Application of the line-width method to the spectrochemical analysis of oils,fats, and related substances

Summary The application of the line-width method to the spectrochemical analysis of oils and fats in conjunction with the use of an improved ashing technique has been shown to permit the quantitative determination of copper, iron, manganese, nickel, and tin in quantities as low as 1 part in 10 million. The procedure has been critically examined by precision tests on commercial and experimental samples, by accuracy tests on synthetic samples, and by recovery tests. Results of actual analysis of 30 vegetable oils and fats indicate the use of the procedure as a research tool. The procedure may be used for the trace element analysis of organic material low in ash content. One of the laboratories of the Bureau of Agricultural and Industrial Chemistry, Agricultural Research Administration, U. S. Department of Agriculture.     

Enhanced multiclass SVM with thresholding fusion for speech-based emotion classification

As an essential approach to understanding human interactions, emotion classification is a vital component of behavioral studies as well as being important in the design of context-aware systems. Recent studies have shown that speech contains rich information about emotion, and numerous speech-based emotion classification methods have been proposed. However, the classification performance is still short of what is desired for the algorithms to be used in real systems. We present an emotion classification system using several one-against-all support vector machines with a thresholding fusion mechanism to combine the individual outputs, which provides the functionality to effectively increase the emotion classification accuracy at the expense of rejecting some samples as unclassified. Results show that the proposed system outperforms three state-of-the-art methods and that the thresholding fusion mechanism can effectively improve the emotion classification, which is important for applications that require very high accuracy but do not require that all samples be classified. We evaluate the system performance for several challenging scenarios including speaker-independent tests, tests on noisy speech signals, and tests using non-professional acted recordings, in order to demonstrate the performance of the system and the effectiveness of the thresholding fusion mechanism in real scenarios.     

Analytical performance of soft clustering protocols

The success of a mobile ad hoc network (MANET) is strongly related to the protocol used at the medium access control (MAC) layer. Depending on the requirements and the specific network under concern, the protocol parameters at the MAC layer can be arbitrated to make best use of the channel resources. Typically, extensive simulation studies are used to find the best values for these variables. The problem with this approach is the need for excessive amounts of processing power and time. As the dimensions of the decision space increase, the need for processing power grows exponentially. This paper addresses this problem by developing an analytical model that reflects the relationships between protocol parameters and the overall performance of the protocol under various network conditions. Specifically, we model the MH-TRACE cluster-based protocol, which is capable of supporting real-time data transmission. The model is capable of estimating performance measures such as energy consumption and number of receptions while being simple enough to be run for a large set of parameters. The model can be used to optimize parameters of the protocol (such as the number of frames per superframe) as well as to predict the performance variations as the external conditions (such as data generation rate) vary.     

An application-specific protocol architecture for wireless microsensor networks

Networking together hundreds or thousands of cheap microsensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. These networks require robust wireless communication protocols that are energy efficient and provide low latency. We develop and analyze low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality. LEACH includes a new, distributed cluster formation technique that enables self-organization of large numbers of nodes, algorithms for adapting clusters and rotating cluster head positions to evenly distribute the energy load among all the nodes, and techniques to enable distributed signal processing to save communication resources. Our results show that LEACH can improve system lifetime by an order of magnitude compared with general-purpose multihop approaches.     

Flooding Strategy for Target Discovery in Wireless Networks

In this paper, we address a fundamental problem concerning the best flooding strategy to minimize cost and latency for target discovery in wireless networks. Should we flood the network only once to search for the target, or should we apply a so-called “expansion ring” mechanism to reduce the cost? If the “expansion ring” mechanism is better in terms of the average cost, how many rings should there be and what should be the radius of each ring? We separate wireless networks based on network scale and explore these questions. We prove that two-ring and three-ring schemes can reduce the cost of flooding compared to a single attempt, and we provide a general formula to determine good parameters for the two-ring and three-ring hop-based flooding schemes. Through simulations, we show that choosing flooding parameters according to our techniques gives performance close to that of ideal flooding schemes. Afterwards, we extend our work from the single target discovery problem to the multi-target discovery problem. We show that a properly chosen searching radius can save much more searching cost than a simple radius selection scheme for multi-target discovery problems.     

General Network Lifetime and Cost Models for Evaluating Sensor Network Deployment Strategies

In multihop wireless sensor networks that are often characterized by many-to-one (convergecast) traffic patterns, problems related to energy imbalance among sensors often appear. Sensors closer to a data sink are usually required to forward a large amount of traffic for sensors farther from the data sink. Therefore, these sensors tend to die early, leaving areas of the network completely unmonitored and reducing the functional network lifetime. In our study, we explore possible sensor network deployment strategies that maximize sensor network lifetime by mitigating the problem of the hot spot around the data sink. Strategies such as variable-range transmission power control with optimal traffic distribution, mobile-data-sink deployment, multiple-data-sink deployment, nonuniform initial energy assignment, and intelligent sensor/relay deployment are investigated. We suggest a general model to analyze and evaluate these strategies. In this model, we not only discover how to maximize the network lifetime given certain network constraints but also consider the factor of extra costs involved in more complex deployment strategies. This paper presents a comprehensive analysis on the maximum achievable sensor network lifetime for different deployment strategies, and it also provides practical cost-efficient sensor network deployment guidelines.     

Spectrophotometric estimation of soybean oil in admixture with cottonseed and peanut oils

Conclusion A spectrophotometric method has been described for the determination of soybean oil in admixture with cottonseed oil. The method provides a simple and rapid means of detecting gross adulteration of one oil with another and permits an accurate determination of linolenic acid for use as a criterion of the economic value of an oil mixture and as a guide in oil processing. The factor limiting the precision of the method is variation in composition of the cottonseed and soybean oils in the mixtures to be analyzed. Variations in composition affect the proportion of measured triene conjugation, due to the linolenic acid content of the soybean oil and the apparent linolenic acid content of the cottonseed oil. Thus, for unknown mixtures only average value corrections can be made for apparent linolenic acid content and the accuracy of a particular analysis will depend upon how well the composition of the oils in the particular mixture follows those of the average mixture. The method described can be extended to mixtures other than those of soybean and cottonseed oils. Thus, soybean oil may be determined in admixture with a peanut oil. In general, any oil which has an unsaturated fatty acid capable of producing triene conjugation upon alkali isomerization can be determined in the presence of any other oil containing no appreciable quantity of unsaturated fatty acids which can produce triene conjugation by such treatment. Presented before The American Oil Chemists’ Society, New Orleans, Louisiana, May 10–12, 1944. One of the laboratories of the Bureau of Agricultural and Industrial Chemistry, Agricultural Research Administration, U. S. Department of Agriculture.     

A method for the determination of linoleic acid and conjugated dienoic acids in materials containing eleostearic acids

Summary A procedure has been described which extends the scope of the spectrophotometric method for polyun-saturated acids to the determination of linoleic and conjugated acids in the presence of large quantities of conjugated trienoic acids. Basis for the proposed method rests on equations which are offered to correct the “end” or “back-ground” absorption of the highly absorbing triene conjugated acids at 233 mμ, the position of maximum absorption of conjugated dienoic acids and alkali isomerized linoleic acids. The method is limited to samples which do not contain nonconjugated trienoic acids (linolenic acids). The method has been tested by the analysis of several mixtures of cottonseed and dehydrated castor oils of known composition, to which varying amounts of alpha, beta, and mixtures of alpha- and beta-eleostearic acids have been added. These samples have been used to demonstrate the application of the proposed method for the determination of dienoic conjugated acids, alpha-eleostearic acid, beta-eleostearic acid linoleic acid, oleic acid, and total saturated fatty acids. Comparisons of the results obtained with similar values, calculated from the known composition of the mixtures, prove that the proposed method gives reasonable results. Standard deviations between determined and calculated results vary from 0.36 for diene conjugated acids to 1.40 for oleic acid. The method has been applied to the analysis of foreign and domestic tung oils. Presented before the American Oil Chemists' Society, Cincinnati, O., Oct. 20–22, 1952. One of the laboratories of the Bureau of Agricultural and Industrial Chemistry, Agricultural Research Administration, U. S. Department of Agriculture.     

Energy-Scalable Protocols for Battery-Operated MicroSensor Networks

In wireless sensor networks, the goal is to gather information from a large number of sensor nodes and communicate the information to the end-user, all under the constraint of limited energy resources. Network protocols minimize energy by using localized communication and control and by exploiting computation/communication tradeoffs. In addition, data fusion algorithms such as beamforming aggregate data from multiple sources to reduce data redundancy and enhance signal-to-noise ratios, thus further reducing the required communications. We have developed a sensor network system that uses a localized clustering protocol and beamforming data fusion to enable energy-efficient collaboration. We compare the performance of two beamforming algorithms, the Maximum Power and the Least Mean Squares (LMS) beamforming algorithms, using the StrongARM SA-1100 processor. Results show that the LMS algorithm requires less than one-fifth the energy required by the Maximum Power beamforming algorithm with only a 3 dB loss in performance, thus showing that the LMS algorithm is better suited for energy-constrained systems. We explore the energy-scalability of the LMS algorithm, and we propose an energy-quality scalable architecture that incorporates techniques such as variable filter length, variable voltage supply and variable adaptation time.