Text simplification supports second language (L2) learning by providing comprehensible input, consistent with the Input Hypothesis.However, constructing personalized parallel corpora is costly, while existing large language model (LLM)-based readability control methods rely on pre-labeled sentence corpora and primarily target English.We propose Re-RIGHT, a unified reinforcement learning framework for adaptive multilingual text simplification without parallel corpus supervision.We first show that prompting-based lexical simplification at target proficiency levels (CEFR, JLPT, TOPIK, and HSK) performs poorly at easier levels and for non-English languages, even with state-of-the-art LLMs such as GPT-5.2 and Gemini 2.5.To address this, we collect 43K vocabulary-level data across four languages (English, Japanese, Korean, and Chinese) and train a compact 4B policy model using Re-RIGHT, which integrates three reward modules: vocabulary coverage, semantic preservation, and coherence.Compared to the stronger LLM baselines, Re-RIGHT achieves higher lexical coverage at target proficiency levels while maintaining original meaning and fluency.(1) Preparation Complex Seed Text "Pigeon photography is an aerial photography technique invented in 1907 by the German apothecary Julius Neubronner, ...

This paper presents a uGPS (Underground GPS), which is the first SDR (Software Defined Radio)-based GNSS service to commodity GNSS receivers, including the latest iPhone, Android, and Car navigation. The uGPS is a system consisting of SDRs for GNSS signal generation, a GNSS D.O. for nano-second level timing synchronization's economic selection, fiber optic, and leaky feeder for a minimal environmental effect in tunnel environments. The proposed uGPS provides consistent 8 GPS satellites and 4 GLONASS satellites signal through a 1.5-kilometer-long tunnel. The uGPS equipped tunnel is highly compatible with commodity GNSS/GPS receivers. Therefore, it does not require any APP or special hardware. Our benchmark tested package was on top of the FPGA, in which modifications and upgrades were demonstrated via evaluation on three popular GNSS/GPS devices including Android phones, iPhones, and Car navigation systems. Further extensive evaluations demonstrated that the uGPS consistently achieved average location accuracy of 10 meters in 30~70km/h speed driving tests (without a map-matching algorithm), and a seamless handover between live GNSS and the uGPS system.

This paper presents ABC, the AR(augmented reality), and BLE combined target detector in a crowd of objects. The AR design of BLE analysis is a ready-to-use option for the ever-growing app-based ride market. The carefully designed AR tags and BLE beacons effectively collaborate to identify the target car. Such that a passenger can pinpoint the ride from a far distance. ABC consistently identify the target in a realistic environment through evaluations.

NPU Scheduler Tiling memory transactions between internal memories and external memories Communicating with AP Host and other processing units

A new scheme that classifies the Internet traffic according to their application types for scalable QoS provision is proposed in this work. The traditional port-based classification method does not yield satisfactory performance, since the same port can be shared by multiple applications. Furthermore, asymmetric routing and errors of modern measurement tools such as PCF and NetFlow degrades the classification performance. To address these issues, the proposed classification process consists of two steps: feature selection and classification. Candidate features that can be obtained easily by ISP are examined. Then, we perform feature reduction so as to balance the performance and complexity. As to classification, the REPTree and the bagging schemes are adopted and compared. It is demonstrated by simulations with real data that the proposed classification scheme outperforms existing techniques

A denial-of-service (DoS) attack which can waste wireless resources by using the destination address of IP packets is introduced. To prevent the attack more effectively, early detection, efficiency, and small overhead are suggested as requirements in a detection system. We use a second order Markov model to suggest a detection system against the attack in 3G1x system. The states in the model are representative of each user's transmission activities during a fixed interval. Parameters of the model in our simulation are obtained from a traffic model. Our proposed detection system detects the attack by comparing the parameters in the model with each user's parameters which are generated during their transmission activity. The proposed system is analyzed in terms of the requirements for the detection system by varying the interval. Finally, we conclude that there are tradeoffs between efficiency, overhead and early detection for the design of the detection system.