Miracle-dz/UniFAR-FTUs huggingface dataset:
Off-line handwriting identification using HMM based recognizers

An off-line, text independent system for writer identification using hidden Markov model (HMM) based recognizers is described. For each writer we build an individual recognizer and train it on text lines written by that writer. A text line of unknown origin is presented to each of these recognizers. As a result we get, from each recognizer, a transcription including the log-likelihood score for the considered input. We rank all scores, and based on the assumption that the recognizer with the highest log-likelihood is the one that has been trained using text lines of this writer, we assign the text line to the writer whose score ranks first. We tested our system using over 2,200 text lines from 50 writers and have in 94.47% of all cases correctly identified the writer. Using a simple confidence measure to define a rejection mechanism, we achieved an error rate of 0% by rejecting 15% of the results.
Classification of tree species in hyperspectral image

Hyperspectral remote sensing explores the surface of the earth using sensors that deliver large amounts of data. Satellite collects the data and sends it to ground station for processing. The work focuses on classification of tree species (like Bamboo, Arjun, koroi, Ejar, Mohr) in the forest and it is very important in forest records. In late years, numerous studies have been done using various types of hyperspectral sensors under diverse forest conditions. The complexity present in hyperspectral sensing is mainly due to the curse of dimensionality. A possible solution to overcome the dimensionality problem is to select the features using feature-selection technique. Features which increase the certainty of a given situation are considered more informative than other features. Sequential forward floating selection is the feature selection algorithm used in this paper. It selects the features with highest information so that it is easy for the classification. Classification is done after feature selection. Self organizing map, an unsupervised learning technique which is used to classify the species of tree. Further optimization can be done if more number of features are selected which may increases the classification accuracy considerably.
Closed-Form Solutions for Minimizing Sum MSE in Multiuser Relay Networks

A scenario consisting of single antenna source- destination node pairs communicating using multiple single antenna relays is considered. A transmission scheme utilizing two subsequent time-slots assuming a time invariant channel throughout the transmission period is applied to this scenario. In the first time-slot, the source nodes transmit to both the relays and the destination nodes. Both the source nodes and the relays retransmit to the destination nodes in the second time-slot. As the relays can not decode the received signals, amplify and forward relaying is used. By exploiting the direct links between the source and the destination nodes, each destination node observes a two dimensional signal space. In the present paper, the sum mean square error can be written as a convex quadratic function of the relays' gain and part of the temporal filters at the source and the destination nodes. Moreover, closed form solutions for the minimum sum mean square error with interference zero forcing constraints and a total energy constraint are obtained. The results show that the proposed schemes outperform the interference alignment scheme at low and moderate SNRs.
Far-Field Deformation Resulting from Rheologic Differences Interacting with Tectonic Stresses: An Example from the Pacific/Australian Plate Boundary in Southern New Zealand

The Miocene in Southern New Zealand was dominated by strike-slip tectonics. Stratigraphic evidence from this time attests to two zones of subsidence in the south: (a) a middle Cenozoic pull-apart basin and (b) a regionally extensive subsiding lake complex, which developed east and distal to the developing plate boundary structure. The lake overlay a block of crust with a significantly weak mid-crustal section and we pose the question: can rheological transitions at an angle to a plate boundary produce distal subsidence and/or uplift? We use stratigraphic, structural and geophysical observations from Southern New Zealand to constrain three-dimensional numerical models for a variety of boundary conditions and rheological scenarios. We show that coincident subsidence and uplift can result from purely strike-slip boundary conditions interacting with a transition from strong to weak to strong mid-crustal rheology. The resulting pattern of vertical displacement is a function of the symmetry or asymmetry of the boundary conditions and the extent and orientation of the rheological transitions. For the Southern New Zealand case study, subsidence rates of ~0.1 mm/yr are predicted for a relative plate motion of 25 mm/yr, leading to ~500 m of subsidence over a 5 Ma time period, comparable to the thickness of preserved lacustrine sediments.
MOBILITY PREDICTION AND NODE PREDICTION BASED LIGHT-WEIGHT RELIABLE BROADCAST MESSAGE DELIVERY IN VEHICULAR AD-HOC NETWORKS

VANET is a Vehicular Ad hoc-Network; it can able to communicate between the moving vehicles. The Reliability as well as Efficiency of Transmissions is of a paramount issue for the safety critical services of VANET due to the urgency and/or significance of the messages. The main problem in VANET is data transmission cannot be done in cross street due to some obstacles. To overcome this, existing work proposed "Light Weight Reliable Broadcast Message Delivery" mechanism is not effective but, in LWRBMD mechanisms broadcast the Message delivery could be difficult at the intersection zone due to choosing the wrong node and the node will be moving out of zone, which results in packet loss occur. While rebroadcasting is done the Bandwidth will be increased. Thus in our proposed work, we introduce two methods in order to predict the node and mobility. Based on these prediction methods we can improve the energy efficient. Which will decrease the Bandwidth for Packet Forwarding? In Intersection Zone the Packet will be forwarded, which decreases the packet loss and low data rate. Time Complexity Simulation results show that the proposed mechanism can provide similar or better reliability while incurring prominently less overheads than the existing approaches.1
History, identity, representation : public-private-community partnerships and the Batlokoa community.

iii Acronyms iv Map ix Chapter One : Introduction 1 Navigating the complexities of a New South Africa 1 What is a community? 3 Background of the Witsieshoek Mountain Lodge Establishment 4 Getting lost 4 Background of the Batlokoa Community 8 Situating this study 9 Background to study 10 Impetus for the creation of Independent ‘homelands’ or reserves 10 Outline of study 11 Chapter Two: Literature Review 13 Striking a balance within public-private-community partnerships 13 Tourism in Everyday Life 13 Tourism in the South African Context 14 Tourism as an enactment of affluence 15 Community-Based Tourism in Developing Countries 15 Sustainable Tourism 19 Tourism Partnerships 20 Women and Tourism 21
Readjusting Unstable Regions to Improve the Quality of High Accuracy Optical Flow

Optical flow is an important problem in computer vision since applications of accurate optical flow estimation enable us to control and manipulate tracking, 3-D reconstruction, motion blurring, and dirt removal. Many powerful methods have been proposed to solve the optical flow problem; however, instabilities at the boundaries of moving objects are still challenges. A difficult part of the optical flow problem is how to accurately and quickly detect and readjust unstable regions at the boundaries. This paper aims to enhance optical flow estimation by detecting and readjusting the unstable regions. In this paper, a new algorithm to detect and quickly readjust unstable regions at the boundaries of moving objects is presented in a more general and compact manner. In addition, a new context-based anisotropic diffusion filter, which is significant in processing intermediate data, is discussed in detail. Our approach has demonstrated more accurate results than previous approaches.
Optimal search strategies on complex networks

Complex networks are ubiquitous in nature and play a role of paramount importance in many contexts. Internet and the cyberworld, which permeate our everyday life, are self-organized hierarchical graphs. Urban traffic flows on intricate road networks, which impact both transportation design and epidemic control. In the brain, neurons are cabled through heterogeneous connections, which support the propagation of electric signals. In all these cases, the true challenge is to unveil the mechanisms through which specific dynamical features are modulated by the underlying topology of the network. Here, we consider agents randomly hopping along the links of a graph, with the additional possibility of performing long-range hops to randomly chosen disconnected nodes with a given probability. We show that an optimal combination of the two jump rules exists that maximises the efficiency of target search, the optimum reflecting the topology of the network.
Spurious long-range dependence: evidence from Malaysian equity markets

In this paper, a modified variance aggregated-time approach is used to examine the long-range dependence behaviour of the Malaysian stock exchange. We studied the 20 years daily data which included the pre- and post-economic crises encountered in the Malaysian stock exchange. The unawareness of economic shocks and short-range dependence in all the indices has triggered the spurious long-range dependence in our empirical results. It is also found that the modified approach estimation is robust under the presence of short-range dependence.
Performance evaluation of searching using various indexing techniques in Lucene with Relational Databases

The Organizations commonly use relational databases for transaction processing, but big portion of database operations involve select operation. As data grows beyond few million records selection tends to take much time in whole transaction. One approach is to build indexes in database on columns which are frequently used in selection. If there are more than one table (which is general case) selection takes more time. Another approach is to use searching framework for searching records. Apache lucene is very popular, fast open source searching framework used in many projects. So here we are trying to evaluate use of lucene searching to find records fast so as to get performance benefits from lucene's fast searching capabilities and offload selection work from databases. We will evaluate different indexing types in lucene to see which best fits to our need. At last we evaluate that is this arrangement can provide performance benefits, and which index type is best suited for that.
Opportunistic Cooperative Network-Coding Based on Space-Time Coding for Bi-Directional Traffic Flows

In multi-hop wireless networks, network coding can take advantage of the bi-directional traffic flows to increase the achievable throughput. To combat fading in wireless channel, cooperative diversity is integrated into the network-coding schemes. In this paper, we propose an opportunistic cooperative network-coding scheme based on space-time coding (OCNC), which combats channel fading and improves resource efficiency and network throughput. Focusing on the bi-directional traffic flows in wireless cooperative relaying networks, we develop and analyze the outage probabilities and the network-coding gain of different bi-directional relaying schemes. The numerical results show that in contrast to traditional scheme both full diversity (i.e. K-order diversity in case of K relay nodes) and asymptotical 4/3 times of network-coding gain are achieved by OCNC. In addition, because of opportunistic relaying of multiple nodes, the network-coding gain is more considerable in the low and middle SNR regimes.
On the hydrogen recombination time in Type II supernova atmospheres

Non-local thermodynamic equilibrium radiative transfer calculations of differentially expanding supernovae atmospheres are computationally intensive and are almost universally performed in a time-independent snapshot mode, where both the radiative transfer problem and the rate equations are solved assuming the steady-state approximation. The validity of the steady-state approximation in the rate equations has recently been questioned for Type II supernova (SN II) atmospheres after maximum light on to the plateau. We calculate the effective recombination time of hydrogen in SN II using our general purpose model atmosphere code phoenix. While we find that the recombination time for the conditions of SNe II at early times is increased over the classical value for the case of a simple hydrogen model atom with energy levels corresponding to just the first two principal quantum numbers, the classical value of the recombination time is recovered in the case of a multilevel hydrogen atom. We also find that the recombination time at most optical depths is smaller in the case of a multilevel atom than for a simple two-level hydrogen atom. We find that time dependence in the rate equations is important in the early epochs of a supernova's lifetime. The changes due to the time-dependent rate equation (at constant input luminosity) are manifested in physical parameters such as the level populations which directly affect the spectra. The Hα profile is affected by the time-dependent rate equations at early times. At later times, time dependence does not significantly modify the level populations and therefore the Hα profile is roughly independent of whether the steady-state or time-dependent approach is used.
Simultaneous Visual and Linguistic Embeddings with CNNs and T-LSTMs

We explore embedding visual depictions of scenes and their linguistic descriptions in a common vector space by joint learning. This is achieved via a layered neural network system, leveraging a convolutional neural network (CNN) and a tree “long short term memory” network (T-LSTM) to transform the respective scene representations into a vector space such that distance between vector representation of associated image/description pairs is minimized and that between contrastive pairs is maximized. We find that T-LSTMs and our model architecture performs strongly, although it performs significantly inferior as compared to the current state-of-the-art. This is potentially due to an abbreviated training schedule.
Reactive Power and Voltage Control in Distribution Systems With Limited Switching Operations

An algorithm based on a nonlinear interior-point method and discretization penalties is proposed in this paper for the solution of the mixed-integer nonlinear programming (MINLP) problem associated with reactive power and voltage control in distribution systems to minimize daily energy losses, with time-related constraints being considered. Some of these constraints represent limits on the number of switching operations of transformer load tap changers (LTCs) and capacitors, which are modeled as discrete control variables. The discrete variables are treated here as continuous variables during the solution process, thus transforming the MINLP problem into an NLP problem that can be more efficiently solved exploiting its highly sparse matrix structure; a strategy is developed to round these variables off to their nearest discrete values, so that daily switching operation limits are properly met. The proposed method is compared with respect to other well-known MINLP solution methods, namely, a genetic algorithm and the popular GAMS MINLP solvers BARON and DICOPT. The effectiveness of the proposed method is demonstrated in the well-known PG&E 69-bus distribution network and a real distribution system in the city of Guangzhou, China, where the proposed technique has been in operation since 2003.
NOISE TRAPS AND SNAGS IN ITERATING SYSTEMS

Irregular dynamics of simple chaotic systems containing noise sensitive features are considered Some results are given on the statistics of the time development of the resulting bursty epochs in the state variable of the system Crisis driven intermit tency may occur where the behaviours are almost indistinguishable from those of the noise sensitive features Experimental results are presented which illustrate the theoretical studies
Sustainable Computing: Informatics and Systems on Leakage Power Optimization in Clock Tree Networks for Asics and General-purpose Processors

Leakage power has grown significantly and is a major challenge in SoC design. Among SoC's components, clock distribution network power accounts for a large portion of chip power. This paper proposes to deploy sleep transistor insertion (STI) in the clock tree of datapaths in ASICs or in general-purpose processors in order to reduce leakage power. It characterizes the effect of sleep transistor sharing and sizing on clock tree wakeup time, leakage power, and propagation delay. It then uses these characteristics during leakage power optimization. It describes a post synthesis sleep transistor insertion (PSSTI), a heuristic clustering algorithm for sleep transistor insertion with the objective of total power minimization in a given clock tree. Sleep transistor sharing and sizing are deployed in order to meet the clock skew and wakeup delay constraints. The potential benefits of STI in ASIC design are evaluated using a standard industrial VLSI-CAD flow including sleep-transistor insertion and routing after the clock synthesis and place-and-route of the benchmark circuits. The results show that the clock tree leakage power is reduced by 19–32% depending on the topology of the synthesized clock tree. We also apply PSSTI in the clock tree of the datapaths in general-purpose processors using architectural control of the sleep mode. This achieves a reduction in the leakage power and the dynamic power of the clock tree within different datapath components (adder, multiplier, etc.) of as much as 80%. This approach is also applicable to other on-chip structure where inverters are large in size and commonly used, e.g. SRAMs or networks-on-a-chip, which combined with the clock tree savings will significantly reduce processor or ASIC overall power consumption.
Murder by numbers: Socio-economic determinants of homicide and civil war

Deliberate killing is a common part of the defining features of both homicide and civil war. Often, the scale of killing is also similar: most countries have homicide rates that exceed the threshold of one thousand combat-related deaths during a year that is the standard criterion for civil war. What is clearly different is the organization of killing: the perpetrators of homicide are usually individuals or small groups, whereas rebellion – the direct cause of a civil war - requires a cohesive group of at least several hundred killers. Beyond this, the motivation for the two types of killing may differ systematically, although evidently both homicide and rebellion have many different motivations, including error and irrationality. In this paper we investigate whether the socio-economic determinants of homicide and civil war are similar, and then explore potential inter-relationships between them. We compare our existing model of the risk of civil war with a new model of the homicide rate. We find that there is a ‘family resemblance’ between the two types of killing, but surprising differences. Furthermore, we turn to the inter-relationships between homicide and the risk of civil war. Specifically, we ask whether a high rate of homicide makes a country more prone to civil war, and whether a civil war makes a country more prone to homicide. Our results indicate that higher homicide rate do not increase the risk of war but that civil wars generate a legacy of increased post-conflict homicide rates.
Draft Genome Sequence of Pseudomonas sp. Strain BMS12, a Plant Growth-Promoting and Protease-Producing Bacterium, Isolated from the Rhizosphere Sediment of Phragmites karka of Chilika Lake, India

ABSTRACT We report the 4.51 Mb draft genome of Pseudomonas sp. strain BMS12, a Gram-negative bacterium in the class of Gammaproteobacteria, isolated from the rhizospheric sediment of Phragmites karka, an invasive weed in Chilika Lake, Odisha, India. The Pseudomonas sp. strain BMS12 is capable of producing proteases and is also an efficient plant growth promoter that can be useful for various phytoremedial and industrial applications.
Differences in Semantic Relatedness as Judged by Humans and Algorithms

Quantifying the semantic relatedness of two terms is a field with vast amounts of research, as the knowledge provided by it has applications for many Natural Language Processing problems. While many algorithmic measures have been proposed, it is often hard to say if one measure outperforms another, since their evaluation often lacks meaningful comparisons to human judgement on semantic relatedness. In this paper we present a study using the BLESS data set to compare the preferences of humans regarding semantic relatedness to popular algorithmic baselines, PMI and NGD, which shows that significant differences in relationship-type preferences between humans and algorithms exist.
A Generalized Guarantee Model for Servicing Sporadic Tasks with Firm Deadlines

A new guarantee model for accepting dynamically arriving sporadic tasks is presented in this paper. In this model, sporadic tasks have two costs associated with them. The costs represent the overheads a system will incur if the task is rejected and/or misses its deadline. The basic idea of the proposed model is to accept a task only if accepting the task lowers the expected cost due missed sporadic task deadlines. The key feature of the proposed model is that it can be viewed as a generalization of the traditional deterministic and the probabilistic guarantee models. By suitably setting the costs associated with the sporadic tasks, the proposed model can be made equivalent to either the deterministic or the probabilistic guarantee model. In general, however, the proposed model achieves a balance between the two types of guarantee depending on the exact costs associated with a sporadic task. A scheduling policy based on the proposed model is also presented in this paper. The policy is then empirically evaluated using a Monte Carlo simulation. The evaluation shows that the proposed model along with its scheduling policy are superior to related work in literature. Any opinions, ndings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reeect the views of NSF.