Image compression based on 2D Discrete Fourier Transform and matrix minimization algorithm

In the present era of the internet and multimedia, image compression techniques are essential to improve image and video performance in terms of storage space, network bandwidth usage, and secure transmission. A number of image compression methods are available with largely differing compression ratios and coding complexity. In this paper we propose a new method for compressing high-resolution images based on the Discrete Fourier Transform (DFT) and Matrix Minimization (MM) algorithm. The method consists of transforming an image by DFT yielding the real and imaginary components. A quantization process is applied to both components independently aiming at increasing the number of high frequency coefficients. The real component matrix is separated into Low Frequency Coefficients (LFC) and High Frequency Coefficients (HFC). Finally, the MM algorithm followed by arithmetic coding is applied to the LFC and HFC matrices. The decompression algorithm decodes the data in reverse order. A sequential search algorithm is used to decode the data from the MM matrix. Thereafter, all decoded LFC and HFC values are combined into one matrix followed by the inverse DFT. Results demonstrate that the proposed method yields high compression ratios over 98% for structured light images with good image reconstruction. Moreover, it is shown that the proposed method compares favorably with the JPEG technique based on compression ratios and image quality

Improving The Algorithm To Detect Internet Worms

Worm detection and response systems must act quickly to identify and quarantine scanning worms, as when left unchecked such worms have been able to infect the majority of vulnerable hosts on the Internet in a matter of minutes [53]. Active worm spread in an automated fashion and can flood the internet in a very short time. The aim of this project is to improved algorithm to detect internet worm by two sub algorithm. The first is detecting the internet worm and the second is detecting stealth internet worm. A new equation created for depending on the average failure connection. The study based on the comparison and analysis of many worm detection and containment strategies. The principle of this effective algorithm is an improved two rotation process to detect and contain all types of internet worms

An Innovative Signature Detection System for Polymorphic and Monomorphic Internet Worms Detection and Containment

Most current anti-worm systems and intrusion-detection systems use signature-based technology instead of anomaly-based technology. Signature-based technology can only detect known attacks with identified signatures. Existing anti-worm systems cannot detect unknown Internet scanning worms automatically because these systems do not depend upon worm behaviour but upon the worm’s signature. Most detection algorithms used in current detection systems target only monomorphic worm payloads and offer no defence against polymorphic worms, which changes the payload dynamically. Anomaly detection systems can detect unknown worms but usually suffer from a high false alarm rate. Detecting unknown worms is challenging, and the worm defence must be automated because worms spread quickly and can flood the Internet in a short time. This research proposes an accurate, robust and fast technique to detect and contain Internet worms (monomorphic and polymorphic). The detection technique uses specific failure connection statuses on specific protocols such as UDP, TCP, ICMP, TCP slow scanning and stealth scanning as characteristics of the worms. Whereas the containment utilizes flags and labels of the segment header and the source and destination ports to generate the traffic signature of the worms. Experiments using eight different worms (monomorphic and polymorphic) in a testbed environment were conducted to verify the performance of the proposed technique. The experiment results showed that the proposed technique could detect stealth scanning up to 30 times faster than the technique proposed by another researcher and had no false-positive alarms for all scanning detection cases. The experiments showed the proposed technique was capable of containing the worm because of the traffic signature’s uniqueness

Integrated Social-sector Macroeconometric Model for Pakistan

While the traditional neoclassical production model postulates that it is the physical inputs such as private capital, labour, land, and technology that are the key determinants of output and economic development, in recent years, however, the social sector variables are also considered to be critical, particularly for the long-run sustainable growth of the economy. If fact, what has been argued in the form of “new growth theories” is that social variables (e.g., education, health, knowledge, etc.) generate “positive externalities” and, thus, may facilitate and foster the process of economic growth and development. Recently, the World Bank, based on a broad cross-country study, found some very interesting results in the above context. According to the World Development Report (1991): about fifty percent of the factor productivity contribution to output growth comes not from traditional physical inputs (capital, labour and land) but is a residual factor.

What Explains the Current High Rate of Inflation in Pakistan?

One of the most significant developments in the current economic scene in Pakistan has been the sharp increase in the rate of inflation. The annual average rate of increase in the wholesale price index (WPI) during the first seven months (July-January 1994-95) of the current fiscal year has been about 19 percent as opposed to 11.3 percent during the same period last year. A similar increase was also witnessed in the consumer price index (CPI) which accelerated to 13 percent as opposed to 11.1 percent during the previous period. Such a sharp increase in prices in recent months has not only caused alarm in the academic circles but has equally disturbed the country’s chief executive, the Prime Minister. The recent surge of inflation is a matter of serious concern for a variety of reasons. First, Pakistan has been a low-inflation country as it has experienced price stability during the last three decades. The rate of inflation, as measured by an increase in the WPI, averaged 2.6 percent during the 1960s. The components of the WPI, i.e., food, raw materials, manufactures, and fuel and lubricants, also grew by an average rate ranging from 2.0 to 3.4 percent p.a. during then 1960s (see Table 1 for relevant statistics). The rate of inflation crossed the single-digit threshold during the 1970s. The WPI and its components increased at an annual average rate ranging from 12 to 18 percent. The double-digit inflation during the 1970s has been the result of two major oil shocks, a massive devaluation of currency, and devastating floods destroying agricultural crops. Pakistan returned to the fold of the single-digit inflation during the 1980s. The rate of inflation remained at the single-digit level during the first three years of the 1990s with the exception of 1990-91, when the rate of inflation increased to 11.7 percent as a result of the Gulf War. It is only during the outgoing fiscal year and in the current year that the rising inflation is posing a major threat to macroeconomic stability.

The effect of polluted samples on Bayesian Estimators of Burr type –XII distribution

Bayesian estimators may be affected by the polluted samples, because these samples can lead to the influence of the estimation methods in general and the Bayesian methods in particular, and thus the deviation of the values of the distribution parameter from their real values, and this leads to the divergence of the capabilities of the Bayes survival estimators from the real values. The results showed that the estimators of the parameters were affected by many factors (sample size, distribution parameter, number of outliers and the estimation method). Simulation experiment results also showed a difference in Mean Square Error (MSE) of the Bayes survival estimators for each different experiment. Bayesian methods can be compared with other estimation methods (Maximum likelihood Estimation (MLE), Moment estimation (MOM) and shrinkage method (SH)). Also, Bayesian methods can be used to estimate the survival function of other distributions (exponential, Gamma and mixed) to observe the estimation results with the presence of extreme values

Efficacy of fine needle aspiration cytology in the diagnosis of lymphadenopathies

Background: Enlarged lymph nodes were the first organs to be diagnosed by fine needle aspiration. Objectives were to study the role of FNAC in the evaluation of lymphadenopathies, to study the various cyto-morphological patterns in correlation with histopathology of various lymph node lesions and to document the diagnostic accuracy of FNAC in correlation with histopathology.Methods: All patients referred to the department of pathology K.V.G. Medical College and Hospital, Sullia, Karnataka, India for FNAC of palpable lymph nodes were included in present study. FNAC was done and the standard method for the procedure adopted. All the slides were reviewed and their diagnosis was made. FNAC diagnosis was compared with histopathology in cases which underwent surgical excision and thus its diagnostic accuracy determined. This was two years and two months’ prospective study from July 2008 to August 2010.Results: A total of` 150 patients were included in the present study, reported to various clinical departments with history of swelling. Lymph node biopsy was done in 50 cases. Statistical analysis was done in 50 cases, where FNAC diagnosis was correlated well with histopathological diagnosis. Maximum number of cases was in the age group of 31-40 years. Present study showed female preponderance of cases. Cervical group of nodes were most commonly involved. Benign lymphadenopathies were diagnosed in 69.8% of cases. Maximum number of cases being reactive lymphadenitis (65.4%). Metastatic deposit was diagnosed in 23.5% of cases. Most common subtype being adenocarcinoma. Lymphomas were diagnosed in 09 cases. 1 case of Hodgkin’s lymphoma and 8 cases of NHL were diagnosed. The overall correlation between FNAC and histopathology was 98% (49 out of 50).Conclusions: FNAC is an accurate, sensitive, specific and cost effective procedure in the diagnosis of lymphadenopathies

IoT and Neural Network-Based Water Pumping Control System For Smart Irrigation

This article aims at saving the wasted water in the process of irrigation using the Internet of Things (IoT) based on a set of sensors and Multi-Layer Perceptron (MLP) neural network. The developed system handles the sensor data using the Arduino board to control the water pump automatically. The sensors measure the environmental factors; namely temperature, humidity, and soil moisture to estimate the required time for the operation of water irrigation. The water pump control system consists of software and hardware tools such as Arduino Remote XY interface and electronic sensors in the framework of IoT technology. The machine learning algorithm such as the MLP neural network plays an important role to support the decision of automatic control of IoT-based irrigation system, managing the water consumption effectively.Comment: 6 pages, 5 figures, 1 tabl

Fluoride in the drinking water of Pakistan and the possible risk of crippling fluorosis

To explore the possibility of fluoride toxicity, 747 water samples were collected from surface water and groundwater sources of 16 major cities of Pakistan, adopting a uniform sampling design with distribution of samples: Lahore (79), Kasur (46), Faisalabad (30), Khushab (50), Chakwal (51), Mianwali (30), Jhelum (53), Bahawalpur (60), Karachi (60), Mirpur Khas (55), Peshawar (38), Risalpur (35), Quetta (81), Ziarat (21), Loralai (21), and Mastung (37). Comparison of analytical findings with WHO Guidelines of Drinking Water for Fluoride (i.e., 1.5 ppm) has concluded that 16% of the monitored water sources have fluoride concentration beyond the permissible safe limit of 1.5 mg L^−1 falling in the concentration range of 1.6–25 mg L^−1. The highest fluoride contamination (22%) is detected in the Balochistan province followed by 19% in Punjab province. Comparatively higher fluoride levels of > 20% in the groundwater sources like hand pumps supported the possibility of increased groundwater contamination as excessive fluoride concentrations are expected to come from calcium-poor aquifers and in areas where fluoride-bearing minerals are common or where cation exchange of sodium for calcium occurs. Field observations have also indicated the prevalence of fluoride-associated health implications in the study areas with excessive fluoride in water sources. Findings of this study have provided bidirectional vision for the epidemiological investigations as well as to mitigate the issues in the affected vicinities of fluoride-rich areas