Information and Technology

TCP/IP has become an undeniable leader in the areas of Information Technology. It is a well-established fact that data transfer between devices occur by the rules defined by the TCP/IP protocol. Each layer of TCP/IP model generally has more than one protocol for carrying out the functions that the layer complies to. TCP/IP model is used widely and it is essential to understand how different protocols work to provide different functionalities. In this article, through the deep consideration of TCP/IP protocol the understanding of the protocols at five layers of TCP/IP is specified.

- Result of “the Onlife Initiative,” a one-year project funded by the European Commission to study the deployment of ICTs and its effects on the human condition
- Inspires reflection on the ways in which a hyperconnected world forces the rethinking of the conceptual frameworks on which policies are built
- Draws upon the work of a group of scholars from a wide range of disciplines including, anthropology, cognitive science, computer science, law, philosophy, political science

What is the impact of information and communication technologies (ICTs) on the human condition? In order to address this question, in 2012 the European Commission organized a research project entitled The Onlife Initiative: concept reengineering for rethinking societal concerns in the digital transition. This volume collects the work of the Onlife Initiative. It explores how the development and widespread use of ICTs have a radical impact on the human condition.

ICTs are not mere tools but rather social forces that are increasingly affecting our self-conception (who we are), our mutual interactions (how we socialise); our conception of reality (our metaphysics); and our interactions with reality (our agency). In each case, ICTs have a huge ethical, legal, and political significance, yet one with which we have begun to come to terms only recently.

The impact exercised by ICTs is due to at least four major transformations: the blurring of the distinction between reality and virtuality; the blurring of the distinction between human, machine and nature; the reversal from information scarcity to information abundance; and the shift from the primacy of stand-alone things, properties, and binary relations, to the primacy of interactions, processes and networks.

Such transformations are testing the foundations of our conceptual frameworks. Our current conceptual toolbox is no longer fitted to address new ICT-related challenges. This is not only a problem in itself. It is also a risk, because the lack of a clear understanding of our present time may easily lead to negative projections about the future. The goal of The Manifesto, and of the whole book that contextualises, is therefore that of contributing to the update of our philosophy. It is a constructive goal. The book is meant to be a positive contribution to rethinking the philosophy on which policies are built in a hyperconnected world, so that we may have a better chance of understanding our ICT-related problems and solving them satisfactorily.

The Manifesto launches an open debate on the impacts of ICTs on public spaces, politics and societal expectations toward policymaking in the Digital Agenda for Europe’s remit. More broadly, it helps start a reflection on the way in which a hyperconnected world calls for rethinking the referential frameworks on which policies are built.

Breast cancer is a top killer disease for women globally. The long term survival rate of women can be improved through early and effective screening of breast cancer cells. Currently, a mammogram is the recommended tool for breast cancer screening since it can identify breast cancer cells several years before physical signs appear and it is cost effective. This paper analyzes mammographic detection of breast cancer by providing an explanation on development and classification of Breast Cancer, Image representation models for breast tumor, mammography technologies, a discussion on various mammographic signs of breast cancer, breast cancer feature extraction techniques, popular breast cancer classification techniques, comparative analysis of existing mammogram breast cancer databases, and a review of mammographic breast cancer detection studies are presented. Finally, a highlight on future work is given.

The main purpose of this paper is to examine some (potential) applications of quantum computation in AI and to review the interplay between quantum theory and AI. For the readers who are not familiar with quantum computation, a brief introduction to it is provided, and a famous but simple quantum algorithm is introduced so that they can appreciate the power of quantum computation. Also, a (quite personal) survey of quantum computation is presented in order to give the readers a (unbalanced) panorama of the field. The author hopes that this paper will be a useful map for AI researchers who are going to explore further and deeper connections between AI and quantum computation as well as quantum theory although some parts of the map are very rough and other parts are empty, and waiting for the readers to fill in.

Sustaining technologies and innovations are important driving forces behind the modern day business and the working space. Sustaining technology and innovation enables businesses to improve their products and services in a way that makes them compete with competitors in the same market space. The Internet and social media platforms are sustaining technologies and innovations that are currently altering the economic, social and political landscapes by changing the way people live, do business and work. Proper and informed usage of these technologies in business can have the potentials of empowering entrepreneurs economically, socially as well as contributing to environmental conservation and protection. This research sought to develop a model that would encourage utilization of the Internet and social media platforms by women entrepreneurs of small businesses in rural areas. This was achieved by analyzing Internet usage, evaluating social media platforms usage by women entrepreneurs in rural parts of Siaya County in Kenya and developing a model of utilization of the Internet and social media platforms for sustainable development. The six social media platforms that were evaluated are Facebook, Twitter, WhatsApp, Instagram, LinkedIn and YouTube. The target population was women entrepreneurs of small businesses in Siaya County. Cochran formula was used to calculate the ideal sample size and sample size of 272 was used. A response rate of 91.91% was achieved. Simple random sampling was used to select one county out of 45 counties and snowball sampling technique was used to select the respondents. Questionnaires were used to collect data. The reliability of the research tool was arrived at using composite reliability test and Cronbach’s Alpha test whereas the validity of the research instrument was assessed using content and construct validity. Ethical issues arising from the research such as informed voluntary consent, no harm to participants, confidentiality of information and data integrity were accounted for. Data analysis was done using PLS-SEM statistical model and descriptive, inferential and predictive statistics that encompassed regression and correlation were used to analyze the data and develop and validate the model. The validity of the model was assessed and approved by ten SME experts and its applicability in business for sustainable development of entrepreneurs of small businesses was ascertained through simulation. The purpose of the study was achieved.

In today’s society, most if not all sectors digitize and automate in order to become more efficient. The increasing availability and sophistication of software technologies disrupt labor markets by making workers redundant. Within this context, a significant change is companies’ introduction of chatbots as a supplement to human customer support is vital. Chatbots are computer programs that interact with humans through natural language. The purpose of chatbots is to simulate a human conversation in response to natural language input through text or voice. There seems to be no proper guidelines for adoption of chatbots for provision of customer care support services in telecommunication industry in Kenya. The aim of this research was to develop a framework for adoption of artificially intelligent chatbot application in telecommunication industry. This was achieved through determination of the status of implementation of chatbots in Kenya and identification of key metrics that served as indicators for chatbot adoption. The metrics were identified through review of previous technology adoption frameworks and models. The study adopted mixed methods where qualitative and quantitative data was collected using interview schedules and questionnaires respectively. Content analysis was used in analyzing qualitative data. Quantitative data was analyzed descriptively and results were presented using tables. The target population included experts in the field of AI in two telecommunication firms in Kenya. The study sample was drawn, using Delphi technique, from the two telecommunication firms. The descriptive and principal component analysis were utilized. The results of this research study will be crucial to all telecommunication firms in guiding them on the most effective and efficient way of adopting AI chatbot application for customer support services.

The present review reports the work done by the various authors towards rainfall forecasting using the different techniques within Artificial Neural Network concepts. Back-Propagation, Auto-Regressive Moving Average (ARIMA), ANN , K- Nearest Neighbourhood (K-NN), Hybrid model (Wavelet-ANN), Hybrid Wavelet-NARX model, Rainfall-runoff models, (Two-stage optimization technique), Adaptive Basis Function Neural Network (ABFNN), Multilayer perceptron, etc., algorithms/technologies were reviewed. A tabular representation was used to compare the above-mentioned technologies for rainfall predictions. In most of the articles, training and testing, accuracy was found more than 95%. The rainfall prediction done using the ANN techniques was found much superior to the other techniques like Numerical Weather Prediction (NWP) and Statistical Method because of the non-linear and complex physical conditions affecting the occurrence of rainfall.

Identifying indices of effort in post-editing of machine translation can have a number of applications, including estimating machine translation quality and calculating post-editors’ pay rates. Both source-text and machine-output features as well as subjects’ traits are investigated here in view of their impact on cognitive effort, which is measured with eye tracking and a subjective scale borrowed from the field of Educational Psychology. Data is analysed with mixed-effects models, and results indicate that the semantics-based automatic evaluation metric Meteor is significantly correlated with all measures of cognitive effort considered. Smaller effects are also observed for source-text linguistic features. Further insight is provided into the role of the source text in post-editing, with results suggesting that consulting the source text is only associated with how cognitively demanding the task is perceived in the case of those with a low level of proficiency in the source language. Subjects’ working memory capacity was also taken into account and a relationship with post-editing productivity could be noticed. Scaled-up studies into the construct of working memory capacity and the use of eye tracking in models for quality estimation are suggested as future work.

Prediction of reservoir yield is an important for fisheries managers to use appropriate scientific management practices to increase the fishery production. Many mathematical or applied mathematics and Artificial Neural Networks models were developed to predict fish production forecast of reservoirs. Ecology of reservoirs is dynamic, extraordinarily advanced and nonlinear in nature. There are several drivers have an effect on the fisheries, both internal and external environmental parameters. Many researchers have assessed fish yield potential based on leaner models using multiple linear regressions. Accurate modelling to predict fish yield of the reservoirs and lakes helps to understand behaviour of the system and managers can formulate appropriate management practices to improve fish yield. This paper provides an in-depth review on existing model developed from simple empirical estimation to high-level non-linear model for assessing fishery potential of lakes and reservoirs.

This paper discusses the concept of "human disenhancement", i.e. the worsening of human individual abilities and expectations through technology. The goal is provoking ethical reflection on technological innovation outside the biomedical realm, in particular the substitution of human work with computer-driven automation, and drawing useful analogies between this and future biomedical enhancements. According to some widely accepted economic theories, automatization and computerization are responsible for the disappearance of many middle-class jobs. I argue that, if that is the case, a technological innovation can be a cause of "human disenhancement", globally, and all things considered, even when the local and immediate effect of that technology is to increase the demand of more sophisticated human skills than the ones they substitute. Two conclusions are reached: 1) current innovations in the ICT sector are objectionable from a moral point of view, because they disenhance more people than they enhance; 2) even cheap and widely accessible technological enhancements can contribute to inequality. These conclusions are morally relevant in themselves and provide a cautionary tale about biological enhancement technologies, which, similarly, may turn out to be morally objectionable even if cheap and available to all.

Scientific writing is a technical form of writing that is designed to communicate scientific information to other scientists. Scientific writing is predicated on the rigors of scientific inquiry; therefore, it must reflect the same precision as that demanded in the research process. Successful scientific writing depends on the individual writer’s projection of a shared professional context. Writers seek to embed their writing in a particular social world which they reflect and conjure up through approved discourses. The objective of scientific writing is to record data and all ideas which must be supported by evidence, with appropriate citations of the source of the evidence. This paper therefore looks at introduction to scientific writing, types of scientific writing and their styles. This is underscored by the fact that without a written record of the findings and observations of researchers, no proof exists that any research was conducted. Scientific writing should build on and extend prior research. Becoming familiar with existing scientific literature is a crucial first step in planning. In fine understanding the criteria of doing good scientific research is key for communicating your findings in a clear and interesting fashion focusing on the subject matter.

The development of mobile payment in the country is significant each year, has become a trend and lifestyle among the people with a user level reaching 70% by the younger population and 67% by rising digital usage. One of the mobile payment service users that is widely used after transportation is as a means of payment for food delivery and on site dining. From the 2018 Nielsen Survey results, 41% of consumers claimed to have used food delivery services. Based on the JakPat Survey that 36.9% of consumers use mobile payment services for on site dining. Seeing the great opportunities and problems that are often repeated experienced by food & beverage businesses, with the Ideal payment platform, a new innovation business model that can overcome the problems that are often experienced by food & beverage businesses. Ideal Payment is a mobile digital platform application engaged in food & beverage that connects customers and merchants in making ordering and payment transactions using a mobile smartphone without going through the cashier, Ideal payment platform that is equipped with ordering features such as (pickup, pre order and pay at table ) and can help improve the productivity of queue management and customer engagement management. The ideal payment platform can be used in various business types such as (restaurants, fast food, food court, dessert & cakes and coffee shops). The feasibility of the Ideal payment platform business model shows that this business model can be run based on the NPV results with a positive value of NPV> 0 which is Rp. 9,162,356,129

Ensuring sustainability in the long-run necessitates devoting strategic solutions to the rising environmental problems. Unless nations move to a sustainable growth path characterized by economic development and human development that conserve natural resources better, the increased environmental pollution will have negative effects on population well-being. Sustainability has been seen as an entrepreneurial imperative and policy goal (Washington, 2015). However, some building blocks of theory development regarding this process of structural change remain elusive (Savona and Ciarli, 2019). The substantive for sustainable development in which transition pathways are still lacking (Dosi et al., 2017).

Notwithstanding recent work which has demonstrated the potential of using Twitter messages for content-specific data mining and analysis, the depth of such analysis is inherently limited by the scarcity of data imposed by the 140 character tweet limit. In this paper we describe a novel approach for targeted knowledge exploration which uses tweet content analysis as a preliminary step. This step is used to bootstrap more sophisticated data collection from directly related but much richer content sources. In particular we demonstrate that valuable information can be collected by following URLs included in tweets. We automatically extract content from the corresponding web pages and treating each web page as a document linked to the original tweet show how a temporal topic model based on a hierarchical Dirichlet process can be used to track the evolution of a complex topic structure of a Twitter community. Using autism-related tweets we demonstrate that our method is capable of capturing a much more meaningful picture of information exchange than user-chosen hashtags.

Learning efficient options illustrations and equivalency metric measures are imperative to the searching performance of a content-based image retrieval (CBIR) machine. Despite in depth analysis efforts for many years, it remains one amongst the foremost difficult open issues that significantly hinders the success of real- world CBIR systems. The key issue has been associated to the commonly known “linguistic gap” problem that exists between low-level image pixels captured by machines and high-level linguistics ideas perceived by humans. Among varied techniques, machine learning has been actively investigated as a potential direction to bridge the linguistics gap in the long run. Motivated by recent success of deep learning techniques for computer vision and other applications, In this paper, we'll conceive to address an open problem: if deep learning could be a hope for bridging the linguistics gap in CBIR and the way a lot of enhancements in CBIR tasks may be achieved by exploring the progressive deep learning methodologies for learning options illustrations and equivalency measures. Speci?cally, we'll investigate a framework of deep learning with application to CBIR tasks with an extensive set of empirical studies by examining a progressive deep learning technique (Convolutional Neural Networks) for CBIR tasks in varied settings. From our empirical studies, we found some encouraging results and summarized some vital insights for future analysis. CBIR tasks may be achieved by exploring the progressive deep learning techniques for learning options illustrations and equivalency measures.

The internet has provided many novel ways for people to express their ideas and views about different topics, ideas and trends. The contents generated by the users which are present on various mediums like internet blogs, discussion forums, and groups paves a strong base for decision making in diverse fields such as digital advertising, election polls, scientific predictions, market surveys and business zones etc. Sentiment analysis is the process of mining the sentiments from the data that are available in online platforms and categorizing the opinion towards a particular entity that falls on three different categories which are positive, neutral and negative. In this paper, the problem of sentiment classification of election dataset in twitter has been addressed. This paper summarizes the ensemble method, the best way to achieve classification. And also about the ada boosting algorithm and artificial neural networks by which the optimized prediction accuracy is achieved.

As technology advances, it makes life easy and straightforward by solving many of the real-life problems which are faced by people in their daily life. Various types of technologies are used to improve the life of humans. Hence, this paper has used one of the technologies to ease the life of humans i.e. IoT. This paper represents IoT (Internet of Things) for the smart home automation system. There are many proposed systems which make the home easy to live in. But this paper tells about the newer advanced system. This paper tells the usage of motion detection technique to perform light on/off, MQ2 sensor for gas detection, machine learning for facial expression detection, motor for facade opening/closing, motor for room rotation and last the website “ThingsBoard” to collect the whole data at one place. The main goal of this paper is to provide full security with innovation at home.

The novel human coronavirus is highly contagious and can lead to significant morbidity and mortality. This has triggered major and cascading economic and societal consequences that have contributed considerably to global impact and suffering. It is obvious that there is no immediate solution and one has to learn to live with the virus until either herd immunity has been achieved or a vaccine has been found. As countries exit lockdowns and economies try to revive themselves, it is important to practice social distancing, use masks, avoid fomites and adopt safe practices. Artificial intelligence-based technologies hold the key to success as we emerge back to work and try to revive economies. At the same time, one must also acknowledge its downsides. This article reviews the various artificial intelligence technologies employed as part of exit strategies from lockdowns.

The battle of corona-virus and mankind is possible to be tackled as long as we maintain the basic norm of social distancing and wearing masks amongst ourselves as it is through our droplets from the respiratory tract that the virus spreads. With the increasing demand for man-force and people requiring to go to their workplaces post lockdown, it is very necessary that we save each other from the virus. In this project, we will go through a detailed explanation of how we can use Python, AI and Deep Learning to monitor social distancing at public places and workplaces are keeping a safe distance from each other by analyzing real-time video streams from the camera and also detect facial mask monitoring using OpenCV and Python. To ensure if people are following social distancing protocols in public places and workplaces, we wanted to develop a tool that can monitor if people are keeping a safe distance from one another, wearing masks or not by processing real-time video footage from the camera. People at workplaces, factories, shops can integrate this tool into their security camera systems and can monitor whether people are keeping a safe distance from each other or not along with that we detect facial mask monitoring using Python with help of haar-cascade algorithm to see whether a person is wearing a mask or not. We are also planning to include thermal screening detection to measure the temperature of the subjects, a dashboard which will display a live report of corona cases around the world. We will also include an alert system that will send a notification to the authorities if the social distancing is not followed or if the temperature exceeds the threshold. The authorities can take suitable measures to isolate the subject and thus prevent the spread of Covid-19.

The development and upgrades that mobile gadgets have encountered, they are as yet considered as restricted registering gadgets. Presently, clients become the more requesting and hope to execute computational serious applications on their mobile gadgets. Accordingly, Mobile Cloud Computing (MCC) coordinates versatile figuring and Cloud Computing (CC) so as to broaden capacities of mobile devices utilizing of?oading procedures. Computational of?oading handles restrictions of Smart Mobile Devices (SMDs, for example, constrained battery lifetime, constrained preparing capabilities, and constrained Storage capacity by of?oading the execution and outstanding burden to other rich frameworks with better execution and assets. Here, the current of?oading systems, Compuatational of?oading strategies, and evaluate them alongside their principle basic issues. In addition, it investigates distinctive significant parameters dependent on which the systems are actualized, for example, of?oading technique and level of dividing. At last, it condenses the issues in of?oading systems in the MCC space that requires further research.

India is an agricultural country. Agriculture is the important contributor to the Indian economy. There are many classification techniques like Support Vector Machine(SVM), LADTree, Naïve Bayes, Bayesnet, K Nearest Neighbour(KNN), Locally Weighted Learning(LWL) on rice crop production datasets. They have some drawbacks like low accuracy and more errors. To achieve more significant result, To increase classification accuracy and reducing classification errors, our research uses classification method Bayesnet based adaboost will be proposed in work. Rice crop yield depend on environment’s parameters like Rainfall, minimum temperature, average temperature, Maximum temperature, Vapour Pressure, potential evapotranspiration, reference crop evapotranspiration, cloud cover, wet day frequency for the kharif season. our dataset containing these environmental parameters for accurate prediction of Rice crop yield.

Cloud Computing has the facility to transform a large part of information technology into services in which computer resources are virtualized and made available as a utility service. From here comes the importance of scheduling virtual resources to get the maximum utilization of physical resources. The growth in server’s power consumption is increased continuously; and many researchers proposed, if this pattern repeats continuously, then the power consumption cost of a server over its lifespan would be higher than its hardware prices. The power consumption troubles more for clusters, grids, and clouds, which encompass numerous thousand heterogeneous servers. Continuous efforts have been done to reduce the electricity consumption of these massive-scale infrastructures. To identify the challenges and required future enhancements in the field of efficient energy consumption in Cloud Computing, it is necessary to synthesize and categorize the research and development done so far. In this paper, the authors prepare taxonomy of huge energy consumption problems and its related solutions. The authors cover all aspects of energy consumption by Cloud Datacenters and analyze many more research papers to find out the better solution for efficient energy consumption. Keywords: Cloud computing, Collocated virtual machines, Live migration, Load balancing, Resource scheduling

Datacenters are becoming the indispensable infrastructure for supporting the services offered by cloud computing. Unfortunately, datacenters consume a lot of energy, which currently stands at 3% of global electrical energy consumption. Consequently, cloud service providers (CSP) experience high operating costs (in terms of electricity bills), which is, in turn, passed to the cloud users. In addition, there is an increased emission of carbon dioxide to the environment. Before one embarks on addressing the problem of energy wastage in a datacenter, it is important to understand the causes of energy wastage in datacenter servers. In this paper, we elaborate on the concept of cloud computing and virtualization. Later, we present a survey of the main causes of energy wastage in datacenter servers as well as proposed solutions to address the problem.

This paper deals with a low cost solution to problem avoidance for a mobile machine using just a single Artifical Intelligennce. It allows the machine to navigate smoothly in an unknown environment, avoiding collisions, without having to stop in front of problems. The problem avoidance process is made up of three distinct stages - the mapping algorithm, the core problem avoidance algorithm, and the steering algorithm. The mapping algorithm takes the raw Artifical Intelligennce readings and processes them to create higher resolution maps from the wide-angle Artifical Intelligennce. The problem avoidance algorithm is based on the potential field theory which considers the machine to be a test charge that is repelled by all the problems around it, and which moves in the direction of the resultant of the forces acting on it. An algorithm which steers a mobile machine based on the differential drive system is also discussed.

Drowsiness as well as Tiredness of motorists is amongst the considerable root causes of road crashes. Yearly, they raise the quantities of deaths as well as fatalities injuries globally. In this paper, a module for Advanced Motorist Aid System (ADAS) is presented to lower the number of crashes as a result of chauffeurs tiredness as well as therefore in-crease the transport safety; this system manages automatic chauffeur drowsiness detection based on aesthetic info and also Artificial Intelligence. We suggest a formula to find, track, and evaluate both the vehicle driver’s deal with and also eyes to determine PERCLOS, a scientifically supported measure of sleepiness related to slow-moving eye closure.

The GIS smart campuses have been constituted as an efficient system that allows the integration of information from different agencies inside universities, with the use of geographic applications developed for different types of users. This research describes general considerations to begin implementation of a smart GIS at the Nueva Granada Campus, in Cajicá. This phase was developed based on the generation of a campus base map, which is used as a spatial reference for the elaboration of all applications that require associated geographic information, as well as the implementation of a Gisweb system for the monitoring, verification, and updating of the campus trees. The result of the work provides the basis for subsequent systems and applications of location, mobility and efficacy management related with the academic and administrative activities in the university campus.

This research is aimed at developing a Software Framework for poultry management with the objectives: To provide poultry farmers with expert knowledge from the comfort of their homes. The system is developed using generic iterative waterfall model as methodology, HTML, CSS, JavaScript and Bootstrap for graphical user interface. PHP is used as programming language and MySQL as DBMS and normalization technique. The system is hosted locally for validation and testing on Xampp local host. The researchers recommended Poultry farmers to adopt and use the software framework because it can give knowledge on how to manage poultry expert system of different categories in poultry farming.

This series of studies make it clear that a wide range of both physical and digital resources are involved in domestic music consumption. The selection of digital resources is particularly evident, and it can be observed that domestic music consumption is a fragmented business, taking advantage of many different ''channels'' for getting, using and preparing music. While there are not a series of common channels, each home displayed a variety of methods in respect to using metadata in multiple different modalities: regardless, the activities involved in getting, using and preparing music cohere through a noticeable, emergent set of workflows. We find that not only does metadata support searching, as one might expect, but also it pervades all parts of the workflow and is used in real-time as a reflexive artifact and in terms of its future perceived/ prescribed use. The findings of the research raise a series of possibilities and issues that form the basis for understanding and designing for metadata use.

A Mobile Adhoc Network (MANET) is prone to attacks. Adversaries take hold of the network, thus degrading their performance. Various attacks are prevalent in MANET, out of which Byzantine attack plays a vital role. A node or group of nodes present in the routing path between the source and the destination may be compromised due to Byzantine attack. In this paper, Cohen Kappa Reliability Coefficient based Mitigation (CKRCM) mechanism is proposed to deal with these attacks. The intermediate nodes are monitored by their neighbors for a timestamp. If the monitoring node does not receive an acknowledgment, then the nodes are perceived to be attacked. The trustworthiness of the nodes is built by computing the trusts and reliabilities of the nodes. It is seen that the proposed scheme outperforms the existing scheme in terms of Throughput, Packet Delivery Ratio (PDR) and Packet Loss Ratio (PLR).

Cloud Computing (CC) is the advancement of the Grid Computing (GC) worldview in the direction of administration arranged structures. The phrasing connected to this sort of handling, while portraying shared resources, alludes to the idea of Service of X. Such assets are accessible on interest and at an altogether low cost contrasted with self-conveyance of individual segments. CC is found everywhere in current situations, from vast scale associations to a just little scale business, everybody is equipping themselves cloud. Due to its effortlessness, observing and support over remote association, expansive territory inclusion. Cloud can be any sort Software as an administration, stage as an administration, foundation as an administration dependent on its use. High Performance Computing (HIPECO) implies the accumulation of computational capacity to build the capacity of handling substantial issues in science, designing, and business. HIPECO on the cloud permits performing on interest HIPECO errands by superior clusters in a cloud atmosphere. Currently, CC arrangements (e.g., Microsoft Azure, Amazon EC2) enable the users to make use of only the fundamental storage and computational utilities. They prevent the allowance of custom adjustments of the topology designs or parameters of the system. The associations structures of the nodes in HIPECO clusters ought to give a quick bury node correspondence. It is vital that adaptability is safeguarded also. In a foundation, as an administration, virtualization viably maps virtual machines to the physical machines. In spite of the fact that it is difficult, undertaking for hypervisor to choose fitting host to serve up and coming virtual machine is a must requirement. In this paper, our main aim is to examine different techniques/types of cluster topology mapping and their necessities in numerous Cloud situations to accomplish higher dependability along with adaptability of utilization which is executed inside Cloud resources (CR), HIPECO resource allocation (RA) on the cloud clusters and Cluster based designation procedure.

The serious constraints and requiring deployment atmospheres of wireless sensor networks make safety for these systems extra difficult than for traditional networks Nevertheless, a number of residential or commercial properties of sensor networks may help address the challenge of building safe and secure networks. The distinct aspects of sensor networks may enable novel defenses not available in traditional networks.In this paper, we examine the security related concerns and also obstacles in wireless sensor networks. We identify the safety and security threats, testimonial suggested protection devices for wireless sensor networks.

Malicious users use different techniques such as cracking passwords, text traffic, sniffing unencrypted or light, etc. System overhead and compromise critical systems. Therefore, there must be some sort of security for the organization's private resources from the Internet and from the inside. Therefore, the intrusion detection system (IDS) could be the best solution. It complements the firewall to improve the security holes. An intrusion detection system includes a management console and sensors. The management console holds all the responsibility of functionality of IDS comprises with its initialization, packet capturing, and report generation, whereas the sensors used to monitor hosts or networks in real time. There may be different categories of Intrusion Detection System. IDS can be designed in the concept of Signature analysis as well as anomaly behavior analysis. Therefore IDS used to capture the behavior of suspected packets. These functions are in host mode and called as Host Intrusion Detection System (HIDS) and in Network mode called as Network Intrusion Detection System (NIDS). The entitled dissertation work is carried out to obtain the best analysis performance through signature based detection system. It is efficient for host as well as network system .here basically Transmission Control Packets (TCP) and User Datagram Packets (UDP) considered to analysis for finding different attacks like Probe,DoS,R2l and U2R. This system is being found functionally efficient and also provide layer wise attacks details. Here different agent modules used to perform desired isolated responsibility like Mobile Agent (MA) to activate different IDS chest at different hosts, Tenet Agent (TA) for signature rule, Analysis Agent (AA) etc. The proposed system can greatly improve efficiency from offline detection to real-time online detection. Since the proposed system derives features from packet headers. Many attacks were experimented in this system. Experiments were performed to demonstrate the excellent effectiveness and efficiency of the proposed system. The proposed system can greatly improve efficiency from offline detection to real-time online detection. Since the proposed system derives features from packet headers. The entitled system can be further enhanced to capture more type of attacks at the levels of multiple layers and also may stop attacks as well.

The Powerful software tools and techniques required for the development of data mining applications. With the rapid development of technologies and business interest in using electronics and latest technologies plays important role in improvement of data mining field. Data mining access the meaningful and efficient information available in worldwide which is helps in decision making. This paper described the (a) various tools and techniques used by data mining applications. (b) compared features and limitations both in Proprietary and open sources data mining tools. (c) technical analysis of proprietary and open source data mining tools. On the basis of well-designed User interface, short time analysis, statistical and mathematical analysis user can select the best tool as per their requirements. Analysis of these tools makes easy to select appropriate tool.

Mobile health apps usually have a user interface that is difficult for elderly users to understand. With the increase in the number of elder users using applications on mobile phone, research on this area is important to do. This research aim is to present comprehensive review of mobile application evaluation for the elderly. The research methodology adapted PRISMA method to find and review relevance research articles in order to reach research goal. Based on literature study, we found three methods or models that have been applied for elderly user usability evaluation, including usability heuristics, system usability scale and technology acceptance model.

As India is rich in talent, lagging in research and poor in finance, authors sincerely appeal UGC, NAAC, NPTEL, IIT, AICTE, IISER, IISc and administrative institutions like IIM, UPSC and Supreme Court core committees to take initiative in implementing and maintaining industrial and research oriented certified online audio-visual interactive degree courses across the Indian boundaries. Benefits and implications of this scheme are: 1) Distance education system, Open education system and Open book exam etc can be eliminated. 2) High quality research orientation can be inculcated among teaching staff. 3) Experimental approach and industrial orientation- both can be implemented and maintained simultaneously. 4) Educational stress on teenage students and financial burdens on parents - both can be eliminated. 5) Reservation issues pertaining to caste and seat allocation can be eliminated. 6) Degree level scholarship schemes can be eliminated. 7) All educational institutions can be encouraged to tie up with online degree system with unique pattern and quality and can be forced to focus on laboratory activities rather than teaching. 8) Current educational staff can be classified into five broad categories as Education wing, Call center wing, Research wing, Oration wing and Industrial wing. 9) Students lagging in grasping the key technical points can listen & watch the recorded and edited information several times for a better understanding and thus doubts, subject fear, back logs and detaining issues can be avoided to a great extent. 10) By maintaining educational call centers, interaction with students can be established and online degree courses can be strengthened further. 11) With recorded and edited lab experiments and 3D modeling tools, virtual laboratories can be developed and thus awareness can be inculcated in students on knowledge acquisition on various experiments and experimental setups. 12) As there is no restriction on available number of (electronic) seats, stress oriented and suicide provoking complicated entrance exams can be relinquished. 13) Poor students, Female students, male and female job holders, physically handicapped students and students not interested to attend colleges can get better education in this scheme. 14) For maintaining this online degree system across India, there seems a big scope for new employment. 15) By 2040, India can have a leading role in world science, engineering and technology. Even though the proposal under consideration is interlinked with many political and social issues, with reference to ‘Vision2040’ program, this proposal can be given a chance in Indian higher education system.

In recent years, Wireless sensor networks (WSNs) have been emerged as an important research area due to its wide spread application in various domains such as military sensing and tracking, environment monitoring, patient monitoring, etc. WSN also have various advantages in gathering the data also with data transmission as well. Even though WSN has such advantages, there is certain drawback related to the energy consumption for data transmission over the network. Wireless sensor networks basically depend on the availability of nodes for transmission and if some dead nodes are available on the designated path of transmission, there will be delay in communication and also will affect the energy consumptions. Also, when a particular node is transmitting any data packet with high power, it may lead to interference which will affect the proper transmission of data and wastage of power as well. For power level reduction proper methodology has to be followed starting with the clustering and designing of routing protocols in WSNs. We intend to develop an enhanced clustering algorithm for initial clustering of sensor nodes for data transmission. Nodes will be clustered based on working attributes. Once nodes are clustered into different groups, transmission path will be assigned. An energy efficient optimal protocol will be designed in our approach for routing to improve the energy utilization by optimal power utilization. For optimization, we can employ multi objective optimization techniques which can enhance the optimal selection of power utilization. The proposed scheme will be then compared with some existing techniques to show the efficiency of the proposed approach.

Natural language processing (NLP) is very much needed in today’s world to enhance human-machine interaction. It is an important concern to process textual data and obtain useful and meaningful information from these texts. NLP parses the texts and provides information to machine for further processing. The present status of NLP’s computational process of identifying the meaning (sense) of a word in a particular context is ambiguous, where the meaning of word in the context is not clear and may point to multiple senses. Ambiguity in understanding correct meaning of texts is hampering the growth and development in various fields of Natural language processing applications like Machine translation, Human Machine interface etc. The process of finding the correct meaning of the ambiguous texts in the given context is called as word sense disambiguation (WSD). WSD is perceived as one of the most challenging problem in the Natural language processing community and is still unsolved. It is evident that different ambiguities exist in natural languages and researchers are contributing to resolve the problem in different languages for successful disambiguation. These ambiguities must be resolved in order to understand the meaning of the text and help to boost NLP processing and applications. Objective is to investigate how WSD can be used to alleviate ambiguities, automatically determine the correct meaning of the ambiguous text and help to boost NLP processing and applications. Resolving ambiguity for translation involves working with various natural language processing techniques to investigate the structure of the languages, availability of lexical resources etc. Word Sense Disambiguation (WSD) in the field of computing linguistics is an area which is still unsolved. This paper focus on the in-depth analysis of such ambiguity, issues in Language Translation, how WSD resolves the ambiguity and contribute towards building a framework.

The aim of this paper is to automatically identify a Roman Imperial denarius from a single query photograph of its obverse and reverse. Such functionality has the potential to contribute greatly to various national schemes which encourage laymen to report their finds to local museums. Our work introduces a series of novelties: (i) this is the first paper which describes a method for extracting the legend of an ancient coin from a photograph; (ii) we are also the first to suggest the idea and propose a method for identifying a coin using a series of carefully engineered retrievals, each harnessed for further information using visual or meta-data processing; (iii) we show how in addition to a unique standard reference number for a query coin, the proposed system can be used to extract salient coin information (issuing authority, obverse and reverse descriptions, mint date) and retrieve images of other coins of the same type.

Social networks have become a vital component in personal life. People are addicted to social network features, updating their profile page and collaborating virtually with other members have become daily routines. Web data mining is a new trend in current research studies. This study sought to develop a framework for social media data mining and analysis for the betterment and advancement of products (art effects) and services (exhibitions) with in the contemporary art industry of Zimbabwe through a case study of the Zimbabwean National Art Gallery. The information for this paper was gathered through the use of in-depth interviews, questionnaires, key-word search and API from the organization’s social media twitter handle were used to get the data for analysis. Focus group participants were chosen from the National art gallery and a matching number was selected from the artist who makes the artworks which will be soles or exhibited through the national art gallery. The findings suggested that, yes it is possible to inform the next batch of products with information mined from analyzing the sentiments or reviews of the previous set of artworks. Hence with this in mind the researchers managed to develop a framework which can be used to implement social media mining in the art sector of Zimbabwe. The proposed framework tried to handle the major limitations in current web mining frameworks by handling challenges such as special symbols, slang use, Data Validity analysis, time frame, and methodologies.

Brushless DC motor has a rotor with permanent magnet and has no mechanical commutator which leads to many advantages like less maintenance, long life, high reliability, low inertia, low friction and low noise. Since the brush system/commutator assembly is replaced by an electronic controller which can be easily integrated into other required electronics, thereby improving the effective power to weight and power to volume ratio. In this paper the direct torque control method is employed to improve its torque ripple content which is been compared with conventional method by using MATLAB. In this project the three phase brushless DC motor model is designed with proportional integral controller and tested in MATLAB software. The PI controller is used to control the speed of the brushless DC motor. On the other hand parameters like Back EMF, current; speed and torque are evaluated for the designed models of BLDC motor. Due to the easy implementation and simple control structure the convectional PI controller are used in industries.

Bitcoin is a Cryptocurrency which is evolving in digital world and gaining a larger market related to digital currency and stands on all the user expectation of decentralize mechanism of system by providing proof of work in peer-to-peer network with the help of Blockchain. In this paper I have done a literature review on Blockchain technology and its application in Bitcoin.

Machine learning is embraced in an extensive variety of areas where it demonstrates its predominance over customary lead based calculations. These strategies are being coordinated in digital recognition frameworks with the objective of supporting or notwithstanding supplanting the principal level of security experts although the total mechanization of identification and examination is a luring objective, the adequacy of machine learning in digital security must be assessed with the due steadiness. With the improvement of the Internet, digital assaults are changing quickly and the digital security circumstance isn't hopeful. Since information are so critical in ML/DL strategies, we portray a portion of the normally utilized system datasets utilized in ML/DL, examine the difficulties of utilizing ML/DL for digital security and give recommendations to look into bearings. Malware has developed over the previous decades including novel engendering vectors, strong versatility methods and different and progressively propelled assault procedures. The most recent manifestation of malware is the infamous bot malware that furnish the aggressor with the capacity to remotely control traded off machines therefore making them a piece of systems of bargained machines otherwise called botnets. Bot malware depend on the Internet for proliferation, speaking with the remote assailant and executing assorted noxious exercises. As system movement, action is one of the principle characteristics of malware and botnet task, activity investigation is frequently observed as one of the key methods for recognizing traded off machines inside the system. We present an examination, routed to security experts, of machine learning methods connected to the recognition of interruption, malware, and spam.

In this paper the use of online learning, assessment and self-evaluation platform to aid in teaching and assessment of computer programming and Aptitudes in classrooms are discussed. Based on the skills of the users, the programming and aptitude concepts are taught. This paper describes the technology and implementation of the learning and assessment platform and new methods for automated assessment of programming assignments and for competitive exams. Finally, the application of the system is to help the users to learn the concept and to crack the exams easily.

The degree of pollution has expanded with times by parcel of variables like the expansion in populace, expanded vehicle use, industrialization and urbanization, which brings about hurtful impacts on human prosperity by legitimately affecting soundness of populace presented to it. Poor environmental conditions can prompt serious medical issues. Destructive gases in hazardous environment influence these days individuals. The significant of this paper is watching unsafe environmental conditions for wellbeing applications. Right now itemized a study on toxic environment monitoring dependent on various innovations utilizing sensors.