This thesis is a descriptive grammar of Ambel [wgo], an endangered Austronesian (South Halmahera-West New Guinea) language. Ambel is spoken by approximately 1600 people on Waigeo, the largest island in the Raja Ampat archipelago (West Papua province, Indonesia). This grammar is based on naturalistic and elicited data, collected by the author from native speakers of Ambel. Ambel is a head-marking language, with basic SV/AVO constituent order. There are 14 native consonant phonemes and five vowel phonemes. Ambel has a tone system, in which /H/ syllables contrast with toneless syllables. Neither stress nor vowel length are contrastive. In verbal clauses, the subject of the clause is marked on the verb. This system makes a four-way number distinction (singular, dual, paucal, and plural), an animacy distinction in the third person, and a clusivity distinction in the non-singular first person. The Ambel noun phrase is mainly head-initial. There are five distinct morphosyntactic possessive constructions, the choice of which is primarily determined by a lexical specification on the possessed noun. Some nouns (including most body parts and some kin terms) are possessed in one of three constructions in which the person, number, and animacy of the possessor is marked directly on the possessed noun, while most other nouns are possessed in one of two constructions in which the possessor is marked on a prenominal possessive classifier. Within the clause, all negation particles and most aspect and mode particles are clause-final. There is no passive construction. Ambel has a rich system of spatial deixis, in which six different classes of deictic words (such as demonstratives, deictic prepositions, and deictic nouns) are derived from one of four demonstrative roots or 28 directional stems. Verb serialisation is used to express, among other things, purposive motion and changes of state. This thesis is the first major description and documentation of the Ambel language. As such, it will be of considerable interest to typologists and historical linguists, as well as others interested in the languages, cultures, and history of New Guinea. All of the data on which this grammar is based have been archived with both the Endangered Languages Archive, and the Center for Endangered Languages Documentation at Universitas Papua in Manokwari. The data will thus be available to future generations, including the Ambel community themselves.

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Le principale objectif de l'imagerie sismique pétrolière telle qu'elle est réalisée de nos jours est de fournir une image représentative des quelques premiers kilomètres du sous-sol. Cette image permettra la localisation des structures géologiques formant les réservoirs où sont piégées les ressources en hydrocarbures. Pour pouvoir caractériser ces réservoirs et permettre la production des hydrocarbures, le géophysicien utilise la migration-profondeur qui est un outil d'imagerie sismique qui sert à convertir des données-temps enregistrées lors des campagnes d'acquisition sismique en des images-profondeur qui seront exploitées par l'ingénieur-réservoir avec l'aide de l'interprète sismique et du géologue. Lors de la migration profondeur, les évènements sismiques (réflecteurs,…) sont replacés à leurs positions spatiales correctes. Une migration-profondeur pertinente requiert une évaluation précise modèle de vitesse. La précision du modèle de vitesse utilisé pour une migration est jugée au travers l'alignement horizontal des évènements présents sur les Common Image Gather (CIG). Les évènements non horizontaux (Residual Move Out) présents sur les CIG sont dus au ratio du modèle de vitesse de migration par la vitesse effective du milieu. L'analyse du Residual Move Out (RMO) a pour but d'évaluer ce ratio pour juger de la pertinence du modèle de vitesse et permettre sa mise à jour. Les CIG qui servent de données pour l'analyse du RMO sont solutions de problèmes inverses mal posés, et sont corrompues par du bruit. Une analyse de l'incertitude s'avère nécessaire pour améliorer l'évaluation des résultats obtenus. Le manque d'outils d'analyse de l'incertitude dans l'analyse du RMO en fait sa faiblesse. L'analyse et la quantification de l'incertitude pourrait aider à la prise de décisions qui auront des impacts socio-économiques importantes. Ce travail de thèse a pour but de contribuer à l'analyse et à la quantification de l'incertitude dans l'analyse des paramètres calculés pendant le traitement des données sismiques et particulièrement dans l'analyse du RMO. Pour atteindre ces objectifs plusieurs étapes ont été nécessaires. Elles sont entre autres :- L’appropriation des différents concepts géophysiques nécessaires à la compréhension du problème (organisation des données de sismique réflexion, outils mathématiques et méthodologiques utilisés);- Présentations des méthodes et outils pour l'analyse classique du RMO;- Interprétation statistique de l’analyse classique;- Proposition d’une approche stochastique;Cette approche stochastique consiste en un modèle statistique hiérarchique dont les paramètres sont :- la variance traduisant le niveau de bruit dans les données estimée par une méthode basée sur les ondelettes, - une fonction qui traduit la cohérence des amplitudes le long des évènements estimée par des méthodes de lissages de données,- le ratio qui est considéré comme une variable aléatoire et non comme un paramètre fixe inconnue comme c'est le cas dans l'approche classique de l'analyse du RMO. Il est estimé par des méthodes de simulations de Monte Carlo par Chaîne de Markov.L'approche proposée dans cette thèse permet d'obtenir autant de cartes de valeurs du paramètre qu'on le désire par le biais des quantiles. La méthodologie proposée est validée par l'application à des données synthétiques et à des données réelles. Une étude de sensibilité de l'estimation du paramètre a été réalisée. L'utilisation de l'incertitude de ce paramètre pour quantifier l'incertitude des positions spatiales des réflecteurs est présentée dans ce travail de thèse. / The main goal of the seismic imaging for oil exploration and production as it is done nowadays is to provide an image of the first kilometers of the subsurface to allow the localization and an accurate estimation of hydrocarbon resources. The reservoirs where these hydrocarbons are trapped are structures which have a more or less complex geology. To characterize these reservoirs and allow the production of hydrocarbons, the geophysicist uses the depth migration which is a seismic imaging tool which serves to convert time data recorded during seismic surveys into depth images which will be exploited by the reservoir engineer with the help of the seismic interpreter and the geologist. During the depth migration, seismic events (reflectors, diffractions, faults …) are moved to their correct locations in space. Relevant depth migration requires an accurate knowledge of vertical and horizontal seismic velocity variations (velocity model). Usually the so-called Common-Image-Gathers (CIGs) serve as a tool to verify correctness of the velocity model. Often the CIGs are computed in the surface offset (distance between shot point and receiver) domain and their flatness serve as criteria of the velocity model correctness. Residual moveout (RMO) of the events on CIGs due to the ratio of migration velocity model and effective velocity model indicates incorrectness of the velocity model and is used for the velocity model updating. The post-stacked images forming the CIGs which are used as data for the RMO analysis are the results of an inverse problem and are corrupt by noises. An uncertainty analysis is necessary to improve evaluation of the results. Dealing with the uncertainty is a major issue, which supposes to help in decisions that have important social and commercial implications. The goal of this thesis is to contribute to the uncertainty analysis and its quantification in the analysis of various parameters computed during the seismic processing and particularly in RMO analysis. To reach these goals several stages were necessary. We began by appropriating the various geophysical concepts necessary for the understanding of:- the organization of the seismic data ;- the various processing ;- the various mathematical and methodological tools which are used (chapters 2 and 3). In the chapter 4, we present different tools used for the conventional RMO analysis. In the fifth one, we give a statistical interpretation of the conventional RMO analysis and we propose a stochastic approach of this analysis. This approach consists in hierarchical statistical model where the parameters are: - the variance which express the noise level in the data ;- a functional parameter which express coherency of the amplitudes along events ; - the ratio which is assume to be a random variable and not an unknown fixed parameter as it is the case in conventional approach. The adjustment of data to the model done by using smoothing methods of data, combined with the using of the wavelets for the estimation of allow to compute the posterior distribution of given the data by the empirical Bayes methods. An estimation of the parameter is obtained by using Markov Chain Monte Carlo simulations of its posterior distribution. The various quantiles of these simulations provide different estimations of . The proposed methodology is validated in the sixth chapter by its application on synthetic data and real data. A sensitivity analysis of the estimation of the parameter was done. The using of the uncertainty of this parameter to quantify the uncertainty of the spatial positions of reflectors is presented in this thesis.

Abstracts in English, Zulu and Shona / The purpose of the study was to examine the role of educators in enhancing the social wellness on juvenile offenders in Zimbabwe. The theoretical framework that underpinned the study was the Wellness Theory of Bill Hettler (1980) used as the lens to explore and generate understanding on how educators enhance the social wellness of juvenile offenders. The study was located within an interpretive paradigm. Qualitative research design and case study approach were used in this study. Moreover, purposive sampling approach was used to select the samples of educators and juvenile learners who responded to the qualitative questionnaires and those who participated in the interviews, which were used for data collection. The research had five educators and ten juvenile offenders who participated at one of the correctional centres in Zimbabwe based on availability and willingness. In addition, the researcher adhered to ethical standards in terms of gaining permission for access, issues of informed consent, voluntary participation, and confidentiality. Data were gathered by means of self-administered qualitative questionnaires with open-ended questions, interviews and observation. The research identified that no research has been carried out in Zimbabwe’s correctional centres to thoroughly explore the role of educators in the enhancement of the social wellness of juvenile offenders. The findings firstly revealed that education promoted the social wellness and resulted in positive behavioural change among juvenile offenders at the correctional centre. Secondly, education promoted the development of various technical skills in juvenile learners, such as agriculture and welding, as well as interpersonal skills such as anger management, respect, problem solving, and communication. The findings revealed that some juvenile offenders developed entrepreneurship skills. Some of the juveniles were making doormats, fence making and plaiting extensions. One of the juveniles had a unique skill in plaiting and braiding. He taught his friends, and now they are plaiting extensions and selling them. Thirdly, the findings revealed that educators are essential in the enhancement of the social wellness of juvenile offenders in an effort to reduce recidivism and facilitation of good and smooth social reintegration into mainstream society after incarceration. The challenges faced by the educators included limited resources and inadequate training as specialists who teach juvenile offenders. It was recommended that educators be empowered through in-service training to enable them to facilitate the capacitation of juvenile learners’ social wellness. / Ucwaningo lolu luphenye ngendima yothisha ekuthuthukisweni kwenhlalonhle yabantu abahlukumezanayo abasebasha eZimbabwe. Lolu cwaningo lugqamisa imfundo yasejele njengengxenye ebalulekile yenqubo yokuvuselela kanye nentuthuko yezoni zabasha. Uhlaka lwethiyori oluqondise lolu cwaningo luyimodeli yokuphila kahle ekaBill Hettler futhi ucwaningo lutholwa phakathi kwomongo wendaba ohumushekayo. Kusetjenziswe ukuhlahlela okuphathelene nesimo kanye nokuhlaziya okubhekane nesimo esisodwa noma nomuntu oyedwa isikhathi esithile okwenziwe esikhungweni esisodwa sokuLungiswa eZimbabwe. Ngaphezu kwalokho, isampula elinenhloso lalisetshenziselwa ukukhetha isampula eyayiqukethe othisha abahlanu nabahlukumezi abasebasha abayishumi. Leli sampula labantu lihanganyele ngokutholakala kanye nokuvuma kwayo. Umcwaningi wenze izinto ngenkambo elungileyo ngocela imvume yokungena endaweni, ukuthola imvume ebhaliwe ebantwini abayingxenye yocwaningo, ukuhlanganyelwa ngokuzikhethela, nokugcina umbiko ngokwemfihlo. Idatha iqoqwe ngohlu lwemibuzo evulekile, izingxoxo kanye nokubukwa. Lokhu okutholiwe kubonisa ukuthi alukho ucwaningo oluyenziwe emajele aseZimbabwe ukuhlola indima yothisha ekuthuthukisweni kwenhlalonhle yabantu abahlukumezanayo abasebasha. Ucwaningo lubonisa ukuthi, okokuqala, imfundo ithuthukisa inhlalonhle yomphakathi, futhi iholele ekuguqukeni kokuziphatha okuhle kubahlukumezi abasebasha. Ngaphezu kwalokho, imfundo ithuthukise amakhono ahlukahlukene wezobuchwepheshe, njengezolimo, ukushisela, namakhono wokusebenzisana nabantu njengokuphatha intukuthelo, inhlonipho, ukuxazulula izinkinga nokukhulumisana. Okunye okutholakele ukuthi abanye abahlulumezi bathuthukise ikhono lokuqala ibhizinisi elizimele. Abanye bayenze izisulelo zasemnyango, ukuyenza ucingo, nokuluka. Omunye wabahlukumezi nokhono olukhethekile lokuqhina izinwele. Wafundisa abangani bakhe, kanti futhi manje baqhina imifakelo yezinwele, bese bayazithengisa. Okwesithathu, ucwaningo lubonisa ukuthi abothisha babalulekile ekuthuthukisweni kwenhlalonhle yabantu abahlukumezanayo abasebasha njengendlela yokugwema ukona ukophindaphindiwe kwabahlukumezi, kanye nokuthuthukisa ukubuyela kwabo ephakathini okukahle emva kwokuboshwa. Ezinye izinselelo ezibhekane nabothisa izinsizakusebenza ezilinganiselwe nokuqeqeshwa okunganele njengongoti abafundisa iziboshwa zentsha. Kululekwe ukuthi othisha banikezwe amandla ngokuqeqeshwa basasebenza okuzokwenza ukuthi balungiselele ukhlomisa kwenhlalonhle yabantu abahlukumezanayo abasebasha. / Chinangwa chetsvakurudzo ino chaiva chekuongorora basa revarairidzi mukuvandudza ukama nemagariro akanaka munharaunda evapari vemhosva vechiki muZimbabwe. Donzvo rakateverwa netsvakurudzo ino raiva ramafungiro ava Bill Hetter (1980) anotaridza zveukama namagariro akanaka ayo akashandiswa semuono wekuferefeta nekubudisa manzwisisiro angavapo pakuti varairidzi vangavandudza sei ukama namagariro akanaka munharaunda evapari vemhosva vechidiki. Tsvakurudzo iyi yakazendama pamafungiro anosimbisa madudzirirwo akanaka epfungwa. Mutsvakurudzi akashandisa maonere anokoshesa kunzwisisa mashoko avanhu munharaunda, maitiro avo nemaonere avo. Mutsvakurudzo iyi, umboo hwakadzika hwakatorwa muzviitiko zvikuru zvakamiririra zviitiko zvakada kufanana nazvo. Pamusoro pazvo, avo vakasharwa kuti vave vapi vepfungwa vakasarudzwa zvichienderana nezvavakambosangana nazvo uyewo zvavanoziva pamusoro pedambudziko riri kuferefetwa. Vapi vepfungwa ava vaisanganisira varairidzi uye vadzidzi vechidiki vemazera epakati nepakati. Ava vakapindura mibvunzo yaiva yakagadzirwa pamagwaro avaizadzisa uye vamwe vakaita zvekupa pfungwa dzavo kupfurikidza nehurukuro dzakarongwa nemutsvakurudzi. Pfungwa dzakabuda mutsvakurudzo iyi dzakabuda kubva kuvarairidzi vashanu nevapari vemhosva vechidiki gumi avo vakasarudzwa kubva munzvimbo dzinochengeterwa vakapara mhosva nechinangwa chekuvavandudza mararamiro avo muZimbabwe zvichienderana neuvepo hwavo uye kuzvisarudzira zvakasunguka kupinda mutsvakurudzo. Mutsvakurudzi akatevera mitemo inomusungira kuremekedza kodzero dzevanhu, uye nzvimbo zvinosanganisira kuwana mvumo yekupinda munzvimbo, kupa vapi vepfungwa ruzivo rwakakwana pamusoro pechinangwa chetsvakurudzo, kupa vapi vepfungwa sununguko yekupinda mutsvakurudzo pasina kumanidzwa uyewo mutsvakurudzi akavimbisa kubata hana nekusashambadzira mazita avanhu vakapinda mutsvakurudzo. Pfungwa dzakaunganidzwa kuchishandiswa magwaro emibvunzo akapiwa kunevamwe vevakapinda mutsvakurudzo. Mutsvakurudzi pachezvake ndiye akagovera magwaro aya kuvapi vepfungwa. Mibvunzo yaiva mumagwaro aya yaipa vapi vepfungwa mukana wekurondedzera maonero avo vakasununguka. Dzimwe nzira dzakashandiswa dzaisanganisira hurukuro pakati pemupi wepfungwa nemutsvakurudzi uye kuongorora kupfurikidza nekucherechedza zvakadzika zviitiko. Tsvakurudzo iyi yakawana kuti hapana tsvakurudzo yati yamboitwa inoongorora basa revarairidzi mukuvandudza ukama nemagaririo akanaka munharaunda evana vemazero epakati nepakati munzvimbo dzinochendeterwa vapari vemhosva nechinangwa chekuvandudza magariro avo akanaka munharaunda. Chekutanga, kwakaonekwa kuti dzidzo inosimudzira ukama nemagariro akanaka munharaunda zvinozoita kuti pave nekushanduka kwakanaka kweunhu hwevapari vemhosva vechidiki vezera repakati nepakati. Chepiri, zvakabuda kuti dzidzo inosimudzira kuvandudzwa kweunyanzvi hwekurima, kupisira simbi, kudyidzana, kuzvidzora pahasha, ruremekedzo, kugadzirisa matambudziko uye kutaurirana. Zvakabuda mutsvakurudzo zvinotaridza kuti vamwe vapari vemhosva vechidiki vakavandudza unyanzvi hwekutanga mibato inovandudza upfumi. Vamwe vechidiki ava vaigadzira zvidhava zvepamikova, mafenzi uye kuruka kwamazuva ano. Umwe wevechidiki ava akataridza unyanzvi hwepamusoro hwekuruka nekukosha bvudzi remvere mumusoro. Akadzidzisa vamwe vake avo vave mubasa rekuruka nekukosha bvudzi remvere vachitengesa. Chetatu, zvakaonekwa kuti varairidzi vakakosha pakuvandudza ukama nemagariro akanaka evadiki vezera rekapati nepakati munharaunda nechinangwa chekudzikisa kupariwazve kwemhosva naavo vakasimbopara mhosva uye kuona kuti kupinda nekukwana zvakare munharaunda kwevakambopara mhosva kwaitwa zvakanaka pasina zvigozhero. Matambudziko anosanganikwa nawo navarairidzi anosanganisira kushaikwa kwezvishandiso uye kushaikwa kwemukana wekudzidza unyanzvi hwakakwana hwekudzidzisa vapari vemhosva vechidiki vezera repakati nepakati. Mutsvakurudzi akapa rairo yekuti varairidzi vapiwe unyanzvi kupfurikidza nekudzidziswa vari pamabasa avo zvingaite kuti vagone kubetsera vechidiki vemazera epakati nepakati ukama nemagarire akanaka munharaunda. / Psychology of Education / M. Ed. (Psychology of Education)