Instruction Word Research Articles

Learning Chinese as a Second Language: Implications of the Character-Word Dual Function Model

Learning new words is fundamental in both first and second-language reading. There are, however, divided opinions on the best instructional approaches. Two widely used approaches across languages are whole-word focus and word-constituent focus. The appropriateness of each approach has varied historically, even within a single language (e.g., the debate between whole-word instruction and phonics in English). In teaching Chinese, both approaches are applied but to different learner groups. Whole-word instruction predominates in teaching Chinese as a second language (L2), while instruction for Chinese children focuses more on character-level mappings. It may seem reasonable in L2 Chinese instructions to focus on direct mappings between Chinese words and their L1 equivalent words. However, this raises a question: Is whole-word instruction the most efficient approach in L2 Chinese instruction? Based on an analysis of the Chinese writing system, we proposed a Character-Word Dual Function model of Chinese and tested its application of a dual-focus approach on both characters and words in L2 Chinese classroom instruction. Empirical findings support the advantage of this new approach compared to conventional whole-word instruction. We discuss the alignment between our findings and the Unified Computational Model and its implications for word instruction across languages.

Exploring the Potential of Code-Free Custom GPTs in Ophthalmology: An Early Analysis of GPT Store and User-Creator Guidance.

OpenAI recently introduced the ability to create custom generative pre-trained transformers (cGPTs) using text-based instruction and/or external documents using retrieval-augmented generation (RAG) architecture without coding knowledge. This study aimed to analyze the features of ophthalmology-related cGPTs and explore their potential utilities. Data collection took place on January 20 and 21, 2024, and custom GPTs were found by entering ophthalmology keywords into the "Explore GPTS" section of the website. General and specific features of cGPTs were recorded, such as knowledge other than GPT-4 training data. The instruction and description sections were analyzed for compatibility using the Likert scale. We analyzed two custom GPTs with the highest Likert score in detail. We attempted to create a convincingly presented yet potentially harmful cGPT to test safety features. We analyzed 22 ophthalmic cGPTs, of which 55% were for general use and the most common subspecialty was glaucoma (18%). Over half (55%) contained knowledge other than GPT-4 training data. The representation of the instructions through the description was between "Moderately representative" and "Very representative" with a median Likert score of 3.5 (IQR 3.0-4.0). The instruction word count was significantly associated with Likert scores (P = 0.03). Tested cGPTs demonstrated potential for specific conversational tone, information, retrieval and combining knowledge from an uploaded source. With these safety settings, creating a malicious GPT was possible. This is the first study to our knowledge to examine the GPT store for a medical field. Our findings suggest that these cGPTs can be immediately implemented in practice and may offer more targeted and effective solutions compared to the standard GPT-4. However, further research is necessary to evaluate their capabilities and limitations comprehensively. The safety features currently appear to be rather limited. It may be helpful for the user to review the instruction section before using a cGPT.

Using dialogic reading and direct instruction of emotion words to increase emotion vocabulary knowledge in the preschool classroom

PurposeThis research addresses a need in early childhood education for evidence-based teaching strategies that build emotional self-regulation skills in young children. The intervention assessed in this study focused on increasing the emotion vocabulary of preschool-aged students.Design/methodology/approachThis mixed-methods, quasi-experimental study evaluated the impact a dialogic reading approach combined with direct instruction of emotion words during a shared book-reading activity had on students' emotion vocabulary knowledge. The study was conducted in a licensed daycare center in a suburb of Chicago, Illinois, with ten four- and five-year-old students. Pre- and post-session surveys assessed the intervention's impact on the students' receptive and expressive vocabulary knowledge, and observation notes captured the students' responses to the intervention activities.FindingsThe results showed significant increases with small to medium effect sizes between the students’ pre- and post-session survey scores for both receptive and expressive emotion vocabulary knowledge, a strong positive correlation between the level of student engagement during the intervention and their emotion vocabulary assessment scores, and the impact other variables had on the intervention’s effectiveness.Practical implicationsThis research provides information on a culturally adaptable and quickly learned teaching strategy that could be used to build emotional self-regulation skills in the early childhood classroom.Originality/valueThis research uniquely applies this intervention as a universal strategy with preschool-aged children.

Who Knows the Answer? Finding the Best Model and Prompt for Each Query Using Confidence-Based Search

There are increasingly many large language models (LLMs) available to the public. While these LLMs have exhibited impressive abilities on a variety of task, any individual LLM in particular may do well on some tasks and worse on others. Additionally, the performance of these models is heavily dependent on the choice of prompt template used. For instance, they exhibit sensitivity to the few shot examples chosen or brittleness to the wording of instructions. Moreover, a prompt template that makes a model perform well for one input may not be the optimal template for another input. This necessitates an approach for adaptively selecting LLM and prompt template pairs for each input. Recent work has shown that the accuracy of LLM's responses is correlated with the LLM's confidence in the response. Thus, a natural choice for selecting which model and prompt template to use is to select the pair that is most confident in its response. However, existing confidence metrics are expensive to calculate - necessitating multiple calls to each LLm and prompt pair. We thus propose an approach to predict the confidence of each pair using an auxiliary regression model that is inexpensive to run. Using this auxiliary model, we select the LLM and prompt template with the highest predicted confidence for a given input. Results on a range of benchmark datasets show that our confidence-based instance-level prompt search method consistently improves the performance of LLMs.

Wireless vision-based digital media fixed-point DSP processor depending robots for natural calamities

AbstractNatural calamities are affecting many parts of the world. Natural disasters, terrorist attacks, earthquakes, wildfires, floods and all unpredicted phenomena. Disasters cause emergency conditions, so imperative to coordinate the prompt delivery of essential services to the sufferers. Often, disasters lead many people to perish by becoming trapped inside, but many more also perish as a result of individuals receiving rescue either too late or not at all. The implementation and design of a Receiver module utilizing Davinci code processor DVM6437, Wireless camera receiver, Zigbee Transceiver and Global Positioning System (GPS) is proposed in this manuscript for Wireless Vision-based Semi-Autonomous rescue robots that are employed in rough terrain. The receiver side’s Zigbee transceiver module eliminates the limitations of tele-operating rescue robots by enabling the control station to receive GPS data signals and aids in robot management by sending control signals wirelessly. Half and full-duplex communication are supported by the Davinci processor DVM6437, a digital media fixed-point DSP processor that relies on Very Long Instruction Words. It includes an extensive instruction set that is ideal for real-time salvage operations. DVM processor is coded utilizing MATLAB Simulink. MATLAB codes and Simulink blocks are employed under Embedded IDE link.

Optimizing VLIW Instruction Scheduling via a Two-Dimensional Constrained Dynamic Programming

Typical embedded processors, such as Digital Signal Processors (DSPs), usually adopt Very Long Instruction Word (VLIW) architecture to improve computing efficiency. The performance of VLIW processors heavily relies on Instruction-Level Parallelism (ILP). Therefore, it is crucial to develop an efficient instruction scheduling algorithm to explore more ILP. While heuristic algorithms are widely used in modern compilers due to simple implementation and low computational cost, they have limitations in providing accurate solutions and are prone to local optima. On the other hand, exact algorithms can usually find the optimal solution, but their high time overhead makes them less suitable for large-scale problems. This paper proposes a two-dimensional constrained dynamic programming (TDCDP) approach and a quantitative model for instruction scheduling. The TDCDP approach achieves near-optimal solutions within an acceptable time overhead. Furthermore, we integrate our TDCDP approach into mainstream compiler architecture, encompassing Pre- and Post-RA (register allocation) scheduling. We conduct a quantitative evaluation of TDCDP compared to four heuristic algorithms on a typical VLIW processor. Our approach achieves an efficiency improvement of up to 58.34% in final solutions compared to the heuristic algorithms. Additionally, the Post-RA Scheduling enhances programs with an average speedup of 14.04% than solely applying the Pre-RA Scheduling.

How police investigators seek to secure that suspects speaking a second language understand their rights in investigative interviews

ABSTRACT This study presents an empirical investigation of 54 police interviews in Norway conducted with suspects speaking Norwegian as a second language. Using Conversation Analysis as our method, we examine how investigators seek to ensure that suspects understand their rights. We find a range of practices for making rights more accessible compared to how they are formulated in legal acts. Investigators divide their turns into smaller segments and monitor the suspect for displays of understanding along the way. They simplify the syntax and substitute technical terms with plain vocabulary. Sometimes they supplement the wording of the prosecution instructions with explanations or reformulations. In a few instances, they also check understanding by asking a simple yes/no question. However, such questions only generate claims of understanding and no actual evidence of what has been understood. While there are isolated cases of requests to retell the rights, even these practices are problematic in generating strong evidence of understanding. This study discusses the importance of linguistic education and training in police forces for dealing with potential or emerging understanding problems during investigative interviews.

External Focus Affects Drop Jump Performance: Focusing on Different Aims and Words of Instruction.

Attentional focus strategies eliciting external focus of attention effectively enhance drop jump (DJ) performance, however, their effects vary depending on the words used for the instructions. We aimed to examine the effects of different words on DJ performance using instructions eliciting external focus to minimize contact time (CT) or maximize jump height (JH). Twenty collegiate athletes performed DJs from a 30-cm platform after receiving one of the four instructions: two instructions (COND 1 and 2) about minimizing CT, and two instructions (COND 3 and 4) about maximizing JH. The reactive strength index (RSI), CT, JH, relative peak vertical ground reaction force (vGRF), and leg stiffness (kvert) were compared between conditions using repeated-measures analysis of variance. There was no significant main effect of conditions on the RSI, relative peak vGRF, and kvert (p > 0.05). CT was significantly shorter under CONDs 1 and 2 than COND 3 (p < 0.05); JH was significantly higher under COND 3 than CONDs 1 and 2 (p < 0.05), and under COND 4 than COND 1 (p < 0.05). When using attentional focus strategies in DJ, it is necessary to use different words and purposes according to the players' tasks.

Development and content validity assessment of the Dry Eye Disease Questionnaire in patients with dry eye disease, meibomian gland dysfunction, and Sjögren’s syndrome dry eye disease

BackgroundDry eye disease (DED), Meibomian gland dysfunction (MGD), and Sjögren’s syndrome dry eye disease (SS-DED) are eye dryness conditions that show significant overlap in various symptoms of ocular discomfort. The aim of this study was to qualitatively explore the patient experience and evaluate content validity of the newly developed Dry Eye Disease Questionnaire (DED-Q).MethodsSemi-structured interviews were conducted with 61 US adults who reported experiencing ocular symptoms due to their physician-confirmed primary diagnosis of DED (n = 21), MGD (n = 20), or SS-DED (n = 20). The open-ended concept-elicitation phase was followed by cognitive debriefing (CD) of the DED-Q to evaluate participants’ understanding and relevance of the instructions, items, response options, and recall periods. Interviews were also conducted with eight specialist healthcare professionals to assess clinical relevance of the concepts included. Verbatim interview transcripts were analyzed using thematic analysis in ATLAS.ti v8 software.ResultsA total of 29 symptoms and 14 impacts on quality of life were reported across participant interviews. Primary ocular symptoms reported included eye dryness (n = 61/61; 100%), eye irritation (n = 55/61; 90%), eye itch (n = 54/61; 89%), burning sensation (n = 52/61; 85%), and foreign body sensation (n = 51/61; 84%). The most impacted aspects of daily life were using digital screens (n = 46/61; 75%), driving (n = 45/61; 74%), working (n = 39/61; 64%), and reading (n = 37/61; 61%). CD findings showed most participants had good understanding of DED-Q items and confirmed most concepts were relevant to the lived experience of their condition. Aside from few minor changes to the items and examples to facilitate more accurate interpretation, the proposed instruction wording was modified for various symptom and impact modules to encourage participants to focus only on dry eye vision problems.ConclusionsThis research identified multiple prevalent symptoms and impacts of DED, MGD, and SS-DED, most of which were similar across the conditions. The DED-Q was confirmed to be a content-valid PRO measure suitable for use in clinical studies to assess the patient experience of DED, MGD, and SS-DED. Future work will focus on evaluating the psychometric properties of the DED-Q for use as an efficacy endpoint in clinical trials.

Features of analysis and selection of microprocessors in modern control systems

The article discusses the results of a brief retrospective review of the current microprocessors in control systems and the main directions of their development. The main requirements and selection criteria presented at the stage of the microprocessor design process in modern control systems, classification and architectural features of microprocessors are described. In addition, the «pipeline» processing method for maximizing processor performance, features of the analysis and selection of microprocessors in modern control systems using various architectural solutions for the elimination of contradictions arising in it related to conflicts are studied. According to the «pipeline» principle, three main types of processor architecture (VLIW – Very Long Instruction Word) with superscalar and multiple computing devices working in parallel are defined - depending on data, management and structural conflicts. Therefore, their use in VLIW processors and the limitation of their application in the field of scientific research is justified, due to the fact that the source codes are transmitted in a «closed» form. The main advantage of superscalar microprocessors is the independence of program-executable codes from their structure and the possibility of their execution on any processor models. In addition, the features of the EPIC architecture are described, which combines the advantages of the two different architectural solutions considered.

Design of an Application-specific VLIW Vector Processor for ORB Feature Extraction

In computer-vision feature extraction algorithms, compressing the image into a sparse set of trackable keypoints, empowers navigation-critical systems such as Simultaneous Localization And Mapping (SLAM) in autonomous robots, and also other applications such as augmented reality and 3D reconstruction. Most of those applications are performed in battery-powered gadgets featuring in common a very stringent power-budget. Near-to-sensor computing of feature extraction algorithms allows for several design optimizations. First, the overall on-chip memory requirements can be lessened, and second, the internal data movement can be minimized. This work explores the usage of an Application Specific Instruction Set Processor (ASIP) dedicated to perform feature extraction in a real-time and energy-efficient manner. The ASIP features a Very Long Instruction Word (VLIW) architecture comprising one RV32I RISC-V and three vector slots. The on-chip memory sub-system implements parallel multi-bank memories with near-memory data shuffling to enable single-cycle multi-pattern vector access. Oriented FAST and Rotated BRIEF (ORB) are thoroughly explored to validate the proposed architecture, achieving a throughput of 140 Frames-Per-Second (FPS) for VGA images for one scale, while reducing the number of memory accesses by 2 orders of magnitude as compared to other embedded general-purpose architectures.

Adaptation and Content Validation of a Patient-Reported Measure of Treatment Burden for use in Stroke Survivors (PETS-Stroke).

Context: Treatment burden is defined as the workload of healthcare for people with long-term conditions and the impact on wellbeing. Stroke survivors often live with considerable treatment burden because of high healthcare workload alongside deficiencies in care provision that can make navigating healthcare systems and managing health more difficult. Ways of measuring treatment burden after stroke are currently lacking. The Patient Experience with Treatment and Self-Management measure (PETS) is a 60-item patient-reported measure that was developed to measure treatment burden in a multi-morbid population. Although comprehensive, this is not a stroke-specific measure and therefore omits some burdens associated with stroke rehabilitation. Objective: Our aim was to adapt (PETS) (version 2.0, English), a patient-reported measure of treatment burden in multimorbidity, to create a stroke-specific measure (PETS-stroke), and to conduct content validity testing in a UK stroke survivor population. Study Design and analysis: PETS items were adapted to create PETS-stroke, using a previously developed conceptual model of treatment burden in stroke. Content validation involved three rounds of qualitative cognitive interviews with stroke survivors in Scotland recruited through stroke groups and primary care. Participants were asked for feedback on the importance, relevance and clarity of content of PETS-stroke. Framework analysis was used to explore responses. Setting: Community. Population studied: Stroke survivors. Instrument: Patient Experience with Treatment and Self-Management in stroke (PETS-stroke) scale. Results: Interviews (n=15) resulted in changes to the wording of instructions and items; location of items within the measure; answer options; and recall period. The final PETS-stroke tool has 34-items, spanning 13 domains. It includes 10 items unchanged from PETS, 6 new and 18 amended. Conclusions: The development of a systematic method of quantifying treatment burden from the perspective of stroke survivors will allow for the identification of patients at high risk of treatment burden and will aid the design and testing of tailored interventions aimed at lessening treatment burden.

WHEN TO TEACH L2 READING TO YOUNG LEARNERS: GENERAL GUIDELINES TO A SEQUENCE OF INSTRUCTION

This paper has two main aims. First, it will clarify some common misconceptions regarding the teaching of reading to young learners in a second language, and second, it will describe some general guidelines that can be followed when implementing a second language reading program. Because reading is a two-step process that involves decoding and then comprehension, second-language reading instruction should not begin until the learners have the appropriate foundation. This paper will describe that foundation in terms of when reading in a second language should begin, how to prepare young learners for the reading program, the importance of building lexical resources, balancing phonics and sight word instructions, and the value of using engaging and comprehensible texts.

Instruction mapping techniques for processors with very long instruction word architectures

Abstract This paper presents an instruction mapping technique for generating a low-level assembly code for digital signal processing algorithms. This technique helps developers to implement retargetable kernel functions with the performance benefits of the low-level assembly languages. The approach is aimed at exceptionally long instruction word (VLIW) architectures, which benefits the most from the proposed method. Mapped algorithms are described by the signal-flow graphs, which are used to find possible parallel operations. The algorithm is converted into low-level code and mapped to the target architecture. This process also introduces the optimization of instruction mapping priority, which leads to the more effective code. The technique was verified on selected kernels, compared to the common programming methods, and proved that it is suitable for VLIW architectures and for portability to other systems.

Effects of Parents’ Word Instruction on Preschoolers’ Receptive Vocabulary Size: Mediating Effect of Word Awareness

Objectives: Word awareness is an important factor in word instruction for children in late preschool. This study aimed to verify whether parents’ word instruction promotes the growth of preschoolers’ receptive vocabulary size and whether the relation between the two variables is mediated by preschoolers’ word awareness.Methods: The study recruited 200 pairs of five to six-year-old preschoolers and their parents from 14 childcare centers in Sejong and Daejeon, South Korea. Experimenters asked the preschoolers to answer questions on word unit awareness, word arbitrariness awareness, word morphology awareness, word type awareness, and receptive vocabulary size from experimenters and videos. Parents were asked to answer the items on word instruction.Results: First, parents’ word instruction, preschoolers’ word awareness and receptive vocabulary size were positively correlated. Second, parents’ word instruction had a direct effect on preschoolers’ receptive vocabulary size and an indirect effect via preschoolers’ word awareness. Lastly, the partial mediating effects of word unit awareness, word arbitrariness awareness, word morphology awareness, and word type awareness on the relation between parents’ word instruction and receptive vocabulary size were all significant.Conclusion: This study revealed the importance of parents’ word instruction to enhance preschoolers’ awareness of various aspects of words. The present results offer useful information for developing vocabulary instruction programs for preschoolers and parents.

Effects of stimulus disparity on acquisition of sight word sets: Manipulation of initial letter.

Due to the prevalence of words that cannot be read phonetically in the English language, sight word instruction is required to supplement phonics instruction. In this study, we manipulated stimulus disparity in sight word sets by comparing the effects of sets of sight words with the same initial letter (3 words per set, 3 total sets) versus distributing words with the same initial letter across sets when assessing acquisition of the combined set (9 words) for 5 children who ranged from 4-6 years of age using a combined adapted alternating treatments design and pre-posttest design. All participants mastered the 3-word sets in both teaching conditions but did not master the control sets. In general, participants required more teaching sessions when the words in sets began with the same letter. These findings are consistent with stimulus disparity research demonstrating that discrimination training is generally less efficient when comparison stimuli are similar.

Translanguaging flows in Chinese word instruction: Potential critical sociolinguistic engagement with children’s artistic representations of Chinese characters

ABSTRACT Translanguaging (TL) theory underscores individuals’ agentive deployment of all semiotic resources to construct meaning, highlighting language as part of an integrated repertoire for communication. To explore the potential of pedagogical TL in Chinese vocabulary instruction, this paper focused on one Chinese Language Arts lesson from a larger study on TL pedagogies in a multiethnic Grade 3 Mandarin-English dual language bilingual education classroom in a U.S. public school. The teacher in this lesson provided an explicit instruction on word origins andknowledge and then students were encouraged to use their imagination to create visual narratives of different Chinese characters based on their orthography and semantics. We performed a fine-grained analysis of the teacher’s instructional practice and a multimodal analysis of children’s Chinese character art as a visual narrative. We found that the teacher engaged in TL practices, mobilizing a range of multimodal, multilingual and multisensory resources to facilitate the co-construction of meaning with students. We also saw that the students’ word art design – the crossing between linguistic and visual signs – index their funds of knowledge and sociocultural values, which could potentially open up spaces for more critical discussions on the complex intersections of language, culture and beliefs.

An Application Specific Vector Processor for Efficient Massive MIMO Processing

This paper presents an implementation for a baseband massive multiple-input multiple-output (MIMO) application-specific instruction set processor (ASIP). The ASIP is geared with vector processing capabilities in the form of single instruction multiple data (SIMD), and furthermore exploits instruction level parallelism by employing a very large instruction word (VLIW) architecture. Additionally, a systolic array is built into the pipeline which is tuned to speed up matrix calculations. A parallel memory subsystem and stand-alone accelerators are integrated into the ASIP architecture in order to meet the processing requirement. The processor is synthesized in 22 nm FD-SOI technology running at a clock frequency of 800 MHz. The system achieves a maximum detection throughput of 0.75 Gb/s/mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> for a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$128\times 8$ </tex-math></inline-formula> massive MIMO system.

Ultra-fast and efficient implementation schemes of complex matrix multiplication algorithm for VLIW architectures

The Complex Matrix Multiplication (CMM) algorithm is known to require a high computing performance and presenting exceptional challenges in real-life applications. Recent advances in Very Long Instruction Word (VLIW) based Digital Signal Processors (DSP) demonstrated high computing capabilities with a very low power consumption. In this work, we propose three ultra-fast, parallel and efficient VLIW implementation approaches of the CMM algorithm which could be used to meet tighter real-time constraints of several signal and image processing applications like radars. A novel parallel kernel, task mapping strategy and low-level optimization techniques are suggested, to fit a set of modern VLIW architectures. Additionally, an original memory access management technique was adopted to accelerate the algorithm by avoiding cache misses and bank conflicts. The experimental results showed the effectiveness of the proposed approaches where a peak performance of 15.89 GFLOPS was achieved on one C66x DSP core with a core utilization of 99% and a speedup of about 1.61, 3 and 10 compared to the state-of-the-art, the most optimized vendor and the conventional approaches, respectively.

Register allocation compilation technique for ASIP in 5G micro base stations

The currently available compilation techniques are for general computing and are not optimized for physical layer computing in 5G micro base stations. In such cases, the foreseeable data sizes and small code size are application specific opportunities for baseband algorithm optimizations. Therefore, the special attention can be paid, for example, the specific register allocation algorithm has not been studied so far. The compilation for kernel sub-routines of baseband in 5G micro base stations is our focusing point. For applications of known and fixed data size, we proposed a compilation scheme of parallel data accessing, while operands can be mainly allocated and stored in registers. Based on a small register group (48×32b), the target of our compilation scheme is the optimization of baseband algorithms based on 4×4 or smaller matrices, maximizing the utilization of register files, and eliminating the extra register data exchanging. Meanwhile, when data is allocated into register files, we used VLIW (Very Long Instruction Word) machine to hide the time of data accessing and minimize the cost of data accessing, thus the total execution time is minimum. Experiments indicate that for algorithms with small data size, the cost of data accessing and extra addressing can be minimized.