Formation of acrylamide in microwave-roasted sorghum and associated dietary risk

The effect of microwave roasting parameters (300, 450 and 600 W; 5, 10 and 15 min) on acrylamide content in sorghum grain was determined using High Pressure Liquid Chromatography (HPLC)-photo diode array (PDA) detector coupled with C-18 column. Samples roasted at 300 and 450 W did not possess acrylamide, whereas 600 W (15 min) favoured formation of 2740.19 µg/kg of acrylamide, levels far exceeding the defined European Union (EU) limits. The chronic daily intake (CDI) for acrylamide through consumption of such grain flour was 3.25–9.5-fold higher to Joint FAO/WHO Expert Committee on Food Additives (JECFA) defined high exposure limits. The margin of exposure (MOE) values ranged from 4.3 to 12.76 and from 11.07 to 32.27 for neoplastic and neurological effects, respectively, demonstrating high exposure and serious health concerns associated with dietary intake of this toxicant. This study assesses the risk for the Indian population and highlights the importance of optimising process parameters for food product to minimise such exposure risks.     

Deep transfer modeling for classification of Maize Plant Leaf Disease

Multimedia Tools and Applications - Currently, Deep Learning is playing an influential role for Image analysis and object classification. Maize’s diseases reduce production that subsequently...     

A privacy-preserving model based on differential approach for sensitive data in cloud environment

A large amount of data and applications need to be shared with various parties and stakeholders in the cloud environment for storage, computation, and data utilization. Since a third party operates the cloud platform, owners cannot fully trust this environment. However, it has become a challenge to ensure privacy preservation when sharing data effectively among different parties. This paper proposes a novel model that partitions data into sensitive and non-sensitive parts, injects the noise into sensitive data, and performs classification tasks using k-anonymization, differential privacy, and machine learning approaches. It allows multiple owners to share their data in the cloud environment for various purposes. The model specifies communication protocol among involved multiple untrusted parties to process owners’ data. The proposed model preserves actual data by providing a robust mechanism. The experiments are performed over Heart Disease, Arrhythmia, Hepatitis, Indian-liver-patient, and Framingham datasets for Support Vector Machine, K-Nearest Neighbor, Random Forest, Naive Bayes, and Artificial Neural Network classifiers to compute the efficiency in terms of accuracy, precision, recall, and F1-score of the proposed model. The achieved results provide high accuracy, precision, recall, and F1-score up to 93.75%, 94.11%, 100%, and 87.99% and improvement up to 16%, 29%, 12%, and 11%, respectively, compared to previous works.

     

直通链路技术的发展与展望

直通链路技术己广泛应用于车联网场景。对于直通链路技术的潜在技术方向给出可行的建议，包括传统直通链路技术的增强方向，如载波聚合、使用非授权频谱等；侧行链路对于中继场景的应用扩展，包括终端到终端之间的中继，以及中继的多链接场景；在高精度定位场景使用直通链路技术。并且，给出直通链路技术与各种新技术的融合应用，如智能反射面与区块链技术，从而解决直通链路技术自身的缺陷。     

外军地面无人装备发展现状与趋势研究

随着通信、计算机、人工智能和传感器等技术的飞速发展与广泛应用，地面无人装备日趋活跃在作战、搜救和消防等多种军民用任务场景中。对于军事领域而言，地面无人装备是陆军和其他地面作战部队迈向无人化、智能化战场的核心装备，将在未来陆战场各类作战任务中发挥不可替代的作用。通过对外军各类典型地面无人装备发展现状进行深入分析，总结出该装备领域的发展特点与趋势，对地面无人装备发展有一定的借鉴意义。     

基于跨临界CO2热泵的茶叶生产能源系统负荷削减潜力

乡村产业中的化石能源设备逐渐被电能技术替代，引起了乡村负荷波动增大、部分时段产生集中高负荷的问题。为了解决以上问题，将低品位清洁能源应用至乡村的茶叶生产中，针对烘茶全过程的工艺要求提出了跨临界CO₂热泵烘茶技术；并以某茶叶生产乡村为对象，对其代表台区的全年日用电量及产茶日负荷进行了分析，得出采用CO₂热泵烘茶后其负荷得到大幅度削减，整体可降低至原负荷的39.6%~46.8%，峰值负荷与平时负荷的比值由原本的13.6降至5.4~6.2。跨临界CO₂热泵应用至农产品生产中可有效缓解乡村供电压力。