Miracle-dz/UniFAR-FTUs huggingface dataset:
Linguistic Features of False Confessions and Confessions Not in Dispute: A Corpus Analysis

Confessions are considered the gold standard of evidence, and yet many cases of false confessions causing wrongful convictions have come to the surface in the past decades. Currently, a method to identify false confessions does not exist and studies focusing on the content of the confessions have found similarities rather than points of distinction. In this study, we approached confessions from a stylistic rather than qualitative point of view, utilizing corpus analysis to outline the linguistic features of two samples of confessions: false confessions (n=37) and confessions not in dispute (n=98). Subsequently, we created a model through logistic regression in order to distinguish the two, based on three predictors: personal pronouns, impersonal pronouns and conjunctions. In a first sample comprised of 25 false confessions and 25 confessions not in dispute the model correctly categorized 37 out of 50 confessions (74% accuracy rate), and in a second out-of-model sample the predictors accurately classified 20 of the 24 confessions (83.3% accuracy rate). A high frequency of impersonal pronouns was found to be associated with a higher likelihood of the confession being false, while confessions containing a higher rate of conjunctions and personal pronouns were more likely to belong to the sample not in dispute. Lastly, in confessions not in dispute “I” was often followed by a lexical verb, a pattern that was found with less frequency in false confessions. Disparities were also found in the way variations of the sentence “I don’t remember” were used within the corpora.
Text Summary using Modified Particle Swarm Optimization Algorithm

Text summarization is the process of provides meaningful and short contents of the documents in the automated manner by using which concept of entire documents can be found. In the existing work, an approach called as unsupervised generic summary creation is introduced to summarize the single document and as well as multiple documents in the generic manner. However, the genetic algorithm will consume more computational time for generating the summaries in case of presence of multiple documents with more sentences. This problem is resolved in the proposed approach by introducing the modified particle swarm optimization where global best would be updated based on weighted mean approach. This proposed approach provides an efficient and flexible creation of summaries with reduced computation time. The experimental tests conducted were proves that the proposed approach provides better result than the existing approach in terms of reduced computational time.
Iron oxides in comet 81P/Wild 2

Abstract– We have used synchrotron Fe‐XANES, XRS, microRaman, and SEM‐TEM analyses of Stardust track 41 slice and track 121 terminal area slices to identify Fe oxide (magnetite‐hematite and amorphous oxide), Fe‐Ti oxide, and V‐rich chromite (Fe‐Cr‐V‐Ti‐Mn oxide) grains ranging in size from 200 nm to ∼10 μm. They co‐exist with relict FeNi metal. Both Fe‐XANES and microRaman analyses suggest that the FeNi metal and magnetite (Fe2O3FeO) also contain some hematite (Fe2O3). The FeNi has been partially oxidized (probably during capture), but on the basis of our experimental work with a light‐gas gun and microRaman analyses, we believe that some of the magnetite‐hematite mixtures may have originated on Wild 2. The terminal samples from track 121 also contain traces of sulfide and Mg‐rich silicate minerals. Our results show an unequilibrated mixture of reduced and oxidized Fe‐bearing minerals in the Wild 2 samples in an analogous way to mineral assemblages seen in carbonaceous chondrites and interplanetary dust particles. The samples contain some evidence for terrestrial contamination, for example, occasional Zn‐bearing grains and amorphous Fe oxide in track 121 for which evidence of a cometary origin is lacking.
Macrophages restrict the nephrogenic field and promote endothelial connections during kidney development

The origins and functions of kidney macrophages in the adult have been explored, but their roles during development remain largely unknown. Here we characterise macrophage arrival, localisation, heterogeneity, and functions during kidney organogenesis. Using genetic approaches to ablate macrophages, we identify a role for macrophages in nephron progenitor cell clearance as mouse kidney development begins. Throughout renal organogenesis, most kidney macrophages are perivascular and express F4/80 and CD206. These macrophages are enriched for mRNAs linked to developmental processes, such as blood vessel morphogenesis. Using antibody-mediated macrophage-depletion, we show macrophages support vascular anastomoses in cultured kidney explants. We also characterise a subpopulation of galectin-3+ (Gal3+) myeloid cells within the developing kidney. Our findings may stimulate research into macrophage-based therapies for renal developmental abnormalities and have implications for the generation of bioengineered kidney tissues.
ライフコード : 史上最強の人生マニュアル : あなたのまわりにある理不尽な悪意に打ち勝ち、成功を手繰り寄せる方法 = Life code : The new rules for winning in the real world

第１部 現実社会の悪人たち—彼らを見抜いて遠ざける方法（人生は真剣勝負だ；悪人の８つの特徴；悪人の１５の手口） 第２部 新しい「人生の鉄則」と現実社会で勝つためのルール（ターゲットにならないと決意する；１６の成功戦略；交渉術を磨く；新しい子育ての秘訣） 結論
Privacy-Preserving One-Class Support Vector Machine with Horizontally Partitioned Data

We propose a new algorithm of privacy-preserving one-class support vector machine (SVM) with horizontally partitioned data. Every participant holds a part of data with all the data attributes. They apply the same random matrix to establish their own kernel matrix. By sharing these partial kernel matrices, we generate a global kernel matrix and establish two privacy-preserving one-class SVM models, which include the linear model and the nonlinear model. Partial kernel matrix can protect the privacy of the participants, and the global kernel matrix can ensure the classification accuracy. Experimental results on benchmark data sets indicate the effectiveness of the proposed algorithms.
Why do we reformulate? Automatic Prediction of Pragmatic Functions

Reformulations participate in structuring of discourse, especially in dialogues, and also contribute to the dynamics of the discourse. Reformulation is a signicant act which has to satisfy precise objectives. The purpose of our work is to automatically predict the reason for which a speaker performs a reformulation. We use a classication with eleven pragmatic functions inspired by the existing work and by the data analyzed. The reference data are built through manual and consensual annotations of spontaneous reformulations introduced by three markers (c'est-a-dire, je veux dire, disons) in French. The data are provided by spoken corpora and a corpus with forum discussions on health issues. We exploit supervised categorization algorithms and a set with several features (syntactic, formal, semantic and discursive) for the prediction of the reformulation categories. The distribution of sentences is not homogeneous across categories. The experiments are positioned at two levels: general and specic. Our results indicate that it is easier to predict the types of functions at the general level (the average F-measure is around 0.80), than at the level of individual categories (the average F-measure is around 0.40). We study the inuence of various parameters.
Defeating code reuse attacks with minimal tagged architecture

In this thesis, we argue that software-based defenses to code reuse attacks are fundamentally flawed. With code pointer integrity as a case study, we show that a secure and efficient software-based defense to code reuse attacks is impossible and thus motivate the case for hardware approaches. We then propose our tagged architecture system Taxi (Tagged C) as a practical defense against code reuse attacks which minimally modifies existing hardware components. We also propose strong defense policies which aim to guarantee security while minimizing tag memory usage. Our Taxi prototype, a modified RISC-V ISA simulator, demonstrates that we can defeat code reuse attacks with high compatibility and low memory overhead.
Modeling information flow for an autonomous agent to support reverse engineering work

Reverse engineering is a cyber defense task used to investigate malware, reconstruct functionality of compiled software, and identify vulnerabilities from closed-source software code already being used in operational contexts. While research in this area has mainly focused on techniques to extract information from binary code, it is also important to understand the capabilities and limitations of the human involved in the reverse engineering process (both defensively and offensively), so we can design better information representations and effectively allocate appropriate tasks to autonomous agents. In this paper, we describe our introductory work in developing agent models of reverse engineering. We review what is known about reverse engineers’ mental models, then describe and characterize four human–computer interaction patterns involved in reverse engineering from a cognitive task analysis. Finally, we present a category theoretic model to describe how reverse engineers trace information flow when performing static analysis. Our approach is a first step in modeling, simulating, and optimizing the human interaction components of these tasks to increase the speed, scale, and accuracy of cyber defense efforts.
On Statistical Metrics for Selection and Phrasality

In the following we shall discuss a fairly simple empiricist approach to syntactic structure, which could be considered as some sort of exemplar model.1 We compare this approach and its empirical results and theoretical consequences briefly with a common qualitative theory that is utilizing symbols and rules. The research goal is to evaluate the usability of various information theoretic metrics for unsupervised syntactic chunking, and potentially even basic parsing. The presented experiment is based on ideas formulated in Magerman & Marcus (1990), and Magerman (1994) where Mutual Information (MI) over Part-of-Speech tags in annotated corpora is used as a metric for the identification of syntactic attraction or simply phrasality. A more detailed discussion of this method is presented in section 2. We compare the results of the MI-based approach with results from alternative measures using the same strategy for identification of phrasality. The identification of syntactic phrases or chunks in the second approach is performed by relating pruning decisions to Relative Entropy (RE) scores for adjacent tokens. As mentioned in Ćavar et al. (2004b), this measure might be more adequate given its directional nature (RE) and the relevant properties of syntactic relations.
Nutrient Enrichment of Mannanase-Treated Cassava Peels and Corn Cob

This study aimed at the examination of nutrient enrichment of cassava peels and corn cob through mannanase treatment. Mannanase production was conducted using Locust Bean Gum (LBG) as the sole carbon source; moisten with mineral salt solution and enzyme activity determined by dinitrosalicylic acid. Crude mannanase was concentrated by ammonium sulphate. The samples were hydrolyzed with concentrated mannanase within a sealing system. The chemical compositions of enzyme treated-samples were determined according to standard chemical methods. The mineral compositions of the enzyme-treated samples were determined using atomic absorption spectrophotometer method. The result obtained showed an increase in crude protein from 5.34±0.17% in non-enzyme treated corn cob to 9.61±0.98% in enzyme treated corn cob. The enzyme treated samples showed a markedly reduction in crude fiber by 13.75 and 29.70% for cassava peels and corn cob respectively. The lignin (9.49%), cellulose (68.75, 33.06 and 10.82%) and hemicellulose (55.38 and 9.64%) contents decreased in enzyme treated samples for cassava peels and corn cob. Cyanide decreased significantly in all the mannanase-treated samples. Mineral composition varied significantly with treatment type and the substrate treated. The treatment of cassava peels and corn cob with mannanase resulted in the degradation of the complex carbohydrate fractions in the samples to increase its crude protein and certain minerals contents.
Survey on Colour, Texture and Shape Features for Person Re-Identification

Background: Re-identification is the pattern recognition problem which helps to identify the person in surveillance network. Feature plays an important role in person re-identification. Objective: The main objective of this paper is to analyze the properties of few existing features for person re-identification. Methods/Statistical Analysis: The features for re-identification is categorized into three groups namely colour, texture and shape. In this work various methods for extracting these features and their challenges are considered for survey and their properties, advantages disadvantages and applications are presented as a summary. Findings: From the analysis we found that colour and texture features outperform the shape feature. Application/Improvements: This analysis helps to understand the characteristics of the existing features and develop the new robust feature for improving the matching rate for person re-identification.
Multiple Kinect V2 Calibration

In this paper, we propose a method to easily calibrate multiple Kinect V2 sensors. It requires the cameras to simultaneously observe a 1D object shown at different orientations (three at least) or a 2D object for at least one acquisition. This is possible due to the built-in coordinate mapping capabilities of the Kinect. Our method follows five steps: image acquisition, pre-calibration, point cloud matching, intrinsic parameters initialization, and final calibration. We modeled radial and distortion parameters of all the cameras, obtaining a root mean square re-projection error of 0.2 pixels on the depth cameras and 0.4 pixels on the color cameras. To validate the calibration results we performed point cloud fusion with color and 3D reconstruction using the depth and color information from four Kinect sensors.
Analyzing data from a pretest-posttest control group design: The importance of statistical assumptions

Purpose Among the gold standards in human resource development (HRD) research are studies that test theoretically developed hypotheses and use experimental designs. A somewhat typical experimental design would involve collecting pretest and posttest data on individuals assigned to a control or experimental group. Data from such a design that considered if training made a difference in knowledge, skills or attitudes, for example, could help advance practice. Using simulated datasets, situated in the example of a scenario-planning intervention, this paper aims to show that choosing a data analysis path that does not consider the associated assumptions can misrepresent findings and resulting conclusions. A review of HRD articles in a select set of journals indicated that some researchers reporting on pretest-posttest designs with two groups were not reporting associated statistical assumptions and reported results from repeated-measures analysis of variance that are considered of minimal utility. Design/methodology/approach Using heuristic datasets, situated in the example of a scenario-planning intervention, this paper will show that choosing a data analysis path that does not consider the associated assumptions can misrepresent findings and resulting conclusions. Journals in the HRD field that conducted pretest-posttest control group designs were coded. Findings The authors' illustrations provide evidence for the importance of testing assumptions and the need for researchers to consider alternate analyses when assumptions fail, particularly the homogeneity of regression slopes assumption. Originality/value This paper provides guidance to researchers faced with analyzing data from a pretest-posttest control group experimental design, so that they may select the most parsimonious solution that honors the ecological validity of the data.
Handbook for Synthesizing Qualitative Research

This handbook presents guidelines for synthesizing findings of qualitative research.After discussing the importance of such synthesis for building knowledge, in the second chapter the authors introduce definitions of and types of qualitative research synthesis.They view the synthesis as a study comprising a series of steps, starting with the formulation of a problem and a statement of purpose. In chapter 3 the authors focus on the steps of retrieving all research reports and determining their relevance to the study domain. In chapter 4 they describe strategies for appraising individual study reports and for conducting a comparative appraisal. Comparative appraisal consists of displaying key elements of the studies included in the synthesis and comparing them in order to determine whether they confirm, extend, refute, or complement each other. In chapter 5 Sandelowski and Barroso discuss issues encountered in appraising the quality of qualitative studies and present a typology of findings that can be used to classify results. In chapters 6 and 7 they describe the process of implementing the two types of qualitative research synthesis, metasummary and metasynthesis. In chapter 8 the authors review strategies for maintaining validity of qualitative research synthesis and in chapter 9 they review content and format for presenting the results of the synthesis. Sandelowski and Barroso are to be commended for addressing a controversial topic, and for refining the types of qualitative research findings and procedures for conducting a synthesis of these findings.They clarify the arguments advanced by proponents and opponents of the qualitative research synthesis, thereby facilitating our understanding of the rationale underlying the two types of synthesis. Conceiving the synthesis as a study that is conducted in steps, similar to those entailed in a metaanalysis, helps us to view the process as a systematic one with a welldefined sequence of steps.The book is structured accordingly, starting with the formulation of a researchable problem, moving on to the conduct of an extensive search of the relevant literature, then to an appraisal and synthesis of findings across studies, and ending with CJNR 2008,Vol. 40 No 3, 179 –180
Coupled Multipath-Aware Congestion Control

Often endpoints are connected by multiple paths, but communications are usually restricted to a single path per socket. Resource usage within the network would be more efficient were it possible for these multiple paths to be used concurrently. The use of multiple paths simultaneously, specifically within a Multipath TCP protocol, necessitates the development of new congestion control algorithms. If existing algorithms such as TCP New Reno were run independently on each path, the multipath flow would take more than its fair share if there was a common bottleneck. Further, it is desirable that a source with multiple paths available will transfer more traffic using the least congested of the paths, hence achieving resource pooling. This would increase the overall utilization of the network and also its robustness to failure. This document presents a congestion control algorithm which couples the congestion control algorithms running on different subflows by linking their increase functions, and dynamically controls the overall aggresiveness of the multipath flow. The result is a practical algorithm that is fair to TCP at bottlenecks while moving traffic away from congested links.
Color Science, Concepts and Methods. Quantitative Data and Formulas

G. Wyszecki and W. S. Stiles London: John Wiley. 1967. Pp. xiv + 628. Price £11. This remarkable and unusual book is by two outstanding authorities on the science of colour: Dr. Stiles, for many years a senior member of the Light Division at the National Physical Laboratory, and Dr. Wyszecki, currently in charge of the Radiation Optics Section of the Canadian National Research Council. The authors' aim has been to provide a comprehensive source book of data required by the practical and theoretical worker in the field of colour and they have achieved this aim so successfully that their book is likely to become the standard work on the subject and to remain so for a good many years.
Evaluating Effectiveness with Regard to the Implementation of the SMED Method for A Flexographic Machine-A case study

This paper aims to present a process of implementing a Single-Minute Exchange of Die (SMED) method and a manner of evaluating the effectiveness of such an undertaking. The subject of the study is a printing enterprise that conducts its business activity in Poland and the chosen research area is a flexographic machine Gidue Master Combat 430. The article presents specific stages of implementing the SMED method, describes activities aimed at determining the causes of the resulting waste and proposes ways of improving the changeover process. It should be emphasised that the article presents the effectiveness of implementing the SMED method in a measurable and quantitative manner. Keywords-lean manufacturing; flexographic machine changeover; elimination of waste; SMED method
Random motion of image sensor based super-resolution technique

This paper is about new method of image resolution enhancement that is a new method of Super-resolution. Super-Resolution is the word given to the techniques that generate high resolution image from a set of low resolution images. The paper describes about a new Super-resolution technique based on random motion of image sensor. However the term Super-resolution is usually used to describe methods that differ on mathematical aspects and do not involve any hardware change. But this time the change in hardware is simple and does not involve much complexity. So it will serve as an inexpensive technique to acquire high resolution images. The required low resolution images that contains sub-pixel information for the generation of high resolution image is acquired by the image sensor which is free to move on its horizontal and vertical axes but only in sub-pixel range. This motion of the image sensor is the result of vibration of piezoelectric material on the edges of the image sensor. The generation of high resolution image from the acquired set of low resolution images is based on Maximum-a-posteriori method of Super-resolution.
Hardware-in-the-loop Simulation System of Communication Satellite Countermeasure Based on HLA and Reflective Memory Network

Aiming at the need of the research on satellite countermeasure,the system design of a hardware-in-the-loop simulation system was discussed based on HLA and reflective memory networks(RMN). Furthermore,the development of real-time simulation of four entity simulators interconnected via RMN and the distributed numeric simulation based on HLA was realized.Some key problems in real-time simulation were investigated,such as HLA time management,message transportation scheme,and communication mode of RMN,harmonization of RMN and HLA application.The simulation result shows that it completely satisfies the real-time requirement,and it is valuable for the design and research on satellite countermeasure.