Modelling and Simulation of the Dynamics of Cross Vane Expander-Compressor Unit for Vapour Compression Cycle

The Cross Vane mechanism was recently invented and employed in the design and development of an expander-compressor unit, named Cross Vane expander-compressor or CVEC in short. This device replaces the compressor and expansion valve of a conventional vapour compression cycle, and improves the energy efficiency of the system. Theoretical models which include geometrical, thermodynamics, mass flow, as well as mechanical loss models are developed to characterize the performance of CVEC. Numerical simulation was performed, and the results show that the device is capable of reducing the energy consumption and the peak power requirement of the refrigeration system. Energy saving and peak power reduction of up to 18.0% and 3.8% respectively is achievable with the introduction of CVEC. In addition, due to its unique rotating cylinder design the mechanical losses in CVEC are relatively low. Its mechanical efficiency is calculated to be up to 96.5%

Introduction of the Novel Cross Vane Expander-Compressor Unit for Vapour Compression Cycle

A new type of expander-compressor system called Cross Vane expander-compressor (CVEC) was introduced. This device replaces the expansion valve and compressor in conventional refrigeration systems to reduce the energy consumption and improve the coefficient of performance (COP) of the system. As opposed to many expander-compressor systems in the literature, whereby a separated expander is coupled to a separated compressor of the same or different mechanism, the novel Cross Vane mechanism performs both the function of expander and compressor in a single mechanism. Therefore, one machine is built rather than two as required in the former system. This has significant advantages on the manufacturing process and mechanical efficiency. In this paper, the design and working principle of CVEC are presented and the comparison between the novel CVEC and various types of rotary expander-compressor systems are discussed

Top-Down Framework for Weakly-supervised Grounded Image Captioning

Weakly-supervised grounded image captioning (WSGIC) aims to generate the caption and ground (localize) predicted object words in the input image without using bounding box supervision. Recent two-stage solutions mostly apply a bottom-up pipeline: (1) encode the input image into multiple region features using an object detector; (2) leverage region features for captioning and grounding. However, utilizing independent proposals produced by object detectors tends to make the subsequent grounded captioner overfitted in finding the correct object words, overlooking the relation between objects, and selecting incompatible proposal regions for grounding. To address these issues, we propose a one-stage weakly-supervised grounded captioner that directly takes the RGB image as input to perform captioning and grounding at the top-down image level. Specifically, we encode the image into visual token representations and propose a Recurrent Grounding Module (RGM) in the decoder to obtain precise Visual Language Attention Maps (VLAMs), which recognize the spatial locations of the objects. In addition, we explicitly inject a relation module into our one-stage framework to encourage relation understanding through multi-label classification. This relation semantics served as contextual information facilitating the prediction of relation and object words in the caption. We observe that the relation semantic not only assists the grounded captioner in generating a more accurate caption but also improves the grounding performance. We validate the effectiveness of our proposed method on two challenging datasets (Flick30k Entities captioning and MSCOCO captioning). The experimental results demonstrate that our method achieves state-of-the-art grounding performance

A Comparison between the Post- and Pre-dispersive Near Infrared Spectroscopy in Non-Destructive Brix Prediction Using Artificial Neural Network

Even though near infrared (NIR) spectroscopy have been implemented in determining the Brix of pineapples, no traceable study compares the effects of different acquisition designs. Thus, this study aims to evaluate the prediction performance of both pre- and post-dispersive NIR sensing devices in non-destructive Brix prediction using artificial neural network (ANN). The pre-dispersive device has five narrowband light emitting diodes (LEDs) with different wavelengths and a photodiode detector, whereas the post-dispersive device has a bifurcated fiber optic, a broadband LED, and a spectral sensor. First, the NIR diffuse reflectance was non-destructively collected using both NIR devices. Then, the collected diffuse reflectance was calibrated with the white and dark references, and then pre-processed using normalization and standard normal variate methods. After that, ANNs were built for both devices using the pre-processed data. Results show both devices are suitable for sample screening application with range error ratio (RER) of more than seven. Nevertheless, the ANN that trained using the post-dispersive device outperformed that trained using the pre-dispersive device with an 8.1% improvement of correlation coefficient of prediction (i.e. from 0.6853 to 0.7408), and a 5.7% improvement of root mean square error of prediction (i.e. from 1.3918 to 1.313°Brix)

A comparative study of the efficacy and requirement of remifentanil infusion alone versus remifentanil infusion + midazolam for end stage renal failure (ESRF) patient during tenckhoff insertion in monitored anaesthesia care (MAC) : a randomized controlled double blinded trial

Introduction: Remifentanil ,an ultra-short acting opioid analgesic, may be useful as an intravenous adjuvant to local anaesthetic for treating patient discomfort and pain during monitored anesthesia care ( MAC). However , the remifentanil dose requirement , interaction with other commonly used sedative drug ( such as midazolam ), and the safety profile especially in ESRF patient for tenckhoff surgery have not been determined . Therefore , this study was designed to define the appropriate dose of remifentanil hydrochloride alone or combined with midazolam , and at the same time to evaluate the safety and efficacy of remifentanil during tenckhoff surgery MAC setting . Methods: 58 patients scheduled for tenckhoff catheter insertion under MAC setting were recruited in this double‐blind study after approved by Research and Ethics Committee, school of Medical Sciences, University Sains Malaysia, Kelantan Health Campus. However, 3 patients had drop off due to convert general anaesthesia. Patients were randomly assigned to one of two groups: ( 1) remifentanil TCI starting at 0.5ng/ml plasma concentration + placebo normal saline , ( 2) remifentanil TCI starting at 0.5ng/ml plasma concentration + midazolam 0.02mg/kg . Standard local anesthetic ( LA) ( max dose of 2 mg /kg levobupivacaine ) was allowed to be injected after that. Verbal assessments of pain, discomfort and sedation according to modified OAA/S score were assessed with 1 st LA injection. The level of pain , discomfort and sedation were subsequently assessed every 5 minutes. Patient oxygen saturation, respiratory rate and heart rate were monitored at 5 minutes interval. Remifentanil was titrated (in increments of 0.1ng/ml from the initial rate) to limit patient discomfort or pain intraoperatively and the infusion was terminated at the completion of skin closure. Post operatively, patient were assessed for incidence of opioid’s side effect such as nausea , vomiting and pruritus Results: At the time of the local anaesthetic, more patients in the remifentanil + placebo group experienced severe pain (78.6%) and severe discomfort ( 46.4%) as compared with midazolam + remifetanil group ( 29.6% and 11.1%, respectively). The final mean �}SD remifentanil TCI were 1.57 �} 0.11 ng/ml (remifentanil + placebo ) and 0.92 �} 0.11 ng/ml (remifentanil + midazolam). Midazolam + remifentanil group achieved pain score <4 in the faster time ( minutes) compared with placebo group ( 9.78 vs 22.36 minutes ; p < 0.05 ) Generally, Midazolam + remifentanil group patients had higher incidences of all adverse evenst intraoperatively. 7 patients (25.9%) in the remifentanil + midazolam group and 2 patients (7.1%) in the remifentanil alone group experienced brief periods hypoventilation (< 8 breaths/min). On the other hand, Remifetanil placebo group patient had higher incidence of post operative opioid side effects . 7 patients (25%) in the remifentanil placebo group and 1 patients (3.7%) in the remifentanil + midazolam group experienced vomiting . Conclusions TCI remifentanil provided effective analgesia and comfort during MAC at a mean plasma concentration 1.57ng/ml when administered alone, or at a mean plasma concentration of 0.92ng/ml in combination with midazolam. Thus , the adding of midazolam in combination with TCI remifentanil could reducing the dose of TCI remifentanil used , and faster time to achieve satisfactory pain score during surgery. However, there were increased incidences of intraoperative adverse even ( hypotension , bradycardia and respiratory depression ) with midazolam + remifentanil group and on the other hand, increase incidences of opiods side effecst ( nausea , vomiting , prutitus ) with remifentanil alone . Keyword: Monitored Anesthesia Care , End Stage Renal Failure , Tenkchoff Surgery , Midazolam Remifentanil , Target Controlled Infusio

Theoretical and Experimental Studies of Heat Straightening and Cambering

Civil Engineerin