Using Machine Learning to Optimize Energy Consumption of HVAC Systems in Vehicles

The detachment and calculation of functionalities from a vehicle into a cloud creates new chances. By linking different data sources with the in-vehicle data in the cloud, an optimization of these functionalities in terms of en-ergy efficiency can be applied. For example, the Heating, Ventilation and Air Conditioning (HVAC) consumes up to 30% of total energy in a vehicle. Electric vehicles in particular lead to these high values because they are not able to re-cover the waste heat from combustion engines for interior heating. Therefore, the optimization of energy efficient strategies with respect to the vehicle energy management system becomes more relevant. Forecasts of the interior vehicle temperature are directly related to the HVAC energy consumption. This work focuses on the implementation and accuracy evaluation of Recurrent Neural Networks (RNN) for interior vehicle temperature forecasting

Late onset of Huntington's disease

Twenty-five patients with late-onset Huntington's disease were studied; motor impairment appeared at age 50 years or later. The average age at onset of chorea was 57.5 years, with an average age at diagnosis of 63.1 years. Approximately 25% of persons affected by Huntington's disease exhibit late onset. A preponderance of maternal transmission was noted in late-onset Huntington's disease. The clinical features resembled those of mid-life onset Huntington's disease but progressed more slowly. Neuropathological evaluation of two cases reveal less severe neuronal atrophy than for mid-life onset disease

Applied Machine Learning: Reconstruction of Spectral Data for the Classification of Oil-Quality Levels

In modern complex systems and machines - e.g., automobiles or construction vehicles - different versions of a "Condition Based Service" (CBS) are deployed for maintenance and supervision. According to the current state of the art, CBS is focusing on monitoring of static factors and rules. In the area of agricultural machines, these are for example operating hours, kilometers driven or the number of engine starts. The decision to substitute hydraulic oil is determined on the basis of the factors listed. A data-driven procedure is proposed instead to leverage the decision-making process. Thus, this paper presents a method to support continuous oil monitoring with the emphasis on artificial intelligence using real-world spectral oil-data. The reconstruction of the spectral data is essential, as a complete spectral analysis for the ultraviolet and visible range is not available. Instead, a possibility of reconstruction by sparse supporting wavelengths through neural networks is proposed and benchmarked by standard interpolation methods. Furthermore, a classification via a feed-forward neural network with the conjunction of Dynamic Time Warping (DTW) algorithm for the production of labeled data was developed. Conclusively, the extent to which changes in hyper-parameters (number of hidden layers, number of neurons, weight initialization) affect the accuracy of the classification results have been investigated

Agreement of Air Bike and Treadmill Protocols To Assess Maximal Oxygen Uptake: An Exploratory Study

International Journal of Exercise Science 17(4): 633-647, 2024. Maximal oxygen consumption (V̇O2max) is an important measure of aerobic fitness, with applications in evaluating fitness, designing training programs, and assessing overall health. While treadmill assessments are considered the gold standard, airbikes (ABs) are increasingly popular exercise machines. However, limited research exists on AB-based V̇O2max assessments, particularly regarding agreement with treadmill graded exercise tests. To address this gap, a randomized crossover study was conducted, involving 15 healthy adults (9M, 6F, 7 familiar with AB) aged 30.1 ± 8.6 years. Paired t-tests, intraclass correlation coefficients (ICC), Bland-Altman and Principal component (PC) analyses were used to assess agreement between protocols. The results demonstrated good to excellent agreement in V̇O2max, maximum heart rate (HR), and rating of perceived exertion (ICC range: 0.89-0.92). However, significant differences were observed in several measures, including V̇O2max and maximum HR (p \u3c 0.01). Overall a systematic bias 3.31 mL/kg/min (treadmill \u3e AB, 95%CI[1.67,4.94]) was observed, no proportional bias was present; however, regular AB users (systematic bias: 1.27 (95%CI[0.20,2.34]) mL/kg/min) exhibited higher agreement in V̇O2max measures compared to non-regular users (systematic bias: 5.09 (95%CI[3.69,6.49]) mL/kg/min). There were no significant differences in cardiorespiratory coordination, between the AB and the treadmill. These findings suggest that for individuals familiar with the AB, it can be a suitable alternative for assessing V̇O2max compared to the treadmill. Future research with larger samples should focus on developing prediction equations for field AB tests to predict V̇O2max. Practitioners should consider using the AB to assess V̇O2max in individuals who prefer it over running

Effect of the Law Enforcement Duty Belt on Muscle Activation during Hip Hinging Movements in Young, Healthy Adults

Sixty percent of all law enforcement officers (LEOs) experience low back pain (LBP), with the LEO duty belt (LEODB) commonly reported to be a contributing factor. The primary purpose of the study was to investigate the LEODB’s effect on muscular activity and compare it to a tactical vest, which is a commonly used alternative to an LEODB. In total, 24 participants (13 male, 11 female; mass, 73.0 ± 11.1 kg; height, 169.0 ± 10.0 cm; age, 24.0 ± 5.8 years) completed a progressive series of hip hinge tasks in a single testing session. All participants completed four conditions (no belt, leather belt, nylon belt, and weight VEST) in a randomized order. Surface electromyography (sEMG) sensors were placed bilaterally on the rectus abdominus, multifidus, biceps femoris, and rectus femoris. Across all tasks, no significant effects of load on muscle activity were found for any of the muscles. Participants rated the VEST condition as more comfortable (p < 0.05) and less restrictive (p < 0.05) than either LEODB. The findings suggest an LEODB does not alter muscle activity during bodyweight hip hinging or lifting objects from the ground. Future research should examine whether changes in muscle activity occur with durations of LEODB wear more similar to an actual work shift duration for LEOs (≥8 h)