snu-aidas/HVMap-dataset huggingface dataset:
Forensic Analysis of WhatsApp on Android Smartphones

ii Acknowledgements The research and writing of this thesis has been one of the most significant academic challenges I ever had to face. Without the support and guidance of the following people, this study would not have been completed. It is to them that I owe my deepest gratitude. I would sincerely like to thank my advisor, Dr. Golden G. Richard III for giving me an opportunity to conduct this thesis research under his excellent guidance. His exceptional knowledge, wisdom and understanding have inspired and motivated me. My professors, Dr. Shengru Tu and Dr. Adlai DePano for being on my thesis committee and mentoring me during my Master's degree in Computer Science at University of New Orleans. I am thankful to my friend Thomas Sires, for initiating my interest in Linux, making sure I keep it up and help me solve technical issues. I appreciate the help from Aisha Ali-Gombe, Joe Sylve and Andrew Case who are on our Information Assurance group, for their contributions in the Information Assurance field and answering my questions. Finally, I would like to thank my Parents and each member in my family and friends for their unconditional love and support. I specially want to thank my husband Mr. Naveen Singh, who has been my core source of strength through every phase of this effort and constantly encouraged me to do my best. His systematic approach and kind feedback towards my thesis has helped me improve. Words cannot express how grateful I am to you. My heartfelt gratitude to my precious daughter Navya Singh, who was born during my Master's program and has spent many days without my complete attention. With her never give up attitude she has taught me perseverance to work around a problem until I succeed. Thank you for all your love my little girl, it kept me going. Abstract Android forensics has evolved over time offering significant opportunities and exciting challenges. On one hand, being an open source platform Android is giving developers the freedom to contribute to the rapid growth of the Android market whereas on the other hand Android users may not be aware of the security and privacy implications of installing these applications on their phones. Users may assume that a password-locked device protects their personal information, but applications may retain private information on devices, in ways that users might not anticipate. In this thesis we will be …
Kernel regression in mixed feature spaces for spatio-temporal saliency detection

Spatio-temporal saliency detection has attracted lots of research interests due to its competitive performance on wide multimedia applications. For spatio-temporal saliency detection, existing bottom-up algorithms often over-simplify the fusion strategy, which results in the inferior performance than the human vision system. In this paper, a novel bottom-up spatio-temporal saliency model is proposed to improve the accuracy of attentional region estimation in videos through fully exploiting the merit of fusion. In order to represent the space constructed by several types of features such as location, appearance and temporal cues extracted from video, kernel regression in mixed feature spaces (KR-MFS) including three approximation entity-models is proposed. Using KR-MFS, a hybrid fusion strategy which considers the combination of spatial and temporal saliency of each individual unit and incorporates the impacts from the neighboring units is presented and embedded into the spatio-temporal saliency model. The proposed model has been evaluated on the publicly available dataset. Experimental results show that the proposed spatio-temporal saliency model can achieve better performance than the state-of-the-art approaches. 2015 Elsevier Inc. All rights reserved.
The web impact factor: a critical review

Purpose – We analyse the link-based web site impact measure known as the Web Impact Factor (WIF). It is a quantitative tool for evaluating and ranking web sites, top-level domains and sub-domains. We also discuss the WIF's advantages and disadvantages, data collection problems, and validity and reliability of WIF results. Design/methodology/approach – A key to webometric studies has been the use of largescale search engines, such as Yahoo and AltaVista that allow measurements to be made of the total number of pages in a web site and the total number of backlinks to the web site. These search engines provide similar possibilities for the investigation of links between web sites/pages to those provided by the academic journals citation databases from the Institute of Scientific Information (ISI). But the content of the Web is not of the same nature and quality as the databases maintained by the ISI. Findings – This paper reviews how the WIF has been developed and applied. It has been suggested that Web Impact Factors can be calculated as a way of comparing the attractiveness of web sites or domains on the Web. It is concluded that, while the WIF is arguably useful for quantitative intra-country comparison, application beyond this (i.e., to inter-country assessment) has little value. Originality/value – The paper attempts to make a critical review over literature on the WIF and associated indicators.
Strategies for Evaluating Software Usability

This paper presents a usage analysis and taxonomy of methods which are used to evaluate the usability of computer systems. To accommodate the analysis and taxonomy, a matrix of strategies which can be used for effective usability evaluation is presented. Such an analysis, taxonomy and strategies support human-computer interaction (HCI) professionals who have the responsibility for ensuring computer system usability. The strategies outlined are named Virtual Engineering, Soft Modelling, Hard Review and Real World. This paper also uses a composite set of existing popular generic evaluation methods which can be used as part of these strategies. The methods used are observation, questionnaire, interview, empirical methods, user groups, cognitive walkthroughs, heuristic methods, review methods and model methods. The paper continues by presenting a Usage Analysis Table of these methods and concludes by grouping them into a Taxonomy of Usability Evaluation Methods. A key emphasis of this paper is the appropriateness of individual methods to lifecycle timing.
10 An Empirical Approach for the Evaluation of Voice User Interfaces

Nowadays, the convergence of devices, electronic computing, and massive media produces huge volumes of information, which demands the need for faster and more efficient interaction between users and information. How to make information access manageable, efficient, and easy becomes the major challenge for Human-Computer Interaction (HCI) researchers. The different types of computing devices, such as PDAs (personal digital assistants), tablet PCs, desktops, game consoles, and the next generation phones, provide many different modalities for information access. This makes it possible to dynamically adapt application user interfaces to the changing context. However, as applications go more and more pervasive, these devices show theirs limited input/output capacity caused by small visual displays, use of hands to operate buttons and the lack of an alphanumeric keyboard and mouse (Gu & Gilbert, 2004). Voice User Interface (VUI) systems are capable of, besides recognizing the voice of their users, to understand voice commands, and to provide responses to them, usually, in real time. The state-of-the-art in speech technology already allows the development of automatic systems designed to work in real conditions. VUI is perhaps the most critical factor in the success of any automated speech recognition (ASR) system, determining whether the user experience will be satisfying or frustrating, or even whether the customer will remain one. This chapter describes a practical methodology for creating an effective VUI design. The methodology is scientifically based on principles in linguistics, psychology, and language technology (Cohen et al. 2004; San-Segundo et al., 2005). Given the limited input/output capabilities of mobile devices, speech presents an excellent way to enter and retrieve information either alone or in combination with other modalities. Furthermore, people with disabilities should be provided with a wide range of alternative interaction modalities other than the traditional screen-mouse based desktop computing devices. Whether the disability is temporary or permanent, people with reading difficulty, visual impairment, and/or any difficulty using a keyboard, or mouse can rely on speech as an alternate approach for information access. Source: User Interfaces, Book edited by: Rita Mátrai, ISBN 978-953-307-084-1, pp. 270, May 2010, INTECH, Croatia, downloaded from SCIYO.COM
Handwriting instruction in elementary schools.

OBJECTIVE
Classroom teachers teach handwriting, but when problems arise, students are referred to occupational therapy for remediation. This study, conducted by occupational therapists, reviews handwriting instruction by classroom teachers in one school district.


METHOD
Teachers from kindergarten through grade 6 were asked to complete an open-ended questionnaire regarding handwriting instruction.


RESULTS
Teachers differed in their methods of instruction, including in the programs and paper used, and practice provided. Teachers of grades 5 and 6 had to continue to review handwriting instruction, because all students could not fluently use handwriting as a tool of expression.


CONCLUSION
Elementary students need structured instruction to develop the motor skill of writing. School-based occupational therapists can support effective handwriting instruction by interpreting information from motor learning theory pertaining to instruction and practice, which supports acquisition, transfer, and retention of handwriting skills. They also need to be cognizant of prior handwriting instruction when addressing handwriting difficulties.
Exploratory analysis of OpenStreetMap for land use classification

In the last years, volunteers have been contributing massively to what we know nowadays as Volunteered Geographic Information. This huge amount of data might be hiding a vast geographical richness and therefore research needs to be conducted to explore their potential and use it in the solution of real world problems. In this study we conduct an exploratory analysis of data from the OpenStreetMap initiative. Using the Corine Land Cover database as reference and continental Portugal as the study area, we establish a possible correspondence between both classification nomenclatures, evaluate the quality of OpenStreetMap polygon features classification against Corine Land Cover classes from level 1 nomenclature, and analyze the spatial distribution of OpenStreetMap classes over continental Portugal. A global classification accuracy around 76% and interesting coverage areas' values are remarkable and promising results that encourages us for future research on this topic.
An Empirical Study on Detecting and Fixing Buffer Overflow Bugs

Buffer overflow is one of the most common types of software security vulnerabilities. Although researchers have proposed various static and dynamic techniques for buffer overflow detection, buffer overflow attacks against both legacy and newly-deployed software systems are still quite prevalent. Compared with dynamic detection techniques, static techniques are more systematic and scalable. However, there are few studies on the effectiveness of state-of-the-art static buffer overflow detection techniques. In this paper, we perform an in-depth quantitative and qualitative study on static buffer overflow detection. More specifically, we obtain both the buggy and fixed versions of 100 buffer overflow bugs from 63 real-world projects totalling 28 MLoC (Millions of Lines of Code) based on the reports in Common Vulnerabilities and Exposures (CVE). Then, quantitatively, we apply Fortify, Checkmarx, and Splint to all the buggy versions to investigate their false negatives, and also apply them to all the fixed versions to investigate their false positives. We also qualitatively investigate the causes for the false-negatives and false-positives of studied techniques to guide the design and implementation of more advanced buffer overflow detection techniques. Finally, we also categorized the patterns of manual buffer overflow repair actions to guide automated repair techniques for buffer overflow. The experiment data is available at http://bo-study.github.io/Buffer-Overflow-Cases/.
The Impact of Brand Equity and Innovation on the Long-Term Effectiveness of Promotions

Vol. XLV (June 2008), 293–306 293 © 2008, American Marketing Association ISSN: 0022-2437 (print), 1547-7193 (electronic) *Rebecca J. Slotegraaf is Assistant Professor of Marketing and Eli Lilly Faculty Fellow, Kelley School of Business, Indiana University (e-mail: rslotegr@indiana.edu). Koen Pauwels is Associate Professor of Business Administration, Tuck School of Business, Dartmouth College (e-mail: koen.h.pauwels@dartmouth.edu). Both authors contributed equally to this research. The authors thank Kevin Keller; Don Lehmann; the two anonymous JMR reviewers; and seminar participants at Emory University, the London Business School, Rice University, University of Michigan, University of Illinois, Georgia Institute of Technology, ANZMAC, and the Marketing Dynamics Conference for their valuable comments. The authors also appreciate the generous financial support of the 3M University Relations faculty grant awarded to the first author. Michel Wedel served as associate editor for this article. REBECCA J. SLOTEGRAAF and KOEN PAUWELS*
ACStream: Enforcing Access Control over Data Streams

In this demo proposal, we illustrate ACStream, a system built on top of Stream Base [1], to specify and enforce access control policies over data streams. ACStream supports a very flexible role-based access control model specifically designed to protect against unauthorized access to streaming data. The core component of ACStream is a query rewriting mechanism that, by exploiting a set of secure operators proposed by us in [2], rewrites a user query in such a way that it does not violate the specified access control policies during its execution. The demo will show how policies modelling a variety of access control requirements can be easily specified and enforced using ACStream.
Multi-criteria ABC analysis using artificial-intelligence-based classification techniques

ABC analysis is a popular and effective method used to classify inventory items into specific categories that can be managed and controlled separately. Conventional ABC analysis classifies inventory items three categories: A, B, or C based on annual dollar usage of an inventory item. Multi-criteria inventory classification has been proposed by a number of researchers in order to take other important criteria into consideration. These researchers have compared artificial-intelligence (AI)-based classification techniques with traditional multiple discriminant analysis (MDA). Examples of these AI-based techniques include support vector machines (SVMs), backpropagation networks (BPNs), and the k-nearest neighbor (k-NN) algorithm. To test the effectiveness of these techniques, classification results based on four benchmark techniques are compared. The results show that AI-based techniques demonstrate superior accuracy to MDA. Statistical analysis reveals that SVM enables more accurate classification than other AI-based techniques. This finding suggests the possibility of implementing AI-based techniques for multi-criteria ABC analysis in enterprise resource planning (ERP) systems. 2010 Elsevier Ltd. All rights reserved.
Owlready: Ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies

OBJECTIVE
Ontologies are widely used in the biomedical domain. While many tools exist for the edition, alignment or evaluation of ontologies, few solutions have been proposed for ontology programming interface, i.e. for accessing and modifying an ontology within a programming language. Existing query languages (such as SPARQL) and APIs (such as OWLAPI) are not as easy-to-use as object programming languages are. Moreover, they provide few solutions to difficulties encountered with biomedical ontologies. Our objective was to design a tool for accessing easily the entities of an OWL ontology, with high-level constructs helping with biomedical ontologies.


METHODS
From our experience on medical ontologies, we identified two difficulties: (1) many entities are represented by classes (rather than individuals), but the existing tools do not permit manipulating classes as easily as individuals, (2) ontologies rely on the open-world assumption, whereas the medical reasoning must consider only evidence-based medical knowledge as true. We designed a Python module for ontology-oriented programming. It allows access to the entities of an OWL ontology as if they were objects in the programming language. We propose a simple high-level syntax for managing classes and the associated "role-filler" constraints. We also propose an algorithm for performing local closed world reasoning in simple situations.


RESULTS
We developed Owlready, a Python module for a high-level access to OWL ontologies. The paper describes the architecture and the syntax of the module version 2. It details how we integrated the OWL ontology model with the Python object model. The paper provides examples based on Gene Ontology (GO). We also demonstrate the interest of Owlready in a use case focused on the automatic comparison of the contraindications of several drugs. This use case illustrates the use of the specific syntax proposed for manipulating classes and for performing local closed world reasoning.


CONCLUSION
Owlready has been successfully used in a medical research project. It has been published as Open-Source software and then used by many other researchers. Future developments will focus on the support of vagueness and additional non-monotonic reasoning feature, and automatic dialog box generation.
Vascular Complications After Chin Augmentation Using Hyaluronic Acid

Vascular complications after hyaluronic acid (HA) filling of the chin have rarely been reported. In this report, two cases of vascular occlusion after HA augmentation of the mentum are presented. The first case involved local skin necrosis that resulted from a massive microcirculatory embolism and/or external compression of the chin skin microvasculature. The second case involved vascular compromise in the tongue that resulted from HA injection in the chin. The diagnosis was established on the basis of interventional angiography findings. Concerning the pathogenesis, we hypothesized that the filler embolus flowed into the branches of the deep lingual artery through the rich vascular anastomoses among the submental, sublingual, and deep lingual arteries, after being accidentally injected into the submental artery (or its branches). Level of Evidence V This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.
Food Addiction and Bulimia Nervosa: New Data Based on the Yale Food Addiction Scale 2.0.

Previous research on 'food addiction' as measured with the Yale Food Addiction Scale (YFAS) showed a large overlap between addiction-like eating and bulimia nervosa. Most recently, a revised version of the YFAS has been developed according to the changes made in the diagnostic criteria for substance use disorder in the Diagnostic and Statistical Manual of Mental Disorders fifth edition. The current study examined prevalence and correlates of the YFAS2.0 in individuals with bulimia (n = 115) and controls (n = 341). Ninety-six per cent of participants with bulimia and 14% of controls received a YFAS2.0 diagnosis. A higher number of YFAS2.0 symptoms was associated with lower interoceptive awareness, higher depressiveness, and higher impulsivity in both groups. However, a higher number of YFAS2.0 symptoms was associated with higher body mass and weight suppression in controls only and not in participants with bulimia. The current study is the first to show a large overlap between bulimia and 'food addiction' as measured with the YFAS2.0, replicating and extending findings from studies, which used the previous version of the YFAS. Compensatory weight control behaviours in individuals with bulimia likely alleviate the association between addiction-like eating and higher body mass. Thus, the large overlap between bulimia and 'food addiction' should be taken into consideration when examining the role of addiction-like eating in weight gain and obesity. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association.
Database forensic analysis through internal structure carving

Forensic tools assist analysts with recovery of both the data and system events, even from corrupted storage. These tools typically rely on “file carving” techniques to restore files after metadata loss by analyzing the remaining raw file content. A significant amount of sensitive data is stored and processed in relational databases thus creating the need for database forensic tools that will extend file carving solutions to the database realm. Raw database storage is partitioned into individual “pages” that cannot be read or presented to the analyst without the help of the database itself. Furthermore, by directly accessing raw database storage, we can reveal things that are normally hidden from database users. There exists a number of database-specific tools developed for emergency database recovery, though not usually for forensic analysis of a database. In this paper, we present a universal tool that seamlessly supports many different databases, rebuilding table and other data content from any remaining storage fragments on disk or in memory. We define an approach for automatically (with minimal user intervention) reverse engineering storage in new databases, for detecting volatile data changes and discovering user action artifacts. Finally, we empirically verify our tool's ability to recover both deleted and partially corrupted data directly from the internal storage of different databases. © 2015 The Authors. Published by Elsevier Ltd on behalf of DFRWS. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/
Naive Bayes for Text Classification with Unbalanced Classes

Abstract. Multinomial naive Bayes (MNB) is a popular method for document classification due to its computational efficiency and relatively good predictive performance. It has recently been established that predictive performance can be improved further by appropriate data transformations [1, 2]. In this paper we present another transformation that is designed to combat a potential problem with the application of MNB to unbalanced datasets. We propose an appropriate correction by adjusting attribute priors. This correction can be implemented as another data normalization step, and we show that it can significantly improve the area under the ROC curve. We also show that the modified version of MNB is very closely related to the simple centroid-based classifier and compare the two methods empirically.