Reviewerly/exHarmony huggingface dataset:
Computer Forensics: Seizing And Securing Digital Evidence

Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Computer Forensics — Seizing and Securing Digital Evidence I. Abstract The current paper focuses on the importance of properly seizing and securing digital evidence and the need to educate law enforcement personnel with the correct methods of collecting, documenting, packaging, labeling, and protecting computer related evidence. The paper presents an overview of computer related crimes, computer forensics, and the proper procedures for seizing and securing digital evidence. A description of a short course that was designed to provide law enforcement and forensic personnel with the knowledge needed to collect and preserve digital evidence, and the results gained from this experience are also provided. II. Introduction Computer related crimes are steadily increasing at an alarming rate. Digital evidence, as with any evidence, must be preserved in its original state. The law requires that evidence be authentic and unaltered. For digital evidence to be successfully utilized in a criminal investigation, no spoliation to that evidence should occur. A major aspect of preserving digital evidence is collecting it in a way that does not alter it. Computer forensics involves the preservation, identification, extraction, and documentation of digital evidence in the form of magnetically, optically, or electronically stored media (J.P. Craiger 2005). Therefore, law enforcement agents nowadays face a new challenge; they must be familiar with the proper procedures of seizing and securing digital evidence. 1. Computer Forensics Computer forensics may be defined as the retrieval and analysis of data from a seized computer or any other electronic media performed in such a manner that the results are reproducible by another examiner who, by following the same steps, reaches the same conclusions. Computer forensics has also been described as an “electronic autopsy” of a digital media, because specialized training and hardware/software tools and techniques are all required to make an exact image/copy of the drive. The retrieved data is then analyzed along with the various levels at which that data is stored. 2. Computer Crimes Computers and digital media have become integral parts of our lives. In 1997, the US Census estimated that only about 18% of households in the US had computers. In 2000, this number grew to 51% with 42% of those households having Internet access. In 2003, the number has increased to 62% of households with 52% having Internet access. Currently, almost 90% of households in the US have computers. Therefore, crimes committed on computers are no longer limited to skinny guys with pimples, a tape on their glasses, and squeaky voices. Almost anyone nowadays can point, click, and use a computer to commit just about any crime. So what type of crimes are being committed using computers? What information is generated to corroborate the facts and circumstances and help in the crime investigation?
Teaching Basic Class Diagram Notation with UMLGrader

Abstract Teaching Basic Class Diagram Notation with UMLGrader UMLGrader is a tool designed to help students learn the basics of drawingUniﬁed Modeling Language (UML) class diagrams. In our experience, studentsstruggle with using the appropriate notation for generalization and association aswell as with assigning association roles and multiplicities. The classic solution isto assign problems and grade the resulting diagrams, but grading such diagrams islabor intensive and so students may not get feedback in a timely manner. UML-Grader attempts to automate the grading process so that students can receive moretimely feedback on how to use the notation. To set up an assignment with UMLGrader, the instructor writes up a sys-tem description using relatively tight constraints such as “a library contains manybooks, where books can be either novels or reference works.” The instructor alsogenerates a target class diagram using expected class and role names reﬂecting theproblem description. Alternative names for certain entities may be provided to al-low for slight variations. The student then uses a tool such as Rational Rose orRhapsody to create a domain model and submits it to UMLGrader. UMLGraderthen compares the student’s diagram against the target, giving the student feed-back on missing or extra classes, attributes, methods, and relationships in a formthat points the student at how to ﬁx the model without speciﬁcally telling the stu-dent what needs to be changed. The student then corrects the errors, iterating untilthere are no signiﬁcant differences between the submitted and target diagrams. The authors have used UMLGrader for several semesters to teach UML classdiagram notation to software engineering and computer science students at thesophomore and junior levels. This paper describes UMLGrader in more detailand presents experimental results from using the tool in two classes. After re-ceiving instruction on UML class notation, students were given a quiz in whichthey modeled a simple domain. The students were then exposed to UMLGrader,and a similar modeling problem was placed on an exam. We document signiﬁcantimprovements in performance, suggesting that UMLGrader does help studentslearn UML class notation. We then discuss possible additional studies which tocompare this method of teaching UML notation against alternatives.
Multi-floor Mapping and Navigation with Uncertainty

This paper outlines the research using autonomous robots conducted by a group of undergraduate engineering students from the University of St. Thomas.The students were able to develop a mutli-floor mapping and navigation system that allowed a robot, named Turtlebot, to give nearly autonomous tours of their multi-floor engineering building.The Turtlebot can effectively traverse the hallways, use the elevator, and play audio files during tours.
Ontologies And Web Semantics For Improvement Of Curriculum In Civil Engineering

federated databases, database models and design, and ontologies.His current research focuses on dynamic ontologies, user-customized information access, database semantic heterogeneity resolution and interoperation; personalized information management environments via cooperative immersipresence; information management environments for geoscience and homeland security information, crisis management decision support systems, and privacy and trust in information systems.
Separable Data Aggregation by Layers of Binary Classifiers

Aggregating layers can be designed from binary classifiers on the principle of preserving data sets separability. Formal neurons or logical elements are treated here as basic examples of binary classifiers. Learning data sets are composed of such feature vectors which are linked to particular categories (classes). Separability of the learning sets is preserved during transformation of feature vectors from these sets by a dipolar layer of binary classifiers. The dipolar layer separates all such pairs of feature vectors that have been linked to different classes and belong to different learning sets.
Research Guides: Radiography: E-books

This Research Guide helps in the location of resources, including images, for the topic of radiography. Full-text books available through library databases.
Using multilayered neural networks for determining global solar radiation upon tilted surface in Fianarantsoa Madagascar

The knowledge of the local solar radiation characteristics is indispensable in the survey of any system exploiting solar energy in any location. The author is particularly interested by the global solar radiance upon tilted surface per time unit to help operators using solar energy in their work. The target is, among others, helping solar drying operators that need while tuning drying system the knowledge of the global solar radiation that could be received on inclined solar captors in implantation site. The aim of this paper is to use neural network method to search for solar radiation upon a tilted surface. Multilayered neural networks (MNN) trained by gradient back-propagation are used to determine numeric values of monthly means and hourly variations of the global solar radiation upon a titled surface per time unit. The numerical calculations are made with the geographical and meteorological parameters (latitude, longitude and clearness index) of the location of Fianarantsoa, Madagascar.
Prediction of the daily global solar Irradiation of the great Maghreb region using the complex-valued neural networks

In this paper, the prediction of the daily global solar irradiation of the great Maghreb’s region using the complex-valued neural networks (CVNN) is presented. This paper is an extension of our recent published work which is the complex-valued forecasting of the global solar irradiation. Both multi-input single-output (MISO) and multi-input multi-output (MIMO) strategies are considered. The data of the capitals of the great Maghreb, which are Tripoli (Libya), Tunis (Tunisia), Algiers (Algeria), Rabat (Morocco), El Aaiun (Western Sahara) and Nouakchott (Mauritania), are used like sample from each country. To test the applicability and the feasibility of the CVNN to predict the daily global irradiation for the great Maghreb case, several models are presented. Results obtained throughout this paper show that the CVNN technique is suitable for prediction of the daily solar irradiation of the region of region of the great Maghreb.
Optimization of influencing factors of camera distortion calibration

The camera distortion is affected by many factors such as the calibration environment, the size of the calibration object, and the number of captured images, which lead to reducing the measurement accuracy of image detection. The experimental analysis of the calibration accuracy is carried out from both the number of photos and the area division of the calibration board. The experiment of the number of photos used three different sizes of calibration board. The number of pictures with the effective focal length of the photo calibration tends to be stable is 10-18. Another experiment was used cross-division to calculate of distortion coefficient and distortion correction by cross-ratio invariance. Take the points which on the diagonal of Calibration plate image after distortion correction to calculate the average linear offset. The linear offset without partition is 0.8651 and 0.6439. And the linear offset after the sub-region is 0.6439 and 0.2817. Therefore dividing the area can improve the accuracy of distortion correction.
Galveston College Library: Galveston College Library Homepage: Library Policies

Welcome to Galveston College library. The David Glenn Hunt Memorial Library provides access to college level print and electronic resources for GC students, faculty, staff and the community.
Spatial Multi-scale Motion History Histograms and Its Applications

Precisely describing the action inside of a video is a challenging task because the content of the video includes various objects, with different local motion information at different speed in the video frames. In this paper, a new video feature is proposed based on the spatial information of the objects in a frame, along with the motion information between one against multiple consecutive frames. Motion information between pixels at the same position in the whole video are all combined for a new Spatial Multi-Scale Motion History Histogram (SMMHH) dynamic descriptor. The detailed algorithm of the SMMHH was given and it is tested in both human action recognition and touch gesture recognition applications based on the public video datasets. Experimental results demonstrate its excellent performance compared to other traditional methods.
Research on the Integrated Platform of the Comprehensive Management Information System of the Hollow Village in the Hilly Area

Hollow villages are located in hilly areas and their important land resources. There are a lot of data in the research and planning of hollow villages. Therefore, this paper studies the integrated information system platform of hollow villages'comprehensive renovation in Hilly areas. The design principle of the platform is reliability, openness, standardization and practicability. The overall logical framework of the platform is hardware support layer, software support layer, integrated layer and application layer. Data aggregation is used to integrate land use status data, soil quality data and land evaluation data in mountainous and hilly areas. AAF framework is used to complete the application and development of framework-based B/S structure. Knowledge visualization-based comprehensive integration is used to realize the integrated level of hollow village renovation in mountainous and hilly areas. Taiwanese Provides reliable data base and land management for hollow village renovation in mountainous and hilly areas.
Security for Distributed Machine Learning Based Software

Current developments in Enterprise Systems observe a paradigm shift, moving the needle from the backend to the edge sectors of those; by distributing data, decentralizing applications and integrating novel components seamlessly to the central systems. Distributively deployed AI capabilities will thrust this transition. Several non-functional requirements arise along with these developments, security being at the center of the discussions. Bearing those requirements in mind, hereby we propose an approach to holistically protect distributed Deep Neural Network (DNN) based/enhanced software assets, i.e. confidentiality of their input & output data streams as well as safeguarding their Intellectual Property. Making use of Fully Homomorphic Encryption (FHE), our approach enables the protection of Distributed Neural Networks, while processing encrypted data. On that respect we evaluate the feasibility of this solution on a Convolutional Neuronal Network (CNN) for image classification deployed on distributed infrastructures.
3D-Scans und 3D-Drucke in der Musikarchäologie. Möglichkeiten und experimentalarchäologische Praxisbeispiele

3D-scans and 3D-printing in music archaeology. Possibilities and experimental archaeological practical examples. Due to new technologies, such as 3D-scanning and 3D-printing, revolutionary approaches have been made possible in the reconstruction of musical instruments found in archaeological sites. According to our tests, the method of 3D-scanning is safe, free of contamination, as well as interferences and does not affect the original material, provided that the original is made of suitable material and does not contain any metal parts. Whereas an ordinary documentation based on drawings and pictures does not always allow deeper understanding of the reconstruction of a fragmented instrument, the method of micro CT-scanning, if necessary digitally completing (based on pre-scannedsamples) and 3D-printing allows the creation of an exact copy of the examined object, which is innumerably reproducible in order to experiment with different possibilities of the reconstruction. The exactness of these approaches has been successfully proven through frequency analysis on both the original and the 3D-printed clone. So the music of broken instruments can be brought back to life with comparatively little effort of timeand money.
Deriving an Optimal Noise Adding Mechanism for Privacy-Preserving Machine Learning.

Differential privacy is a standard mathematical framework to quantify the degree to which individual privacy in a statistical dataset is preserved. We derive an optimal \((\epsilon ,\delta )\)–differentially private noise adding mechanism for real-valued data matrices meant for the training of models by machine learning algorithms. The aim is to protect a machine learning algorithm from an adversary who seeks to gain an information about the data from algorithm’s output by perturbing the value in a sample of the training data. The fundamental issue of trade-off between privacy and utility is addressed by presenting a novel approach consisting of three steps: (1) the sufficient conditions on the probability density function of noise for \((\epsilon ,\delta )\)–differential privacy of a machine learning algorithm are derived; (2) the noise distribution that, for a given level of entropy, minimizes the expected noise magnitude is derived; (3) using entropy level as the design parameter, the optimal entropy level and the corresponding probability density function of the noise are derived.
One-dimensional Hadamard Quantum Walk on a Cycle with Rotational Implementation

Quantum walks have been extensively studied recently, mainly due to theirvast difference in behavior to classical random walks. This paper is concernedwith discrete time and space quantum walks of particles that propagate througha one-dimensional line. This line can be either a lattice or a graph or anyother form of mathematical structure that can be viewed as a one-dimensionalline. First is defined a concrete way to describe the unitary evolution of aquantum walk through a balanced coin operator and a shift operator. Thenfollows the implementation of the quantum walk on an $8$-cycle, i.e a cyclegraph with $8$ nodes, which is then run locally as a simulation and on IBM'squantum computer. The paper explores two implementations of the quantum walk asa quantum circuit: the first one consists of generalised controlled inversions,as introduced in \cite{EffWalk}, whereas the second one tries to replace themwith rotation operators around the basis states. The main aim is to find a wayaround the caveat resulting from the large amount of ancilla qubits required tocarry out the computation in the case where only generalised inverters areused. Next, another three experiments are computed, involving cycles with alarger state space, more specifically $16$, $32$ and $64$ possible positions.In order to measure the magnitude of the error of the circuit we use the crossentropy benchmarking method, calculated through the Hellinger distance.Finally, a derivation of the variance of the quantum walk is provided alongwith a calculation of the variance for our experiment.
Improving Multi Object Tracking-By-Detection Model Using a Temporal Interlaced Encoding and a Specialized Deep Detector.

Tracking-by-detection have become a hot topic for intelligent vehicle applications in recent year. Generally, the existing tracking-by-detection frameworks have difficulties with congestion, occlusion, and inaccurate detection in crowded scenes. In this paper, we propose a new framework for Multi-Object Tracking-by-detection (MOT-TbD) based on an temporal interlaced encoding video model and a specialized Deep Convolutional Neural Network (DCNN) detector. Spatio-temporal variation of objects between images are encoded into “interlaced images”. A specialized “interlaced object” deep detector is trained on a interlaced dataset. The detected objects are associated with a classical data association algorithm. Since interlaced objects are built to increase overlap during the association step, the performance of the MOT-TbD increases related to the same detector/association algorithm applied on non-interlaced images. The effectiveness of the method is demonstrated by experiments on popular tracking-by-detection datasets such as the PETS 2009 and TUD. Experimental results show that the proposed framework outperforms several state-of-the-art MOT-TbD methods.
Gender Responsive Budgeting Across Municipal Offices of Education : What Has Changed and Determined?

이 연구는 시 도 교육청 성인지 예산의 변화 추이를 살펴보고, 성인지 예산에 영향을 미치는 요인을 분석하는데 목적이 있다. 이를 위해 지방교육재정알리미에서 제공하는 시 도 교육청의 성인지 예산 관련 자료를 활용하여 성인지 예산의 규모 및 대상사업수의 추이를 살펴보았고, 이원고정효과모형(two way fixed effect model)을 활용하여 성인지 예산 총액과 성인지 예산 대상사업수의 결정요인 분석을 실시하 였다. 분석 결과를 요약하면 다음과 같다. 첫째, 전체 시 도 교육청의 성인지 예산 규모 및 대상사업수는 2013년부터 2015년까지 감소 추세를 보이다가 2016년을 기점으로 증가하는 경향을 보이는 것으로 나타났 다. 그러나 시 도 교육청별 성인지 예산 규모의 변화를 살펴본 결과, 각 시기 및 지역별 격차가 큰 것으로 나타났다. 또한 시 도 교육청별 성인지 예산의 사업별 규모 및 대상사업수를 살펴본 결과, 각 사업별 규모는 모두 증가하였으며 대상사업수 역시 비슷한 수준을 유지하거나 증가한 것으로 확인되었다. 둘째, 시 도 교육청 성인지 예산 총액의 결정요인을 분석한 결과, 사회적 요인인 여학생 비율과 정치적 요인인 시·도의회 여성의원 비율이 성인지 예산 총액 증가에 정적인 영향을 미치는 것으로 나타났으며, 지역성평등지수는 성인지 예산 총액에 부적인 영향을 미치는 것으로 나타났다. 시 도 교육청 성인지 예산 대상사업수의 결정요인을 분석한 결과, 학생수는 대상사업수에 부적인 영향을 미쳤으며, 시 도 교육감의 정치성향이 보수일 경우, 시 도 교육감이 초선일 경우 대상사업수가 증가하는 것으로 나타났다. 이상의 분석 결과를 바탕으로, 시 도 교육청이 성인지 예산 제도를 운영하는데 있어서 안정적인 예산 확보를 위한 노력, 지역성평등지수와 연계한 제도 운영을 위한 노력이 지속될 필요가 있으며, 시 도 교육청 성인지 예산 제도에 대한 관심을 제고할 필요가 있음을 제언하였다.This study is an initial attempt to empirically analyze the gender responsive budgeting across 17 metropolitan and provincial offices of education. Using relevant data from The Local Educational Finance Disclosure System, established respectively for all the 17 offices of education, we probe what has changed over years and the determinants thereof in the relevant. On the basis of two way fixed effect model, major findings demonstrate as follows. First, in general, the volume and the projects of gender responsive budget have reduced from 2013 to 2015 where they rebounded to grow in 2016. In specific, however, large variation between regions and years is observed. Comparing across the offices, the results show that every office had coherent budgetary expansion. Also, the number of projects has increased as the kinds are added or maintained. Second, factor analysis showed that the number of female students and female members of the local assembly have significant positive impact on the amount of gender responsive budgets while Regional Equality Gender Index(REGI) has negative relation with it. Third, the number of students has negative impact on the number of gender equality projects whereas the conservative and newly-elected superintendents have positive impact on it. Based on the findings, we suggest to ensure the fiscal stability in regional levels, to revise and develop the system based on the REGI and to enhance the municipal attention to the gender responsive budgeting.
LibGuides: Library Liaison List: Home

This is a list of areas of the university that currently have a librarian assigned as a liaison.
Willson Auditorium renovation

As a small-city community theater, the 1100 seat Willson Auditorium is a multi-use facility in every sense of the word. This former high school auditorium, where Gary Cooper performed as a student, is now home to performances by the local symphony, an opera company, ballet companies, traveling amplified acts, and high-school and middle-school music and drama students. This case study discusses how the distribution of sound-absorptive material and the shapes of surfaces used in the auditorium provided less than ideal acoustical characteristics and weak projection of sound from the stage for many of the users. The measures taken to correct those issues as part of a renovation will also be discussed, including an increase in volume and redistribution of sound-absorbing and sound-reflecting surfaces, that prompted the school district music director to say the teachers “are going to freak out when they hear the way it sounds.”