Improvised explosive devices (IEDs) are charged devices often used by terrorists and criminals to create public panic. When the general public is targeted by an act of terrorism, people who are not injured or killed in the explosion remain in fear until the perpetrator(s) has been apprehended. Methods that can provide investigators and first responders with prompt investigative information are required in such cases. However, information is generally not provided quickly, in part because of time-consuming techniques employed in many forensic laboratories. As a result, case report turnaround time is longer. Direct analysis in real time - mass spectrometry (DART-MS) is a promising analytical technique that can address this challenge in the Forensic Science community by permitting rapid trace analysis of energetic materials. The builder of an IED will often charge the device with materials that are readily available. The most common materials employed in the construction of IEDs are black and smokeless powder. However, other materials may include ammonia- or peroxide-based materials such as common household detergents. Smokeless powder is a propellant that is readily available to civilians. They are typically used for reloading ammunition and are sold in large quantities each year in the United States. Some states have stricter regulations than others but typically a firearms license is all that’s required to possess smokeless powder. Smokeless powder is considered a low explosive which is capable of causing an explosion if a sufficient quantity is deflagrated inside a confined container. The most commonly employed confirmatory techniques for the analysis of smokeless powder are gas chromatography-mass spectrometry (GC-MS) or liquid chromatography-mass spectrometry (LC-MS). These methods often require extensive and time-consuming sample preparation procedures to prepare the powders for analysis. In addition to lengthy sample preparation procedures, GC-MS and LC-MS often require chromatographic separations that can range anywhere from 5 to 30 minutes or longer per sample. Ion mobility spectrometry (IMS) is widely used for the field analysis of smokeless powder and can provide faster results in comparison to GC-MS or LC-MS. However, identification is limited to drift time and no structural information is provided unless coupled to a mass spectrometer. In an effort to accelerate the speed of collection and characterization of smokeless powder, an analytical approach that utilizes novel wire mesh coated with CarbopackTM X, dynamic headspace concentration and DART-MS was evaluated to determine if the approach could generate information rich chemical attribute signatures (CAS) for smokeless powder. CarbopackTM X is a graphitized carbon material that has been employed for the collection of various volatile and semi-volatile organic compounds. The goal of using CarbopackTM X coated wire mesh was to increase the collection efficiency of smokeless powder in comparison to traditional swabbing and swiping methods. DART is an ambient ionization technique that permits analysis of a variety of samples in seconds with minimal to no sample preparation and offers several advantages over conventional methods. Heating time, heating temperature and flow rate for dynamic headspace concentration were optimized using Hodgdon Lil’ Gun smokeless powder. DART-MS was compared to GC-MS and validated using the National Institute of Standards and Technology reference material 8107 (NIST RM 8107) smokeless powder standard. Additives and energetic materials from unburnt and burnt smokeless powders were rapidly and efficiently captured by the CarbopackTM X coated wire mesh and successfully detected and identified using DART-MS. The DART source temperature was evaluated with the goal of providing the most efficient desorption of the analytes adsorbed onto the wire mesh. For this to be a robust approach in forensic analysis, chemometric analysis employing predictive models was used to simplify the data and increase the confidence of assigning a mass spectrum to a particular powder. Predictive models were constructed using the machine learning techniques available in Analyze IQ Lab and evaluated for their performance in classifying three smokeless powders: Alliant Reloder 19, Hodgdon LEVERevolution and Winchester Ball 296. The models were able to accurately predict the presence or absence of these three powders from burnt residues with error rates that were less than 4%. This approach has demonstrated the capability of generating comparable data and sensitivity in a significantly shorter amount of time in comparison to GC-MS. In addition, DART-MS also permits the detection of targeted analytes that are not amenable to GC-MS. The speed and efficiency associated with both the sample preparation technique and DART-MS, and the ability to employ chemometric analysis to the generated data demonstrate an attractive and viable alternative to conventional techniques for smokeless powder analysis.

Dieser Bericht präsentiert RACR-NET, eine Schnittstelle der Referenzattributgrammatik-gesteuerten Graphersetzungsbibliothek RACR für C#. RACR-NET ermöglicht die Nutzung der deklarativen, dynamischen Sprachspezifikations-, Instanziierungs- und Auswertungsmeachanismen der RACR Scheme-Bibliothek in der objektorientierten Programmierung. Dies umfasst insbesondere die automatische inkrementelle Auswertung attributbasierter semantischer Analysen und somit das automatische Cachen parametrisierter Funktionsmethoden. Graphersetzungen entsprechen hierbei Zustandsänderungen von Objektinstanzen und der Invalidierung abgeleiteter Berechnungen. Schwerpunkt dieses Berichts ist die objektorientierte Programmierschnittstelle von RACR-NET, dessen praktische Anwendung und Implementierung. Der Bericht ist ein Referenzhandbuch für RACR-NET Anwender und Entwickler.

La présente thèse relève à la fois de la linguistique et de la traduction. La traduction fait apparaître les similitudes et les différences sémantiques et syntaxiques entre les systèmes langagiers de la langue de départ et la langue d’arrivée. La traduction des verbes à compléments attributifs exige une connaissance approfondie de leur grammaire et de la syntaxe de leurs constructions. Une étude descriptive séparée de chaque langue présente un schéma syntaxique de ces verbes en français et en arabe. Cette thèse examine dans la dernière partie le cas du verbe kāna, verbe très important et de haute fréquence parmi les verbes à compléments attributifs étudiés. L’analyse portait sur le texte coranique. Une approche comparative montre que les équivalents de « kāna + préposition » trouvés dans la traduction de Blachère ne correspondent pas aux équivalents donnés par les dictionnaires et qu’il était impossible de traduire un verbe en se contentant de recourir à ces derniers, qui ne nous donnent pas toujours un équivalent parfait du verbe étudié et ne recouvrent pas tous les contextes possibles. En tant qu’exposant temporel ou verbe d’état, le verbe kāna doit être traduit d’après des indices contextuels (les marqueurs de la négation, modalités, préposition, …). Cette analyse indique clairement que le contexte immédiat et médiat du verbe joue un rôle primordial dans sa traduction comme on peut le voir avec le verbe kāna illustré par des exemples tirés du texte coranique. / This thesis pertains to both linguistics and translation studies. Translating from one language to another presents semantic and syntactic similarities and differences between Arabic and French. The translation of verbs with attributive complement demands a very good understanding of the grammar and of the syntactic constructions of the phrases containing these verbs. Separate studies of Arabic and French show a syntactical pattern of their verbs with attributive complement. This thesis also analyzes the use of the extremely important verb, kāna, the most frequently used between the Arabic verbs with an attribute studied in the corpus. We analysed its uses in the Coran. A close comparison shows that the equivalents of " kāna + preposition " that Blachère gives in his translation do not match with those found in dictionaries. In fact, translating this verb only with the definitions found in dictionaries is impossible. A dictionary as a single source will never be sufficient in the realm of translation. As a temporal exponent or a state verb, kāna must be translated by using contextual clues including (negation marker, modality, prepositions, …). This analysis clearly indicates that both direct and indirect contexts of a verb play an essential role in its translation. The verb, kāna, with its examples from the Coran documents this principle.

No description available.

Master of Science / Department of Geology / Matthew W. Totten / Ness County has contributed 30 billion barrels to Kansas oil production since 1995, and has been an actively developing county in oil activity. The focus of this research project is to identify the reservoir qualities that make Mississippian-aged production favorable. Modern day logging techniques and seismic data allow specialists to seek out subtle heterogeneities to an oil producing formation once thought to be homogenous. Having success with horizontal drilling in other locations worldwide, large oil companies have acquired tens of thousands of acres with the intentions of drilling into the Mississippian, although some have recently backed out of the area. While some horizontal wells are producing today, complications with the compartmentalized, relatively thin Mississippian producing zones and short production longevities make horizontal drilling a high risk technique. Better understanding favorable reservoir qualities are essential for future production and development of oil fields in Ness County. This case study utilizes different variations of post and pre-stack 3D and 2D seismic data shot on about 3,200 acres spanning over 8 sections located in northwestern Ness County. The physical and chemical properties associated with the Mississippian formation in this area can be better analyzed with different methods for processing seismic data. Raw seismic signatures show little variation within the Mississippi Lime/Dolomite. Utilizing Seismic attributes derived from raw data may bring certain featured hydrocarbon bearing zones into view. Attributes such as curvature and coherency aid in interpreting physical features within the study area while spectral decomposition, amplitude, instantaneous frequency, and instantaneous Q hold detailed signatures dependent upon rock properties.

This study shows how the use of modern geological investigative techniques can reopen old, “drained” hydrocarbon fields. Specifically, it looks at the White Castle Field in South Louisiana. This field has pay sections ranging from late Oligocene to late Miocene. The late Oligocene package is underexplored and understudied and contains 3 primary reservoirs (Cib Haz (CH), MW, and MR). This study established the depositional history of these reservoirs. During most of the late Oligocene, the White Castle Salt Dome was located in a minibasin on the continental slope. The CH and MW deposited in this minibasin. The CH is an amalgamation of slumped shelfal limestones, sandstones, and shales deposited during a lowstand systems tract (LST). The MW comprises a shelf-edge delta that is part of a LST. The MR is an incised valley fill located in the continental shelf that was deposited during LST after the minibasin was filled.

Mathematical modeling is a thinking process that applies various sets of cognitive attributes – one component of intellectual resources (i.e., cognitive resources). Students are able to develop cognitive attributes when they engage in mathematical modeling activities. Furthermore, using many of the cognitive attributes developed during the mathematical modeling process, students solve mathematics problems, for example, in assessments. Examining students’ mastery of these cognitive attributes, we can investigate relationships between students’ cognitive development through mathematical modeling practices in classrooms and their performance on mathematics assessments. The purpose of this research is to quantitatively and empirically investigate the relationships between students’ development of mathematics cognitive attributes and their achievement. For the current study, we selected the four cognitive attributes representing different stages of the mathematical modeling practices – select, analyze, compute, and represent. The generalized DINA (deterministic inputs, noisy “and” gate) is applied to generate students’ mastery profiles of the cognitive attributes from their responses to test items. Using students’ mastery profiles as datasets, three secondary analysis studies are conducted with linear regression analysis and multivariate approach to repeated measure ANOVA. The findings show that development of the four cognitive attributes in mathematical modeling is positively related to mathematics achievement. In addition, students, who developed select and compute throughout 4th to 8th grades, scored higher in mathematics assessment with large degrees of effects. The findings suggest important implications to teachers: Students need to have opportunities develop a wide range of cognitive attributes of mathematical modeling, which would result in higher achievement. Teachers need to have instructional emphases on different stages of mathematical modeling depending on grade levels: students’ representing a solution at elementary-school levels; and analyzing a problem situation and selecting strategies at middle-school levels. The study also suggests teachers shift an instructional emphasis from learning mathematics contents to high-order thinking like mathematical modeling to accomplish higher mathematics achievement.

Omega is a description system for knowledge embedding which incorporates some of the attractive modes of expression in common sense reasoning such as descriptions, inheritance, quantification, negation, attributions and multiple viewpoints. A formalization of Omega is developed as a framework for investigations on the foundations of knowledge representation. As a logic, Omega achieves the goal of an intuitively sound and consistent theory of classes which permits unrestricted abstraction within a powerful logic system. Description abstraction is the construct provided in Omega corresponding to set abstraction. Attributions and inheritance are the basic mechanisms for knowledge structuring. To achieve flexibility and incrementality, the language allows descriptions with an arbitrary number of attributions, rather than predicates with a fixed number of arguments as in predicate logic. This requires a peculiar interpretation for instance descriptions, which in turn provides insights into the use and meaning of several kinds of attributions. The formal treatment consists in presenting semantic models for Omega, deriving an axiomatization and establishing the consistency and completeness of the logic.

There are many different techniques and notations for extracting architecturally interesting information from the source code of existing software systems. This process is known as reverse engineering. One current problem with reverse engineering techniques is that models of software systems cannot easily be transferred from one notation and storage format to another. We refer to this as the problem of bridging <em>technical spaces</em>. <br /><br /> In this work, we approach the issue of bridging between the SWAG technical space and the UML technical space. The SWAG technical space, named after the Software Architecture Group at the University of Waterloo, consists of fact extractors, fact manipulators, schemas, and a fact storage language - the Tuple-Attribute language (TA). The UML technical space consists of the UML metamodel, the XML Metadata Interchange (XMI) format for encoding UML models, and various UML modeling tools. We have designed and implemented a plugin for MagicDraw UML, which will import, export, and merge between XMI-encoded UML models and TA-encoded Function-Level Schema models. <br /><br /> We document evidence of what is referred to as a <em>Bridge Domain</em> - a technical space which exists between two encodable spaces. The metamodels of the two notation languages that we have focused on are very rich and flexible, but neither technical space is capable of fully expressing an accurate architectural model of any given software system; however, each technical space is capable of maintaining certain semantic information relevant to that technical space through multiple merge operations.

In current age, various companies are using a centralized database system for dailybusiness transactions in different domains. Some critical issues have been observedrelated to the complexity, maintenance, performance and communication cost of datain centralized data repository for query processing, according to the demand of endusersfrom different locations. So, different enterprises are striving to implementefficient distributed database systems in their business environments for scalability.The distributed database architecture covers different factors such as transparentmanagement system, replication, fragmentation and allocation etc. This dissertationfocuses on database fragmentation and techniques which are useful for performingdatabase fragmentation. The objective of this research is to investigate efficient algorithm and technique fordatabase fragmentation in distributed environment. We proposed a customized ISUD(Insert, Select, Update, Delete) technique after comparative study of the best suitabletechniques, which is selected for implementation purpose. The functionality of thecustomized ISUD technique helps to get the precedence of the attribute of a relationhorizontally in database from various sites or location. The practical objective of this dissertation is to design the architecture and develop,implement customized ISUD (Insert, Select, Update, Delete) user interface, and to testthe selected algorithm or technique by using the interface. We used C#.Net as adevelopment tool. This user interface accepts ISUD frequency as an input andproduces ALP (attribute location precedence) values as output. We have incorporateddesign science research (DSR) method for customized ISUD technique development.This customized ISUD technique can be considered as a foundation to implementhorizontal database fragmentation in distributed environment, so that the databaseadministrator can take a proper decision for allocating the fragmented data to varioussites at initial state of distributed database design.