Improving efficiency and Lifetime of Mobile Devices Using Cloud Environment

Mobile Cloud Computing is process to compute the resources between multiple mobile devices. The mobile users demand a certain level of quality of services (QoS) of their device. If the mobile change the interface gateway in the mobility of device. In this paper we are Identify, Formulate, and address the problem of QoS. The process of Bandwidth sifting and redistribution by interfacing gateway for maximizing their utility. The bandwidth sifting alone is not sufficient for maintaining QoS-guaranteed because of verifying spectral efficiency across the multiple channels.For maximum utility problem we formulate bandwidth redistribution and by using modified descending bid auction solved it. In the AQUM schema as per required amount of bandwidth we generate a big request in each gateway aggregate demand of the entire connecting mobile node. Simulation results establish the correctness of the proposed algorithm. Theoretically, we prove the convergence of AQUM by deduce the maximum and minimum selling prices of bandwidth DOI: 10.17762/ijritcc2321-8169.15076

Predicting DDoS Attacks Preventively Using Darknet Time-Series Dataset

The cyber crimes in today’s world have been a major concern for network administrators. The number of DDoS attacks in the last few decades is increasing at the fastest pace. Hackers are attacking the network, small or large with this common attacks named as DDoS. The consequences of this attack are worse as it disrupts the service provider’s trust among its customers. This article employs machine learning methods to estimate short-term consequences on the number and dimension of hosts that an assault may target. KDD Cup 99, CIC IDS 2017 and CIC Darknet 2020 datasets are used for building a prediction model. The feature selection for prediction is based on KDD Cup 99 and CIC IDS 2017 dataset; CIC Darknet 2020 dataset is used for prediction of impact of DDoS attack by employing LSTM (Long Short Term Memory) algorithm. This model can help network administrators to identify and preventively predict the attacks within five minutes of the commencement of the potential attack

Hiding Text in Audio Using LSB Based Steganography

A Steganographic method for embedding  textual information in WAV audio  is discussed here. In the proposed method each audio sample is converted into bits and then the textual information is embedded in it. In embedding process , first the message character is converted into its equivalent binary. The last 4 bits of this binary is taken into consideration and applying redundancy of the binary code the prefix either 0 or 1 is used. To identify the uppercase, lower case, space ,and number the control symbols in the form of binary is used. By using proposed LSB based algorithm, the capacity of stego system to hide the text increases. The performance evaluation is done on the basis of MOS by taking 20 samples and comparison of  SNR values with some known and proposed algorithm. Keywords: LSB, WAV, MOS , control symbols, stego system , SNR

Design and Development of Hydro-Optical Communication-Based Invasive Wireless Sensor Networks

The selection and implementation of a hydro-optical communication connection for real-time position tracking of remotely operated vehicles (ROVs) in underwater settings are the main topics of this research article. For a variety of applications, including pipeline maintenance, environmental research, and undersea infrastructure inspection, effective monitoring and control of ROVs is essential. Due to signal attenuation and interference, conventional communication techniques are difficult to use in aquatic environments. To get over these restrictions, hydro-optical communication, which sends light messages through water, presents a viable option. The paper examines current hydro-optical communication methods and technology, pointing out their benefits and drawbacks. It deals with the technical needs of setting up a trustworthy communication channel for monitoring the real-time location of ROVs. To ensure accurate and timely data delivery, an appropriate communication protocol is created. The research also demonstrates the smooth operation of hydro-optical communication with the ROV's navigation system. The suggested method is put into practise and tested in safe underwater environments in order to assess how well it works at pinpointing the position of ROVs. Among the performance indicators evaluated are data rate, communication range, and energy efficiency. The results of this study help to advance the area of underwater communication and make it easier to monitor and manage ROVs in real-time for a variety of underwater applications

Grapes Quality Prediction Using Iot & Machine Learning Based on Pre Harvesting

Minimizing pesticide use, preserving water, as well as enhancing soil health are just a few of the sustainable farming techniques that must be carefully considered while growing grapes of a high calibre. These practices can help preserve the environment and ensure the longevity of the vineyard. However, it is difficult for the farmers to find the suitability of the soil and its environment to cultivate grapes with high quality. Thus this research aims to evaluate the fitness of the soil for the fitness of growing quality grapes with the aid of machine learning algorithm. The research was done on Nasik region which is called as the “Grape Capital of India” situated in Maharashtra. Total of 154 villages were considered for the examination and soil specimens were collected and sent to the government testing lab in Maharashtra. The soil characteristics by considering both micro and macro nutrients, and the water characteristics were obtained from the lab. Also the climatic features, quality of the petiole and fruit characteristics were included for creating the dataset. These data was given to six different machine learning algorithm to classify the soil by defining whether the soil is fit for grapes or not. Moreover, this research proposed to analyze the correlation between the nutrients by which the relationship and dependency between the different nutrients and features were considered for defining the grapes quality. Also both the micro and macro nutrients were given equal importance in defining the soil quality suitable for obtaining high quality grapes. Based on the results obtained, Pimpalas Ramche contains more nutrients for the grape to grow more successfully based on samples gathered from different vine yards and the decision tree classifier scores better than any other classifiers among the machine learning algorithms employed in terms of accuracy

Early Breast Cancer Prediction using Machine Learning and Deep Learning Techniques

Breast Cancer (BC) is a considered as one of the utmost lethal diseases across the globe that has a very high morbidity and mortality rate. Accurate and early prediction along with diagnosis is one of the most crucial characteristics for the treatment of Breast Cancer. Doctors can have an edge over Breast cancer if they are able to predict it in its early stages using deep learning and machine learning techniques. This paper proposed consists of comparison between the and accuracy of various machine learning models like Support vector machine (SVM), K-Nearest Neighbours (KNN), Naïve Bayes (NB), Logistic Regression (LR), Random Forest (RF), Decision Tree (DT), XGB Classifier and deep learning model of Artificial neural networks (ANN) for the precise detection of breast cancer. The most crucial properties from the database have been chosen using one feature-selection technique. Correlation is also used to choose the most correlated features from the data. Implementing the ANN model consists of one input layer, two hidden layers, and one output layer. All Machine Learning models and ANN model are then applied to selected features. The results demonstrated that the SVM classifier achieved the highest performance with an accuracy of ~98.24%

A retrospective study to evaluate the pattern of spontaneously reported antiretroviral induced adverse drug reactions in a tertiary care hospital

Background: To evaluate the adverse effect profile of spontaneously reported cases of adverse drug reactions due to antiretroviral (ART) drugs in a tertiary care teaching hospital.Methods: A descriptive retrospective study of pattern of ART induced adverse drug reactions (ADRs) spontaneously reported to the Pharmacology department at a tertiary care hospital from January 2011 to December 2016. The details of suspected ADRs including drugs involved, treatment given for ADRs, and the outcome were also documented. These ADRs were analyzed for causality (WHO scale), severity (Hartwig et al. scale), seriousness (ICH E 2A guidelines), preventability (Schumock and Thornton scale) and type based on Edwards and Aronson classification system.Results: Of the 75 cases of ART induced ADRs, reactions were slightly more common in males (52%) and had median age and duration of ART as 36 years and 109 days respectively. Drug induced anemia was the most common presentation followed by cutaneous ADR and zidovudine being the commonest offender. Severity was moderate in 85.3% and causality was probable in 16% and possible in 84% cases. The type reaction was augmented type in 41.3% and not preventable in 76%.Conclusions: Zidovudine is the commonest drug implicated in causing anemia amongst the antiretrovirals. Spontaneous reporting method for antiretroviral pharmacovigilance is insufficient. Targeted spontaneous reporting or cohort event monitoring need to be studied for antiretroviral pharmacovigilance

Detection and Localization of Wireless Jammer using XBee module

Now days, wireless technologies has becomes more popular and affordable. In every field e.g. government sector, education, business, military, medical etc. use of wireless network have been increased which enables broad class of new applications. These applications make work easier and faster but one threat which is harmful i.e. jamming attack. The wireless jammer continually emits a radio signal along the same frequency that the wireless nodes use. Jamming technology generally does not discriminate between desirable and undesirable communication. A jammer can block all radio communication on any device that operates on radio frequencies within its range which create nuisance in our critical communication services. Most reliable solution to avoid nuisance is detection and localization of wireless jammer which helps to take further security actions. This project aims to detect wireless jammer and find the location of wireless jammer by experimental setup. DOI: 10.17762/ijritcc2321-8169.15017

Comparison of efficacy of levofloxacin-metronidazole combination versus ceftriaxone in cases of moderate diabetic foot infection

Background: Foot ulcers are a significant complication of diabetes and are the most common cause of non-traumatic lower extremity amputations in the industrialized world. Diabetic foot infections can be treated effectively with cephalosporins and fluoroquinolnes. The purpose of this study was to compare the efficacy, safety and microbiological outcomes of ceftriaxone and combination of levofloxacin and metronidazole.Methods: This was a prospective, open labelled, randomized controlled trial study. Patients diagnosed of having diabetic foot infection were recruited for the study from the OPD and IPD of the surgery department of Govt. Medical College and Hospital, Miraj and PVP Govt. Hospital, Sangli from June 2007 to December 2007. Signed informed consents were obtained from the patients. The study complied with declaration of Helsinki. Enrolled patients were randomized in 2 groups. Group 1: ceftriaxone group: patients were hospitalized and received ceftriaxone1 gm intravenously for 14 days. Group 2: levofloxacin and metronidazole group: patients were treated as out-patients and received Levofloxacin 500 mg orally once daily with metronidazole 400 mg orally thrice daily for 14 days. Detailed history and complete physical examination was done for all patients. Sequential measurement of the lesion was done, to assess the change in size. Bacteriological evaluation was done. Clinical and microbiological outcome and safety parameters were assessed after treatment.Results: The baseline characteristics in both the groups were comparable and were not significant with each other (p >0.05). In both the groups the most commonly isolated aerobe was staphylococci species followed by different species of enterobacteriacae and pseudomonas. Most commonly isolated anaerobe was bacteroides fragilis. Microbiological and clinical outcomes were assessed and the total no of patients recovered in both groups were almost similar. The percentage of wound healing in both the treatment groups was equal. None of the patients in both the groups had shown complete wound healing. The number of adverse effects associated with the therapies was also similar. The cost of therapies in both the groups were assessed and found the difference was highly significant.Conclusions: Even though combination of levofloxacin-metronidazole and ceftriaxone alone had similar outcomes in terms of efficacy, on contrary in comparison of cost and convenience, levofloxacin - metronidazole therapy was proved better than ceftriaxone in treatment of diabetic foot ulcers