With the above said emphasis on the current and future potential of a smartphone, the ability to virtualize smartphones with all their real-world features into a virtual platform, is a boon for those who want to rigorously experiment and customize the virtualized smartphone hardware without spending an extra penny.
When accessible remotely with the real-time responsiveness, the above mentioned real-world behavior will be a real dealmaker in many real-world systems, namely, the life-saving systems like the ones that instantaneously get alerts about harmful magnetic radiations in the deep mining areas, etc.
And these life-saving systems would be installed on a large scale on the desktops or large servers as virtualized smartphones having the added support of virtualized sensors which remotely fetch the real hardware sensor readings from a real smartphone in real-time. Based on these readings the lives working in the affected areas can be alerted and thus saved by the people who are operating the at the desktops or large servers hosting the virtualized smartphones.
The current work of Sensor Emulation is quite unique when compared to the existing and past sensor-related works. The uniqueness comes from the full-fledged sensoremulation in a virtualized smartphone environment as opposed to building some sophisticated physical systems that usually aggregate the sensor readings from the real hardware sensors, might be in a remote manner and in real-time. For example, wireless sensor networks based remote-sensing systems that install real hardware sensors in remote places and have the sensor readings from all those sensors at a centralized server or something similar, for the necessary real-time or offline analysis.
In these systems, apart from collecting mere real hardware sensor readings into a centralized entity, nothing more is being achieved unlike in the current work of Sensor Emulation wherein the emulated sensors behave exactly like the remote real hardware sensors. The emulated sensors can be calibrated, speeded up or slowed down in terms of their sampling frequency , influence the sensor-based application running inside the virtualized smartphone environment exactly as the real hardware sensors of a real phone would do to the sensor-based application running in that real phone.
In essence, the current work is more about generalizing the sensors with all its real-world characteristics as far as possible in a virtualized platform than just a framework to send and receive sensor readings over the network between the real and virtual phones.
Realizing the useful advantages of Sensor Emulation which is about adding virtualized sensors support to emulated environments, the current work emulates a total of ten sensors present in the real smartphone, Samsung Nexus S, an Android device. Virtual phones run Android-x86 while real phones run Android.
The real reason behind choosing Android-x86 for virtual phone is that xbased Android devices are feature-rich over ARM based ones, for example a full-fledged x86 desktop or a tablet has more features than a relatively small smartphone. Out of the ten, five are real sensors and the rest are virtual or synthetic ones. The emulated Android-x86 is of Android release version Jelly Bean 4. One of the noteworthy aspects of the Sensor Emulation accomplished is being demand-less - exactly the same sensor-based Android applications will be able to use the sensors on the real and virtual phones, with absolutely no difference in terms of their sensor-based behavior.
Apart from a Paired real-device scenario from which the real hardware sensor readings are fetched, the Sensor Emulation also is compatible with a Remote Server Scenario wherein the artificially generated sensor readings are fetched from a remote server. Sensor Emulation once completed was evaluated for each of the emulated sensors using applications from Android Market as well as Amazon Appstore. The applications category include both the basic sensor-test applications that show raw sensor readings, as well as the advanced 3D sensor-driven games which are emulator compatible, especially in terms of the graphics.
The evaluations proved the current work of Sensor Emulation to be generic, efficient, robust, fast, accurate, and real. As of this writing i. It is important to note that though the current work is targeted for Android-x86, the code written for the current work makes no assumptions about underlying platform to be an x86 one. Hence, the work is also logically seen as compatible with ARM based emulated Android environment though not actually tested.
Our measurements show that the video players frequently discard a large amount of video content although it is successfully delivered to a client. We first investigate the root cause of this unwanted behavior.
The architecture includes a selective packet discarding mechanism, which can be placed in packet data network gateways P-GW. In addition, our QoS-aware rules assist video players in selecting an appropriate resolution under a fluctuating channel condition.
We monitor network condition and configure QoS parameters to control availability of the maximum bandwidth in real time. In our experimental setup, the proposed platform shows up to We investigate video server selection algorithms in a distributed video-on-demand system.
We proved that a location-aware video server selection algorithm assigns a video content server based on the network attachment point of a client.
We found out that such distance-based algorithms carry the risk of directing a client to a less optimal content server, although there may exist other better performing video delivery servers. In order to solve this problem, we propose to use dynamic network information such as packet loss rates and Round Trip Time RTT between an edge node of an wireless network e. Our empirical study shows that the proposed architecture can provide higher TCP performance, leading to better viewing quality compared to location-based video server selection algorithms.
However, it may converge only to a local optimum or may not converge at all. We explore an application to predicting equipment failure on an urban power network and demonstrate that the Bethe approximation can perform well even when BP fails to converge.
Introductory computer science courses traditionally focus on exposing students to basic programming and computer science theory, leaving little or no time to teach students about software testing. In the long term, they will appreciate the importance of testing as part of the software development life cycle. As voice, multimedia, and data services are converging to IP, there is a need for a new networking architecture to support future innovations and applications.
Such diverse network connectivity can be used to increase both reliability and performance by running applications over multiple links, sequentially for seamless user experience, or in parallel for bandwidth and performance enhancements. The existing networking stack, however, offers almost no support for intelligently exploiting such network, device, and location diversity. In this work, we survey recently proposed protocols and architectures that enable heterogeneous networking support.
Upon evaluation, we abstract common design patterns and propose a unified networking architecture that makes better use of a heterogeneous dynamic environment, both in terms of networks and devices. The architecture enables mobile nodes to make intelligent decisions about how and when to use each or a combination of networks, based on access policies.
With this new architecture, we envision a shift from current applications, which support a single network, location, and device at a time to applications that can support multiple networks, multiple locations, and multiple devices.
To provide high performance at practical power levels, tomorrow's chips will have to consist primarily of application-specific logic that is only powered on when needed.
This paper discusses synthesizing such logic from the functional language Haskell. The proposed approach, which consists of rewriting steps that ultimately dismantle the source program into a simple dialect that enables a syntax-directed translation to hardware, enables aggressive parallelization and the synthesis of application-specific distributed memory systems.
Transformations include scheduling arithmetic operations onto specific data paths, replacing recursion with iteration, and improving data locality by inlining recursive types. A compiler based on these principles is under development. Social network platforms have transformed how people communicate and share information. However, as these platforms have evolved, the ability for users to control how and with whom information is being shared introduces challenges concerning the configuration and comprehension of privacy settings.
To validate our approach we conducted an online survey with closed and open questions and collected 50 valid responses after which we conducted follow-up interviews with 10 respondents. However, only a little is known about how users and developers perceive privacy and which concrete measures would mitigate privacy concerns.
Users are more concerned about the content of their documents and personal data such as location than their interaction data. Testing large software packages can become very time intensive. To address this problem, researchers have investigated techniques such as Test Suite Minimization. Test Suite Minimization reduces the number of tests in a suite by removing tests that appear redundant, at the risk of a reduction in fault-finding ability since it can be difficult to identify which tests are truly redundant.
We take a completely different approach to solving the same problem of long running test suites by instead reducing the time needed to execute each test, an approach that we call Unit Test Virtualization. With Unit Test Virtualization, we reduce the overhead of isolating each unit test with a lightweight virtualization container. We describe the empirical analysis that grounds our approach and provide an implementation of Unit Test Virtualization targeting Java applications.
We also compared VMVM to a well known Test Suite Minimization technique, finding the reduction provided by VMVM to be four times greater, while still executing every test with no loss of fault-finding ability.
Challenges arise in testing applications that do not have test oracles, i. Metamorphic testing, introduced by Chen et al. Here, we improve upon previous work by presenting a new technique called Metamorphic Runtime Checking, which automatically conducts metamorphic testing of both the entire application and individual functions during a program's execution.
This new approach improves the scope, scale, and sensitivity of metamorphic testing by allowing for the identification of more properties and execution of more tests, and increasing the likelihood of detecting faults not found by application-level properties.
We previously reported our investigation of the fall offering of the Columbia University course COMS W Advanced Software Engineering, and here report on the fall offering and contrast it to the previous year. Our main findings are: 1 Although the students in the second offering did not do very well on the newly added individual assignment specifically focused on metamorphic testing, thereafter they were better able to find metamorphic properties for their team projects than the students from the previous year who did not have that preliminary homework and, perhaps most significantly, did not have the solution set for that homework.
Sambuddho Chakravarty, Marco V. Low-latency anonymous communication networks, such as Tor, are geared towards web browsing, instant messaging, and other semi-interactive applications. To achieve acceptable quality of service, these systems attempt to preserve packet inter-arrival characteristics, such as inter-packet delay. Consequently, a powerful adversary can mount traffic analysis attacks by observing similar traffic patterns at various points of the network, linking together otherwise unrelated network connections.
Previous research has shown that having access to a few Internet exchange points is enough for monitoring a significant percentage of the network paths from Tor nodes to destination servers. Although the capacity of current networks makes packet-level monitoring at such a scale quite challenging, adversaries could potentially use less accurate but readily available traffic monitoring functionality, such as Cisco's NetFlow, to mount large-scale traffic analysis attacks.
In this paper, we assess the feasibility and effectiveness of practical traffic analysis attacks against the Tor network using NetFlow data. We present an active traffic analysis method based on deliberately perturbing the characteristics of user traffic at the server side, and observing a similar perturbation at the client side through statistical correlation. We evaluate the accuracy of our method using both in-lab testing, as well as data gathered from a public Tor relay serving hundreds of users.
Video streaming on mobile devices is on the rise. According to recent reports, mobile video streaming traffic accounted for Our research indicates that the network traffic behavior depends on factors such as the type of device, multimedia applications in use and network conditions. Furthermore, we found that a large part of the downloaded video content can be unaccepted by a video player even though it is successfully delivered to a client. This unwanted behavior often occurs when the video player changes the resolution in a fluctuating network condition and the playout buffer is full while downloading a video.
Energy optimizations are being aggressively pursued today. Can these optimizations open up security vulnerabilities? In this invited talk at the Energy Secure System Architectures Workshop run by Pradip Bose from IBM Watson research center I discussed security implications of energy optimizations, capabilities of attackers, ease of exploitation, and potential payoff to the attacker.
I presented a mini tutorial on security for computer architects, and a personal research wish list for this emerging topic. This paper presents a review of modern-day schlieren optics system and its application. Schlieren imaging systems provide a powerful technique to visualize changes or nonuniformities in refractive index of air or other transparent media.
With the popularization of computational imaging techniques and widespread availability of digital imaging systems, schlieren systems provide novel methods of viewing transparent fluid dynamics. This paper presents a historical background of the technique, describes the methodology behind the system, presents a mathematical proof of schlieren fundamentals, and lists various recent applications and advancements in schlieren studies.
The increasing number of In addition, non-WiFi devices sharing the same spectrum with Although the problem sources can be easily removed in many cases, it is difficult for end users to identify the root cause. We introduce WiSlow, a software tool that diagnoses the root causes of poor WiFi performance with user-level network probes and leverages peer collaboration to identify the location of the causes.
We elaborate on two main methods: packet loss analysis and The Internet of Things IoT enables the physical world to be connected and controlled over the Internet. This paper presents a smart gateway platform that connects everyday objects such as lights, thermometers, and TVs over the Internet.
The proposed hardware architecture is implemented on an Arduino platform with a variety of off the shelf home automation technologies such as Zigbee and X Using the microcontroller-based platform, the SECE Sense Everything, Control Everything system allows users to create various IoT services such as monitoring sensors, controlling actuators, triggering action events, and periodic sensor reporting.
Mobile devices are vertically integrated systems that are powerful, useful platforms, but unfortunately limit user choice and lock users and developers into a particular mobile ecosystem, such as iOS or Android.
We present Chameleon, a multi-persona binary compatibility architecture that allows mobile device users to run applications built for different mobile ecosystems together on the same smartphone or tablet.
Chameleon enhances the domestic operating system of a device with personas to mimic the application binary interface of a foreign operating system to run unmodified foreign binary applications.
To accomplish this without reimplementing the entire foreign operating system from scratch, Chameleon provides four key mechanisms. First, a multi-persona binary interface is used that can load and execute both domestic and foreign applications that use different sets of system calls.
Second, compile-time code adaptation makes it simple to reuse existing unmodified foreign kernel code in the domestic kernel. Third, API interposition and passport system calls make it possible to reuse foreign user code together with domestic kernel facilities to support foreign kernel functionality in user space. Fourth, schizophrenic processes allow foreign applications to use domestic libraries to access proprietary software and hardware interfaces on the device.
We have built a Chameleon prototype and demonstrate that it imposes only modest performance overhead and can run iOS applications from the Apple App Store together with Android applications from Google Play on a Nexus 7 tablet running the latest version of Android. We provide the first measurements on real hardware of a complete hypervisor using ARM hardware virtualization support. System reliability is a critical requirement of cyber-physical systems.
An unreliable CPS often leads to system malfunctions, service disruptions, financial losses and even human life. Some prior researches have proposed reliability benchmark for some specific CPS such as wind power plant and wireless sensor networks. There were also some prior researches on the components of CPS such as software and some specific hardware. FARE framework provides a CPS reliability model, a set of methods and metrics on the evaluation environment selection, failure analysis and reliability estimation for benchmarking CPS reliability.
It not only provides a retrospect evaluation and estimation of the CPS system reliability using the past data, but also provides a mechanism for continuous monitoring and evaluation of CPS reliability for runtime enhancement. The framework is extensible for accommodating new reliability measurement techniques and metrics. It is also generic and applicable to a wide range of CPS applications. For empirical study, we applied the FARE framework on a smart building management system for a large commercial building in New York City.
Our experiments showed that FARE is easy to implement, accurate for comparison and can be used for building useful industry benchmarks and standards after accumulating enough data. Additional remarks on designing category-level attributes for discriminative visual recognition. Our accelerating computational demand and the rise of multicore hardware have made parallel programs increasingly pervasive and critical.
Yet, these programs remain extremely difficult to write, test, analyze, debug, and verify. In this article, we provide our view on why parallel programs, specifically multithreaded programs, are difficult to get right. Through a series of mechanical, semantics-preserving transformations, I show how a three-line recursive Haskell program Fibonacci can be transformed to a hardware description language -- Verilog -- that can be synthesized on an FPGA.
This report lays groundwork for a compiler that will perform this transformation automatically. We discuss practical details and basic scalability for two recent ideas for hardware encryption for trojan prevention. The broad idea is to encrypt the data used as inputs to hardware circuits to make it more difficult for malicious attackers to exploit hardware trojans. The two methods we discuss are data obfuscation and fully homomorphic encryption FHE.
Data obfuscation is a technique wherein specific data inputs are encrypted so that they can be operated on within a hardware module without exposing the data itself to the hardware. FHE is a technique recently discovered to be theoretically possible.
With FHE, not only the data but also the operations and the entire circuit are encrypted. FHE primarily exists as a theoretical construct currently. It has been shown that it can theoretically be applied to any program or circuit. It has also been applied in a limited respect to some software. Some initial algorithms for hardware applications have been proposed.
We find that data obfuscation is efficient enough to be immediately practical, while FHE is not yet in the practical realm. There are also scalability concerns regarding current algorithms for FHE. This thesis will consist of the following four projects that aim to address the issues of Societal Computing. First, privacy in the context of ubiquitous social computing systems has become a major concern for society at large.
As the number of online social computing systems that collect user data grows, concerns with privacy are further exacerbated. Examples of such online systems include social networks, recommender systems, and so on. Approaches to addressing these privacy concerns typically require substantial extra computational resources, which might be beneficial where privacy is concerned, but may have significant negative impact with respect to Green Computing and sustainability, another major societal concern.
We describe how privacy can indeed be achieved for free an accidental and beneficial side effect of doing some existing computation in web applications and online systems that have access to user data.
Second, we aim to understand what the expectations and needs to end-users and software developers are, with respect to privacy in social systems. Some questions that we want to answer are: Do end-users care about privacy? What aspects of privacy are the most important to end-users?
Do we need different privacy mechanisms for technical vs. Should we customize privacy settings and systems based on the geographic location of the users? We have created a large scale user study using an online questionnaire to gather privacy requirements from a variety of stakeholders.
We also plan to conduct follow-up semi-structured interviews. This user study will help us answer these questions.
Third, a related challenge to above, is to make privacy more understandable in complex systems that may have a variety of user interface options, which may change often.
We have a large dataset of privacy settings for over users on Facebook and we plan to create a user study that will use the data to make privacy settings more understandable. Finally, end-users of such systems find it increasingly hard to understand complex privacy settings. As software evolves over time, this might introduce bugs that breach users' privacy. Further, there might be system-wide policy changes that could change users' settings to be more or less private than before. Accurately determining a user's floor location is essential for minimizing delays in emergency response.
This paper presents a floor localization system intended for emergency calls. We aim to provide floor-level accuracy with minimum infrastructure support.
Our approach is to use multiple sensors, all available in today's smartphones, to trace a user's vertical movements inside buildings. We make three contributions. First, we present a hybrid architecture for floor localization with emergency calls in mind. The architecture combines beacon-based infrastructure and sensor-based dead reckoning, striking the right balance between accurately determining a user's location and minimizing the required infrastructure.
Second, we present the elevator module for tracking a user's movement in an elevator. The elevator module addresses three core challenges that make it difficult to accurately derive displacement from acceleration. Third, we present the stairway module which determines the number of floors a user has traveled on foot.
Unlike previous systems that track users' foot steps, our stairway module uses a novel landing counting technique. Alias analysis is perhaps one of the most crucial and widely used analyses, and has attracted tremendous research efforts over the years.
Yet, advanced alias analyses are extremely difficult to get right, and the bugs in these analyses are most likely the reason that they have not been adopted to production compilers. This paper presents NEONGOBY, a system for effectively detecting errors in alias analysis implementations, improving their correctness and hopefully widening their adoption.
NEONGOBY works by dynamically observing pointer addresses during the execution of a test program and then checking these addresses against an alias analysis for errors. It is explicitly designed to 1 be agnostic to the alias analysis it checks for maximum applicability and ease of use and 2 detect alias analysis errors that manifest on real-world programs and workloads.
It reduces false positives and performance overhead using a practical selection of techniques. We prove new formulations of derivatives of the Bethe free energy, provide bounds on the derivatives and bracket the locations of stationary points, introducing a new technique called Bethe bound propagation.
Several results apply to pairwise models whether associative or not. I describe in detail the circuitry of the original Pong video arcade game and how I reconstructed it on an FPGA -- a modern-day programmable logic device. In the original circuit, I discover some sloppy timing and a previously unidentified bug that subtly affected gameplay. The result is an accurate reproduction that exhibits many idiosyncracies of the original.
A conventional camera has a limited depth of field DOF , which often results in defocus blur and loss of image detail. The technique of image refocusing allows a user to interactively change the plane of focus and DOF of an image after it is captured.
One way to achieve refocusing is to capture the entire light field. But this requires a significant compromise of spatial resolution. This is because of the dimensionality gap - the captured information a light field is 4-D, while the information required for refocusing a focal stack is only 3-D. In this paper, we present an imaging system that directly captures a focal stack by physically sweeping the focal plane.
We first describe how to sweep the focal plane so that the aggregate DOF of the focal stack covers the entire desired depth range without gaps or overlaps. Since the focal stack is captured in a duration of time when scene objects can move, we refer to the captured focal stack as a duration focal stack.
We then propose an algorithm for computing a space-time in-focus index map from the focal stack, which represents the time at which each pixel is best focused. The algorithm is designed to enable a seamless refocusing experience, even for textureless regions and at depth discontinuities.
We have implemented two prototype focal-sweep cameras and captured several duration focal stacks. Results obtained using our method can be viewed at www. The main findings were: 1 most of the students either misunderstood what metamorphic properties are or fell short of identifying all the metamorphic properties in their respective projects, 2 most of the students that were successful in finding all the metamorphic properties in their respective projects had incorporated certain arithmetic rules into their project logic, and 3 most of the properties identified were numerical metamorphic properties.
A possible reason for this could be that the two relevant lectures given in class cited examples of metamorphic properties that were based on numerical properties.
Based on the findings of the case study, pertinent suggestions were made in order to improve the impact of lectures provided for Metamorphic Testing. Introductory Computer Science CS classes are typically competitive in nature. The cutthroat nature of these classes comes from students attempting to get as high a grade as possible, which may or may not correlate with actual learning. Further, there is very little collaboration allowed in most introductory CS classes. Most assignments are completed individually since many educators feel that students learn the most, especially in introductory classes, by working alone.
In this paper, we describe how we leveraged competition and collaboration in a CS2 to help students learn aspects of computer science better in this case, good software design and software testing and summarize student feedback.
Gamification, or the use of game elements in non-game contexts, has become an increasingly popular approach to increasing end-user engagement in many contexts, including employee productivity, sales, recycling, and education. Our preliminary work has shown that gamification can be used to boost student engagement and learning in basic software testing.
We seek to expand our gamified software engineering approach to motivate other software engineering best practices. We propose to build a game layer on top of traditional continuous integration technologies to increase student engagement in development, documentation, bug reporting, and test coverage.
This poster describes to our approach and presents some early results showing feasibility. The emergency communication systems are undergoing a transition from the PSTN-based legacy system to an IP-based next generation system.
In the next generation system, GPS accurately provides a user's location when the user makes an emergency call outdoors using a mobile phone. Indoor positioning, however, presents a challenge because GPS does not generally work indoors. Moreover, unlike outdoors, vertical accuracy is critical indoors because an error of few meters will send emergency responders to a different floor in a building. This paper presents an indoor positioning system which focuses on improving the accuracy of vertical location.
We aim to provide floor-level accuracy with minimal infrastructure support. Our approach is to use multiple sensors available in today's smartphones to trace users' vertical movements inside buildings.
First, we present the elevator module for tracking a user's movement in elevators. Second, we present the stairway module which determines the number of floors a user has traveled on foot. Third, we present a hybrid architecture that combines the sensor-based components with minimal and practical infrastructure. The infrastructure provides initial anchor and periodic corrections of a user's vertical location indoors.
The architecture strikes the right balance between the accuracy of location and the feasibility of deployment for the purpose of emergency communication. System reliability is a fundamental requirement of cyber-physical systems.
Unreliable systems can lead to disruption of service, financial cost and even loss of human life. Typical cyber-physical systems are designed to process large amounts of data, employ software as a system component, run online continuously and retain an operator-in-the-loop because of human judgment and accountability requirements for safety-critical systems.
This paper describes a data-centric runtime monitoring system named ARIS Autonomic Reliability Improvement System for improving the reliability of these types of cyber-physical systems. ARIS employs automated online evaluation, working in parallel with the cyber-physical system to continuously conduct automated evaluation at multiple stages in the system workflow and provide real-time feedback for reliability improvement.
This approach enables effective evaluation of data from cyber-physical systems. For example, abnormal input and output data can be detected and flagged through data quality analysis.
As a result, alerts can be sent to the operator-in-the-loop, who can then take actions and make changes to the system based on these alerts in order to achieve minimal system downtime and higher system reliability. We have implemented ARIS in a large commercial building cyber-physical system in New York City, and our experiment has shown that it is effective and efficient in improving building system reliability.
With global pool of data growing at over 2. This trend has brought database performance to the forefront of high throughput, low energy system design. This paper explores targeted deploy- ment of hardware accelerators to improve the throughput and efficiency of database processing.
Partitioning, a critical operation when manipulating large data sets, is often the limiting factor in database performance, and represents a significant amount of the overall runtime of database processing workloads. This paper describes a hardware-software streaming framework and a hardware accelerator for range partitioning, or HARP.
The streaming framework offers seamless execution environment for database processing elements such as HARP. Arun P Kedar, Dr. Manushree Muley, Dr. Sunil Vasant Prayagi, Dr.
Nischal Mungle, Dr. Ritu Bhattacharyya, Mr. Nikhelesh Bhattacharyya, Mr. Shail Sharaff. Selvakumaran Thunaipragasam, Dr. Om Prakash C, Dr. Prabhu A, Ms. Shanmugapriya, Dr.
Mariam F. Ghazy, Metwally A. AbdElaty, Mohamed H. Taman, El Sayed A. Qayes Jamal Abdel Qader, A. Ismail Hammadi Mujbil. Samsiah Mohd. Power transformer Internal winding faults detection and classification using AI based Classifiers.
Effect of using ground heat exchanger on the energy consumption, A review. Saif H. Majeed , Dheyaa G. Mtasher, Amar S. Korla Swaroopa, Dr. Chaitanya Kumar, Ms. Kadiri Padmaja, Dr. Shobha Rani, Dr.
Sanjaya Kumar Sarangi. Security Implementation Using Penetration Testing. Aswathy Mohan, G. Nitin Dhimole, Dr. Subramaniyam, Dr Varsha Namdeo. Anish kumar, G. Kaarthikeyan, J. Lokesh, N. Kaushik Kumar , V. Joly, Addluru mahesh , Mada upendra , Bhaskar karthik, Peddisetty sumanth. Shanmuga Kani,Dr. Ulagammai, Mr. Rohith,Arigala Manikanta. H Shree Kumar, K. Mintu Debnath, Dr.
Nitesh M. Sureja, Chetan J. Shingadiya, Hemant H. Patel, Divyarajsinh N. Srinivasu, G. Venkata Gopi, CH. Ravi Kishore, R. Bala Gangadhar, K. Srinivasa Reddy. Kanthi Kumar, Mrs. Suneetha, Dr. Ratna Babu. Nishant Pattanaik, Dr. Akanksha Mehta, Dr. Priyanka Bachhav, Ramesh Chandra Panda. Abha Pandey, Dr. Manish Shrimali, Dr. Arun Vaishnav. Regonda Nagaraju, Dr. Prakash Chandra Choudhary , Dr. Suresh Kumar Mishra, Dr. Saher Samir Saad Ali, Dr. Mahmoud Mohamed Ghaith, Dr. Sherif Sabry. Rohimi R.
S Wan Ismail, A. Ireana Yusra, Abd. Rahman, Z. Manideep Gopathi, K. The influence of vertical openings on the structural behavior of RC deep beams. Hasheesh, Ali M. Sanjay Kumar Bharti, Dr. Hilles, Alaa M. Pandranki Sowjanya, Dr. Radha Rani, Dr. Entropy Generation Analysis of the CNT-water nanofluid mixed convection inside a vented cavity with different number of elastic step and a Hexagonal solid under uniform magnetic field.
Stroke extraction for offline handwritten mathematical expression recognition. Kosaj, Dr. Rafid S. Alboresha, Dr. Sadeq O. Ravindranadh, U. Rama Krishna, A. Murali Krishna, K. Ashok Kumar, K. Sunitha, S. Ramesh Babu, K. Anil Kumar, P. Krishna Kanth, N. Pavan Kumar, Chilaka Jayaram. Rajesh Bhagat, Dr. Ranjit N. Patil, Dr. Rakesh Kumar Pandey. Jha, T. Dinesh Kumar, Vipan Kumar, Dr.
Muhammad Ahtesham Farooqui, Dr. Tasneem Bano Rehman, Dr. Shalu, Prof. Ramesh Chandra Panda. Brijesh Patil, Shrikant K. Yadav, Dr. Divya Midhunchakkaravathy.
The Case of Jakarta, Indonesia. A Review on Classification of Malignant Cells. A novel approach using Machine Learning Algorithm on healthy liver. Vikas Verma, Prachi Sengar, Md. Manzar Nezami,.
Machine Learning approach to detect Breast Cancer. Abdulhasan F. Thejel, Diyah K. Wind Turbine Performance: Review. Shabana Banu Shaik, Dr. Kotaiah, Dr. Ali Jabir Yousif, Dr. Kadhim J. Kadhim, Dr. Assel Mustafa Abd Al-Mjed. Dina Ahmed Mohamed, Jassim M. Najim, Yousif Al Mashhadany.
Latha Kalyampudi, Dr. Venkata Krishna, Dr. Aruna Rao S. Rama Devi. Extended Gibonacci Polynomial with Determinant Identities. Recent Developments and Applications in Welding Technology. Omar Sulaiman Khalaf Al. Hadad, Hasan Abdulrazzaq Hasan Al. Abid Ali, Farzad Mahboubi. Nabil M. Salih M. Lakshmidevi N. Vamsikrishna, Dr. Senthil Murugan,Dr. Sathya, Dr. P; Mrs. BinduMadavi K P, P. Dhanasekaran, S.
A novel classification approaches For eeg signals in brain computer interface. Jyostna Pandit Khedar, Arindam das, D. Deep Reinforcement learning approach towards autonomous navigation and its challenges.
Gayathiri Devi, Dr. Krishna Veni, Dr. Sankar, Dr. Manju Jose,. Reservoir Model for an Iraqi Oil Field. Social Orientation of Economic Development in a Pandemic. Gandla Shivakanth, Dr. Glass fiber reinforced epoxy composites. Analysis of soil stabilization in dal lake Srinagar using waste plastic fibre.
Evaluation of stabilized earth blocks in construction Of Nonstructural walls with different additives. Visual Vehicle Counting and Classification System.
Chinnasamy, V. Niveditha , S. Ramamoorthy, I. Beschi, Amandeep Singh K. Niveditha, T. Ananthan, S. Ramamoorthy, Amandeep Singh K. Saravanan, Dr. Adaikalam Arulanantham, Ms. Jayalakshmi, Dr. Performance study on stabilizaion of peat soil Using flyash and m sand. A study on factors influence on purchasing decision special reference to cosmetic products.
Machine learning techniques using big data analytics for electronic health record system- a survey. Covid Relevance of yoga practices and balanced diet for maintaining healthy lifestyle continuity under restrictions and stress imposed by lockdown. Study of Isomorphism, Homomorphism and their application. Constitutional morality vis- a- vis sentencing policy and punishments in India in the light of discretionary power of judiciary.
Rowthu Hemanth Kumar, Prof. Kiranmayi, K. Nagabhushanam, N. Rahul Shivaji Pol, Dr. Sheela Rani, Dr. Automatic generation of Ontology Diagrams. Hemant H. Patel, Dr. Shingadiya, Jay D. Measurement of total factor productivity in Indian pharmaceutical industry: An application of Data Envelopment Analysis. V Vijayalalitha, Prof. Sharma, Prof. Tapan Kumar Nayak, Prof. P Sivakumar,. Pandranki Sowjanya,Dr. Nagarani, Dr. Isaiyarasi, Mr. Sundarakannan, Dr.
Evaluation of Solar radiation in humid subtropical climatic belt in north India. Angeline Ruba, Dr. Golden Ebenezer Jebamani, Dr. Grace Prema. Prasanna, M. Premkumar, A. Sugapriya, M. Kannan, A. Arul Staline. Sumit Mor, Dr. Vikas Nandal, Dr. Vipin Saini, Dr. Surender Singh. Text with Image Editing Using Steganography.
Prevalence Rates of E. Optimization of cutting conditions parameters in Milling Process on surface roughness. Nizar N. Ismaeal, Saleh Hameed Ahmed. Sarah A. Al-Dahan, Moatz Majeed Ali. Optimum safe design of bridge abutments to control and decrease the scouring. Experimental study of fire resistant properties of Quartz powder filled areca phenolic resin composites.
Viswaprakash Babu, Dr. Shafeeque Ahmed K. Mohamed Shuaib, Dr. Manikandan, Dr. Sathik Basha. Soma Hari Sudharshan, Dr. Arun Kumar, K. Pavan Kumar. Solar pv powered srm drive for electric vehicles with flexible energy control functions Using incremental conductance algorithm. Hari Praneet Sreenivasula. Pritam Khatarkar,Prof. Vikas Rohit,Dr. Anjana Pandey, Dr. Roopam Gupta. Shabeeb Alzuabi, M. Abdelrahman, M. Moawad, M. Ban Ghulam Ridha Ali, Prof.
Zena Khalefa Kadhim. Anantha Babu, S. Deepak, M. Ashokkumar, M. Mathanbabu, K. Mathivanan, R. A ranking method for solving type-2 fuzzy unbalanced transportation problem using the triangular fuzzy number. Aliaa A. Mahmoud, Mohamed M. El Attar, Alaa M. El Eishy. Vijaya Nirmala, M. Thyagaraju, Dr. Jayakranth Rapoori. Iman Ali Shawkat, Kamalaldin F. Hasan, Qayssar Mahmood Ajaj. Samer S. Abdulhussein, Ahmed G. Manhl, Maryam S. Chinnapothula Sowjanya, Dr.
Gudapati Sambasivarao, Dr. Haydar H. Gehad F. Abdel Aziz, Tarek M. Attia, Aly S. There is a Matlab Tutorial here. We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously. Analysis of the failure of cell signaling networks is an important topic in systems biology and has applications in target discovery and drug development. Unzip the vehicle images and load the vehicle ground truth data. Create a file datastore with a custom read function, c ocoAnnotationMATReader , that reads the content of the unpacked annotation MAT files, converts grayscale training images to RGB, and returns the This paper presents information on wide aspects of the computer graphics, introduction to Matlab and its Image Processing Toolbox.
Directly on the program. This will be used to convert all image pixels in to their number numpy array correspondent and store it in our storage system. First and foremost, we will need to get the image data for training the model. Step 3 — Buliding the CNN. Game, Mastermind, in learning theory language, i. We pride ourselves on high-quality, peer-reviewed code, written by an active community of volunteers. Malaria is an extremely infectious disease cause due to blood parasite of genus plasmodium.
That brings your grand total to 50! When I resize some small sized images for example 32x32 to input size, the content of the image is stretched horizontally too much, but for some medium size images it looks okay.
Malaria is a terrible disease in the hematological region causing millions of mortality; hence the fast diagnosing is the extreme requirement of era. Randomly assigning weights for the different filters. It takes an input image and transforms it through a series of functions into class probabilities at the end. Say you want to label some images as "cars" and "trees"-Then you save them as sub folders of myImages with the folder names as "cars" and "trees".
It is simple, efficient, and can run and learn state-of-the-art CNNs. Motivated by that, we use a deep CNN for image denoising. This division is done by writing Matlab code. It contains the ready trained network, the source code, the matlab binaries of the modified caffe network, all essential third party libraries, the matlab-interface for overlap-tile segmentation and a greedy tracking algorithm used for our submission for the ISBI cell tracking image copy-move matlab free download.
One deep learning approach, regions with convolutional neural networks R-CNN , combines rectangular region proposals with convolutional neural network features. Since the breakthrough work of [8], CNNs have had a major impact in computer vision, and image understanding in particular, essentially replacing traditional image representations such as the ones implemented in our own VLFeat [13] open This amounts to: converting the image to single format but with range 0,, rather than [0, 1] as typical in MATLAB , resizing the image to a fixed size, and then subtracting an average image.
Create an R-CNN object detector for two object classes: dogs and cats. Each image contains one or two labeled instances of a vehicle. This is a simple to use code of Convolution Neural Network -a deep learning tool. We propose a deep learning method for single image super-resolution SR. More realistically would be 5. AlexNet contained eight layers; the first five were convolutional layers, some of the R-CNN is an object detection framework, which uses a convolutional neural network CNN to classify image regions within an image [1].
It includes software for examining, constructing and converting DICOM image files, handling offline media, sending and receiving images over a network connection, as well as demonstrative image storage and worklist servers. Create a file datastore with a custom read function, c ocoAnnotationMATReader , that reads the content of the unpacked annotation MAT files, converts grayscale training images to RGB, and returns the Inspired by the fact, we propose an attention-guided denoising convolutional neural network ADNet , mainly including a sparse block SB , a feature enhancement block FEB , an attention block AB and a reconstruction block RB for image denoising.
The RAW circle and cross image files are available here. I did the same thing with the pristine images, calling the 4D array Y. AlexNet is a pre-trained class image classifier using deep learning more specifically a convolutional neural networks CNN. This greatly reduces the computational cost incurred when running Select a Web Site. Start Hunting!
Discover Live Editor. PST implemented using MATLAB here, takes an intensity image I as its input, and returns a binary image out of the same size as I, with 1's where the function finds sharp transitions in I and 0's elsewhere.
Example 3. This demo shows how to perform image clustering and dimension reduction using a pre-trained network. My previous model achieved accuracy of Contact me: email: p-ahmed. It involves training process adaboost can combine weak classifiers and provide accurate classifier. You can train a CNN to do image analysis tasks, including scene classification, object detection and segmentation, and image processing.
0コメント