Translation Recognition in Learners of Arabic

The current study explored the role of phonology in the processing of Arabic words in native English speakers learning Arabic. Previous research demonstrates that three factors play a role in the mental processing of multiple languages: orthography, phonology, and semantics. Cognate studies have revealed that orthography is not the most important factor, but the roles of phonology and semantics are still indistinguishable from one another. The current study utilized phonologically-embedded English words within Arabic words at three different points in the word, beginning, middle, and end, to determine the role of phonology separate from that of semantics (e.g., [written Arabic] pronounced tareekh, and tar is a beginning overlap pair). Participants from the University of Arkansas Arabic language program completed a translation recognition task. They were shown an Arabic word, followed by an English word, and asked to identify whether the English word was the correct translation. It was predicted that participants would take longer to say “no” to false translations with phonological overlap than to false translations without phonological overlap and that less experienced learners would exhibit this effect to a higher degree than more experienced learners. While, as predicted, the reaction times for false translations with phonological overlap were substantially slower than reaction times for false translations without phonological overlap in beginning and middle overlap conditions, no significant differences were found. Arabic proficiency was found to be negatively correlated with amount of phonological interference. The results generally support the importance of phonology in the mental processing of multiple languages, which can be combined with other findings in language research to supplement language learning programs

Trump and U.S. Immigration Policies. Lessons from the Eisenhower Administration

While U.S. immigration entry policies after 1953 became a hallmark of ideological openness, designating the United States as the unquestioned leader of a freer and more just world order, Donald Trump’s current immigration strategies isolate America, damage her economy, and fuel divisive feelings among citizens. This paper hopes to persuade the Republican Party not to revert to its pre-1953 restrictionist and nativist stance, thereby undoing the crucial work undertaken by the Eisenhower Administration. The author argues that a sound grasp of the debate that led to the approval of the Refugee Relief Act in 1953 can lead to better informed political decision-making, tracing a new phase of America’s active presence on the world stage, in line with the country’s national interest and Cold war tradition

From the Middle East to the Midwest: the Transition Experiences of Saudi Female International Students at a Midwest University Campus

This study explored the essence of the transition experiences of 10 female international students when they made the decision to study and live in the U.S. through their third semester in college. The main research question that framed this study was: How do Saudi female international students navigate their transitional experiences to study and live during their first two academic years in an urban Midwest university? Most research about international students does not account for their national, religious, cultural, and linguistic differences. Much of this previous research focuses on the students’ academic challenges and language barriers and non-academic challenges such as acculturation difficulties, alienation, and discrimination. The few studies that have addressed the specific experiences of Saudi female international students emphasized the social and academic challenges they encountered in the U.S. Because Saudi female students come from a segregated culture where historic and current conditions for women leave them without many human rights in Saudi Arabia, I sought to understand their experiences in a U.S. university from their own perspectives. Schlossberg’s (1983) transition theory provided the theoretical foundation for understanding how Saudi female sophomore students progressed through moving in to a Midwestern university in the U.S., moving through their first year, and moving on to their second year of study at the university. Phenomenological inquiry approach was implemented to understand the essence of the 10 Saudi sophomores lived experiences. In-depth individual interviews followed by a focus interview with four of the participants elicited their reflections about their transition experiences evolved over time and the coping resources they employed to facilitate their transition. Data analysis proceeded across five time periods starting from Time One, when they Saudi females made the decision to study and live in the U.S. Time Two, addressed their first semester in the U.S and Time Three addressed their experiences in the second semester of their freshman year. Time Four encompassed the transition experiences of six of the participants who visited Saudi Arabia in summer, and Time Five addressed their transition experiences during the first semester of their sophomore year. Data analysis within each time period used the four Ss, of transition theory (Schlossberg, 1983): situation, support, self, and strategies, to understand the Saudi females own perspectives about their transitions over time. Five main findings emerged from the data analysis: 1. Saudi females who participated in this study described primarily positive feelings about their experiences during the five stages of their transition to live and study in the U.S. 2. There was a strong relationship between the support these participants received from their fathers and their initial and emerging self- confidence. 3. Although they enjoyed life in the U.S., almost all Saudi females expressed their desire to go back to Saudi Arabia upon graduation to create positive changes in their home county. 4. The interrelationship between the four coping resources, situation, support, self, and strategies, fostered the emergence of self as a primary asset for all the participants. 5. Because of the inadequate campus support they received during their first academic year, these Saudi female students began to find ways to gain support from other resources during their second year. This study also suggested four implications for practice and two implications for future research: 1. Because campus support for international students is inadequate, their services should be improved. 2. The English language support program that is expected to prepare international students linguistically and academically for college life needs to be improved to enable them to do college level work in English. 3. As Saudi students were not fully aware of the education system on U.S. campuses, a one credit course on college study skills would enhance their academic preparation for academic programs. 4. Fostering cultural awareness among domestic students would be through holding cultural events on campus. These events would break the ice between both domestic and international students that would foster healthy campus climate. Future research should address the following two issues: 1. The transition experiences of Saudi female students when they go back to their home country upon completion of their academic programs should be explored to improve understanding of the repatriate experience life in Saudi Arabia. 2. More research is needed on American students’ perceptions of international students, particularly Muslim students

Driver Drowsiness Detection Using Gray Wolf Optimizer Based on Face and Eye Tracking

It is critical today to provide safe and collision-free transport. As a result, identifying the driver’s drowsiness before their capacity to drive is jeopardized. An automated hybrid drowsiness classification method that incorporates the artificial neural network (ANN) and the gray wolf optimizer (GWO) is presented to discriminate human drowsiness and fatigue for this aim. The proposed method is evaluated in alert and sleep-deprived settings on the driver drowsiness detection of video dataset from the National Tsing Hua University Computer Vision Lab. The video was subjected to various video and image processing techniques to detect the drivers’ eye condition. Four features of the eye were extracted to determine the condition of drowsiness, the percentage of eyelid closure (PERCLOS), blink frequency, maximum closure duration of the eyes, and eye aspect ratio (ARE). These parameters were then integrated into an ANN and combined with the proposed method (gray wolf optimizer with ANN [GWOANN]) for drowsiness classification. The accuracy of these models was calculated, and the results demonstrate that the proposed method is the best. An Adadelta optimizer with 3 and 4 hidden layer networks of (13, 9, 7, and 5) and (200, 150, 100, 50, and 25) neurons was utilized. The GWOANN technique had 91.18% and 97.06% accuracy, whereas the ANN model had 82.35% and 86.76%

Driver Drowsiness Detection Using Gray Wolf Optimizer Based on Voice Recognition

Globally, drowsiness detection prevents accidents. Blood biochemicals, brain impulses, etc., can measure tiredness. However, due to user discomfort, these approaches are challenging to implement. This article describes a voice-based drowsiness detection system and shows how to detect driver fatigue before it hampers driving. A neural network and Gray Wolf Optimizer are used to classify sleepiness automatically. The recommended approach is evaluated in alert and sleep-deprived states on the driver tiredness detection voice real dataset. The approach used in speech recognition is mel-frequency cepstral coefficients (MFCCs) and linear prediction coefficients (LPCs). The SVM algorithm has the lowest accuracy (71.8%) compared to the typical neural network. GWOANN employs 13-9-7-5 and 30-20-13-7 neurons in hidden layers, where the GWOANN technique had 86.96% and 90.05% accuracy, respectively, whereas the ANN model achieved 82.50% and 85.27% accuracy, respectively

Filosofia e politica nel conservatorismo statunitense del novecento. Eredità storico-concettuali

The U.S. Republican Party has always consisted of of different elements, which belong to deep and diverse historical and cultural tradition. Throughout the twentieth century, these currents within the Grand Old Party worked sometimes separately, albeit more often in mutual agreement, united by the need to oppose a federal overreach domestically, and the threat of totalitarianism abroad. This paper analyzes the birth and evolution of the various strands of thought which constitute the conservative front today. Their philisophies came into being through the spread of a new, entrepreneurial middle class in the Thirties and grew stronger with the support of the common people from the East Coast during the economic boom in the early Fifties. Such process culminated in the nomination of Barry Goldwater as the GOP Presidential candidate in 1964. Goldwater embodied those features that still distinguish the American conservatism today: a limited government, the free market, individual freedom coupled with personal responsibility, a strong national defense and the appeal to traditional American values

Classification of Different Shoulder Girdle Motions for Prosthesis Control Using a Time-Domain Feature Extraction Technique

Abstract—The upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patients’ quality of life can be improved if they have natural control over their prosthetic hands. Among the biological signals, most commonly used to predict upper limb motor intentions, surface electromyography (sEMG), and axial acceleration sensor signals are essential components of shoulder-level upper limb prosthetic hand control systems. In this work, a pattern recognition system is proposed to create a plan for categorizing high-level upper limb prostheses in seven various types of shoulder girdle motions. Thus, combining seven feature groups, which are root mean square, four-order autoregressive, wavelength, slope sign change, zero crossing (ZC), mean absolute value, and cardinality. In this article, the time-domain features were first extracted from the EMG and acceleration signals. Then, the spectral regression (SR) and principal component analysis dimensionality reduction methods are employed to identify the most salient features, which are then passed to the linear discriminant analysis (LDA) classifier. EMG and axial acceleration signal datasets from six intact-limbed and four amputee participants exhibited an average classification error of 15.68 % based on SR dimensionality reduction using the LDA classifier