Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification For 2011-2012 Bangladesh Integrated Household Survey By Iterative Clustering Technique

In this project, the raw data from a survey, 2011-2012 Bangladesh Integrated Household Survey, is cleaned. Based on the research purpose of the collaborator, important variables are extracted and principal component analysis is used to form a new data set. The iterative clustering technique is applied to the new data set to classify the households involved in the survey into different categories. The categories are interpreted as reflecting the different economic activities in Bangladesh. INDEX WORDS: Data clustering, Principal component analysis, Agriculture, Livestock, Rural development, Fisheries, Integrated farming, Bangladesh CLASSIFICATION FOR 2011-2012 BANGLADESH INTEGRATED HOUSEHOLD SURVEY BY ITERATIVE CLUSTERING TECHNIQUE
Title A new method for robust beamforming using iterative second-order cone programming

This paper addresses the problem of beamforming for antenna arrays in the presence of mismatches between the true and nominal steering vectors. A new method for robust beamforming is proposed by minimizing the array output power while controlling the array mainlobe response. Due to the presence of the non-convex response constraints, a new approach based on iteratively linearizing the non-convex constraints is proposed to reformulate the non-convex problem to a series of second-order cone programming (SOCP) subproblems, each of which can be optimally solved by wellestablished convex optimization techniques. Simulation results show that the proposed method offers better performance than conventional methods tested.
GTE: a distributional second-order co-occurrence approach to improve the identification of top relevant dates in web snippets

In this paper, we present an approach to identify top relevant dates in Web snippets with respect to a given implicit temporal query. Our approach is two-fold. First, we propose a generic temporal similarity measure called GTE, which evaluates the temporal similarity between a query and a date. Second, we propose a classification model to accurately relate relevant dates to their corresponding query terms and withdraw irrelevant ones. We suggest two different solutions: a threshold-based classification strategy and a supervised classifier based on a combination of multiple similarity measures. We evaluate both strategies over a set of real-world text queries and compare the performance of our Web snippet approach with a query log approach over the same set of queries. Experiments show that determining the most relevant dates of any given implicit temporal query can be improved with GTE combined with the second order similarity measure InfoSimba, the Dice coefficient and the threshold-based strategy compared to (1) first-order similarity measures and (2) the query log based approach.
Constraint-based Trend Template for Intrusion Detection

Intrusion detection systems (IDS) are special computer security tools which help detect intrusion attempts. Misuse based detection is one of the techniques which is used by IDS to recognize predefined attack signatures. Attack languages, also known as detection languages, are used to describe attack signatures. Detection languages should be simple, expressive and flexible enough to help encode event signature accurately and conveniently. This paper shows the effectiveness of constraint based Trend Template (TT) as an efficient detection language by encoding some attack scenarios and focusing on the Trend Detector which recognizes those signatures from intrusion data.
Symbol grounding and a Neuro-Fuzzy architecture for multisensor fusion

The fusion of multisensorial data is a common practice to identify a world model when data coming from a single sensor is unreliable. A possible approach to multisensor data fusion consists in identifying common interpretations of data coming from different sensors, and to integrate the information represented as symbols related to the possible interpretations. In this paper, we present an architecture of integrated instances of Fuzzy ARTMAP, a fuzzy neural network system, able to learn to classify numerical input vectors into fuzzy classes, i.e., to build symbolic interpretations. We have successfully applied this architecture on a navigation task in an unstructured, unknown environment for a mobile robot, integrating data from sensors, omnatidia, bumpers, and the odometric system.
Co-clustering of image segments using convex optimization applied to EM neuronal reconstruction

This paper addresses the problem of jointly clustering two segmentations of closely correlated images. We focus in particular on the application of reconstructing neuronal structures in over-segmented electron microscopy images. We formulate the problem of co-clustering as a quadratic semi-assignment problem and investigate convex relaxations using semidefinite and linear programming. We further introduce a linear programming method with manageable number of constraints and present an approach for learning the cost function. Our method increases computational efficiency by orders of magnitude while maintaining accuracy, automatically finds the optimal number of clusters, and empirically tends to produce binary assignment solutions. We illustrate our approach in simulations and in experiments with real EM data.
Hyperoxia in head injury: therapeutic tool?

Purpose of review Currently, no neuroprotective therapies have been shown to reduce the secondary neuronal damage occurring after traumatic brain injury. Recent studies have addressed the potentiality of hyperoxia to ameliorate brain metabolism after traumatic brain injury. In this article, we present the principles of oxygen transport to the brain, the effects of hyperoxia on cerebral metabolism, and the role of lactate in brain metabolism after traumatic brain injury. Recent findings It has been shown that hyperoxia obtained by increasing the inspired fraction of oxygen results in a decreased cerebral lactate concentration measured in the extracellular space using the microdialysis. However, the brain oxygen delivery is not substantially improved by eubaric hyperoxia and the ratio between lactate and pyruvate (a better indicator of the cellular redox state than lactate alone) is not changed by hyperoxia. In addition, it has been shown the lactate might be an alternative fuel for neurons during the acute postinjury phase. Summary At present, there is no evidence supporting any clinical benefit of hyperoxia in brain-injured patients, and the meaning of posttraumatic brain extracellular lactate accumulation should be further investigated.
Detect functionally equivalent code fragments via k-nearest neighbor algorithm

It is important for improving program to detect duplicated code (also known as code clone) in the field of software development and maintenance. The existing solutions can not effectively analyze the complex semantics of programs, and so can not effectively detect functionally equivalent code fragments that execute the same operations but with different syntax. This paper proposes a method to detect functionally equivalent code fragments via k-nearest neighbor algorithm. Firstly, the source code is statically analyzed to get the information of control dependency and data flow; then, k-nearest neighbor clustering algorithm is performed to form functionally independent code fragments; next, the input and output variables of the code fragments are identified, and the code fragments are transformed to compilable and executable functions, then the automatic random assignment for the input variables of functions are carried out. At last, the functions are dynamically tested and are classified into different clusters according to the testing outputs. Experimental results show that this method can effectively get functionally equivalent code fragments with a lower time complexity.
KNOWLEDGE-BASED SOLUTIONS AS THEY APPLY TO THE GENERAL RADAR PROBLEM

Abstract : This tutorial provides an introduction to the application of knowledge-based processing to the general radar problem. We interpret knowledge-based processing as the use of adaptivity and the exploitation of prior knowledge in such a way as to choose the optimum processing method in each case, and we interpret the general radar problem as the detection, classification and tracking of targets against a background of clutter and interference. As such the tutorial attempts to describe the nature of the general radar problem and the basic processing techniques that are used, and to show why knowledge-based signal processing may be advantageous, setting the scene for the subsequent tutorials covering CFAR detection, space-time adaptive processing, tracking, and emerging technologies. The fundamental concepts of matched filtering, superresolution and adaptive filtering are described, emphasizing the equivalence of time/frequency and aperture/angular domains, and introducing the concept of Space-Time Adaptive Processing. A description is given of some of the statistical clutter models in common use (Rayleigh, Ricean, Lognormal, Weibull and Compound-K), with practical examples of sea clutter and of land clutter which demonstrate that clutter is in general non-Gaussian and non-stationary, both in time and space. Two examples are given of the application of adaptive techniques to the suppression on nonhomogeneous clutter, showing that the performance of the adaptive Doppler filtering algorithm is severely compromised at clutter edges, due to incorrect estimation of the clutter covariance matrix, and how in Space-Time Adaptive Processing a nonhomogeneity detector can be used in the choice of the most appropriate STAP algorithm, forming the so-called Knowledge-Based STAP (KB-STAP) processor.
Prediction of diurnal change in 10-h fuel stick moisture content

Several methods are available for estimating the moisture content of 10-h response time fuels in the U.S. National Fire Danger Rating System (NFDRS). These fuels are represented by an array of four 1.27 cm diameter ponderosa pine (Pinus ponderosa Dougl. ex Laws.) dowels weighing about 100 g when oven dry. The prediction model currently used in the NFDRS is driven by information from afternoon weather readings. To improve responsiveness of the predictions to weather change, a 10-h stick moisture content prediction model is developed that uses observations (air temperature and relative humidity, insolation, and rainfall amount) available from a remote automatic weather station (RAWS). Equations describing the transfer of heat and moisture at the surface and within a 10-h stick are derived and then solved numerically. Collection of field experimental data on weather, stick weight, and stick temperature to guide development of the model is briefly described, and predicted and observed mean moisture contents a.
Intensive follow-up strategies improve outcomes in nonmetastatic colorectal cancer patients after curative surgery: a systematic review and meta-analysis.

BACKGROUND A wide variety of follow-up strategies are used for patients with colorectal cancer (CRC) after curative surgery. The aim of this study is to review the evidence of the impact of different follow-up strategies in patients with nonmetastatic CRC after curative surgery, in relation to overall survival and other outcomes. PATIENTS AND METHODS A systematic search of PubMed, EMBASE, SCOPUS and ISI Web of Knowledge up to June 2014 was carried out. Eligible studies were all randomized clinical trials comparing the effectiveness of different follow-up strategies after curative resection in nonmetastatic CRC. RESULTS Eleven studies with n = 4055 participants were included in a meta-analysis. A significant improvement in overall survival was observed in patients with more intensive follow-up strategies [hazard ratio = 0.75; 95% confidence interval (CI) 0.66-0.86]. A higher probability of detection of asymptomatic recurrences [relative risk (RR) = 2.59; 95% CI 1.66-4.06], curative surgery attempted at recurrences (RR = 1.98; 95% CI 1.51-2.60), survival after recurrences (RR = 2.13; 95% CI 1.24-3.69), and a shorter time in detecting recurrences (mean difference = -5.23 months; 95% CI -9.58 to -0.88) was observed in the intervention group. There were no significant differences in the total tumor recurrences, nor in the mortality related to disease. CONCLUSION Intensive follow-up strategies improve overall survival, increase the detection of asymptomatic recurrences and curative surgery attempted at recurrence, and are associated with a shorter time in detecting recurrences. This more intensive follow-up could not be associated with an improvement in cancer-specific survival nor with an increased detection of total tumor recurrences. Follow-up with serum carcinoembryonic antigen and colonoscopies are related to an increase in overall survival.
Constraints in Non-Boolean Contexts

In high-level constraint modelling languages, constraints can occur in non-Boolean contexts: implicitly, in the form of partial functions, or more explicitly, in the form of constraints on local variables in non-Boolean expressions. Specifications using these facilities are often more succinct. However, these specifications are typically executed on solvers that only support questions of the form of existentially quantified conjunctions of constraints. We show how we can translate expressions with constraints appearing in non-Boolean contexts into conjunctions of ordinary constraints. The translation is clearly structured into constrained type elimination, local variable lifting and partial function elimination. We explain our approach in the context of the modelling language Zinc. An implementation of it is an integral part of our Zinc compiler.
Soft X-Ray Emission Lines in the Early Afterglow of Gamma-Ray Bursts

We compute the luminosity of Kα emission lines produced by astrophysically abundant elements in the soft X-ray spectra of the early afterglow of gamma-ray bursts. We find that the detection of these lines can be a diagnostic for the geometrical setup of the reprocessing material. In particular, we can distinguish between a "geometry-dominated" model, in which the line emission is coming from an extended region and its duration arises from light-travel time effects, and an "engine-dominated" model, where the line-emitting gas is in a smaller region, irradiated for a longer period. These lines therefore offer clues to the dynamics and timescale of the explosion leading to a gamma-ray burst.
Integrated requirements engineering: a tutorial

This short tutorial introduces the fundamental activities of RE (requirements engineering) and discusses how it has evolved as a part of the software engineering process. However, rather than focusing on the established RE techniques, the author discusses how the changing nature of software engineering has led to the new challenges in RE. The author then introduces a number of new techniques that helps us to meet these challenges by integrating RE more closely with other systems implementation activities.
Circuit for reducing devices voltage stress due to DC-link capacitor voltage ripple in a Neutral-Point-Clamped inverter

The paper presents a circuit that reduces the voltage stress caused by DC-link capacitor voltage ripple on the switching devices of a three-level Neutral-Point-Clamped (NPC) inverter. The circuit is capable of halving the amplitude of the voltage ripple seen by the inverter devices. It is proposed as an alternative to over-sizing the inverter's DC-link capacitors, or using capacitor-balancing PWM strategies that increase the switching frequency and associated losses. The structure and operation of the circuit are described and the ratings of its components are determined. The benefit it offers is compared to that of existing solutions, based on an example NPC inverter design. The results, verified using MATLAB-Simulink, indicate that the circuit can outperform other proposed balancing circuits, halve the DC-link capacitance and cover cases where the switching frequency cannot be increased.
Web-based CALL approach – A new trend of College English education in China

This paper firstly presents the implementation of CALL in EFL education in China based on the constructivist theory, then specifies the advantages of the web-based CALL approach. Lastly, the paper points out that the web-based CALL approach will be widely used in China as a new technique in presenting college EFL curriculum content and creating an interactive environment.
Perception based Cued Click Points

Combination of username and password is most commonly used authentication technique. Graphical password facilitate memorability at the same time provide security against various attacks. In Graphical authentication user performs some events on pictures like clicking, dragging, moving mouse etc. Cued Click Point is one of the existing graphical authentication systems. This paper suggests an enhancement to click point based approach. In the proposed method click points will based on user perception of click points not on the basis of traditional technique like tolerance square . A perceptual hash function will be used for comparing click points made at registration time and login time. In the proposed method the click points will be compared based on the content of click points. This method provides more accuracy and security than any other methods available.
A SWOT Analysis on the E-Commerce of Chinese Foreign Trade

This paper analyses the e-commerce development characteristics of Chinese foreign trade with SWOT analysis, and indicates the advantages and disadvantages of the foreign trade e-commerce. It also finds and determines its external opportunities and challenges, in order to facilitating the e-commerce advantages of China's foreign trade, cope with various challenges and seize the opportunities in the 21st century, making foreign trade to achieve long-term sustainable development.
Evaluation of package and technology effects on substrate-crosstalk isolation in CMOS RFIC

Crosstalk propagating through the silicon substrate is a serious limiting factor on the performance of advanced mixed analog-digital CMOS integrated circuits. This problem also appears in RF chips in the form of power leakage from local oscillators or power amplifiers, as well as the noise coupled from the digital baseband circuitry. Several studies have presented measurements on simple test structures to determine the best approach to minimize this leakage. Nevertheless, these studies are usually restricted to a single technology, and the consequences of applying results to other technologies are not evaluated. Also, these studies are usually performed with on-wafer samples, and thus package effects are not taken into account. However, package parasitics are an important factor in the substrate crosstalk, since they determine how much of the leakage finds a return path to external ground. In this paper, we discuss different technological approaches to increase isolation between coupled circuits. Measurements of the isolation on some test structures fabricated in a CMOS RF technology are presented. The package parasitics effect is evaluated by comparing on-wafer vs packaged samples. Measurement results are complemented with simulations of a broader range of situations.
Optimizing and Purification of Recombinant Human Leukemia Inhibitory Factor Produced in E . coli Strain BL 21

Article history: Received: 30 July 2013 Accepted: 19 Oct 2013 Available online: 29 Jan 2014 ZJRMS 2015 Feb; 17(2): 47-51 Background: Leukemia inhibitory factor (LIF) is a glycoprotein, categorized as a subfamily of interleukin 6 cytokines which is known in many mammolals. A pluripotent cytokine with a wide biological function range has numerous effects on target cells. The LIF regulates neuron survival, hematopoiesis and seen in LIF knockout mice affects blastocyst implantation, also acts as pre-inflammolatory cytokine, and regulates immolune response. Further, it is able to maintain stem cells poly potency. The main object of present work was expression, optimizing, and purification of recombinant human leukemia inhibitory factor (rhLIF). Materials and Methods: In this experimental study, Pet28 (+) carrying the LIF gene and kanamycin resistance marker was cloned in E. coli strain BL21. The induction was optimized by altering 3 factors including the temperature, the induction time, and the concentration of the Isopropyl β-D-1-thiogalactopyranoside (IPTG) as inducer. The purification of the recombinant human LIF (rhLIF) was done by single step affinity chromatography. After the purification, method accuracy was proved by Sodium dodecyl sulfate (SDS) -PAGE electrophoresis and Western blotting. Results: Optimizing of the expression was reached by changing various parameters, and purification has been done successful. Conclusion: rhLIF undergoes modification by glycosylation to get its full functionality. The produced rhLIF in prokaryotic host in this work is lacking of glycosylation. However, its proper function should be evaluated in further studies. Copyright © 2015 Zahedan University of Medical Sciences. All rights reserved.
Annotated portfolios and other forms of intermediate-level knowledge

In a recent issue of this magazine, Bill Gaver and John Bowers address the role of design practice in academic research and provide a concrete suggestion: “We propose the notion of annotated portfolios as a way to communicate design research. In part, we do this to provide an alternative to accounts that suggest for design to become productive as research, it should engage in some sort of theory formation. While what exactly is meant by theory is not always clear, writers usually have in mind some conceptual machinery that can explain and predict” [1].
Anomaly Program Behavior Detection Based on Neural Network

Neural network can be used in anomaly detection. In order to improve the traditional IDS (intrusion detection system) performance, we often had to change the network structure and detection algorithm. And because intrusion techniques are most variable and unpredictable, we cannot always use the fixed detection techniques to catch exactly all possible intrusions. It is therefore important to investigate novel detection methods and IDS models. In this paper, a model of intrusion detection system based on BP neural network is proposed through analyzing features of program behavior. Some details and issues on the design and implementation of the model are discussed and experiments are also given.