75 research outputs found
Contemporary explanations for Sunan Nasaie: A study of sheikh Muhammad Ali Adam approach in his commentary Zakhirah al-’Uqba / Romzi Taleh
No full textThe purpose of this research is to study the methodology of Mohammad bin Ali Adam al-Ethiopi in his work, “Zahirah al-„Uqba fi Sharh al-Mujtaba”. This work consists of writings and lectures on Sunan al-Nasa‟i al-Sughra written by Imam al-Nasa‟i. The focus of this study is on the science of narration and analysis of texts applied in the work. This study also introduces Imam al-Nasa‟i‟s work, Sunan al-Nasa‟i, and its position among other books of hadith collections. The biography of Mohammad bin Ali Adam is also introduced based on authoritative sources of reference, besides interviews with his students and followers. This study uses an analytical approach in order to identify the methodology employed by Mohammad bin Ali Adam in his analysis of the hadiths in Sunan al-Nasa‟i, as well as criticisms directed towards him. In producing this study, the writer used the comparison method, by comparing the methods applied in Zahirah al-„Uqba and in al-Shanqiti‟s Shuruq Anwar al-Minan al-Kubra. Zahirah al-„Uqba is a contemporary study of Sunan al-Nasa‟i which is difficult to find nowadays. In order to produce this study, the author studied the hadiths with the utmost care. The uniqueness of this analysis is its thoroughness, introducing readers to the hadiths and the problems contained in Sunan al-Nasa‟i. The author was consistent with the method applied in the study. The author also referred to the study by al-Shanqiti that was written before Zahirah al‟Uqba. However, the author added a few points such as lataif al-isnad besides focusing on the differences between Sunan al-Nasa‟i and the original writing, al-Sunan al-Kubra. Results of the study show that the author focused on the academic issues contained in the writings without being influenced by the source of the various opinions. Harsh criticisms and insults towards other scholars are nowhere to be found in this work. Instead, the author shows respect to scholars who provided insight, as every student should do
The exegesis of Tabatabaei and the Hermeneutics of Hirsch: a comparative study
No full textThis thesis is a comparative study between Hermeneutics on the one hand and exegesis of the Holy Qur'an on the other. Its objective is to discover whether there are salient points of convergence between the two disciples, and whether issues germane to the Hermeneutical tradition in the West have been referred to and/or employed in Muslim works of Qur'an commentary. To this end, the works of one of the most prominent Shi'ite philosophers and exegetes. Allama Mohammad Hossein Tabataei, have been analysed and compared with the perspective and methodology of E D. Hirsch, one of the most important hermeneuticians in the Western World. Hirsch has been chosen since, in the opinion of the author, there is a considerable number of commonalities between the Hirschian approach to hermeneutics and the exegetical methodology of Tabatabaei and other Shi'ite Muslim interpreters of the Qur'an.. Hirsch, as an objectivist, along with a number of other Hermeneutical scholars, are critical of those who subscribe to philosophical Hermeneutics, such as Heideger and Gadimer. The same approach is taken in Tabatabaei's works, thus providing a strong rationale for an academic comparison of these two scholars. For this reason, this thesis attempts to study the theories of Tabatabaei and Hirsch in order to highlight the similarities and differences in their works. The central hypothesis is that while small differences in approach exist, there is much common ground, and that it is possible to use certain facets of Hirschian hermeneutics in the interpretation of the Qur'an, thus modernising some of the existing exegetical approaches employed by Shi'ite scholars.Since the aim of this thesis is to compare the interpretive works of Tabatabaei with those of Hirsch's, an introductory chapter has been dedicated to the study of the evolution of Shi'ite exegesis from the beginning to date. Tabatabaei's Al-Mizan has been chosen as the foremost work of Shi'ite exegesis in the modem period. Furthermore, a complete chapter has also been dedicated to Tabatabai's exegetical modus operandi as reflected in Al-Mizan, in order to arrive at a better understanding of his perspectives. This research arrives at the conclusion that philosophical Hermeneutics and Epistemology have opened new horizons on which we will always be dependent. Whatever interpretive theories with regards to the understanding of the text are accepted, or whatever the tendency as far as literary criticism is concerned, or whatever ideas are accepted in the arena of philosophy of human and social sciences, the discussion of the nature of understanding in general cannot be avoided. This does not mean that Hermeneutics is limited to these new theories. Rather, the opportunity always exists to introduce new interpretive theories in connection with the understanding of the text. It is indeed possible to study these discussions in detail in a separate sphere independent of the other branches of Islamic sciences and arrive at a number of stable principles in the interpretation of the text in Islamic research
Traditions and the Hero Personality Construction (Things Fall Apart as Amodel)
No full textThis paper represents a first attempt to study traditions and the personality construction of the hero in writing the novel. Philosophy of writing novels makes clear that a complete understanding of the novel requires data on both film and writing. Previous empirical work has dealt with the transfer of resources between the hero and the novel, either using data on the novel, or with data solely obtained from the hero. Using a novel things fall apart as a model, I study two types of novels: transfers to the author and the hero towards the personalit
Population aging and the labor market : the case of Sri Lanka
No full textSri Lanka's population is predicted to age vary fast during the next 50 years, bringing a slowdown of labor force growth and after 2030its contraction. Based on a 2006 representative survey of old people in Sri Lanka, the paper examines labor market consequences of this process, focusing on retirement pathways and the determinants of labor market withdrawal. The paper finds that a vast majority of Sri Lankan old workers are engaged in the informal sector, work long hours, and are paid less than younger workers. Moreover, the paper shows that labor market duality carries over to old age: (i) previous employment is the most important predictor of the retirement pathway; (ii) older workers fall into two categories: civil servants and formal private sector workers, who generally stop working before they reach 60 because they are forced to do so by mandatory retirement regulations, and casual workers and the self-employed, who work until very old age (or death) due to poverty and insufficient income and who stop working primarily because of poor health; and (iii) the option of part-time work is used primarily by workers who held regular jobs in their prime age employment, but not by casual workers and self-employed.Labor Markets,Health Monitoring&Evaluation,Labor Policies,Work&Working Conditions,
New, Valid, and Reliable Indonesian Version of the Quality of Life Assessment Instrument Based On the Health Condition: Health-Related Quality of Life With Six Dimensions
No full textHealth-related quality of life is very important to be measured as the parts of Patient-Reported Outcome (PRO). PRO can show the disease proression and also may influence the clinical decision making. There are many QoL instruments available in Indonesia as generic and specific instruments, however, there is no QoL instrument which measured the respondents’ functions based on the health status. This study is aimed to translate, adapt and validate the new QoL instrument based on the health condition, namely HRQ-6D (Health Related Quality of Life, 6 Dimensions). We conducted forward and backward translations. The subjects were people who lived in Yogyakarta city with aged more than 18 years old, and agreed to participate in this study. While the exclusion criteria were patients whose questionnaire data were incomplete. We shared the questionnaire to the area of Yogyakarta from September to October 2023. We used Pearson correlation, Cronbach alpha reliability test and Student T-test for the validity and reliability assessment. We recruited 69 respondents with mostly female (60.9%) and the age is more than 60 yo (80.9%). Based on the health condition, more than fifty percent of the subjects (59.4%) were in Category 1, which considered as healthy, and only one subject were having more than one disease and have been hospitalized more than three times due to the disease or the complications (Category 4). The reliability test showed the Cronbach alpha value between 0.60-0.75. And all of the items in the questionnaire met the convergent and discriminant validity. TheHRQ-6D can be implemented as the new Bahasa Version of QoL instrument, supported with the validity and reliability assessment
The portability of pension rights : general principals and the Caribbean case
No full textThe portability of pension rights is an increasingly important issue in the Caribbean. The large and increasing flows of migrant workers, including both permanent and temporary migrants, the small size of the domestic economies and the process of regional integration and economic openness call for effective means to make pensions portable. This document presents a select survey of the literature on pension portability and reviews the progress made by the Caribbean countries as well as some remaining challenges in the light of the international experience.Pensions&Retirement Systems,Debt Markets,Emerging Markets,Gender and Law,Labor Markets
Specific and selective target detection of supra-genome 21 Mers Salmonella via silicon nanowires biosensor
No full textFighting HIV/AIDS: Reconfiguring the State?
No full textThe author wishes to thank the anonymous reviewers of the article and the ESRC for funding part of this research
Sistem Rekognisi Citra Digital Bahasa Isyarat Menggunakan Convolutional Neural Network Dan Spatial Transformer
No full textBahasa isyarat merupakan hal yang sangat penting bagi suatu kelompok masyarakat, yaitu masyarakat bisu atau tuli. Untuk dapat berkomunikasi dengan masyarakat bisu atau tuli, orang yang tidak bisu atau tuli memerlukan bahasa isyarat tersebut untuk dapat mengerti maksud atau pikiran mereka yang bisu atau tuli. Sebagian besar percakapan pada bahasa isyarat dilakukan dengan menggunakan tangan, dimana tangan beserta jari-jarinya digunakan untuk membentuk pose atau bentuk yang unik, sehingga dapat dikenali sebagai maksud tertentu. Penulis mengusulkan dikembangkan sistem rekognisi citra digital untuk dapat mengenali bahasa isyarat tersebut. Dengan menggunakan metode Convolutional Neural Network (CNN) yang merupakan bagian dari Deep Learning atau Machine Learning, sistem akan mengenali pose atau bentuk dari citra bahasa isyarat yang dimasukkan, dan memberikan luaran yang sesuai dengan maksud dari pose atau bentuk dari citra bahasa isyarat tersebut. Penelitian ini dimulai dengan pengumpulan data, baik data sekunder dari internet maupun data pribadi yang diambil secara manual. Data kemudian melalui pemrosesan awal dan diklasifikasikan dengan CNN, lalu didapatkan hasil untuk dianalisis. Apabila hasil memuaskan, model akan diekspor untuk dimasukkan ke dalam aplikasi berbasis web untuk digunakan secara real-time. Berdasarkan hasil pengujian, model yang terbaik untuk arsitektur adalah model EfficientNet B4 dengan menggunakan Hyperparameter optimizer Adam dan learning rate 0.001 beserta scheduler. Digunakan pretrained weights untuk meningkatkan akurasi tersebut, dan ditambahkan Spatial transformer untuk mencoba membuat model menjadi lebih kokoh. Ditambah dengan pretrained weights, model diekspor untuk digunakan secara real-time. Hasil pengujian real-time menunjukkan bahwa model mampu mendeteksi setidaknya 23 dari 26 alfabet pada latar belakang yang abstrak. Apabila diuji pada latar belakang polos seperti hitam atau putih, model mampu mendeteksi seluruh 26 alfabet dengan probabilitas yang hampir sempurna. Hal ini menunjukkan bahwa metode yang digunakan sudah mampu mengatasi masalah yang disampaikan.
Abstract
Sign language is very important for a group of people, namely the deaf or dumb. To be able to communicate with people who are mute or deaf, people who are not mute or deaf require sign language to be able to understand the intentions or thoughts of those who are mute or deaf. Most conversations in sign language are carried out using the hands, where the hands and their fingers are used to form unique poses or shapes, so that they can be recognized as having certain meanings. The author proposes to develop a digital image recognition system to be able to recognize sign language. By using the Convolutional Neural Network (CNN) method which is part of Deep Learning or Machine Learning, the system will recognize the pose or shape of the entered sign language image, and provide output that matches the meaning of the pose or shape of the sign language image. This research began with data collection, both secondary data from the internet and personal data taken manually. The data then goes through initial processing and is classified with CNN, then results are obtained for analysis. If the results are satisfactory, the model will be exported to be included in a web-based application for use in real-time. Based on the test results, the best model for the architecture is the EfficientNet B4 model with the Hyperparameter consisting of optimizer Adam and learning rate 0.001 along with the scheduler. Pretrained weights were used to improve accuracy, and Spatial transformers were added to try to make the model more robust. Coupled with pretrained weights, the model is exported for use in real-time. Real-time test results show that the model is able to detect at least 23 of the 26 alphabets on an abstract background. When tested on a plain background such as black or white, the model was able to detect all 26 alphabets with almost perfect probability. This shows that the method used is able to overcome the problem presented.Bahasa isyarat merupakan hal yang sangat penting bagi suatu kelompok masyarakat, yaitu masyarakat bisu atau tuli. Untuk dapat berkomunikasi dengan masyarakat bisu atau tuli, orang yang tidak bisu atau tuli memerlukan bahasa isyarat tersebut untuk dapat mengerti maksud atau pikiran mereka yang bisu atau tuli. Sebagian besar percakapan pada bahasa isyarat dilakukan dengan menggunakan tangan, dimana tangan beserta jari-jarinya digunakan untuk membentuk pose atau bentuk yang unik, sehingga dapat dikenali sebagai maksud tertentu. Penulis mengusulkan dikembangkan sistem rekognisi citra digital untuk dapat mengenali bahasa isyarat tersebut. Dengan menggunakan metode Convolutional Neural Network (CNN) yang merupakan bagian dari Deep Learning atau Machine Learning, sistem akan mengenali pose atau bentuk dari citra bahasa isyarat yang dimasukkan, dan memberikan luaran yang sesuai dengan maksud dari pose atau bentuk dari citra bahasa isyarat tersebut. Penelitian ini dimulai dengan pengumpulan data, baik data sekunder dari internet maupun data pribadi yang diambil secara manual. Data kemudian melalui pemrosesan awal dan diklasifikasikan dengan CNN, lalu didapatkan hasil untuk dianalisis. Apabila hasil memuaskan, model akan diekspor untuk dimasukkan ke dalam aplikasi berbasis web untuk digunakan secara real-time. Berdasarkan hasil pengujian, model yang terbaik untuk arsitektur adalah model EfficientNet B4 dengan menggunakan Hyperparameter optimizer Adam dan learning rate 0.001 beserta scheduler. Digunakan pretrained weights untuk meningkatkan akurasi tersebut, dan ditambahkan Spatial transformer untuk mencoba membuat model menjadi lebih kokoh. Ditambah dengan pretrained weights, model diekspor untuk digunakan secara real-time. Hasil pengujian real-time menunjukkan bahwa model mampu mendeteksi setidaknya 23 dari 26 alfabet pada latar belakang yang abstrak. Apabila diuji pada latar belakang polos seperti hitam atau putih, model mampu mendeteksi seluruh 26 alfabet dengan probabilitas yang hampir sempurna. Hal ini menunjukkan bahwa metode yang digunakan sudah mampu mengatasi masalah yang disampaikan.
Abstract
Sign language is very important for a group of people, namely the deaf or dumb. To be able to communicate with people who are mute or deaf, people who are not mute or deaf require sign language to be able to understand the intentions or thoughts of those who are mute or deaf. Most conversations in sign language are carried out using the hands, where the hands and their fingers are used to form unique poses or shapes, so that they can be recognized as having certain meanings. The author proposes to develop a digital image recognition system to be able to recognize sign language. By using the Convolutional Neural Network (CNN) method which is part of Deep Learning or Machine Learning, the system will recognize the pose or shape of the entered sign language image, and provide output that matches the meaning of the pose or shape of the sign language image. This research began with data collection, both secondary data from the internet and personal data taken manually. The data then goes through initial processing and is classified with CNN, then results are obtained for analysis. If the results are satisfactory, the model will be exported to be included in a web-based application for use in real-time. Based on the test results, the best model for the architecture is the EfficientNet B4 model with the Hyperparameter consisting of optimizer Adam and learning rate 0.001 along with the scheduler. Pretrained weights were used to improve accuracy, and Spatial transformers were added to try to make the model more robust. Coupled with pretrained weights, the model is exported for use in real-time. Real-time test results show that the model is able to detect at least 23 of the 26 alphabets on an abstract background. When tested on a plain background such as black or white, the model was able to detect all 26 alphabets with almost perfect probability. This shows that the method used is able to overcome the problem presented
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