Municipal Solid Waste: Pre-Treatment Options and Benefits on Landfill Emissions

Municipal solid waste (MSW) comprises of a wide range of heterogeneous materials generated by individual, household or organization and may include food waste, garden wastes, papers, textiles, rubbers, plastics, glass, ceramics, metals, wood wastes, construction wastes but it is not limited to the above mentioned fractions. The most common Municipal Solid Waste pretreatment method in use is thermal pretreatment (incineration) and Mechanical Biological pretreatment. This paper presents an overview of these two pretreatment methods describing their benefits and laboratory scale reactors that simulate landfill conditions were constructed in order to compare emissions in terms of biogas production and leachate contamination between untreated Municipal Solid Waste and Mechanical Biological Pretreated waste. The findings of this study showed that Mechanical Biological pretreatment of waste reduces the emission level of waste and the benefit over the landfilling of untreated waste is significant.

Sous Vide Packaging Technology Application for Salad with Meat in Mayonnaise Shelf Life Extension

Experiments have been carried out at the Latvia University of Agriculture Department of Food Technology. The aim of this work was to assess the effect of sous vide packaging during the storage time of salad with meat in mayonnaise at different storage temperature. Samples were evaluated at 0, 1, 3, 7, 10, 15, 18, 25, 29, 42, and 52 storage days at the storage temperature of +4±0.5 ºC and +10±0.5 ºC. Experimentally the quality of the salad with meat in mayonnaise was characterized by measuring colour, pH and microbiological properties. The sous vide packaging was effective in protecting the product from physical, chemical, and microbial quality degradation. The sous vide packaging significantly reduces microbial growth at storage temperature of +4±0.5 ºC and +10±0.5 ºC. Moreover, it is possible to extend the product shelf life to 52 days even when stored at +10±0.5 ºC.

A Novel Receiver Algorithm for Coherent Underwater Acoustic Communications

In this paper, we proposed a novel receiver algorithm for coherent underwater acoustic communications. The proposed receiver is composed of three parts: (1) Doppler tracking and correction, (2) Time reversal channel estimation and combining, and (3) Joint iterative equalization and decoding (JIED). To reduce computational complexity and optimize the equalization algorithm, Time reversal (TR) channel estimation and combining is adopted to simplify multi-channel adaptive decision feedback equalizer (ADFE) into single channel ADFE without reducing the system performance. Simultaneously, the turbo theory is adopted to form joint iterative ADFE and convolutional decoder (JIED). In JIED scheme, the ADFE and decoder exchange soft information in an iterative manner, which can enhance the equalizer performance using decoding gain. The simulation results show that the proposed algorithm can reduce computational complexity and improve the performance of equalizer. Therefore, the performance of coherent underwater acoustic communications can be improved greatly.

Equivalence Class Subset Algorithm

The equivalence class subset algorithm is a powerful tool for solving a wide variety of constraint satisfaction problems and is based on the use of a decision function which has a very high but not perfect accuracy. Perfect accuracy is not required in the decision function as even a suboptimal solution contains valuable information that can be used to help find an optimal solution. In the hardest problems, the decision function can break down leading to a suboptimal solution where there are more equivalence classes than are necessary and which can be viewed as a mixture of good decision and bad decisions. By choosing a subset of the decisions made in reaching a suboptimal solution an iterative technique can lead to an optimal solution, using series of steadily improved suboptimal solutions. The goal is to reach an optimal solution as quickly as possible. Various techniques for choosing the decision subset are evaluated.

Arterial CO2 Pressure Drives Ventilation with a Time Delay during Recovery from an Impulse-like Exercise without Metabolic Acidosis

We investigated this hypothesis that arterial CO2 pressure (PaCO2) drives ventilation (V.E) with a time delay duringrecovery from short impulse-like exercise (10 s) with work load of 200 watts. V.E and end tidal CO2 pressure (PETCO2) were measured continuously during rest, warming up, exercise and recovery periods. PaCO2 was predicted (PaCO2 pre) from PETCO2 and tidal volume (VT). PETCO2 and PaCO2 pre peaked at 20 s of recovery. V.E increased and peaked at the end of exercise and then decreased during recovery; however, it peaked again at 30 s of recovery, which was 10 s later than the peak of PaCO2 pre. The relationship between V. E and PaCO2pre was not significant by using data of them obtained at the same time but was significant by using data of V.E obtained 10 s later for data of PaCO2 pre. The results support our hypothesis that PaCO2 drives V.E with a time delay.

Multiple Job Shop-Scheduling using Hybrid Heuristic Algorithm

In this paper, multi-processors job shop scheduling problems are solved by a heuristic algorithm based on the hybrid of priority dispatching rules according to an ant colony optimization algorithm. The objective function is to minimize the makespan, i.e. total completion time, in which a simultanous presence of various kinds of ferons is allowed. By using the suitable hybrid of priority dispatching rules, the process of finding the best solution will be improved. Ant colony optimization algorithm, not only promote the ability of this proposed algorithm, but also decreases the total working time because of decreasing in setup times and modifying the working production line. Thus, the similar work has the same production lines. Other advantage of this algorithm is that the similar machines (not the same) can be considered. So, these machines are able to process a job with different processing and setup times. According to this capability and from this algorithm evaluation point of view, a number of test problems are solved and the associated results are analyzed. The results show a significant decrease in throughput time. It also shows that, this algorithm is able to recognize the bottleneck machine and to schedule jobs in an efficient way.

Combined Feature Based Hyperspectral Image Classification Technique Using Support Vector Machines

A spatial classification technique incorporating a State of Art Feature Extraction algorithm is proposed in this paper for classifying a heterogeneous classes present in hyper spectral images. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes in the hyper spectral images are assumed to have different textures, textural classification is entertained. Run Length feature extraction is entailed along with the Principal Components and Independent Components. A Hyperspectral Image of Indiana Site taken by AVIRIS is inducted for the experiment. Among the original 220 bands, a subset of 120 bands is selected. Gray Level Run Length Matrix (GLRLM) is calculated for the selected forty bands. From GLRLMs the Run Length features for individual pixels are calculated. The Principle Components are calculated for other forty bands. Independent Components are calculated for next forty bands. As Principal & Independent Components have the ability to represent the textural content of pixels, they are treated as features. The summation of Run Length features, Principal Components, and Independent Components forms the Combined Features which are used for classification. SVM with Binary Hierarchical Tree is used to classify the hyper spectral image. Results are validated with ground truth and accuracies are calculated.

Comparison of Fricative Vocal Tract Transfer Functions Derived using Two Different Segmentation Techniques

The acoustic and articulatory properties of fricative speech sounds are being studied using magnetic resonance imaging (MRI) and acoustic recordings from a single subject. Area functions were derived from a complete set of axial and coronal MR slices using two different methods: the Mermelstein technique and the Blum transform. Area functions derived from the two techniques were shown to differ significantly in some cases. Such differences will lead to different acoustic predictions and it is important to know which is the more accurate. The vocal tract acoustic transfer function (VTTF) was derived from these area functions for each fricative and compared with measured speech signals for the same fricative and same subject. The VTTFs for /f/ in two vowel contexts and the corresponding acoustic spectra are derived here; the Blum transform appears to show a better match between prediction and measurement than the Mermelstein technique.

The Impact of the Type of Diversification of Listed Construction Enterprises in China on Corporation Performance

The construction industry is the pillar industry in China, accounting for about 6% of the gross domestic product. Along with changes in the external environment of the construction industry in China, the construction firm faces fierce competition. The paper aims to investigate the relationship between diversified types of construction firm and its performance in China. Based on generalist and specialist strategy in organizational ecology, we think a generalist organization can be applied to an enterprise with diversified developments, while specialist groups are extended to professional enterprises .This study takes advantage of annual financial data of listed construction firm to empirically verify the relationship between diversification and corporation performance establishing a regression equation to econometric analysis. We find that: 1) Specialization can significantly improve the level of profitability of listed construction firms, and there is a significant positive relationship with corporate performance; 2) The level of operating performance of listed construction enterprises which engage in unrelated diversification is higher than those with related diversification; 3) The relationship between state-owned construction firms and corporate performance is negative. The more the year of foundation is, the higher performance will be; however, the more the year of being listed, the lower performance will be.

Forecasting the Istanbul Stock Exchange National 100 Index Using an Artificial Neural Network

Many studies have shown that Artificial Neural Networks (ANN) have been widely used for forecasting financial markets, because of many financial and economic variables are nonlinear, and an ANN can model flexible linear or non-linear relationship among variables. The purpose of the study was to employ an ANN models to predict the direction of the Istanbul Stock Exchange National 100 Indices (ISE National-100). As a result of this study, the model forecast the direction of the ISE National-100 to an accuracy of 74, 51%.

Mainland Chinese Customers' Intention toward Medical Tourism in Taiwan

This study proposes and tests a rescapturing elements of perceived gain and loss that, by perceived value of medical tourism products, influencintention of potential customers. Data from 301 usable qwere tested against the research model using the structmodeling approach. The results indicated that perceivedkey predictor of customer intentions. As for benefimedical quality, service quality and enjoyment wcomponents that significantly influenced the perceptiRegarding sacrifice, the effects of perceived risk on pewere significant. The findings can provide insights intohow destination countries can make medical tourism a wfor themselves and international patients.KeywordsMedical tourism, perceived valueintention.

A Preference-Based Multi-Agent Data Mining Framework for Social Network Service Users' Decision Making

Multi-Agent Systems (MAS) emerged in the pursuit to improve our standard of living, and hence can manifest complex human behaviors such as communication, decision making, negotiation and self-organization. The Social Network Services (SNSs) have attracted millions of users, many of whom have integrated these sites into their daily practices. The domains of MAS and SNS have lots of similarities such as architecture, features and functions. Exploring social network users- behavior through multiagent model is therefore our research focus, in order to generate more accurate and meaningful information to SNS users. An application of MAS is the e-Auction and e-Rental services of the Universiti Cyber AgenT(UniCAT), a Social Network for students in Universiti Tunku Abdul Rahman (UTAR), Kampar, Malaysia, built around the Belief- Desire-Intention (BDI) model. However, in spite of the various advantages of the BDI model, it has also been discovered to have some shortcomings. This paper therefore proposes a multi-agent framework utilizing a modified BDI model- Belief-Desire-Intention in Dynamic and Uncertain Situations (BDIDUS), using UniCAT system as a case study.

IKEv1 and IKEv2: A Quantitative Analyses

Key management is a vital component in any modern security protocol. Due to scalability and practical implementation considerations automatic key management seems a natural choice in significantly large virtual private networks (VPNs). In this context IETF Internet Key Exchange (IKE) is the most promising protocol under permanent review. We have made a humble effort to pinpoint IKEv2 net gain over IKEv1 due to recent modifications in its original structure, along with a brief overview of salient improvements between the two versions. We have used US National Institute of Technology NIIST VPN simulator to get some comparisons of important performance metrics.

Javanese Adolescents- Future Orientation and Support for its Effort: An Indigenous Psychological Analysis

This study aimed to explore future life orientation and support that needed to accomplish it. A total of 258 participants are Javanese high school student. The age of the sample ranges from 14 to 18 years old. Participants were asked about their future aspiration, their reason of choosing them as important goals in their life, and support that they need to accomplished their goals using open ended questionnaire. The responses were categorized through content analysis into four main categories. They are: (1) Self Fulfillment (72.1%) (2) Parents and Family (16.7%) (3) Altruism (8.1%) (4) Social and Economy Status (3.1%). Meanwhile, the categories for support that they needed are shown as follows: (1) Affection Support (64.7%) (2) Spiritual support (17.4%) (3) Material Support (10.9%) (4) Guidance Support (7.0%). The research found that affection support always gets the highest number in every future orientation categories. It can be concluded that although Javanese adolescents have different future orientation, they basically need affection support.

Pleurotus sajor-caju (PSC) Improves Nutrient Contents and Maintains Sensory Properties of Carbohydrate-based Products

The grey oyster mushroom, Pleurotus sajor-caju (PSC), is a common edible mushroom and is now grown commercially around the world for food. This fungus has been broadly used as food or food ingredients in various food products for a long time. To enhance the nutritional quality and sensory attributes of bakery-based products, PSC powder is used in the present study to partially replace wheat flour in baked product formulations. The nutrient content and sensory properties of rice-porridge and unleavened bread (paratha) incorporated with various levels of PSC powder were studied. These food items were formulated with either 0%, 2%, 4% or 6% of PSC powder. Results show PSC powder recorded β-glucan at 3.57g/100g. In sensory evaluation, consumers gave higher score to both rice-porridge and paratha bread containing 2-4% PSC compared to those that are not added with PSC powder. The paratha containing 4% PSC powder can be formulated with the intention in improving overall acceptability of paratha bread. Meanwhile, for rice-porridge, consumers prefer the formulated product added with 4% PSC powder. In conclusion, the addition of PSC powder to partially wheat flour can be recommended for the purpose of enhancing nutritional composition and maintaining the acceptability of carbohydrate-based products.

Plants Cover Effects on Overland Flow and on Soil Erosion under Simulated Rainfall Intensity

The purpose of this article is to study the effects of plants cover on overland flow and, therefore, its influences on the amount of eroded and transported soil. In this investigation, all the experiments were conducted in the LEGHYD laboratory using a rainfall simulator and a soil tray. The experiments were conducted using an experimental plot (soil tray) which is 2m long, 0.5 m wide and 0.15 m deep. The soil used is an agricultural sandy soil (62,08% coarse sand, 19,14% fine sand, 11,57% silt and 7,21% clay). Plastic rods (4 mm in diameter) were used to simulate the plants at different densities: 0 stem/m2 (bared soil), 126 stems/m², 203 stems/m², 461 stems/m² and 2500 stems/m²). The used rainfall intensity is 73mm/h and the soil tray slope is fixed to 3°. The results have shown that the overland flow velocities decreased with increasing stems density, and the density cover has a great effect on sediment concentration. Darcy–Weisbach and Manning friction coefficients of overland flow increased when the stems density increased. Froude and Reynolds numbers decreased with increasing stems density and, consequently, the flow regime of all treatments was laminar and subcritical. From these findings, we conclude that increasing the plants cover can efficiently reduce soil loss and avoid denuding the roots plants.

Generalized Exploratory Model of Human Category Learning

One problem in evaluating recent computational models of human category learning is that there is no standardized method for systematically comparing the models' assumptions or hypotheses. In the present study, a flexible general model (called GECLE) is introduced that can be used as a framework to systematically manipulate and compare the effects and descriptive validities of a limited number of assumptions at a time. Two example simulation studies are presented to show how the GECLE framework can be useful in the field of human high-order cognition research.

Behavior of Optical Fiber Aged in CTAC Solutions

The evolution of silica optical fiber strength aged in cetyltrimethylammonium chloride solution (CTAC) has been investigated. If the solution containing surfactants presents appreciable changes in physical and chemical properties at the critical micelle concentration (CMC), a non negligible mechanical behavior fiber change is observed for silica fiber aged in cationic surfactants as CTAC which can lead to optical fiber reliability questioning. The purpose of this work is to study the mechanical behavior of silica coated and naked optical fibers in contact with CTAC solution at different concentrations. Result analysis proves that the immersion in CTAC drastically decreases the fiber strength and specially near the CMC point. Beyond CMC point, a small increase of fiber strength is analyzed and commented.

Simulation and Experimentation on the Contact Width of New Metal Gasket for Asbestos Substitution

The contact width is important design parameter for optimizing the design of new metal gasket for asbestos substitution gasket. The contact width is found have relationship with the helium leak quantity. In the increasing of axial load value, the helium leak quantity is decreasing and the contact width is increasing. This study provides validity method using simulation analysis and the result is compared to experimental using pressure sensitive paper. The results denote similar trend data between simulation and experimental result. Final evaluation is determined by helium leak quantity to check leakage performance of gasket design. Considering the phenomena of position change on the convex contact, it can be developed the optimization of gasket design by increasing contact width.

Emotion Recognition Using Neural Network: A Comparative Study

Emotion recognition is an important research field that finds lots of applications nowadays. This work emphasizes on recognizing different emotions from speech signal. The extracted features are related to statistics of pitch, formants, and energy contours, as well as spectral, perceptual and temporal features, jitter, and shimmer. The Artificial Neural Networks (ANN) was chosen as the classifier. Working on finding a robust and fast ANN classifier suitable for different real life application is our concern. Several experiments were carried out on different ANN to investigate the different factors that impact the classification success rate. Using a database containing 7 different emotions, it will be shown that with a proper and careful adjustment of features format, training data sorting, number of features selected and even the ANN type and architecture used, a success rate of 85% or even more can be achieved without increasing the system complicity and the computation time