Painsight: An Extendable Opinion Mining Framework for Detecting Pain Points Based on Online Customer Reviews

As the e-commerce market continues to expand and online transactions proliferate, customer reviews have emerged as a critical element in shaping the purchasing decisions of prospective buyers. Previous studies have endeavored to identify key aspects of customer reviews through the development of sentiment analysis models and topic models. However, extracting specific dissatisfaction factors remains a challenging task. In this study, we delineate the pain point detection problem and propose Painsight, an unsupervised framework for automatically extracting distinct dissatisfaction factors from customer reviews without relying on ground truth labels. Painsight employs pre-trained language models to construct sentiment analysis and topic models, leveraging attribution scores derived from model gradients to extract dissatisfaction factors. Upon application of the proposed methodology to customer review data spanning five product categories, we successfully identified and categorized dissatisfaction factors within each group, as well as isolated factors for each type. Notably, Painsight outperformed benchmark methods, achieving substantial performance enhancements and exceptional results in human evaluations.Comment: WASSA at ACL 202

Towards Integrated Sensing and Communications for 6G: A Standardization Perspective

The radio communication division of the International Telecommunication Union (ITU-R) has recently adopted Integrated Sensing and Communication (ISAC) among the key usage scenarios for IMT-2030/6G. ISAC is envisioned to play a vital role in the upcoming wireless generation standards. In this work, we bring together several paramount and innovative aspects of ISAC technology from a global 6G standardization perspective, including both industrial and academic progress. Specifically, this article provides 6G requirements and ISAC-enabled vision, including various aspects of 6G standardization, benefits of ISAC co-existence, and integration challenges. Moreover, we present key enabling technologies, including intelligent metasurface-aided ISAC, as well as Orthogonal Time Frequency Space (OTFS) waveform design and interference management for ISAC. Finally, future aspects are discussed to open various research opportunities and challenges on the ISAC technology towards 6G wireless communications.Comment: 7 pages, 5 figure

Proof of Concept of Home IoT Connected Vehicles

The way in which we interact with our cars is changing, driven by the increased use of mobile devices, cloud-based services, and advanced automotive technology. In particular, the requirements and market demand for the Internet of Things (IoT) device-connected vehicles will continuously increase. In addition, the advances in cloud computing and IoT have provided a promising opportunity for developing vehicular software and services in the automotive domain. In this paper, we introduce the concept of a home IoT connected vehicle with a voice-based virtual personal assistant comprised of a vehicle agent and a home agent. The proposed concept is evaluated by implementing a smartphone linked with home IoT devices that are connected to an infotainment system for the vehicle, a smartphone-based natural language interface input device, and cloud-based home IoT devices for the home. The home-to-vehicle connected service scenarios that aim to reduce the inconvenience due to simple and repetitive tasks by improving the urban mobility efficiency in IoT environments are substantiated by analyzing real vehicle testing and lifestyle research. Remarkable benefits are derived by making repetitive routine tasks one task that is executed by a command and by executing essential tasks automatically, without any request. However, it should be used with authorized permission, applied without any error at the right time, and applied under limited conditions to sense the habitants’ intention correctly and to gain the required trust regarding the remote execution of tasks

Eco Assist Techniques through Real-time Monitoring of BEV Energy Usage Efficiency

Energy efficiency enhancement has become an increasingly important issue for battery electric vehicles. Even if it can be improved in many ways, the driver’s driving pattern strongly influences the battery energy consumption of a vehicle. In this paper, eco assist techniques to simply implement an energy-efficient driving assistant system are introduced, including eco guide, eco control and eco monitoring methods. The eco guide is provided to control the vehicle speed and accelerator pedal stroke, and eco control is suggested to limit the output power of the battery. For eco monitoring, the eco indicator and eco report are suggested to teach eco-friendly driving habits. The vehicle test, which is done in four ways, consists of federal test procedure (FTP)-75, new european driving cycle (NEDC), city and highway cycles, and visual feedback with audible warnings is provided to attract the driver’s voluntary participation. The vehicle test result shows that the energy usage efficiency can be increased up to 19.41%

Towards Faster-Than-Nyquist Transmission for Beyond 5G Wireless Communications

Faster-Than-Nyquist (FTN) is a technique that can improve the spectral efficiency of communication systems by making better use of available spectrum resources at the cost of inter-symbol interference (ISI) and inter-carrier interference (ICI). In this paper, we propose a hybrid signaling scheme for a practical application of FTN for MIMO transmission. We propose a new slot structure optimized for the hybrid signaling supporting both FTN signaling and orthogonal frequency division multiplexing (OFDM) signaling. Specifically, in the proposed slot structure, data transmission is based on the FTN signaling and the pilot transmission is based on the OFDM signaling. Numerical results confirm that the proposed signaling scheme has clear benefit over the systems employing only OFDM or FTN signaling.N