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To support the standardized evaluation of bicyclist automatic emergency braking (AEB) systems, test scenarios, test procedures and test system hardware and software tools have been investigated and developed by the Transportation Active Safety Institute (TASI) at Indiana University-Purdue University Indianapolis. This paper aims to focus on the development of test scenarios and bicyclist surrogate for evaluating vehicle–bicyclist AEB systems.

The harmonized general estimates system (GES)/FARS 2010-2011 crash data and TASI 110-car naturalistic driving data (NDD) are used to determine the crash geometries and environmental factors of crash scenarios including lighting conditions, vehicle speeds, bicyclist speeds, etc. A surrogate bicyclist including a bicycle rider and a bicycle surrogate is designed to match the visual and radar characteristics of bicyclists in the USA. A bicycle target is designed with both leg pedaling and wheel rotation to produce proper micro-Doppler features and generate realistic motion for camera-based AEB systems.

Based on the analysis of the harmonized GES/FARS crash data, five crash scenarios are recommended for performance testing of bicyclist AEB systems. Combined with TASI 110-car naturalistic driving data, the crash environmental factors including lighting conditions, obscuring objects, vehicle speed and bicyclist speed are determined. The surrogate bicyclist was designed to represent the visual and radar characteristics of the real bicyclists in the USA. The height of the bicycle rider mannequin is 173 cm, representing the weighted height of 50th percentile US male and female adults. The size and shape of the surrogate bicycle were determined as 26-inch wheel and mountain/road bicycle frame, respectively. Both leg pedaling motion and wheel rotation are suggested to produce proper micro-Doppler features and support the camera-based AEB systems.

The results have demonstrated that the developed scenarios, test procedures and bicyclist surrogate will provide effective objective methods and necessary hardware and software tools for the evaluation and validation of bicyclist AEB systems. This is crucial for the development of advanced driver assistance systems.

Smart manufacturing can lead to disruptive changes in production technologies and business models in the manufacturing industry. This paper aims to identify technological topics in smart manufacturing by using patent data, investigating technological trends and exploring potential opportunities.

The latent Dirichlet allocation (LDA) topic modeling technique was used to extract latent technological topics, and the generalized linear mixed model (GLMM) was used to analyze the relative emergence levels of the topics. Topic value and topic competitive analyses were developed to evaluate each topic's potential value and identify technological positions of competing firms, respectively.

A total of 14 topics were extracted from the collected patent data and several fast growth and high-value topics were identified, such as smart connection, cyber-physical systems (CPSs), manufacturing data analytics and powder bed fusion additive manufacturing. Several leading firms apply broad R&D emphasis across a variety of technological topics, while others focus on a few technological topics.

The developed methodology can help firms identify important technological topics in smart manufacturing for making their R&D investment decisions. Firms can select appropriate technology strategies depending on the topic's emergence position in the topic strategy matrix.

Previous research studies have not analyzed the maturity levels of technological topics. The topic-based patent analytics approach can complement previous studies. In addition, this study provides a multi-valuation framework for exploring technological opportunities, thus providing valuable information that supports a more robust understanding of the technology landscape of smart manufacturing.

This study aims to examine the effectiveness of an integrated intervention program for alcoholism (IIPA) for improving verbal encoding and memory, visuospatial construction, visual memory and quality of life (QoL) in persons with alcohol dependence.

The sample comprised treatment-seeking alcohol-dependent persons (n = 50), allotted into two groups: (1) the treatment as usual (TAU) group (n = 25) and (2) the treatment group (n = 25)]. The groups were matched on age (±1 year) and education (±1 year). The TAU group received standard pharmacological treatment, psychotherapeutic sessions on relapse prevention and yoga for 18 days, while the treatment group received IIPA sessions in addition to the usual treatment. Auditory verbal learning test, complex figure test and QoL scale were administered at pre- and post-treatment along with screening measures.

The two groups were comparable on demographic variables, clinical characteristics and outcome measures at baseline. Pre- to post-treatment changes (gain scores) comparison between the treatment and TAU groups revealed a significant difference in verbal encoding, verbal and visual memory, verbal recognition, visuospatial construction and QoL.

This study suggests that IIPA is effective for improving learning and memory in both modality (verbal and visual) and QoL in persons with alcoholism. The IIPA may help in better treatment recovery.

The IIPA may help in treatment for alcoholism and may enhance treatment efficacy.

IIPA is effective for improving learning and memory in both modalities and QoL in persons with alcohol dependence. The IIPA may help in better treatment recovery.