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The purpose of this paper is to reduce the post-harvest loss occurring through respiration and CO₂ emission produce by the selected produces, during logistics. This paper proposes a supply chain (SC) structure for the Indian traditional agriculture SC planning model to reduce post-harvest loss and mixed closed transportation to reduce CO₂ emission.

The Indian agriculture SC structure is modeled and solved by genetic algorithm using a MATLAB Optimization toolbox. The respiration rate is measured by a static method. These values are applied in an SC planning model and the post-harvest loss and its corresponding CO₂ emission are estimated.

This paper proposes a supply structure for the Indian traditional agriculture SC to reduce the post-harvest loss; the experiments measured the respiration rate to estimate the CO₂ emission. The mixed closed transportation method is found to be suitable for short-purpose domestic transportation.

The optimized supply structure leads to unemployment through eliminating the intermediaries. Therefore, further research encourages the conversion of intermediaries into hub instead of eliminating them.

This paper includes implications for the development of Indian traditional agriculture SC by an optimized supply structure and novel transportation method for the selected agriculture produces based on compatibility.

This paper identified that the agriculture produces respiration can also emit the CO₂. The closed transportation method can reduce the CO₂ emission of produces respiration than traditional open transportation.

The purpose of this paper is to explore how web-based science curriculum materials designed to develop autonomous learners can succeed in Brunei. In this instruction, designed to prepare students to independently explore new topics, students and teachers take new roles. Students collaborate with a peer to engage in inquiry and teachers monitor progress and guide students rather than leading the class.

The authors studied two Web-based Inquiry Science Environment (WISE) units (photosynthesis and cellular respiration) developed using the knowledge integration framework. The framework promotes autonomous learning by building on the diverse ideas that students bring to science lessons and encouraging them to distinguish among their own ideas and those they encounter when using scientific visualizations. In a study on “How People Learn: Brain, Mind, Experience and School”, Bransford et al. (1999) suggest that the students’ preconceptions of how the world works must be engaged, as failing to do so may hinder them from grasping new concepts and information that are taught. Two intact classes of students from two secondary schools in Brunei each studied one of the WISE units. Observations revealed that students could work in pairs to jointly engage in inquiry with encouragement from teachers. Embedded assessments and interviews were analyzed to show how students linked observable events and scientific ideas when explaining the conversion of solar energy to chemical energy in photosynthesis.

Significant gains in knowledge integration show that Brunei students who collaboratively study WISE inquiry units can autonomously succeed. Specifically, students using WISE were able to construct complex ideas about photosynthesis and cellular respiration by linking observable events and scientific ideas while working autonomously with infrequent teacher monitoring.

The paper provides invaluable insights into ways in which web-based learning supports students to become autonomous learners.

Describes research designed to examine the effects of subject positioning on the accuracy of body scan data. A body measurement system developed by the Textile Clothing Technology Corporation was used to acquire two scans from each of 72 subjects. The subjects were instructed to continue to breathe normally and stand with their feet shoulder‐width apart. The two scans were compared and statistical analysis was performed to determine the precision of the results and whether this lack of standardization affected the data. Physical measurements were also obtained from each subject and served as a basis for comparison to the scanned measurements. Since physical measurements are the current accepted “true value”, these measurements determined the level of accuracy of scanned data. Three separate scans of 72 different subjects were taken at various levels of breathing and at various foot positions to determine the effect of the variables. This study certainly indicates that respiration and foot placement has a significant effect on body scan data. It was established that the scan data rendered by the software does have precision, but lacks accuracy when compared against physical measurements. This may be owing to the inaccuracies of the physical measurement process or to differences in measurement location between the anthropometrist and the 3D measurement extraction software. Information detailing the level of accuracy and precision that can be obtained with scanning software and how respiration and subject positioning can affect the data are included.

The purpose of this paper is to introduce a novel respiration pattern-based biometric prediction system (BPS) by using artificial neural network (ANN).

Respiration patterns were obtained using a knitted piezoresistive smart chest band. The ANN model was implemented by using four hidden layers to help achieve the best complexity to produce an adequate fit for the data. Not only did this study give a detailed distribution of an ANN model construction including the scheme of parameters and network layers, ablation of the architecture and the derivation of back-propagation during the iterations but also engaged a step-based decay to systematically drop the learning rate after specific epochs during training to minimize the loss and increase the model’s accuracy as well as to limit the risk of overfitting.

Findings establish the feasibility of using respiratory patterns for biometric identification. Experimental results show that, with a learning rate drop factor = 0.5, the network is able to continue to learn past epoch 40 until stagnation occurs which yielded a classification accuracy of 98 per cent. Out of 51,338 test set, the model achieved 51,557 correctly classified instances and 169 misclassified instances.

The findings provide an impetus for possible studies into the application of chest breathing sensors for human machine interfaces in the area of entertainment.

This is the first time respiratory patterns have been applied in biometric prediction system design.

The Guilty Knowledge Test (GKT) is a psychophysiological questioning technique that can be used as part of a polygraph examination which purports to assess whether suspects conceal “guilty knowledge” by measuring their physiological responses while responding to a series of multiple choice questions. The present study sets out to consider a number of key issues in relation to the GKT paradigm. Specifically, the following questions were considered: Does response mode matter? Does motivation influence outcome? Are combined physiological measures better than single ones? Does gender have an effect on physiological responsivity during a polygraph examination? Results demonstrated real variations between the physiological measures used. Gender differences were also observed in polygraph response patterns. These findings are discussed in relation to the validity of the Guilty Knowledge Test.

The purpose of this paper is to provide a comparative review of intensity‐modulated fiber optic sensors with non‐optical sensors for health monitoring applications, from the current research activities in the area.

A range of published research work in sensor design for four different health monitoring applications, including, lumbar spine bending, upper and lower limb motion tracking, respiration and heart rate monitoring, are presented and discussed in terms of their respective advantages and limitations.

This paper provides information on the various types of sensors applied into the health monitoring area. The sensing techniques of the fiber optic sensor for the stated applications are focused and compared in details to highlight their contributions.

A comparative review of published work is illustrated in an informative table content, to allow a clear idea of the current sensing approaches for health monitoring applications.

The aim of this study is to investigate subject independent emotion recognition capabilities of EEG and peripheral physiological signals namely: electroocoulogram (EOG), electromyography (EMG), electrodermal activity (EDA), temperature, plethysmograph and respiration. The experiments are conducted on both modalities independently and in combination. This study arranges the physiological signals in order based on the prediction accuracy obtained on test data using time and frequency domain features.

DEAP dataset is used in this experiment. Time and frequency domain features of EEG and physiological signals are extracted, followed by correlation-based feature selection. Classifiers namely – Naïve Bayes, logistic regression, linear discriminant analysis, quadratic discriminant analysis, logit boost and stacking are trained on the selected features. Based on the performance of the classifiers on the test set, the best modality for each dimension of emotion is identified.

 The experimental results with EEG as one modality and all physiological signals as another modality indicate that EEG signals are better at arousal prediction compared to physiological signals by 7.18%, while physiological signals are better at valence prediction compared to EEG signals by 3.51%. The valence prediction accuracy of EOG is superior to zygomaticus electromyography (zEMG) and EDA by 1.75% at the cost of higher number of electrodes. This paper concludes that valence can be measured from the eyes (EOG) while arousal can be measured from the changes in blood volume (plethysmograph). The sorted order of physiological signals based on arousal prediction accuracy is plethysmograph, EOG (hEOG + vEOG), vEOG, hEOG, zEMG, tEMG, temperature, EMG (tEMG + zEMG), respiration, EDA, while based on valence prediction accuracy the sorted order is EOG (hEOG + vEOG), EDA, zEMG, hEOG, respiration, tEMG, vEOG, EMG (tEMG + zEMG), temperature and plethysmograph.

Many of the emotion recognition studies in literature are subject dependent and the limited subject independent emotion recognition studies in the literature report an average of leave one subject out (LOSO) validation result as accuracy. The work reported in this paper sets the baseline for subject independent emotion recognition using DEAP dataset by clearly specifying the subjects used in training and test set. In addition, this work specifies the cut-off score used to classify the scale as low or high in arousal and valence dimensions. Generally, statistical features are used for emotion recognition using physiological signals as a modality, whereas in this work, time and frequency domain features of physiological signals and EEG are used. This paper concludes that valence can be identified from EOG while arousal can be predicted from plethysmograph.

Honey peaches are rich in a variety of vitamins and are well known in China as the queen of fruit. However, as highly climacteric fruit, peach is too easy to affect its economic value. In this paper, a new passive modified atmosphere packaging system was proposed to solve the lack of water vapour removal capacity – which is still the technical bottleneck of passive modified atmosphere packaging. This paper aims to address this issue.

Under the conditions of relative humidity 85−90% and temperature 28°C−38°C, the influence of new passive modified atmosphere packaging on the shelf life and quality of 70% ripe peaches was studied in the paper. The effect of the new passive modified atmosphere packaging (PMAP) on fruit appearance, colour, taste, flavour, soluble solids, Vitamin C and titratable acid was investigated.

Regardless of whether 1-Methylcyclopropene is added or not, the research results show that the new PMAP has a significant effect on extending the shelf life and maintaining the quality of peaches. Compared with the control group, the shelf life of peaches treated with modified atmosphere packaging and 1-Methylcyclopropene was prolonged by 7 and 11 days, increasing the retailer's revenue by 44 and 75%.

A new integrated structure, which is composed of two types of films with high oxygen and high water vapour permeability was designed for the retail of peaches at room temperature. The former was mainly responsible for regulating the concentration of O₂ and CO₂, while the latter was for removing water vapour and regulating the relative humidity in PMAP.

Reprenant les equations d'un modèle d'échanges gazeux alvéolo‐capillaires établi par J. Brocas et Y. Cherruault, les auteurs montrent que l'on peut résoudre ces équations, trouver les solutions explicites et les identifier. Starting from the model of alveolo‐capillary gas exchanges of Professors J. Brocas and Y. Cherruault, the authors solve equations, find explicit solutions by an original method and identify these.

This paper aims to update with information about edible coating on minimally processed and fresh fruits, focussing on the composition, active ingredients, antimicrobial concentration and their effect on ripening rate, phytonutrients retention and shelf-life of fruits. In future, the data will be helpful for the processors to select the best coating material and its effective concentration for different fresh and minimally processed fruits.

Major scientific information was collected from Scopus, Web of Science, Mendeley and Google Scholar. Several key words such as postharvest, edible coating, phytonutrients, shelf-life enhancement, bioactive compounds, minimally processed fruits and antimicrobial compounds were used to find the data. Relevant information was collected by using 90 recent research and review articles.

The main findings of this comprehensive review are to improve the quality of fruits, to meet the next-generation food security needs. However, in the process of achieving the goal of improving quality of food produce, embrace of synthetic, non-biodegradable packaging materials have increased, creating serious pollution problem. Amidst several alternatives for replacement of synthetic packaging, the option of biodegradable films and coatings showed promising results.

The paper represents recent information about the edible coating used for the enhancement of shelf-life of fresh and minimally processed fruits.