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Register a new userReligious terms (study of lexical- semantic)
الألفاظ الدينية و دلالاتها في النصوص الأوجاريتية (دراسة معجمية – دلالية)
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Aِl-Baath University ورقة بحثية
Publication date
2017
fields
History
and research's language is
العربية
Authors
محمد محمد( باحث )
Created by
Shamra Editor
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يهدف هذا البحث إلى القاء الضوء على المصطلحات الدينية في النصوص المسمارية الأوجاريتية، و توضيح طريقة و أسلوب صياغتها لتخدم الغرض الروحي المرجو من تضمينها للنصوص الشعرية الميثولوجيا التي صاغها الأديب و الشاعر الأوجاريتي في مجموعة القصائد المغناة في مناسبات دينية و شعائرية دورية متعددة.
This research aims to shed light on the religious terminology in cuneiform texts Aloojarretah, and describes amethod and style formulated to serve the spiritual purpose of the desired included texts poetic mythology penned by writer and poet Aloojarreta in lyrics group in multi- religious events and periodic ritual.
References used
Aistleiner.J, 1902- Wörterbuch der Ugaritischen Sprache. Akadmie Verlag, Berlin, 362p
Del Olmo.G, 2004- ADictionary of the Ugaritic Language in the Alphabetic Tradition. Boston, 1006p
GORDON C.H, 1967- UGARlTlC TEXT Book. Roma, 547p
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Every era has its own intellectual and social dimensions the influence of which extend to
touch the artistic topics in terms of creativity and production conditions. The religious belief
is considered as an important effect on the whole historicall
y-successive artistic process. The
oppression exercised by the religious authority on creativity has always been present, but in
forms that differ from an era to another.
Viewing the religious theme embodied in art works, we will recognize that vast area achieved
throughout ages.
At early stages art rested on primitive, mysterious magic-based beliefs. Then art introduced a
physical representation of the images of the national gods and religious beliefs that used to
give explanations about the universe and glorify kings. Clergymen, then, started to identify
the boundaries and function of art in a way that served their goals. Christian religious men
continued to employ art for the sake of their messages and teachings with a controversy over
the role and limits of art. On the other side, Islamic art expanded but it neither served belief
nor subject to any religious guidance. With certain spiritual nature, such Islamic art might
have sought to avoid prohibition fatwas.
Finally, art could not be freed from religion scopes until Renaissance had come with its
human and mental spirit.
Neural models trained for next utterance generation in dialogue task learn to mimic the n-gram sequences in the training set with training objectives like negative log-likelihood (NLL) or cross-entropy. Such commonly used training objectives do not f
oster generating alternate responses to a context. But, the effects of minimizing an alternate training objective that fosters a model to generate alternate response and score it on semantic similarity has not been well studied. We hypothesize that a language generation model can improve on its diversity by learning to generate alternate text during training and minimizing a semantic loss as an auxiliary objective. We explore this idea on two different sized data sets on the task of next utterance generation in goal oriented dialogues. We make two observations (1) minimizing a semantic objective improved diversity in responses in the smaller data set (Frames) but only as-good-as minimizing the NLL in the larger data set (MultiWoZ) (2) large language model embeddings can be more useful as a semantic loss objective than as initialization for token embeddings.
Identification of lexical borrowings, transfer of words between languages, is an essential practice of historical linguistics and a vital tool in analysis of language contact and cultural events in general. We seek to improve tools for automatic dete
ction of lexical borrowings, focusing here on detecting borrowed words from monolingual wordlists. Starting with a recurrent neural lexical language model and competing entropies approach, we incorporate a more current Transformer based lexical model. From there we experiment with several different models and approaches including a lexical donor model with augmented wordlist. The Transformer model reduces execution time and minimally improves borrowing detection. The augmented donor model shows some promise. A substantive change in approach or model is needed to make significant gains in identification of lexical borrowings.
People live in various environments, although they can understand scenes around them with just a glance. To do this, they depend on their high ability to effectively process visual data and connect it to wide pre-knowledge about what they are expecte
d to see. This is not the case for computers, which can’t reach high levels of scene understanding until now. Most researches treat scene understanding as a usual classification problem, where they have just to classify scenes in predefined limited categories (forest, city, garden). They normally used classification or machine learning algorithms, which limit their ability to understand scenes and reduces their chances to be used in a practical way because of a required training phase of these algorithms. Some researches try to make use of knowledge in Ontologies to reach a high level scene understanding, but these researches are still limited to specific domains only. In this thesis we are trying to understand scene images without any pre-knowledge about their domain. We will not treat this problem as a normal classification problem; however we will extract high level concepts from scene images. These concepts will not only represent objects in the scene, but they will also reflect the places and events in the scene. To do this, we develop a novel algorithm named SMHITS. It depends on a semantically rich common sense knowledge base to extract associated concepts with a primitive group of concepts. To use SMHITS in scene understanding, we also develop a system named ICES. Instead of using a classification or machine learning algorithm, ICES depends on a large dataset of images that is independent of any scene domain. Results show the superiority of SMHITS comparing to current ConceptNet associated concepts extraction algorithm, as it has higher precision and can take advantage of expansion of its knowledge base. Results also show that ICES output concepts are semantically rich.
This study aimed at investigating the relationship between psychological support and
religious values among the adolescents in the preparatory year at the Muslim University in
Al-Madīnah Al-Munawwarah. The study employed the descriptive analytical
method, and
the researcher developed the study instruments that consisted of two scales; the
psychological support scale, which consisted of (41) items distributed to four domains:
(emotional support, morale cognitive support, recognition and status support, as well as
social support); and the religious values scale which consisted of (53) items distributed to
three domains: (ideological values, worship values, as well as moral values). The validity
and reliability of study instruments were verified. The study sample consisted of (192)
preparatory-year students studying at the Muslim University in Al-Madīnah Al-
Munawwarah. The results showed that the level of psychological support, with its
domains, was of a high degree, with a mean that ranged between (3.75 - 4.06), and it was
ranked as follows; (cognitive morale support , recognition and status support, social
support, and emotional support). The mean of psychological support in total was (3.91) .
The level of religious values was also of a high degree, with a mean that ranged between
(3.64 - 4.44), in the following order (ideological values, worship values, and finally moral
values), and the mean of the religious values in total was (3.92). The results showed that
there is a statistically significant positive relationship between the psychological support
and the religious values.
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