Flavor and stability of potato chips fried in canola, high oleic acid sunflower, sunflower, and cottonseed oils

The objective of this study was to determine the effects of canola (CA), high oleic acid sunflower (HOSU), regular sunflower (SU), and cottonseed (CS) oils on the characteristics, flavor, and stability of potato chips. Oil degradation during frying was monitored also by peroxide value (PV), free fatty acid (FFA) levels, and fatty acid compositional changes. Chips were fried in the different oils and stored 0 wk (fresh) and under fluorescent light or in the dark at 23°C for 2 and 4 wk. Chips were analyzed for color, moisture and oil contents, PV of chip oil, concentrations of volatile components, flavor desirability, and acceptability. The PV of each frying oil increased then decreased with increasing use. Free fatty acid content of frying oils increased with increasing use (4 hr frying) from 0.022 to 0.071% oleic acid. SU, CS, CA, and HOSU contained, respectively, 66.1, 57.4, 22.4, and 12.4% linoleic (C18:2) and 21.7, 16.4, 57.9, and 77.6% oleic (C18:l) acids. CS was most saturated containing 22.0% palmitic (C16:0). CA contained 9.7% linolenic acid (C18;3), and other oils, \u3c1%. The percentages of C16:0, C18:0, and C18:l increased with increasing oil use, but the levels of C18:2 and C18:3 decreased. Chips contained 1.26% moisture and 44.6% oil and had a mean L value of 54.3, chroma of 27.2, and hue angle of 88.3(yellowcolor). Oil from fresh chips had a mean PV of 4.4. Storage in dark did increased PV of oil in SU fried chips,butnotinCA,HOSUorCSfriedchips. Storage in light increased PV of oil in chips fried in all oils, but of SU fried chips the most. Twenty-four compounds were identified in chip volatiles, which included, 7 pyrazines, 3 alkanals, 4 alkenals, 3 alkadienals, 2-pentylfuran, 2-furaldehyde, benzaldehyde, 1-octen-3-ol, and phenyl- acetaldehyde. Concentrations of many aldehydes increased during storage in light but not in the dark. SU fried chips were most acceptable (like moderately to very much) of all chips. CA fried chips were less acceptable than CS fried chips but HOSU fried chips were just as acceptable as the CS fried chips. Storage in light or dark decreased flavor desirability in SU chips, and storage in light decreased flavor desirability in CS and CA chips but not in HOSU chips. SU and CS chips had higher levels of t,t-2,4- decadienal and CA chips higher levels of t,t-2,4-heptadienal. Increases in levels of hexanal, 2-furaldehyde and 2-nonenal in SU and CA chips during storage may have decreased flavor desirability while increasing concentrations of t,t-2,4-decadienal resulted in a less desirable flavor in the CA chips

A new instrumental method for measurement of thermal oxidative stability of oils with different saturation levels and additives

A computerized instrument (FriLife), which requires only two hours to measure the oxidative stability of oils/fats (200 g sample/test) by monitoring the progression of conductivity in a deionized water trap for oil degradation volatiles, was developed and tested. The linear slope (LS) of conductivity (range 4 to 11 µS/cm) versus time for each oil tested provided one FriLife measurement for oil stability. Conductivity measurements over time were converted to equivalent concentrations (mM) of acetic acid, and time required just to exceed 0.2 mM acetic acid or the induction time (IT) was a second FriLife measurement for oil stability. In one experiment, LS and IT were determined for soybean oils with iodine values (IV) of 70, 94, 110 and 132, and in another, LS and IT were determined for soybean oil (IV=94) alone or with additives (5 ppm dimethyl siloxane, DMS; 100 ppm tertiary-butylated hydroquinone, TBHQ; or their combination). The LS values for the soybean oils with IVs of 70, 94, 110 and 132 were all different (P \u3c 0.05) and were, respectively, 0.12, 0.24, 0.31, and 0.46 µS/cm min. The ITs of the soybean oils ranged from 95.5 min for the most saturated oil (IV=70) to 32.4 min for the most unsaturated one (IV=132). The LSs of soybean oil (IV=94) were greatly reduced, and the ITs increased by the addition of DMS, TBHQ, or both. FriLife also was able to measure the protective effect of DMS against thermal oxidation of oils where the Oxygen Stability Index (OSI) showed no difference. Across all oils, the coefficient of variations of LS and IT generally were less than 10 and 15%, respectively. While both IT and LS are highly correlated (P \u3c 0.05) with OSI (r ≥ |0.95|), the FriLife measurements require much less time than OSI measurement. The hydrogenated soybean oils had more tocopherol destruction (91.3% and 87.8% for IVs of 70 and 94, respectively) during a 200-min FriLife test than the soybean oil with IV of 132 (57.6%). Tested oil measurements (levels of total polar components, free fatty acids, Food Oil Sensor readings, and dienoic acids) generally showed that the more stable oils had lower levels than did the less stable oils. All levels of these measurements increased during the FriUfe test in all oils while the levels of polyunsaturated fatty adds decreased slightly. The Frillfe test Is proposed as a rapid, reproducible, accurate, and simple analytical method to analyze the oxidative stability of fats/oils

Soft Methodology for Cost-and-error Sensitive Classification

Many real-world data mining applications need varying cost for different types of classification errors and thus call for cost-sensitive classification algorithms. Existing algorithms for cost-sensitive classification are successful in terms of minimizing the cost, but can result in a high error rate as the trade-off. The high error rate holds back the practical use of those algorithms. In this paper, we propose a novel cost-sensitive classification methodology that takes both the cost and the error rate into account. The methodology, called soft cost-sensitive classification, is established from a multicriteria optimization problem of the cost and the error rate, and can be viewed as regularizing cost-sensitive classification with the error rate. The simple methodology allows immediate improvements of existing cost-sensitive classification algorithms. Experiments on the benchmark and the real-world data sets show that our proposed methodology indeed achieves lower test error rates and similar (sometimes lower) test costs than existing cost-sensitive classification algorithms. We also demonstrate that the methodology can be extended for considering the weighted error rate instead of the original error rate. This extension is useful for tackling unbalanced classification problems.Comment: A shorter version appeared in KDD '1

Personalized Acoustic Modeling by Weakly Supervised Multi-Task Deep Learning using Acoustic Tokens Discovered from Unlabeled Data

It is well known that recognizers personalized to each user are much more effective than user-independent recognizers. With the popularity of smartphones today, although it is not difficult to collect a large set of audio data for each user, it is difficult to transcribe it. However, it is now possible to automatically discover acoustic tokens from unlabeled personal data in an unsupervised way. We therefore propose a multi-task deep learning framework called a phoneme-token deep neural network (PTDNN), jointly trained from unsupervised acoustic tokens discovered from unlabeled data and very limited transcribed data for personalized acoustic modeling. We term this scenario "weakly supervised". The underlying intuition is that the high degree of similarity between the HMM states of acoustic token models and phoneme models may help them learn from each other in this multi-task learning framework. Initial experiments performed over a personalized audio data set recorded from Facebook posts demonstrated that very good improvements can be achieved in both frame accuracy and word accuracy over popularly-considered baselines such as fDLR, speaker code and lightly supervised adaptation. This approach complements existing speaker adaptation approaches and can be used jointly with such techniques to yield improved results.Comment: 5 pages, 5 figures, published in IEEE ICASSP 201

Augmented Reality Applied in Road Excavation System of Government

As one of the presentative novel technologies in recent years, Augmented Reality (AR) has gotten the ROC government’s attention, and thereby the AR-related applications have been taken into official account in facilitating citizen life. In this research, first, a sort-out of the definitions and the scope of three types of Realities—AR, VR, MR—will be offered to tell the much more realistic dimension of AR. Under the official road excavation context in X city via observation method, second, specific AR applications will be proposed by illustrating it in the pre-excavation, the excavation, and the post-excavation phases, respectively. By cross-referencing between the official road excavation system and public infrastructure pipeline databases, third, the related data of pipeline maps could endow the current AR positioning with better accuracy and directionality

Using the Balanced Scorecard to Evaluate the Value of Information Assets in Security Risk Management of Medical Care

Information technology has been widely applied in the fields of globally medical care, which makes the service apparently progress in its quality and efficiency. However, medical information that was stored in electronic form really causes the risk of leaking. A good security risk management offers a positive guarantee for hospitals, which highly relying on information technology, while running their organization. While carrying out risk analysis, the value of information assets, existing weakness, and potential threat from outside of this information system must be realized. It is quite important to determine the value of information assets for the security risk management. With information age coming, there is the greater part of asset value not shown from the traditional balance sheets in accounting books. This kind of asset, which can’t be shown on the balance sheet, is intellectual capital. In the study of information asset and intellectual capital, Ross et al. (1996) divided information assets into three kinds of capitals - human asset, technology asset and relationship asset. These play the same tune with the three key elements of intellectual capitals- human capital, structural capital and relational capital. Within numerous assessment methods of intellectual capital, balanced scorecard assesses intellectual capital value from the view of management and efficiency. Hence, this research proposes utilizing the balanced scorecard to find out the assessment index of information assets for domestic medical institutes while carrying on risk management. Hopefully, the results of this research can be regarded as the references of risk management of information security for domestic medical institutes

Assessing Social Capital Accumulation in Service System Development with Service-Dominant Logic View

Under the global trend of urbanization, a city ecosystem could be viewed as an integration of various service systems with the Service-Dominant Logic (S-DL) view. To study the composition of the service systems, social capital accumulation could be used to assess the resource distribution in the system development under the value-oriented perspectives of S-DL. Prior researches on related topics usually focused on the performance of social capital. This paper aims to assess social capital by studying the resource integration process, and to answer how social capital was accumulated along with the service system development. Grounded on the S-DL, this research studies the service system development of a traditional market revitalization project by actor-network analysis using the field data from a 30-month ethnographical work. A conceptual framework integrating social capital theory and S-DL perspective was developed. We demonstrate the process of evaluating the social capital generation and integration during value creation, which approaches its accumulation process. We anticipate the framework of accessing the social capital accumulation can reveal the structural holes of service systems by analyzing the accumulated conditions, facilitating the involved actors’ decision making, and communicating the value propositions with the public