Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploratory data analysis on temperature data of Indian states from 1800–2013 (Analysis of trends in temperature data for prediction modelling)

Information about climate changes is required at global, regional and basin levels for a variety of purposes, including the study of impact of the greenhouse gases. The analyses mentioned in this research relate to the observation of trends in the temperatures of the Indian states. The research begins with the exposition of the ongoing analysis methodologies prevalent in exploratory analysis and prediction modeling on temperature data. It further develops into the proposed work, where the analysis of means of the average temperatures observed across the Indian states from 1800–2013 is summarized, which in turn is found to reveal confounding results. The proposed work concludes with further focused analysis of geographically similar states, namely the states lying on the Indo-Gangetic plains, which reveal encouraging results, thereby showing an occurrence of a trend. The research concludes with the propounding of the future scope, which includes modeling for predicting the average temperatures which can be attained over the next few decades, which in turn would be significant for the observation of the corollaries of global warming in India.
A Modified Adaptive Variable Step Size NLMS Adaptive Filtering Algorithm for Rayleigh Fading Environments

This paper presents an adaptive filtering solution for multipath Rayleigh fading channel which is based upon adaptive variable step size parameter. The algorithm is derived from normalized least mean square (NLMS) algorithm to make the step size parameter adaptive of NLMS filter which provides good tracking performance and fast convergence with respect to time varying channel. The simulation results show that the fast convergence as well as low probability of error leads to better signal to noise (SNR) ratio when it is compared to conventional NLMS and Bi-LMS algorithms.
Soft SUSY breaking terms for chiral matter in IIB string compactifications

This paper develops the computation of soft supersymmetry breaking terms for chiral D7 matter fields in IIB Calabi-Yau flux compactifications with stabilised moduli. We determine explicit expressions for soft terms for the single-modulus KKLT scenario and the multiple-moduli large volume scenario. In particular we use the chiral matter metrics for Calabi-Yau backgrounds recently computed in hep-th/0609180. These differ from the better understood metrics for non-chiral matter and therefore give a different structure of soft terms. The soft terms take a simple form depending explicitly on the modular weights of the corresponding matter fields. For the large-volume case we find that in the simplest D7 brane configuration, scalar masses, gaugino masses and A-terms are very similar to the dilaton-dominated scenario. Although all soft masses are suppressed by ln (MP/m3/2) compared to the gravitino mass, the anomaly-mediated contributions do not compete, being doubly suppressed and thus subdominant to the gravity-mediated tree-level terms. Soft terms are flavour-universal to leading order in an expansion in inverse Kahler moduli. They also do not introduce extra CP violating phases to the effective action. We argue that soft term flavour universality should be a property of the large-volume compactifications, and more generally IIB flux models, in which flavour is determined by the complex structure moduli while supersymmetry is broken by the Kahler moduli. For the simplest large-volume case we run the soft terms to low energies and present some sample spectra and a basic phenomenological analysis.
Content Strategies for Digital Consumer Engagement in Social Networks: Why Advertising Is an Antecedent of Engagement

Advertisers need to optimize their efforts on social networks to engage consumers effectively. Existing literature on this topic has not yet explained how social network advertising (SNA) can be categorized into different content types and how to conceptualize and operationalize digital consumer engagement (DCE) in social networks. Thus, we derive seven content categories for social network advertising and a four-level model for DCE based on consumers' intermediate mind-set responses. We propose the impact of different SNA categories as an antecedent of DCE. Our results confirm a significant but unequal impact of at least four content categories on various engagement metrics. We therefore distill the successful content strategies and content attributes for specific types of engagement and confirm intermediate responses to advertising in a real market situation.
Home Palliative Care for Patients with Advanced Chronic Kidney Disease: Preliminary Results

Healthcare for patients with advanced chronic kidney disease (ACKD) on conservative treatment very often poses healthcare problems that are difficult to solve. At the end of 2011, we began a program based on the care and monitoring of these patients by Primary Care Teams. ACKD patients who opted for conservative treatment were offered the chance to be cared for mainly at home by the Primary Care doctor and nurse, under the coordination of the Palliative Care Unit and the Nephrology Department. During 2012, 2013, and 2014, 76 patients received treatment in this program (mean age: 81 years; mean Charlson age-comorbidity index: 10, and mean glomerular filtration rate: 12.4 mL/min/1.73 m2). The median patient follow-up time (until death or until 31 December 2014) was 165 days. During this period, 51% of patients did not have to visit the hospital’s emergency department and 58% did not require hospitalization. Forty-eight of the 76 patients died after a median time of 135 days in the program; 24 (50%) died at home. Our experience indicates that with the support of the Palliative Care Unit and the Nephrology Department, ACKD patients who are not dialysis candidates may be monitored at home by Primary Care Teams.
Ad Hoc grid task scheduling algorithm considering trust-demand

At present, most Ad Hoc grid task scheduling algorithms ignore the impact of trust mechanism, resulting in the potential dangerous in the real scheduling. In this paper, the trust model is defined, which satisfies the tasks' trust demands, in order to choose the suitable resource node to be executed in the scheduling. Moreover, a task scheduling algorithm extended from Min-Min algorithm (T-Min-Min) is proposed. The proposed algorithm not only satisfies the trust demand of the user but also considers the resource nodes' energy consumption and load balancing. The simulation suggests that it can effectively shorten the task completion time and the number of failed tasks in the Ad Hoc grid.
Polyline Simpliication Using Quadric Error Metric with Bounded Error Polyline Simpliication Using Quadric Error Metric with Bounded Error Polyline Simpliication Using Quadric Error Metric with Bounded Error

We study the problem of polygonal line simpliication. The objective is to seek a polygonal line of smaller size that approximates the original one well. We present an algorithm that is based on edge contraction. An edge contraction merges two adjacent vertices into a new vertex and this new vertex will be made the new endpoint of the uncontracted edges incident to the two vertices merged. Thus, repeated applications naturally yield a simpliication algorithm. We implemented three algorithms QG, QGG, and QLG based on this approach. QGG and QG support each edge contraction in O(log m) time, where m is the size of the current polygonal line, whereas QLG supports each edge contraction in O(1) time. The selection of the edge to be contracted is based on the quadric error produced, which was introduced by Garland and Heckbert in simplifying 3D polygonal surfaces. We use and improve their algorithm in 2D. If iv the quadric error of each edge contracted is at most 2 , we can guarantee that the directed Hausdorr distance from the simpliied line to the original one is within. We can supply an error tolerance to QG, QGG and QLG and let edges be contracted repeatedly until the current minimum quadric error exceeds 2. On the other hand QGG and QG can also allow the user to directly and interactively reduce the number of edges in the simpliied line when deemed necessary. We have conducted some experiments to measure the approximation error of the simpliied lines produced by our algorithms. v Chapter 1
An efficient and secure certificateless public key watermarking scheme based on 1VD-DWT

Security and robustness are the main significant properties in watermarking system. In this paper, we propose an effective and secure certificateless public key watermarking scheme based on Singular Value Decomposition (SVD) and Discrete Wavelet Transform (DWT). The proposed method guarantees the non prior knowledge two parties to communicate covertly over an insecure and public channel. Moreover, we examine the robustness of the proposed scheme by analyzing different, original and watermarking images. The results demonstrate that our scheme fulfills all the security requirements of watermarking system and it is a powerful against various types of advanced attacks.
The research of Hibernate cache technique and application of EhCache component

The author has studied Hibernate cache technique. Hibernate cache technique has the primary cache, the secondary cache, the query cache, etc., which are for different applications. The primary cache is built inside Hibernate framework. It cannot be deleted. It comes or goes with Hibernate Session. The secondary cache is a pluggable and configurable component provided by a third party. It caches the data once accessed. The query cache is a special secondary cache that focuses on HQL query results. The author used a third-party cache component "EhCache" to cache the data with the secondary cache and the query cache during the development of her project. The research has shown that for Hibernate Criteria component, the improvement of query efficiency with the secondery cache decreases with the increase of the data quantity in the database table. If the query data quantity is relatively large, the secondary cache can play a negative impact on the application programs.
Genetics of shoulder girdle formation: roles of Tbx15 and aristaless-like genes

The diverse cellular contributions to the skeletal elements of the vertebrate shoulder and pelvic girdles during embryonic development complicate the study of their patterning. Research in avian embryos has recently clarified part of the embryological basis of shoulder formation. Although dermomyotomal cells provide the progenitors of the scapular blade, local signals appear to have an essential guiding role in this process. These signals differ from those that are known to pattern the more distal appendicular skeleton. We have studied the impact of Tbx15, Gli3, Alx4 and related genes on formation of the skeletal elements of the mouse shoulder and pelvic girdles. We observed severe reduction of the scapula in double and triple mutants of these genes. Analyses of a range of complex genotypes revealed aspects of their genetic relationship, as well as functions that had been previously masked due to functional redundancy. Tbx15 and Gli3 appear to have synergistic functions in formation of the scapular blade. Scapular truncation in triple mutants of Tbx15, Alx4 and Cart1 indicates essential functions for Alx4 and Cart1 in the anterior part of the scapula, as opposed to Gli3 function being linked to the posterior part. Especially in Alx4/Cart1 mutants, the expression of markers such as Pax1, Pax3 and Scleraxis is altered prior to stages when anatomical aberrations are visible in the shoulder region. This suggests a disorganization of the proximal limb bud and adjacent flank mesoderm, and is likely to reflect the disruption of a mechanism providing positional cues to guide progenitor cells to their destination in the pectoral girdle.
Table of Contents a Paraphrasing System for Transforming Regular Expressions into Honorifics Have2eat: a Restaurant Finder with Review Summarization for Mobile Phones Comunica -a Question Answering System for Brazilian Portuguese Yanfa: an Online Automatic Scoring and Intelligent Feedback System of 

Honorifics in Japanese plays an incredibly important role in all walks of social life. The demand to transform regular expressions in Japanese into honorifics automatically has increased rapidly especially in business situations. This paper reviews existing studies and proposes a system to fill this demand with more practicable functions. The experiment shows the effectiveness of our strategy.
Modelling and simulation of the locomotion of humanoid robots

Modelling and simulation is a critical stage in the design and testing of complex systems, in particular humanoid robots. Our motivation to develop a new simulator is that existing tools do not provide the flexibility needed for modelling the C-Cub, the most recent open source humanoid robot with compliant joints developed at the Italian Institute of Technology (IIT). Furthermore, we are interested in a simulator where the user has the ability to customize the simulation in order to represent the actuators and sensors that are actually used. In this paper, a simulator based on Robotran, a symbolic multibody modelling software tool, and Matlab is described. The approach presented in the paper has been used to develop and test control systems for the C-Cub and an earlier version (iCub).
Detecting Opinions and their Opinion Targets in NTCIR-8

an opinion target, a primary object of the opinion expression (e.g., the real-world object, event, and abstract entity), is helpful for extracting target-related opinions and detecting user interests. This paper presents a novel framework for target-based opinion analysis, which extracts opinionated sentences and identifies their opinion targets from news articles. To determine whether a sentence includes opinions, we utilize opinion lexicons (i.e., predefined clue words) and linguistic patterns. In identifying the opinion target, candidates are generated and examined for existence of four different features. We attempt to capture the relationship between an object target and opinion clues and utilize a document theme. For evaluation, we used English news articles from New York Times, provided by NTCIR-8 MOAT and annotated opinionated sentences and theirs opinion targets. Experimental results show that our proposed method is promising although many additional issues remain to be studied in the future.
A functional taxonomy of SMSblR systems

Short Short Message Service (SMS) based Information Systems (SMSblR) provide an excellent alternative to a traditional approach of obtaining specific information by direct (through phone) or indirect (IVRS, Web, Email) probing. Number of key players in search industry including Microsoft and Google are attracted by the expected increase in volume of use of such applications. Several SMSblR systems are available and each one supports a typical class of features. In this review paper, we present functional taxonomy of SMSblR systems. We explicitly identify and describe 18 distinct functional features of SMSblR systems, which are further grouped into five categories. These five functional categories are then used to establish a taxonomy under which the analyzed systems are classified. We present a tabular classification for each functional category, with the aim of providing a starting point for researchers to construct their own SMSblR system.
A Survey Paper on Novel Malware Clustering system based on Kernel Data Structure

Analysis of malware detection goes through various problems, such as obfuscations and variation behavior structure in static and dynamic analysis. Malware detection and approaches have been traditionally following on code- centric behavior of malicious programs, such as detection of the injection of malicious programs, code sequences. This paper introduces a new approach to novel clustering of kernel behavior by using kernel data access patterns . However, modern malware has been employing advanced strategies, such as reusing legitimate code or obfuscating malware code to circumvent the detection. To determine the effectivity, we generate the signatures of the classic root kits using their data access patterns, and matched them with the kernel execution instances. The core idea is that when kernel malware tampers with core kernel data, there exist unique kernel data access patterns. As such, we could take a subset of data access patterns that consistently appears in multiple kernel execution instances only when the malware is active and generate the malware signatures using the subset
High Resolution Discrimination of Clinical Mycobacterium tuberculosis Complex Strains Based on Single Nucleotide Polymorphisms

Recently, the diversity of the Mycobacterium tuberculosis complex (MTBC) population structure has been described in detail. Based on geographical separation and specific host pathogen co-evolution shaping MTBC virulence traits, at least 20 major lineages/genotypes have evolved finally leading to a clear influence of strain genetic background on transmissibility, clinical presentation/outcome, and resistance development. Therefore, high resolution genotyping for characterization of strains in larger studies is mandatory for understanding mechanisms of host-pathogen-interaction and to improve tuberculosis (TB) control. Single nucleotide polymorphisms (SNPs) represent the most reliable markers for lineage classification of clinical isolates due to the low levels of homoplasy, however their use is hampered either by low discriminatory power or by the need to analyze a large number of genes to achieve higher resolution. Therefore, we carried out de novo sequencing of 26 genes (approx. 20000 bp per strain) in a reference collection of MTBC strains including all major genotypes to define a highly discriminatory gene set. Overall, 161 polymorphisms were detected of which 59 are genotype-specific, while 13 define deeper branches such as the Euro-American lineage. Unbiased investigation of the most variable set of 11 genes in a population based strain collection (one year, city of Hamburg, Germany) confirmed the validity of SNP analysis as all strains were classified with high accuracy. Taken together, we defined a diagnostic algorithm which allows the identification of 17 MTBC phylogenetic lineages with high confidence for the first time by sequencing analysis of just five genes. In conclusion, the diagnostic algorithm developed in our study is likely to open the door for a low cost high resolution sequence/SNP based differentiation of the MTBC with a very high specificity. High throughput assays can be established which will be needed for large association studies that are mandatory for detailed investigation of host-pathogen-interaction during TB infection.
The net benefit of delayed finite-rate feedback in the MISO broadcast channel

A novel approach recently proposed by Maddah-Ali and Tse (the MAT scheme) achieves significant degrees of freedom (DoF) gain in the multi-input single-output (MISO) broadcast channel (BC) even with channel state information feedback that is completely stale, i.e., uncorrelated with the current channel state. However, their result does not consider the cost of the feedback, which can be quite large with moderate to high mobility/Doppler. In this paper, we introduce a new “net” degrees of freedom metric which is defined as the prelog capacity term remaining after subtracting off the feedback DoF consumed. We closely examine the MAT scheme and compare its maximum net DoF gain to single user transmission (which always achieves 1 DoF) and zero-forcing precoding (which achieves up to K DoF). In particular, assuming the channel coherence time is N symbol periods and the feedback delay is Nfd, we show that when N < (1+o(1))K logK (short coherence time), single user transmission performs best; whereas for N > (1+o(1))(Nfd+K/log K)(1-log−1 K)−1 (long coherence time), zero-forcing precoding outperforms the other two. The MAT scheme is optimal for intermediate coherence times, which for practical parameter choices is indeed quite a large and significant range, even accounting for the feedback cost.
Developing intuitive user interfaces by integrating users' mental models into requirements engineering

Today, the demand for software that is 'intuitive to use' is very high. In fact, this has become a determining factor for the success of a system. However, building software that is intuitive to use is challenging. This is particularly true for small and medium-sized enterprises (SMEs). They have to face a variety of problems to remain competitive: Usually no or just small staff is available that is specialized in user requirements engineering research, design, and testing. Furthermore, time schedules and budget are tight. All these factors require a method that delivers creative and intuitive-to-use software even with little design experience and expertise. In this paper, we address this problem by introducing a method for capturing and specifying the user's mental models with image schemas and image-schematic metaphors during the requirements engineering phase of a software engineering project. This method also enables SMEs to systematically transfer these elicited requirements into design solutions, which then result in software that is intuitive to use.
Impact Location and Quantification on an Aluminum Sandwich Panel Using Principal Component Analysis and Linear Approximation with Maximum Entropy

To avoid structural failures it is of critical importance to detect, locate and quantify impact damage as soon as it occurs. This can be achieved by impact identification methodologies, which continuously monitor the structure, detecting, locating, and quantifying impacts as they occur. This article presents an improved impact identification algorithm that uses principal component analysis (PCA) to extract features from the monitored signals and an algorithm based on linear approximation with maximum entropy to estimate the impacts. The proposed methodology is validated with two experimental applications, which include an aluminum plate and an aluminum sandwich panel. The results are compared with those of other impact identification algorithms available in literature, demonstrating that the proposed method outperforms these algorithms.
Generate Country-Scale Networks of Interaction from Scattered Statistics

It is common to define the structure of interactions among a population of agents by a network. Most of agent-based models were shown highly sensitive to that network, so the relevance of simulation results directely depends on the descriptive power of that network. When studying social dynamics in large populations, that network cannot be collected, and is rather generated by algorithms which aim to fit general properties of social networks. However, more precise data is available at a country scale in the form of socio-demographic studies, census or sociological studies. These "scattered statistics" provide rich information, especially on agents' attributes, similar properties of tied agents and affiliations. In this paper, we propose a generic methodology to bring up together these scattered statistics with bayesian networks. We explain how to generate a population of heterogeneous agents, and how to create links by using both scattered statistics and knowledge on social selection processes. The methodology is illustrated by generating an interaction network for rural Kenya which includes familial structure, colleagues and friendship constrained given field studies and statistics.
Lessons from Developing Audio HTML Interfaces

In this paper, we discuss our previous research on the establishment of guidelines and principles for choosing sounds to use in an audio interface to HTML, called the AHA framework. These principles, along with issues related to the target audience such as user tasks, goals, and interests are factors that can help us to choose specific sounds for the interface. We conclude by describing scenarios of two potential users and the interfaces that would seem to be appropriate for them.