VOLUME 8, ISSUE 10, OCTOBER 2019

Abstract: A system is said to be extensible; if any modifications can be made to any of the existing system functionalities in addition of new functionalities with minimum impact. To attain extensibility, it has to be scheduled properly starting from the initial stage of the system development life cycle. Keeping in mind all the probable upcoming modifications to be made, the software designer should select the appropriate design patterns and finish the design for the application. As soon as the application design is finished, it must be examined to make sure that the application is extensible. This research paper recommends a research framework for Extensibility evaluation process and does an extensive review on extensibility of object oriented software. A metrics based Extensibility Evaluation Model for Object Oriented Design” has been recommended by creating the relationship in the middle of design properties. Consecutively researchers justifying the model correlation with the help of statistical measures, which shows that for all  the System, Coupling, Cohesion, Inheritance, Polymorphism are highly correlated with Extensibility. The developed model has been authenticated by experimental tryout. Finally, it incorporates the empirical validation of the extensibility evaluation model as the author’s most important contribution. In Conclusion, Hypothesis testing is performed to test the significance of r (Correlation Coefficient) using 2-tailed test for a 95% confidence interval with different degrees of freedom. As a result, the researcher’s claim of correlating Extensibility with Coupling, Cohesion, Inheritance and Polymorphism at design phase is statistically extremely justified.

Keywords: Extensibility, Reusability, Flexibility, Extensibility, Maintainability, Scalability, Design Phase, Object Oriented Design, Software Quality, Product Transition

Abstract: An ad hoc mobile network is a set of autonomous nodes; these nodes can send and receive data independently. Security is a major concern for MANET because ad hoc networks are based on trust; each node of a network depends on its neighboring node, each node of a network works well as a router. Now, if a malicious node in that system is a great challenge for researchers. In this paper, we perform a detailed analysis of various types of attacks in mobile ad hoc networks (such as denial of service attacks, investigations, user attacks against root, vampire attacks, etc.) To protect the network against such vulnerabilities, a system capable of mitigating these attacks on the network is needed. Therefore, we have performed a detailed search on various types of intrusion detection systems. After studying the IDS, we conclude that all the above approaches have their advantages and disadvantages, but one thing that is common to all is that the detection rate of hybrid attacks is low, Therefore, we have proposed a new technique in which we use a support vector machine, as well as a dendritic cell algorithm that classifies abnormal and normal data traffic according to its acquired rules, as well as the predefined rules taught by this system. Likewise it is capable of difference between normal data and abnormal data. The proposed IDS approach is equipped with a learning algorithm used to form the support vector machine. Wireless network that achieves high accuracy to detect hybrid attacks, as well as normal and heterogeneous behaviors. The DCA and SVM classifiers will reach a detection rate of 100% (fixed duration).

Keywords: MANET, R2L, U2R, IDS, SVM, MAC

Abstract: In Mobile Ad hoc NETwork (MANET), routing is one of the most important problems and is widely studied in the world. Routing greatly affects performance of the network. In this paper, we compare performance of two famous protocols the Ad hoc On-Demand Distance Vector Routing (AODV) and Dynamic Source Routing (DSR) in terms of Packet Delivery Fraction, Delay, Routing overhead and Nomalize Routing Load. Simulation results show that the AODV’ packet delivery fraction outperforms that of the DSR in some cases. Our results also show that AODV‘Delay is less than DSR but AODV’Routing overhead and Nomalize Routing Load are more than the corresponding results from the DSR.

Keywords: Mobile Ad Hoc Networks; Routing Protocol; AODV; DSR.

Abstract: The need for security cannot be overemphasized in today’s modern world, where residential and industrial fire outbreaks, gas leakages, over-current destructions, theft, suffocation from gas accumulations etc. are increasing alarmingly and becomes a major source of threat and environmental hazards. Current security systems in developing countries (if and when available) treat security as only intrusion based, and are of high operational and setup cost and thus the need for a smart and more integrated security system. The GSM based smart security system using Arduino presented employs the Passive Infrared (PIR), MQ2, MQ7 and the DHT 11 sensors in monitoring intrusion, combustible gases, carbon monoxide and temperature threats respectively  and also incorporates remote monitoring and control capability. The concept of remote monitoring and control is implemented via the use of SMS and mobile phone calls respectively made possible by utilizing the SIM900 GSM module interface. The two operational modes - internal and external mode reduces the overall operational cost of the system and thus Remote monitoring (SMS), is used only when the owner is actually away, while audio and visual forms of alarms are utilized if he is close by the property. The entire system is controlled by the powerful Arduino Uno. The system resulted in a cost saving, smart, portable and a more efficient way of implementing security alarm systems.

Keywords: Arduino, remote monitoring, premises alarm security systems, GSM

Abstract: The Internet plays a vital role in day-to-day human life activities. It became essential to protect these human activities from unknown internet threats such as Cyber terrorism, Identity theft and many others from the same category. There exist many approaches, which deliver security to some extent, but the ultimate goal of the efficient intrusion detection system is still a challenging task. A data mining based intrusion detection system is proposed in this paper. The proposed intrusion detection system ensures the use of feature extraction and feature selection for data mining and processing. A Packet sniffer based approach works well for network packet tracking, which is used by the proposed intrusion detection system. Data mining along with proper decision support tool can work effectively for intrusion detection. The proposed system works efficient and accurate when tested with KDDCup’99 data. Keywords: Decision Support Tool, Intrusion Detection, Feature Eradication, Entropy Function, Feature Election

Abstract: Multipliers are main building block of ALU, which improves the speed of many functions like Fourier transformation, digital filters and Digital Signal Processor (DSP).  For any function we need to reduce the delay in system. Vedic mathematics provides mathematical approaches to increased speed and reduced power consumption as in comparison to conventional multiplier designs. Vedic multiplication algorithm with Vedic mathematics Urdhava Tiryakbhyam Sutra (UTS) method and Carry Select Adder (CSA) technique are useful to reduce power. UTM means vertically and cross wise vedic mathematics. It is ancient Indian technique used for decimal number multiplications. The speed of the computation process is increased and the processing time is reduced due to decrease of combinational path delay compared to the existing multipliers. Leakage power and low speed has become a general issue in circuit design. In our proposed multiplication algorithm, we get less time delay compared to other algorithms. In this paper, Low Power Vedic Architecture is designed reviewed. These Vedic multiplier architectures are decrease in the power consumption and generate the results faster. Keywords: VLSI, CSA, Vedic Multiplier, RCL, High Speed, Urdhava Tiryakbhyam Sutra

Abstract: Since lot of forgeries occur in our day to day life, security and surveillance has become a mandatory aspect. Over the last few decades, face recognition has become a popular area of research in computer vision. This system may be implemented in real time systems requiring user authentication such as attendance systems, ATM security, Electronic Passports and Network security. Our project aims in developing precise way of detecting faces using an algorithm called ”Eigen face detection” which uses Principal Component Analysis(PCA). The algorithm involves comparison of trained samples with the query images. If the trained samples matches with the query images, then the detected face is a “known face”. If there is a mismatch, then the detected face is a “new face”. PCA extracts the eigen values and eigen vectors for the given set of samples in the PCA-sub space and compares it with the new values during run time. Then the threshold value is calculated from these eigen faces. If the new face value is less than the threshold, then it is a “known face”. Otherwise, he/she must be a new user. This algorithm is implemented using python on a Raspberry pi module in which the raspberry camera is used to extract the face values. The Face values are displayed on a 659M10 LCD so that it could act as an alarm in door security system.

Keywords: Arduino, Touchless Interface, Micro Controller, Capacitive Sensing

Abstract: The increase in the amount of information available online has made it a difficult job to search for unique documents and relevant information. This in turn also creates a problem to find the correct required piece of information with a lot of time spent in browsing and searching. And we come up with a faster and more accurate way to make training easier in this process. Today, with the upcoming e-learning trends, the system not only aims to provide efficient searches but also provides the desired information to a consolidated material and provides various tools such as useful links and videos to make our system a reliable and comprehensive source for the user's needs. A process series, namely data cleaning, tokenization, and frequency calculation and log-likelihood function, is performed on all articles in this method after collecting the data of the article. In contrast to measuring the byte structure, it considers the capacity of Natural Language so that more accuracy can be obtained during the measure of similarity. During the estimation of text frequency, it performs pre-processing and inverse report frequency. Pre-processing is performed using a standard set of stop words that also provides almost accurate measurements. The following framework makes it possible to use the different data mining techniques to pre-process a report before uploading it and to identify the main topic covered by the post. Later on, searching we get the article whose match for feature vector of the search query is the highest; this is another step into the world of e-learning. Keywords: Data Cleaning, e-Learning, Tokenization, Natural Language

Abstract: Virtualization can be seen as a significant part of a general example in big business IT that incorporates autonomic registering, a situation where in the IT condition will in all likelihood manage itself reliant on saw movement, and utility figuring, in which PC preparing force is viewed as an utility that customers can pay for similarly as required. The typical objective of virtualization is to unify regulatory missions while improving adaptability and undertaking. Different software has been installed in The Higher Institute of Telecommunications & Navigation laps, some software is missing in some PC's, needs upgrade and reinstallation. This research will review one of Application virtualization arrangement that permits multiuser remote access to local programming virtualization server from any gadget, anyplace, whenever and utilizing different platforms. By creating this server, all instructors and students can use the updated software from the central server whether in LAPs Pc's or from instructor private PC's or gadgets. As a result, this virtualized server will solve software inaccessibility and defective issued in all LAPs PC's will likewise permit all organization segments to remotely associate with this server and utilize the software, will defiantly reduce the effort and cost to software installation and maintenance.

Keywords: Virtualization Software, Vmware, Hyper-V, Vsphere, Citrix Hypervisor

Abstract: Analysis of automation that have near large data storage and storage networking. Data centers and cost reduction have driven the steady adoption of virtual server technologies. It centers on collating the system framework of the different building blocks of storage networks. With the assist of SAN,DAS and NAS, storage can be meticulously applied. Both technologies alternative the need to eliminate direct attached storage to aid more elastic storage access. Induced by peoples and software which is running applications and in this used different types of data format which is test, video, audio and images. DAS uses the IDE, SCSI, SATA, etc protocols and SAN uses the Fiber Channel, iSCSI, FoE, etc protocols to provide the storage facility. NAS is a device that is based on a network and it is used for sharing non-storage traffic.NAS is shareable .NAS provides some features such that provisioning, replication and snapshots .NAS can be costly.SAN provide the dedicated network for storage  devices and the processors that access those devices .SAN used fiber channel technology for sharing data fatly .Replication can be done in SAN storage. The NAS and SAN can be used in industry to providing network protocols for managing storage. Solid State Disks is a type of non-volatile storage media that stores persistent data on solid-state flash memory.  It optimized to deliver high read and write performance for both sequential and random data request. It refers to flash drive or solid-state disks.

Keywords: DAS, NAS and SAN Protocols Compare with SSD

Abstract: Machine Learning is a subset of Artificial Intelligence (AI). Huge set of data is provided to the machine which is trained using Logistic Regression algorithm. We have acquired data from real-time motion sensors continuously over a long period of time. Along with historical data stored in the database, the present runtime data is analysed and used to train the machine. The machine is provided with enough data to learn for itself creating a predictive model with a particular accuracy. Ultrasonic sensors [1] are mounted at different orientations, continuously gathering data of the ether. The data acquired is then analysed, visualized and used for future predictions/ conclusions. Accuracy check is carried out to verify the exactness of the predicted data. In this paper we carry out data visualization procedure and statistical analysis of the data which was acquired in our previous assignment, ‘Motion Detection and Prediction Using ML: Logistic Regression’. The acquired data is made to correspond to a particular Fuzzy Logic by means of programming.

Keywords: Fuzzy Logic, Data Analytics and Machine Learning, Data pre-processing, Logistic regression, accuracy, precision, F1 score