Towards a Bilingual Binational Translation Method: The Amputated Tongue Collection of Short Stories as a Sample

Translators and writers are divided into two main groups regarding the method of translation that should be adopted in translating texts. One group believes that the translator should be true to the translated text, while the other group believes that the translator has the right to recreate the text into a more beautiful one. This study deals with this issue from these two points of view and tries to answer the following questions: Why do we translate? What should we translate? How do we translate? The study relies on an innovative translation method developed by the Board of Maktoub Project for Translation that belongs to Van Leer Institute in Jerusalem to answer these questions. A group of about one hundred Arab and Jewish translators translated Arabic literature texts into Hebrew in an internationally new method, which is neither individual nor collective. It is a bilingual binational method. The translators consist of pairs of a Jewish or/and Arab translator, an Arab/or Jewish literary editor, and a linguistic editor, believing that translation is a text and culture, heritage, and traditions of a people or nation. This dual method gave the translated text its right of accuracy after it had been translated by one translator who can make mistakes due to his ignorance of the writer's culture. The study's conclusion confirms that bilingual binational translation is more fruitful and more accurate because it is based on dialogue, bilingual, and binational cultural knowledge.

On the Primal-Dual Method of Multipliers and its Applications

<p>With ever growing sources of digital data and the reductions in cost of small-scale wireless processing nodes, equipped with various sensors, microprocessors, and communication systems, we are seeing an increasing need for efficient distributed processing algorithms and techniques. This thesis focuses on the Primal-Dual Method of Multipliers (PDMM) as it applies to wireless sensor networks, and develops new algorithms based on PDMM more appropriate for the limitations on processing power, battery life, and memory that these devices suffer from. We develop FS-PDMM and QA-PDMM that greatly improve the efficiency of local node computations when dealing with regularized optimization problems and smooth cost function optimization problems, respectively. We combine these approaches to form the FSQA-PDMM algorithm that may be applied to problems with smooth cost functions and non-smooth regularization functions. Additionally, these three methods often eliminate the need for numerical optimization packages, reducing the memory cost on our nodes. We present the FT-PDMM algorithm for finite-time convergence of quadratic consensus problems, reducing the number of in-network iterations required for network convergence. Finally, we present two signal processing applications that benefit from our theoretical work: a distributed sparse near-field acoustic beamformer; and a distributed image fusion algorithm for use in imaging arrays. Simulated experiments confirm the benefit of our approaches, and demonstrate the computational gains to be made by tailoring our techniques towards sensor networks.</p>

On the Primal-Dual Method of Multipliers and its Applications

<p>With ever growing sources of digital data and the reductions in cost of small-scale wireless processing nodes, equipped with various sensors, microprocessors, and communication systems, we are seeing an increasing need for efficient distributed processing algorithms and techniques. This thesis focuses on the Primal-Dual Method of Multipliers (PDMM) as it applies to wireless sensor networks, and develops new algorithms based on PDMM more appropriate for the limitations on processing power, battery life, and memory that these devices suffer from. We develop FS-PDMM and QA-PDMM that greatly improve the efficiency of local node computations when dealing with regularized optimization problems and smooth cost function optimization problems, respectively. We combine these approaches to form the FSQA-PDMM algorithm that may be applied to problems with smooth cost functions and non-smooth regularization functions. Additionally, these three methods often eliminate the need for numerical optimization packages, reducing the memory cost on our nodes. We present the FT-PDMM algorithm for finite-time convergence of quadratic consensus problems, reducing the number of in-network iterations required for network convergence. Finally, we present two signal processing applications that benefit from our theoretical work: a distributed sparse near-field acoustic beamformer; and a distributed image fusion algorithm for use in imaging arrays. Simulated experiments confirm the benefit of our approaches, and demonstrate the computational gains to be made by tailoring our techniques towards sensor networks.</p>

Proposal of the Dichotomous STATIS DUAL Method: Software and Application for the Analysis of Dichotomous Data, Applied to the Test of Learning Styles in University Students

The present work analyzed a review of methods for analyzing sequences of matrices or dichotomous data. A new method for a sequence of dichotomous matrices with a different number of rows is presented; the Dichotomous STATIS DUAL. Suppose we match the sequence of matrices by different years, with this method. In that case, we can graphically represent the relations among the different columns of all the matrices, and the relations between those columns and the different years, because everything can be represented in the same plots. As in all STATIS methods, three different plots can get: (i) the interstructure, with the relations among the years; (ii) the compromise, with the stable part of the relations between the columns; and (iii) the intrastructure (also known as trajectories), with the relations between columns and years, in other words, the evolution of the columns through the time. This new mathematical method can be used with all kinds of dichotomous data, thanks to the software we propose. In the present work, the software was applied to the assessment of learning styles.

Deciphering Impacts and Human Responses to a Changing Climate in East Africa

Climate-related human mobility (climate mobilities) is often portrayed as a key impact of human-induced climate change. Yet, causal, quantitative evidence on this link remains limited and suffers from disciplinary hurdles. One reason for this is that existing case studies do not incorporate insights from climate science methods and pay little attention to contextual factors in climate mobilities. We use a dual-method approach to categorise and classify. By combining a qualitative case study analysis with statistical approaches from topic modelling in an innovative dual-method framework, we show current empirical evidence on weather and climate-related impacts and human mobility in East Africa, an alleged hot-spot of climate change. We find that although climate change is referred to, implicitly and explicitly, as a tipping point for human mobility, studies imply a causal link between human mobility and climate change while under or misrepresenting evidence in climate science. A map of evidence allows studies to be matched with human mobility types and contextual factors influencing such mobilities in a changing climate with a novel and more ambitious form of synthesis, carving out the multi-causal nature of human mobility. Our findings show that climatic influences on human mobility are not independent. Rather, climate factors influencing human mobility are closely connected with contextual factors such as social norms, economic opportunities, and conflict. The findings suggest that there is currently low confidence in a climate change-human mobility nexus for East Africa. As a way forward, we propose emerging methods to systematically research causal links between climate mobilities and anthropogenic climate change globally.

Positive deviance for promoting dual-method contraceptive use among women in Uganda: a cluster randomised controlled trial

ObjectiveTo examine the effects of a positive deviance intervention on dual-method contraceptive use among married or in-union women.DesignOpen-label cluster randomised controlled trial.Setting20 health facilities in Mbarara District, Uganda.Participants960 married or in-union women aged 18–49 years using a non-barrier modern contraceptive method.InterventionsA combination of clinic-based and telephone-based counselling and a 1-day participatory workshop, which were developed based on a preliminary qualitative study of women practising dual-method contraception.Primary outcome measureDual-method contraceptive use at the last sexual intercourse and its consistent use in the 2 months prior to each follow-up. These outcomes were measured based on participants’ self-reports, and the effect of intervention was assessed using a mixed-effects logistic regression model.ResultsMore women in the intervention group used dual-method contraception at the last sexual intercourse at 2 months (adjusted OR (AOR)=4.12; 95% CI 2.02 to 8.39) and 8 months (AOR=2.16; 95% CI 1.06 to 4.41) than in the control group. At 4 and 6 months, however, the proportion of dual-method contraceptive users was not significantly different between the two groups. Its consistent use was more prevalent in the intervention group than in the control group at 2 months (AOR=14.53; 95% CI 3.63 to 58.13), and this intervention effect lasted throughout the follow-up period.ConclusionsThe positive deviance intervention increased dual-method contraceptive use among women, and could be effective at reducing the dual risk of unintended pregnancies and HIV infections. This study demonstrated that the intervention targeting only women can change behaviours of couples to practise dual-method contraception. Because women using non-barrier modern contraceptives may be more reachable than men, interventions targeting such women should be recommended.Trial registration numberUMIN000037065.