification of the delayed protocol, an aggressive protocol for relaxed memory models. SSM is based on an abstraction technique preserving the properties to verify. We show that with classical, explicit approaches the verification of cache coherence is realistically unfeasible because of the state space explosion problem, whereas SSM is able to verify protocols both at both behavioral and message-passing levels.
Hierarchically Optimal Average Reward Reinforcement Learning

Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality , or the optimal policy in the space de(cid:12)ned by a task hierarchy, and a weaker local model called recursive optimality . In this paper, we introduce two new average-reward HRL algorithms for (cid:12)nding hierarchically optimal policies. We compare them to our previously re-ported algorithms for computing recursively optimal policies, using a grid-world taxi problem and a more real-world AGV scheduling problem. The new algorithms are based on a three-part value function decomposition proposed recently by Andre and Russell, which generalizes Dietterich’s MAXQ value function decomposition. A key di(cid:11)erence between the algorithms proposed in this paper and our previous work is that there is only a single global gain (average reward), instead of a gain for each subtask. Our results show the new average-reward algorithms have better performance than both the previous re-cursively optimal counterparts, as well as the corresponding discounted hierarchical optimal algorithms.
Gene targeted therapeutics for liver disease in alpha-1 antitrypsin deficiency

Alpha-1 antitrypsin (A1AT) is a 52 kDa serine protease inhibitor that is synthesized in and secreted from the liver. Although it is present in all tissues in the body the present consensus is that its main role is to inhibit neutrophil elastase in the lung. A1AT deficiency occurs due to mutations of the A1AT gene that reduce serum A1AT levels to <35% of normal. The most clinically significant form of A1AT deficiency is caused by the Z mutation (Glu342Lys). ZA1AT polymerizes in the endoplasmic reticulum of liver cells and the resulting accumulation of the mutant protein can lead to liver disease, while the reduction in circulating A1AT can result in lung disease including early onset emphysema. There is currently no available treatment for the liver disease other than transplantation and therapies for the lung manifestations of the disease remain limited. Gene therapy is an evolving field which may be of use as a treatment for A1AT deficiency. As the liver disease associated with A1AT deficiency may represent a gain of function possible gene therapies for this condition include the use of ribozymes, peptide nucleic acids (PNAs) and RNA interference (RNAi), which by decreasing the amount of aberrant protein in cells may impact on the pathogenesis of the condition.
The Software Prototype as Digital Boundary Object - A Revelatory Longitudinal Innovation Case

With the availability of lower cost but highly skilled software development labor from offshore regions, entrepreneurs from developed countries who do not have software development experience can utilize this workforce to develop innovative software products. In order to succeed in offshored innovation projects, the often extreme knowledge boundaries between the onsite entrepreneur and the offshore software development team have to be overcome. Prior research has proposed that boundary objects are critical for bridging such boundaries – if they are appropriately used. Our longitudinal, revelatory case study of a software innovation project is one of the first to explore the role of the software prototype as a digital boundary object. Our study empirically unpacks five use practices that transform the software prototype into a boundary object such that knowledge boundaries are bridged. Our findings provide new theoretical insights for literature on software innovation and boundary objects, and have implications for practice.
Addressing the Need for Map-Matching Speed: Localizing Global Curve-Matching Algorithms

With vehicle tracking data becoming an important sensor data resource for a range of applications related to traffic assessment and prediction, fast and accurate map-matching algorithms become a necessary means to ultimately utilize this data. This work proposes a fast map-matching algorithm which exploits tracking data error estimates in a provably correct way and offers a quality guarantee for the computed result trajectory. A new model for the map-matching task is introduced which takes tracking error estimates into account. The proposed adaptive clipping algorithm (i) provably solves this map-matching task and (ii) utilizes the weak Frechet distance to measure similarity between curves. The algorithm uses the error estimates in the trajectory data to reduce the search space (error-aware pruning), while offering the quality guarantee of finding a curve which minimizes the weak Frechet distance to the vehicle trajectory among all possible curves in the road network. Moreover, this work introduces an output-sensitive variant of an existing weak Frechet map-matching algorithm, which is also employed in the adaptive clipping algorithm. Output-sensitiveness paired with error-aware pruning makes adaptive clipping the first map-matching algorithm that provably solves a well-defined map-matching task. An experimental evaluation establishes further that adaptive clipping is also in a practical setting a fast algorithm that at the same time produces high-quality matching results
Increased Glycation and Oxidative Damage to Apolipoprotein B100 of LDL Cholesterol in Patients With Type 2 Diabetes and Effect of Metformin

OBJECTIVE The aim of this study was to investigate whether apolipoprotein B100 of LDL suffers increased damage by glycation, oxidation, and nitration in patients with type 2 diabetes, including patients receiving metformin therapy. RESEARCH DESIGN AND METHODS For this study, 32 type 2 diabetic patients and 21 healthy control subjects were recruited; 13 diabetic patients were receiving metformin therapy (median dose: 1.50 g/day). LDL was isolated from venous plasma by ultracentrifugation, delipidated, digested, and analyzed for protein glycation, oxidation, and nitration adducts by stable isotopic dilution analysis tandem mass spectrometry. RESULTS Advanced glycation end product (AGE) content of apolipoprotein B100 of LDL from type 2 diabetic patients was higher than from healthy subjects: arginine-derived AGE, 15.8 vs. 5.3 mol% (P < 0.001); and lysine-derived AGE, 2.5 vs. 1.5 mol% (P < 0.05). Oxidative damage, mainly methionine sulfoxide residues, was also increased: 2.5 vs. 1.1 molar equivalents (P < 0.001). 3-Nitrotyrosine content was decreased: 0.04 vs. 0.12 mol% (P < 0.05). In diabetic patients receiving metformin therapy, arginine-derived AGE and methionine sulfoxide were lower than in patients not receiving metformin: 19.3 vs. 8.9 mol% (P < 0.01) and 2.9 vs. 1.9 mol% (P < 0.05), respectively; 3-nitrotyrosine content was higher: 0.10 vs. 0.03 mol% (P < 0.05). Fructosyl-lysine residue content correlated positively with fasting plasma glucose. Arginine-derived AGE residue contents were intercorrelated and also correlated positively with methionine sulfoxide. CONCLUSIONS Patients with type 2 diabetes had increased arginine-derived AGEs and oxidative damage in apolipoprotein B100 of LDL. This was lower in patients receiving metformin therapy, which may contribute to decreased oxidative damage, atherogenicity, and cardiovascular disease.
Profile guided code positioning

This paper presents the results of our investigation of code positioning techniques using execution profile data as input into the compilation process. The primary objective of the positioning is to reduce the overhead of the instruction memory hierarchy. After initial investigation in the literature, we decided to implement two prototypes for the Hewlett-Packard Precision Architecture (PA-RISC). The first, built on top of the linker, positions code based on whole procedures. This prototype has the ability to move procedures into an order that is determined by a “closest is best” strategy. The second prototype, built on top of an existing optimizer package, positions code based on basic blocks within procedures. Groups of basic blocks that would be better as straight-line sequences are identified as chains. These chains are then ordered according to branch heuristics. Code that is never executed during the data collection runs can be physically separated from the primary code of a procedure by a technique we devised called procedure splitting. The algorithms we implemented are described through examples in this paper. The performance improvements from our work are also summarized in various tables and charts.
Energy Efficient Routing in Multiple Sink Sensor Networks

Wireless sensor networks have been widely used in many fields with the developments of the related techniques. But there are many problems in traditional single sink sensor networks. The energy of the sensors near the sink or on the critical paths consumes too fast causing unbalanced energy consumption. The routing algorithms mainly focus on the nearest path or minimum hops. The invalidation of the single sink node causes the breakdown of the whole sensor network. In this paper, through the analysis of the disadvantages of single-sink sensor networks, we propose the system architecture of multi-sink sensor networks and new routing algorithms ELBR (Energy Level Based Routing) and PBR (Primary Based Routing) in multi-sink sensor networks. Experiment results show ELBR and PBR have better performances than traditional methods and balance the energy consumption in sensor networks.
Adaptive input admission and management for parallel stream processing

In this paper, we propose a framework for adaptive admission control and management of a large number of dynamic input streams in parallel stream processing engines. The framework takes as input any available information about input stream behaviors and the requirements of the query processing layer, and adaptively decides how to adjust the entry points of streams to the system. As the optimization decisions propagate early from input management layer to the query processing layer, the size of the cluster is minimized, the load balance is maintained, and latency bounds of queries are met in a more effective and timely manner. Declarative integration of external meta-data about data sources makes the system more robust and resource-efficient. Additionally, exploiting knowledge about queries moves data partitioning to the input management layer, where better load balance for query processing can be achieved. We implemented these techniques as a part of the Borealis stream processing system and conducted experiments showing the performance benefits of our framework.
Accurate Wireless Location and Tracking Technique for Indoor UWB Non-linear/Non-Gaussian Systems

This paper deals with the joint TOA/DOA (time of arrival/direction of arrival) estimation and tracking of UWB source. The TOA and DOA of the moving target were estimated with the low complexity array processing, then, a particle filter was presented to accurately track the target's real-time location and velocity. This tracking method is effective to the in door UWB non-Linear/non-Gaussian systems and the performance is greatly superior to the standard extended Kalman filter.
A Highly Parallel Multigrid-Like Method for the Solution of the Euler Equations

A highly parallel multigrid-like method for the solution of the two-dimensional steady Euler equations is considered. The new method, introduced in [T. Chan and R. Tuminaro, in Proc. Third Copper Mountain Conference on Multigrid Methods, 1987, pp. 101–115] as a “filtering” multigrid, is similar to a standard multigrid scheme in that convergence on the finest grid is accelerated by iterations on coarser grids. In the filtering method, however, additional fine grid subproblems are processed concurrently with coarse grid computations to further accelerate convergence. These additional problems are obtained by splitting the residual into a smooth and an oscillatory component. The smooth component is then used to form a coarse grid problem (similar to standard multigrid) while the oscillatory component is used for a fine grid subproblem. The primary advantage in the filtering approach is that fewer iterations are required and that most of the additional work per iteration can be performed in parallel with the .
Topologically correct reconstruction of tortuous contour forests

Motivated by the need for correct and robust 3D models of neuronal processes, we present a method for reconstruction of spatially realistic and topologically correct models from planar cross sections of multiple objects. Previous work in 3D reconstruction from serial contours has focused on reconstructing one object at a time, potentially producing inter-object intersections between slices. We have developed a robust algorithm that removes these intersections using a geometric approach. Our method not only removes intersections but can guarantee a given minimum separation of objects. This paper describes the algorithm for geometric adjustment, proves correctness, and presents several results of our high-fidelity modeling.
Hand gesture recognition using multi-scale colour features, hierarchical models and particle filtering

This paper presents algorithms and a prototype system for hand tracking and hand posture recognition. Hand postures are represented in terms of hierarchies of multi-scale colour image features at different scales, with qualitative inter-relations in terms of scale, position and orientation. In each image, detection of multi-scale colour features is performed. Hand states are then simultaneously detected and tracked using particle filtering, with an extension of layered sampling referred to as hierarchical layered sampling. Experiments are presented showing that the performance of the system is substantially improved by performing feature detection in colour space and including a prior with respect to skin colour. These components have been integrated into a real-time prototype system, applied to a test problem of controlling consumer electronics using hand gestures. In a simplified demo scenario, this system has been successfully tested by participants at two fairs during 2001.
Joint space torque controller based on time-delay control with collision detection

This paper addresses a control method for friction-existing robot manipulators and safe motion with its environment. In order to control the robot manipulator with unknown effects, a time-delay control(TDC) method that eliminates the nonlinear effects is used to control the joint torque servo. Although the TDC is very adaptive in nonlinear systems, there is limitation of the TDC in a high friction robot manipulator; hence, a friction model is considered. A collision detecting method is proposed to secure safety for human and robot-interacting environment. Using the torque sensor attached at the joints of the robot arm, the collision is detected more effectively. After detecting collision, a safety reaction method is applied. A torque sensor based 3-joints robot arm is used to verify the performance of the proposed methods.
The impact of tropical sea surface temperature perturbations on atmospheric circulation over north Canada and Greenland

Identifying the drivers of Arctic climate variability is essential for understanding the recent rapid changes in local climate and determining the mechanisms that cause them. Remote tropical sea surface temperatures (SST) have been identified in previous studies as having contributed to the recent positive trends in surface temperature and geopotential height at 200 hPa over north Canada and Greenland (1979-2012) through poleward propagating Rossby waves. However, the source and direction of wave propagation on to north Canada and Greenland (NCG) differs across climate datasets indicating that there are still uncertainties surrounding the mechanisms for how the tropics influence the NCG climate. This thesis aims to further investigate the robustness of the trends over NCG and understand how circulation in this region responds to imposed tropical SST perturbations. The eddy 200 hPa geopotential height (Z200) trends over NCG are assessed in a number of different datasets and compared to the response of eddy Z200 over NCG to imposed tropical SST perturbations in a number of sensitivity studies using the HadGEM3 atmosphere-only model. These model experiments are forced with observed differences in SSTs from the beginning and end of the satellite record (1979-1988 and 2003-2012), with spatial perturbations for [i] the entire tropics, [ii] global SSTs, [iii] the tropical Pacific only, [iv] the tropical Atlantic SST only, [v] the tropical Indian Ocean only. The positive spatial trends of eddy Z200 over NCG from ERA-Interim reanalysis is largely captured in ensemble means of two available climate datasets, UPSCALE and
Mining Terminological Knowledge in Large Biomedical Corpora

Terminological knowledge of the biomedical domain is important for natural language processing (NLP) and information retrieval (IR) applications, and a number of terminological knowledge sources, such as LocusLink, GeneBank, and the UMLS, already exist. However, because of the tremendous amount of research activity in the field, new terms and symbols are continually being created, many of which are published in the literature, but are not available in any of the other resources. Therefore, effective mining of the literature for new terminology is critical for furthering NLP and IR applications. Abbreviations are widely used in the biomedical domain, and the understanding of abbreviations requires a terminological knowledge base that consists of abbreviations with their associated senses. In previous work, several methods have been developed for automatic construction of abbreviation knowledge bases from parenthetical expressions. However, these methods pair abbreviations and their expansions based on manually crafted patterns or rules. In this paper, we propose an automatic method, which is not based on patterns or rules but is based on the use of collocations, to extract a set of related terms from parenthetical expressions including abbreviations associated with their expansions and other types of related terms such as synonyms, or hyponyms etc. Our method is based on the observation that terms associated with parenthetical expressions i) are usually related, and ii) are often collocations because they tend to co-occur more often than expected by chance. Our method was applied to the collection of MEDLINE abstracts. The method and the results were evaluated using two collections: Berman's handcrafted abbreviation list and the LocusLink collection.