Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Optimal Control of Line of Sight Stabilization of Moving Target

The Line-of-Sight stabilization and tracking control based on gyro stabilized platform is required to isolate Line of sight from the movement and vibration of carrier and ensure pointing and tracking for target in electro-optical tracking system. This work describes the design of a high performance controller for an electromechanical target tracking system with an optical sensor for sighting. The control law has been obtained using a linear model of the electro mechanical system. The modelling of the system has been carried out using the experimental frequency response data. The PID adesigning of control system methodology has been used to design the controller and study the comparative analysis using both controller and optimized tuned performance is also seeing by using the designing the PID controller in different loop analysis and study responses of system by using step response and frequency response analysis by using the bode diagram so as to stabilize the line of sight stabilization and tracking control system. The mixed sensitivity optimisation problem has been posed and weighting functions are selected by using the gradient and dissent method having more numbers of iterations so that they not only encapsulate all the design goals but also accommodate the modelling uncertainties. A stabilising controller with excellent robustness properties has been obtained. Investigator has used MATLAB for the designing of controller and simulated the system for a required criterion of the system.
Climate Change or Urbanization? Impacts on a Traditional Coffee Production System in East Africa over the Last 80 Years

Global environmental changes (GEC) such as climate change (CC) and climate variability have serious impacts in the tropics, particularly in Africa. These are compounded by changes in land use/land cover, which in turn are driven mainly by economic and population growth, and urbanization. These factors create a feedback loop, which affects ecosystems and particularly ecosystem services, for example plant-insect interactions, and by consequence agricultural productivity. We studied effects of GEC at a local level, using a traditional coffee production area in greater Nairobi, Kenya. We chose coffee, the most valuable agricultural commodity worldwide, as it generates income for 100 million people, mainly in the developing world. Using the coffee berry borer, the most serious biotic threat to global coffee production, we show how environmental changes and different production systems (shaded and sun-grown coffee) can affect the crop. We combined detailed entomological assessments with historic climate records (from 1929–2011), and spatial and demographic data, to assess GEC's impact on coffee at a local scale. Additionally, we tested the utility of an adaptation strategy that is simple and easy to implement. Our results show that while interactions between CC and migration/urbanization, with its resultant landscape modifications, create a feedback loop whereby agroecosystems such as coffee are adversely affected, bio-diverse shaded coffee proved far more resilient and productive than coffee grown in monoculture, and was significantly less harmed by its insect pest. Thus, a relatively simple strategy such as shading coffee can tremendously improve resilience of agro-ecosystems, providing small-scale farmers in Africa with an easily implemented tool to safeguard their livelihoods in a changing climate.
Eecient Parallel Algorithms for Planar St-graphs

Planar st-graphs nd applications in a number of areas. In this paper, we present eecient parallel algorithms for solving several fundamental problems on planar st-graphs. The problems we consider include all-pairs shortest paths in weighted planar st-graphs, single-source shortest paths in weighted planar layered digraphs (which can be reduced to single-source shortest paths in certain special planar st-graphs), and depth-rst search in planar st-graphs. Our parallel shortest path techniques exploit the speciic geometric and graphic structures of planar st-graphs, and involve schemes for partitioning planar st-graphs into subgraphs in a way that ensures that the resulting path length matrices have a monotonicity property 1, 2]. The parallel algorithms we obtain are considerable improvement over the previously best known solutions (when they are applied to these st-graph problems), and are in fact relatively simple. The parallel computational models we use are the CREW PRAM and EREW PRAM.
Bile secretory function in the obese Zucker rat: evidence of cholestasis and altered canalicular transport function

Background: Obese Zucker rats (ZR) have been used as an experimental model for non-alcoholic fatty liver disease and are particularly susceptible to various types of liver injury. Bile secretory function has not been assessed in ZR. Aim: To study bile secretion and expression of the main hepatobiliary transporters in ZR. Methods: Bile flow and biliary secretion of lipids and glutathione were determined in eight and 14 week old obese ZR and their lean controls. Protein mass and mRNA of the Na+/taurocholate cotransporting polypeptide (Ntcp), the bile salt export pump (Bsep), and the multidrug resistant associated protein 2 (Mrp2) were assessed by western and northern blot, respectively. The effects of administration of a tumour necrosis factor α inactivator (etanercept) and an insulin sensitiser (rosiglitazone) were assessed in obese ZR while leptin was given to non-obese rats to study its effect on Mrp2 expression. Results: ZR exhibited increased body weight and hyperlipidaemia. Only 14 week old obese ZR has fatty liver. Decreased bile flow and biliary lipid and glutathione secretion as well as reduced hepatic transport of both taurocholate and bromosulphthalein were found in obese ZR. Hepatic Mrp2 protein mass was markedly reduced (−70%) in obese rats while Ntcp and Bsep protein levels were similar to lean rats. Downregulation of Mrp2 seems to involve both transcriptional and post-transcriptional mechanisms probably related to insulin and leptin resistance. Conclusions: Obese ZR exhibit an impaired bile secretory function with significant functional and molecular alterations consistent with mild cholestasis. A defective hepatobiliary transport capacity may be a contributory factor in rendering the obese ZR more susceptible to liver injury.
Video matting by automatic scribbling using Quadra directional filling of segmented frames

Video matting is defined as the process of changing the background of the video by extracting the foreground image from each frame of a video. In this paper, we propose a video matting technique which uses Ncut segmentation technique to segment the frames. Further, Sobel edge detection technique is used on the segmented frames for detecting edges. Afterwards, Edge thickening process fills up all the gaps in between the edges and Quadra directional filling method generates the probability maps (PMs). The frames are scribbled with reference to the constructed PMs. Scribbled frame and the original frame along with a new background image are then fed to closed form matting technique which gives the frame with the changed background.
Power transformer fault diagnosis based on multi-class multi-kernel learning relevance vector machine

Diagnosis of potential faults concealed inside power transformers is the key of ensuring power system safety. The existing transformer diagnosis methods only infer based on single informative data and it is difficult to detect transformer faults more correctly. In this paper, fault diagnosis based on multi-class multi-kernel learning relevance vector machine (MMKL-RVM) is proposed which can integrate the informative data that can indicate the existence of fault. MMKL-RVM achieves sparsity without the constraint of having a binary class problem and provides probabilistic outputs for class membership instead of the hard binary decisions given by the traditional SVM. Most importantly, MMKL-RVM enables informative integration of possibly heterogeneous informative data or feature spaces in a multitude of ways, from the simple summation of feature expansions to weighted product of kernels. Additionally, Genetic Algorithm (GA) combined with K-fold Cross Validation (K-CV) method is adopted to optimize the kernels parameters in order to enhance the performance of the MMKL-RVM. Experimental results show that MMKL-RVM is capable of more excellent diagnosis accuracy to BP neural network and SVM.
Bandit Algorithms in Game Tree Search : Application to Computer Renju ∗

Multi-armed bandit problem is to maximize a cumulated reward by playing arms sequentially without prior knowledge. Algorithms for this problem such as UCT have been successfully extended to computer GO programs and proved significantly effective by defeating professional players. The goal of the project is to implement a Renju AI based on Monte Carlo planning that is able to defeat the oldest known alpha-beta pruning AI. In this project we will give an implementation of the UCT algorithm and attempt to improve the minimax tree search by modeling the dependencies between arms. Our work is greatly inspired by the theoretical advances in GPTS(Gaussian Process for Tree Search) where the mean reward function is drawn from a Gaussian Process. Applying GPTS to game tree search is by no means trivial and it would be interesting to see how it works in practice.
LEDA: A High-Power Test Bed of Innovation and Opportunity

The low-energy demonstration accelerator (LEDA) is an operational 6.7-MeV, 100-mA, cw proton accelerator consisting of an injector, radio-frequency quadrupole (RFQ), and all associated integration equipment. Achieving this unprecedented level of performance (670kW of beam power) from an RFQ required a number of design innovations. We highlight a number of those more-significant technical advances, including those in the proton injector, the RFQ configuration, the RF klystrons, the beam stop, and beam measurements. In addition to identifying the importance of these innovations to LEDA performance, we summarize the plans for further testing, and the possibilities for addition of more accelerating structures, including the possible use of very-low-beta super-conducting structures. LEDA’s current and upgradable configuration is appropriate for several future high-power accelerators, including those for the transmutation of radioactive waste.
Sliding Control Approach to Pneumatic Hydraulic Combination Control (PHCC) Servo System

This paper presents a new model of the pneumatic hydraulic combination control (PHCQ position servo system, which is driven by pulse-width-modulation (PWM). The model was built by applying nonlinear state averaging method into the control of PWM in pneumatic systems, which not only overcame discontinuity of on/off valves, but also changed discontinuous nonlinear and non-affine form into a control canonical nonlinear affine form. Then a sliding controller was designed according to traditional sliding mode controller designing of nonlinear and uncertain systems and the method of sliding mode surface designing. The controller was implemented on PHCC position servo system with fixed liquid throttled, the effectiveness of the proposed approach is validated by experimental tracking data, which shows the aspects on speediness of PHCC systems optimal
Convergence of Mutation and Epigenetic Alterations Identifies Common Genes in Cancer That Predict for Poor Prognosis

Background The identification and characterization of tumor suppressor genes has enhanced our understanding of the biology of cancer and enabled the development of new diagnostic and therapeutic modalities. Whereas in past decades, a handful of tumor suppressors have been slowly identified using techniques such as linkage analysis, large-scale sequencing of the cancer genome has enabled the rapid identification of a large number of genes that are mutated in cancer. However, determining which of these many genes play key roles in cancer development has proven challenging. Specifically, recent sequencing of human breast and colon cancers has revealed a large number of somatic gene mutations, but virtually all are heterozygous, occur at low frequency, and are tumor-type specific. We hypothesize that key tumor suppressor genes in cancer may be subject to mutation or hypermethylation. Methods and Findings Here, we show that combined genetic and epigenetic analysis of these genes reveals many with a higher putative tumor suppressor status than would otherwise be appreciated. At least 36 of the 189 genes newly recognized to be mutated are targets of promoter CpG island hypermethylation, often in both colon and breast cancer cell lines. Analyses of primary tumors show that 18 of these genes are hypermethylated strictly in primary cancers and often with an incidence that is much higher than for the mutations and which is not restricted to a single tumor-type. In the identical breast cancer cell lines in which the mutations were identified, hypermethylation is usually, but not always, mutually exclusive from genetic changes for a given tumor, and there is a high incidence of concomitant loss of expression. Sixteen out of 18 (89%) of these genes map to loci deleted in human cancers. Lastly, and most importantly, the reduced expression of a subset of these genes strongly correlates with poor clinical outcome. Conclusions Using an unbiased genome-wide approach, our analysis has enabled the discovery of a number of clinically significant genes targeted by multiple modes of inactivation in breast and colon cancer. Importantly, we demonstrate that a subset of these genes predict strongly for poor clinical outcome. Our data define a set of genes that are targeted by both genetic and epigenetic events, predict for clinical prognosis, and are likely fundamentally important for cancer initiation or progression.
Flash Storage Applications and Challenges

The Solid State Disk (SSD) implemented using NAND flash memory significantly outperforms conventional rotating magnetic disk drive in read performance. However, write performance of flash based SSDs can be up to an order of magnitude slower than its read performance. This fundamental disparity is caused by the fact that flash write operations are immutable and a data sector must be erased before it is rewritten. Furthermore, frequent write operations degrade the lifetime of flash memory over time. In this thesis, various techniques have been proposed to improve write performance of flash memory as well as flash-aware algorithms are designed to avoid frequent update operations.
An Extensible Framework for Internet Booking Application Based on Rule Engine

The bloom of Internet and the convenience of e-Commerce bring a lot of demands of Internet booking applications. There are two challenges in Internet Booking Applications: high volume concurrent processing and complex business processing. Facing these two challenges, we designed an extensible framework for Internet booking applications, which includes an Internet Booking Engine, a rule engine, and three kinds of servers. The architectures of e-Commerce applications usually consist of web server, application server and database server. The efficiency of the system is deeply influenced by the distribution of the functions among these servers and the communication methods between them. Three different architectures were designed and implemented. The Internet Booking Engine includes two kernel online booking modules: searching tickets and booking tickets. While dealing with complex and flexible business logics, the rule engine can reason with the business facts to get the result and take the corresponding action for specific applications by following the business rules. In vertical and horizontal directions, Internet Booking Engine can be extended to different Internet booking applications.
Incorporated File Replication and Consistency Maintenance in P2P Systems with Sanctuary

— In peer-to-peer file sharing systems, file replication and consistency maintenance are broadly used techniques for high system recital. Despite significant interdependencies between them, these two issues are typically addressed separately. This paper presents an Integrated file Replication and consistency Maintenance mechanism (IRM). Integrated file Replication and consistency Maintenance mechanism integrates the two techniques in a systematic and harmonized manner. The security has become one of the major issues for data communication over worldwide networks. Currently many number of people using the internet. With the lack of security the data may be hacked. So in this we are introducing the routers in between the replica nodes and clients. Which protects sensitive information from unauthorized access? This routers provides security The main objective of the paper is to propose a dynamic routing with security considered using strongest algorithm, such as Blow fish algorithm which is a provide the strong security from the client to the server system. Consequently that the data which is approved by the network can’t be admitted by the hackers. Without bringing up the rear data. At this point expenditure for providing The alleyway in between the client and server is fully covered with high security. It dramatically reduces overhead and yields noteworthy improvements on the competence of file replication, consistency maintenance and security maintenance approaches
Analyzing TCP Throughput Stability and Predictability with Implications for Adaptive Video Streaming

Recent work suggests that TCP throughput stability and predictability within a video viewing session can inform the design of better video bitrate adaptation algorithms. Despite a rich tradition of Internet measurement, however, our understanding of throughput stability and predictability is quite limited. To bridge this gap, we present a measurement study of throughput stability using a large-scale dataset from a video service provider. Drawing on this analysis, we propose a simple-but-effective prediction mechanism based on a hidden Markov model and demonstrate that it outperforms other approaches. We also show the practical implications in improving the user experience of adaptive video streaming.
A Conceptual Framework for Analyzing Pricing Strategies

of the most dif f icult, yet important, issues that a f irm must decide is how much to charge f or its product/ service. Furthermore, considering the pressure of the developing technologies that shif ts the consumers away f rom traditional distribution channels towards the Internet-based distribution channels, determining the most appropriate pricing strategy becomes a more challenging task. In this paper, a generalized f ramework is proposed f rom the perspective of a f irm that needs to decide on its pricing strategy f or each of the possible market scenario. The f ramework allows the f irm to compute the estimated prof it in each scenario and then choose the most prof itable one.
Fault Diagnosis Based on Wavelet Neural Network

As wind power generation is a complicated nonlinear time-varying system, it's hard to extract effective fault feature. A novel arithmetic that combines modified LDB (Local Discriminant Basis) algorithm and SOM-BP network is proposed in this paper for fault diagnosis and location. First original fault features are extracted by improved LDB algorithm, then these fault features are mapped into a new feature space with high class separability via SOM (Self-Organizing Feature Map) nonlinearly transform, finally BP is used as a nonlinear classifier to implement fault diagnosis and location.
Blended Planning and Acting: Preliminary Approach, Research Challenges

In a recent position paper in Artificial Intelligence, we argued that the automated planning research literature has underestimated the importance and difficulty of deliberative acting, which is more than just interleaving planning and execution. We called for more research on the AI problems that emerge when attempting to integrate acting with planning. To provide a basis for such research, it will be important to have a formalization of acting that can be useful in practice. This is needed in the same way that a formal account of planning was necessary for research on planning. We describe some first steps toward developing such a formalization, and invite readers to carry out research along this line.
ERS and ERD analysis during the imaginary movement of arms

Brain-Computer Interface (BCI) is an interface technique between human and computer which can help severely motor-disabled persons to communicate and control their environment. Many researchers use EEG signals for BCI. However, these studies are early stages and it has some problems such as a lack of accurate analysis and measurements with many electrodes. Therefore, we propose an EEG signals measurement method and analysis methods for BCI. Our purpose of this study is to recognize subjectpsilas intention when they move their arms. EEG signals are recorded during the imaginary movement of subjectpsilas arms at electrode positions Fp1, Fp2, C3, and C4. We analyzed ERS (Event-Related Synchronization) and ERD (Event-Related Desynchronization) which are detected when people move their limbs in the mu wave and beta wave. Results of this study showed that ERD occurred in mu waves and ERS occurred in beta waves at C3 during the imaginary movement of right arm. Similarly, ERD occurred in mu waves and ERS occurred in beta waves at C4 during the imaginary movement of left arm. And ERD occurred at Fp1 and Fp2, in both case.
An new algorithm for analyzing driver's attention state

Monitoring and analyzing the fatigue and attention state by using the machine vision is one of hotspots in the assistant safe driving system. The idea of face and face organ location is introduced firstly and the techniques for Driver Face Orientation in this system are discussed mostly and then a strategy is used for judging whether the driver's attention is disturbed or not; Based on analyzing the head rotary motion, an algorithm for calculating the facial rotary angle of drivers is proposed. Practice proves that the algorithm proposed acts in real time and obtains excellent effect, which provide more accurate basis for analyzing of the driver's attention state.
Analysis of Clinical Percussion Signals Using Matching Pursuit

Clinical percussion is a method of eliciting sounds from the body by tapping with either a percussion hammer or fingers to determine the area under the perused is air filled, fluid filled, or solid, and is used in clinical examinations to assess the condition of the thorax or abdomen. Successful diagnosis today is still highly subjective and dependent's on physician skill, experience and require quite surrounding areas. An automated system capable of delivering standardized percussion analysis would remove these limitations on the technique and allow for its usage by those without such specialized training and years of necessary experience. For this to be possible, efficient and informative signal processing algorithms must be employed. In this investigation, clinical percussions from healthy volunteers taken by trained medical professionals were analysed via the matching pursuit (MP) algorithm. Various types of possible dictionaries are discussed comparing their efficiency and convergence behaviour. Noise filtering methods are discussed and a noise reduction method based on MP analysis results is presented.MP is also compared to other methods for representing clinical percussions with regards to informativeness and efficiency. MP is ��(��log��) which is more efficient than current methods which have a complexity of at least ��(�� 3 ).
On the quasi-ordinary cuspidal foliations in (C^3,0)

We study a class of holomorphic foliations in (C^3,0) that can be desingularized following the same desingularization chain that a certain quasi-ordinary surface. This intends to be a generalization to the dimension three of the cuspodal foliations in dimension two studied by different authors.