Multiple-choice cloze questions are commonly used to assess linguistic proficiency and comprehension.However, generating high-quality distractors remains challenging, as existing methods often lack adaptability and control over difficulty levels, and the absence of difficulty-annotated datasets further hinders progress.To address these issues, we propose a novel framework for generating distractors with controllable difficulty by leveraging both data augmentation and a multitask learning strategy.First, to create a high-quality, difficultyannotated dataset, we introduce a two-way distractor generation process to produce diverse and plausible distractors.These candidates are filtered and then categorized by difficulty using an ensemble QA system.Second, this newly created dataset is used to train a difficultycontrollable generation model via multitask learning.Experimental results demonstrate that our method generates high-quality distractors across difficulty levels and substantially outperforms GPT-4o in aligning distractor difficulty with human perception.

3G Long Term Evolution, which aims for various mobile multimedia services provision by enhanced wireless performance, proposes the VoIP-based voice service through the PS domain. When delay and loss-sensitive VoIP traffic flows through the PS domain, more challenging technical difficulties are expected than in the existing 3G systems which provide the CS domain based voice service. Moreover, since 3G LTE, which adopts the OFDM as its physical layer, introduces Physical Resource Block (PRB) as the unit for the transmission resources, it becomes necessary to develop new types of resource management schemes. This paper proposes a MAC layer PRB scheduling algorithm for the efficient VoIP service in 3G LTE and shows the simulation results regarding its performance. The key idea of the algorithm consists of two parts; dynamic activation of a VoIP priority mode for the voice QoS satisfaction and adaptive adjustment of the VoIP priority mode duration in order to minimize the performance degradation induced by its priority mode application.