Semi-automatic detection and counting of oil palm trees from high spatial resolution airborne imagery

Plantation inventory and management require a range of fine-scale remote-sensing data. Remote-sensing images with high spatial and spectral resolution are an efficient source of such information. This article presents an approach to the extraction and counting of oil palm trees from high spatial resolution airborne imagery data. Counting oil palm trees is a crucial problem in specific agricultural areas, especially in Malaysia. The proposed scheme comprises six major parts: (1) discrimination of oil palms from non-oil palms using spectral analysis, (2) texture analysis, (3) edge enhancement, (4) segmentation process, (5) morphological analysis and (6) blob analysis. The average accuracy obtained was 95%, which indicates that high spatial resolution airborne imagery data with an appropriate assessment technique have the potential to provide us with vital information for oil palm plantation management. Information on the number of oil palm trees is crucial to the ability of plantation management to assess the value of the plantation and to monitor its production.     

A review on hyperspectral remote sensing for homogeneous and heterogeneous forest biodiversity assessment

This review paper evaluates the potential of hyperspectral remote sensing for assessing species diversity in homogeneous (non-tropical) and heterogeneous (tropical) forest, an increasingly urgent task. Existing studies of species distribution patterns using hyperspectral remote sensing have used different techniques to discriminate different species, in which the wavelet transforms, derivative analysis and red edge positions are the most important of them. The wavelet transform is used based on its effectiveness and determined as the most powerful technique to identify species. Furthermore, estimations of relationships between spectral values and species distributions using chemical composition of foliage, tree phenology, selection of signature training sites based on field measured canopy composition, selection of the best wavelet coefficient and waveband regions may be useful to identify different plant species. This paper presents a summary on the feasibility, operational applications and possible strategies of hyperspectral remote sensing in forestry, especially in assessing its biodiversity. The paper also reviews the processing and analysis of techniques for hyperspectral data in discriminating different forest tree species.     

Cold temperature PM emissions measurement: method evaluation and application to light duty vehicles

This work examines the methodology to sample and measure the number and size of motor vehicle particulate emissions (PM) at subambient temperatures. The study has two principal objectives. The first is to address the following question: which aspects of the particle sampling, dilution, and size measurement process must be made at the vehicle test temperature to obtain an accurate representation of the PM emissions? The second is to perform a preliminary overview of how subambient temperature operation affects PM emissions from the major classes of current model light duty vehicles. The principal findings are the following: (1) The temperature of the particle size instruments, test cell versus room temperature, has little effect on the measurements. (2) Once the engine has warmed, solid particle (soot) mode emissions in the cold test cell are similar to those at room temperature. The first finding simplifies cold temperature emissionstesting because it allows particle sizing instruments to be placed outside the cold test cell and operated at room temperature. The latter is consistent with the expectation that solid particles are formed in the engine and are therefore relatively unaffected by ambient conditions after engine warm-up. Use of cold dilution air in the room-temperature test cell increases the number and size of nuclei particles; however, the effect of dilution airtemperature was inconclusive in the cold test cell.     

Feasibility and Fundamental Limits of Energy-Harvesting Based M2M Communications

Energy-efficient, reliable and scalable machine-to-machine (M2M) communications is the key technical enabler of Internet-of-Things (IoT) networks. Furthermore, as the number of populated devices is constantly increasing, self-sustaining or energy-autonomous IoT nodes are a promising prospect receiving increasing interest. In this paper, the feasibility and fundamental limits of energy harvesting based M2M communication systems are studied and presented. The derived theoretical bounds are effectively based on the Shannon theorem, combined with selected propagation loss models, assumed link nonidealities, as well as the given energy harvesting and storage capabilities. Fundamental limits and available operational time of the communicating nodes are derived and analyzed, together with extensive numerical results evaluated in different practical scenarios for low power sensor type communication applications.     

Self-destruction in Finnish motor traffic accidents in 1974-1992

The current study presents results of a survey of 3,215 calls received at seven centers of telephone emergency services (TES) in Israel during the Gulf War, when citizens of Israel experienced severe stress resulting from SCUD missile attacks. Whereas former surveys have shown that characteristics of calls to TES in Israel are generally not affected by external stressogenic events, a remarkable change was recorded in both the quantity and quality of calls received in TES centers in Israel during the Gulf War. The relative frequencies of problem categories presented by callers during the Gulf War revealed a significant increase in "environmental pressures," a category that reflected the stressful situation of the war, as opposed to intra- or interpersonal problems typical of peacetime calls. A comparison between this group of "war calls" and a control group of "nonwar calls," revealed that the two groups represented populations of callers differing in sociodemographic characteristics, expectations, and benefits from the calls. Results are discussed in reference to the unique role of TES as a source of psychological first-aid in a community crisis situation.     

Efficacy of adding detergents to sanitizer solutions for inactivation of Escherichia coli O157:H7 on Romaine lettuce

Numerous Escherichia coli O157:H7 outbreaks have been linked to consumption of fresh lettuce. The development of effective and easily implemented wash treatment could reduce such incidents. The purpose of this study was to evaluate the addition of food-grade detergents to sanitizer solutions for inactivation of E. coli O157:H7 on Romaine lettuce. Freshly-cut leaves of Romaine lettuce were dip-inoculated to achieve a final cell concentration of 7.8 ± 0.2 log CFU/g, air-dried for 2 h, and stored overnight at 4 °C. Leaves were then washed for 2 min in an experimental short chain fatty acid formulation (SCFA) or in one of the following solutions with or without 0.2% dodecylbenzenesulfonic acid or 0.2% sodium 2-ethyl hexyl sulfate: 1) deionized water; 2) 100 ppm chlorine dioxide; 3) 100 ppm chlorine; and 4) 200 ppm chlorine. Following wash treatment, samples were blended in neutralizing buffer (1:3) and surface plated on the selective media CT-SMAC. The efficacy of wash treatments, with or without the detergents, in inactivating E. coli O157:H7 cells on lettuce leaves were not significantly different. The most effective wash solution was SCFA, which was capable of reducing E. coli O157:H7 populations by more than 5 log CFU/g. The rest of the wash treatments resulted in a population reduction of less than 1 log CFU/g. The effectiveness of SCFA surpasses that of other sanitizer treatments tested in this study and requires further research to optimize treatments to preserve lettuce quality. Conventional detergents did not enhance the efficacy of any of the wash treatments tested during this study.     

Spectral discrimination of healthy and Ganoderma-infected oil palms from hyperspectral data

Although hyperspectral remote sensing has been used to study many agricultural phenomena such as crop stress and diseases, the potential use of this technique for detecting Ganoderma disease infestations and damage to oil palms under field conditions has not been explored to date. This research was conducted to investigate the feasibility of using a portable hyperspectral remote-sensing instrument to identify spectral differences between oil-palm leaves with and without Ganoderma infections. Reflectance spectra of samples representative of three classes of disease severity were collected. The most significant bands for spectral discrimination were selected from reflectance spectra and first derivatives of reflectance spectra. The significant wavelengths were identified using one-way analysis of variance. Then, a Jeffries–Matusita (JM) distance measurement was used to determine spectral separability between the classes. A maximum likelihood classifier method was used to classify the three classes based on the most significant wavelength spectral responses, and an error matrix was finally used to assess the accuracy of the classification.     

Modelling of a side reactor configuration combining reaction and distillation

A new software tool to simulate and optimise processes that combine distillation column with a reactor sequence has been developed. This kind of combination is particularly interesting when new intensified and integrated processes are developed. The unit block contains both the distillation column model and the models for the coupled reactors. The model equations are solved simultaneously in one block and not sequentially as it is done when the reactor/distillation systems are solved by present flowsheet programs. This software module has been implemented into a flowsheet simulator environment that contains all required physical and chemical data banks and enables large-scale process optimisation. The applicability of the new module is demonstrated by solving two presently interesting processes: production of MTBE and isooctene. The model has shown good convergence properties.     

Mass Measurement of Non-Spherical Particles: TDMA-ELPI Setup and Performance Tests

An ELPI was introduced to the TDMA setup for measurement of effective density and particle mass. This allows measurement of particle mass change also in cases when the particles are non-spherical or have voids. In addition to mass change of a particle, the density of transferred matter can be calculated if either unconditioned or conditioned particles are spherical and the bulk (material) density of the core particle is known. The performance of the system was tested by numerical simulations and laboratory experiments. According to the results, the smallest detectable particle mass change is approximately ± 17%. The measured density for the condensing species was within 15% of the bulk density value. Particle mass change caused by condensation of semi-volatile components of exhaust gas on diesel soot particles was also demonstrated.