Waste management methods and sustainablity

© Springer International Publishing Switzerland 2015. Waste in its different forms is a significant environmental issue that receives a great deal of attention worldwide. Waste is generated as a result of production and consumption (domestic and industrial) activities and tends to increase with the level of prosperity and economic development of the country. Cost efficient, technology-based and sustainable management of both solid and liquid waste is crucial to economic growth and development of a healthy society in any given region. This chapter reviews traditional as well as modern approaches to solid waste management (SWM) and wastewater treatment. Sustainable methods of waste reduction, waste reuse and recycling are the preferred options when managing waste. There are many environmental benefits that can be derived from the use of these methods. They reduce or prevent greenhouse gas emissions, lessen the release of pollutants, conserve resources, save energy and minimise the demand for waste treatment technology and space. Establishment of sanitary landfills that meet standard hygienic requirements is the most widely adopted method of disposing of solid waste in developed countries. Vermicomposting and biogas technology produce reusable manure and combustible gas respectively from organic solid waste while waste-to-energy (incineration of waste) has quickly emerged as one of the most attractive renewable energy options. Wastewater if not properly disposed of, could be hazardous to human health and environment. Natural aquatic and terrestrial treatment systems with the environment-friendly designs and low-cost sanitation provide benefits for the reuse of water. Wise uses of aquatic and terrestrial plants are a means of several natural wastewater treatment methods. A decentralized wastewater treatment is being considered for most communities because of its economic and environmental advantages. Apart from natural treatment methods, membrane technology, nanotechnology, microbial fuel cells and electrocoagulation offer newer approaches to handling wastewater in a sustainable manner. The overall sustainable development ensures the path of reconciliation for society, environment, and economy in the long-term. People who generate waste, institutions who handle it and the local governance are key partners in an efficient waste management system. Need for education to create awareness on the importance of waste treatment and the sustainability aspects of the emerging technologies remains critical at all societal and governmental levels. Applications of information and communication technologies offer ingenious solutions to the problem of waste management

Stock Market Returns and Direction Prediction: An Empirical Study on Karachi Stock Exchange

There has been much research in the recent past on the predictability of stock return, mainly due to its significance in managing economic gains on a high scale. Our research initiates the forecasting of the Karachi stock return with the help of the Wavelet analysis and Empirical mode decomposition method. This paper attends in large part to investors and traders to deduce a method for predicting the stock market. The collected data ranges from Jan 2009 to Dec 2012. Every training set is selected from January through October and the sets left over are used for testing. What we have discovered is that Empirical Mode decomposition (EMD) method supersedes all other models on the Mean square error and Mean Absolute error criteria. We may also evaluate the performance of these models by changing strategy direction and comparing payoffs to understand which framework performs as a better forecasting model. It is establishes by the results of the study that the same model serves better for forecasting in trading strategy and could rule over other possible models for most periods under consideration. It is our belief that this study will help stock investors to come to quick decisions about optimal buying or selling time in Karachi Stock Exchange Key Words: Forecasting, KSE (Karachi Stock Exchange) 100 Index, Empirical Mode Decomposition, Trading Strateg

Parametric entropy based Cluster Centriod Initialization for k-means clustering of various Image datasets

One of the most employed yet simple algorithm for cluster analysis is the k-means algorithm. k-means has successfully witnessed its use in artificial intelligence, market segmentation, fraud detection, data mining, psychology, etc., only to name a few. The k-means algorithm, however, does not always yield the best quality results. Its performance heavily depends upon the number of clusters supplied and the proper initialization of the cluster centroids or seeds. In this paper, we conduct an analysis of the performance of k-means on image data by employing parametric entropies in an entropy based centroid initialization method and propose the best fitting entropy measures for general image datasets. We use several entropies like Taneja entropy, Kapur entropy, Aczel Daroczy entropy, Sharma Mittal entropy. We observe that for different datasets, different entropies provide better results than the conventional methods. We have applied our proposed algorithm on these datasets: Satellite, Toys, Fruits, Cars, Brain MRI, Covid X-Ray.Comment: 6 Pages, 2 tables, one algorithm. Accepted for publication in IEEE International Conference on Signal Processing and Computer Vision (SPCV-2023

Monitoring bacterial diversity in a full-scale municipal wastewater treatment plant in dubai by fluorescence in situ hybridization technique

In this study, the bacterial diversity in the activated sludge system of a full-scale municipal wastewater treatment plant in Dubai was monitored over a period of one year using ribosomal RNA (rRNA) targeted oligonucleotide probes for a defined phylogenetic group of bacteria by the Fluorescence in situ hybridization (FISH) technique. The largest fraction of the bacterial community in the sludge samples belonged to the gamma-subgroup of proteobacteria (25%) followed by gram positive bacteria of high G+C content(16%), gram positive bacteria with low G+C content (9 %), beta-proteobacteria (8%) and alpha-proteobacteria (5 %) with respect to the population percentages stained by DAPI (4,6-diamino-2-phenylindole). A specific nocardioform actinomycete, simultaneously targeted by both HGC69a and MNP1 probes, was predominantly found throughout the study period in all activated sludge mixed liquor samples. The nocardioform actinomycetes group members were detected in both branched and single cell morphotypes. Most of the previously published genus and species specific probes failed to hybridize to the sludge samples. In conclusion, the overall bacterial community populations detected by the sub-group specific 16S rRNA targeted oligonucleotide probes in FISH technique remained almost constant throughout the period of study irrespective of treatment plant conditions

Quantum Dots: Application for the Detection of Salmonella typhimurium

Quantum dots (QDs) or nanocrystals 5 to 50 nm in size have recently emerged as a novel and promising class of fluorophores for cellular imaging. Unlike conventional organic dyes, QDs can be excited by a wide spectrum of wavelengths to give enhanced photostability, and their emission spectra, which differ according to size and material composition, are narrow, symmetrical, and tunable. This novel detection strategy can significantly improve the efficiency of molecular techniques used in the identification of important microbes related to human diseases. The aim of this study was to apply QDs linked antibodies to detect pathogenic Salmonella typhimurium cells. The signal, photostabilty and efficiency of QDs linked antibodies was compared with the organic fluorophore linked antibody for the detection of Salmonella cells. The use of QDs as fluorophores has shown greater enhancement in photostability and brighter signal than conven-tional organic dyes in detecting S. typhimurium cells. This approach might also be extended for the simultaneous detection of more than one pathogenic microorganism in the clinical, food or environmental samples by using specific antibodies linked with the QDs of different sizes and colors

Numerical Solution of Airy Differential Equation by Using Haar Wavelet

Haar wavelet is exceedingly simple and optimized completely for computers, so that it can be used for solving ordinary differential equations and partial differential equations without a hassle. In this paper, numerical solutions of Airy differential equations have been obtained by using the Haar Wavelet Method . Comparisons with exact solutions make clear that the Haar Wavelet Method is a powerful candidate for solving the Airy differential equation. Moreover the use of Haar wavelets is found to be accurate, uncomplicated, speedy, adaptable and convenient with very small computation costs and the extra perk of being computationally attractive. Key Words: Orthogonal Wavelet, Airy Equation, Function Approximation, Operational Matri

Dual Beta Modeling of Karachi Stock Exchange

In the past three decades, the documentation of many features of returns in equity market has been noticed. But less attention has been paid to the feature attacks more commenting else, namely that there are extensive periods of time when equity prices rise and fall colloquially, these periods of time referred to as bull and bear markets respectively. The purpose of this research is to study the betas in the bull and bear market condition for a sample of stocks in the Karachi Stock Market (KSE), major stock market in Pakistan. The data consist of daily returns of two major sectors (Petroleum & Commercial banks) of KSE during the period of February 1997 to December 2007. The data pertains to the daily adjusted closing prices of 15 scripts that form a part of KSE index. This paper investigates whether betas of bull and bear market are statistically different from each other? KSE does not integrate any distribution so we use t-statistics.  Analysis shows that beta is higher when the market is bearish than that when market is bullish for nine stocks while the reverse is true for other six stocks. Keywords: Portfolio Beta, Portfolio Returns, KSE, Dual Bet

Forecasting Gold Price: Evidence from Pakistan Market

In our day to day life, predictability of gold’s prices is significant in many domains such as economics financial and political environment. The main objective of this research is to forecasts the prices of gold, making use of ARIMA and two distinct versions of wavelet scheme. The monthly data consists of 221 observations starting from Dec 2005 to April 2013, has been used in this research. After evaluating the accuracy of these models by mean absolute error and mean square error, it turns out that wavelet neural transformation has better prediction accuracy than rest of the models. Also, this study utilizes the return forecasts from the above mentioned different models in a simple trading strategy and compare pay offs in order to know as to which framework serves a better forecasting model. Keywords: Gold Price, ARIMA, Wavelet, Multiple Regression, Wavelet Neural Transform, Error Analysi

Privacy Preserving Internet Browsers: Forensic Analysis of Browzar

With the advance of technology, Criminal Justice agencies are being confronted with an increased need to investigate crimes perpetuated partially or entirely over the Internet. These types of crime are known as cybercrimes. In order to conceal illegal online activity, criminals often use private browsing features or browsers designed to provide total browsing privacy. The use of private browsing is a common challenge faced in for example child exploitation investigations, which usually originate on the Internet. Although private browsing features are not designed specifically for criminal activity, they have become a valuable tool for criminals looking to conceal their online activity. As such, Technological Crime units often focus their forensic analysis on thoroughly examining the web history on a computer. Private browsing features and browsers often require a more in-depth, post mortem analysis. This often requires the use of multiple tools, as well as different forensic approaches to uncover incriminating evidence. This evidence may be required in a court of law, where analysts are often challenged both on their findings and on the tools and approaches used to recover evidence. However, there are very few research on evaluating of private browsing in terms of privacy preserving as well as forensic acquisition and analysis of privacy preserving internet browsers. Therefore in this chapter, we firstly review the private mode of popular internet browsers. Next, we describe the forensic acquisition and analysis of Browzar, a privacy preserving internet browser and compare it with other popular internet browser