Motor planning for reach memorization task in 3D space

Arm reaching towards remembered targets in three-dimensional space was analyzed. The aim of the project was to test whether various amounts of visual feedback, in combination with constant forces applied to the arm during reaching would affect the magnitude and direction of the reaching errors. The robotic arm (Haptic Master, Moog Inc) recorded the spatial position of the pointer attached to its end effector, thus tracking the movement of the subject\u27s arm. Three haptically rendered targets at different points in space were presented to the subjects using stereo virtual environment. The simulation was programmed using Visual C++ and OpenGL. Eight subjects were asked to remember the position of the target and then to reach the target with the pointer. Three different types of visual feedback were used, with full vision (Vision), with the target disappearing immediately before the movement onset (No Vision) and one second after the movement onset (Intermediate Vision). In all three visual conditions, the subjects arm was visible during the movement. In addition, an external force opposing gravity was applied in half of the trials. Pointing errors and different parameters of movement kinematics were analyzed and compared across conditions. It was observed that both the magnitude and the direction of reaching errors were affected by the amount of visual information available during the movement, as well as by the partial gravity compensation provided by the robot

Cloud Security Issue and Challenges

In past three decades, the world of computation has changed from centralized (client-server not web-based) todistributed systems and now we are getting back to the virtual centralization (Cloud Computing). Location of data and processes makes the difference in the realm of computation. On one hand, an individual has full control on data and processes in his/her computer. On the other hand, we have the cloud computing wherein, the service and data maintenance is provided by some vendor which Leaves the client/customer unaware of where the processes are running or where the data is stored. So, logically speaking, the client has no control over it. The Cloud computing uses the internet as the communication Media. When we look at the security of data in the cloud Computing, the vendor has to provide some assurance in Service level agreements (SLA) to convince the customer on security issues. Organizations use cloud computing as a service infrastructure; critically like to examine the security and confidentiality issues for their business critical insensitive applications. Yet, guaranteeing the security of corporate data in the "cloud" is difficult, if not impossible, as they provide different services like Software as a service (SaaS), Platform as a service (PaaS), and Infrastructure as a service (IaaS). Each service has their own security issues. So the SLA describes different levels of security and their complexity to make the customer understand the security policies that are being implemented. There has to be a standardized way to prepare the SLA irrespective to the providers. This can help some of the enterprises to look forward in using the cloud services. In this paper, we put forward some security issues that have to be included in SLA. Keywords: Cloud Computing, Service Level Agreement (SLA), Software as a Service (SaaS), Cloud computing Security

Fundamentals and Literature Review of Discrete Fourier Transform in Digital Signal Processing

Today’s world is digital world. While designing and analyzing the digital phenomena the most desired factor are high performance, time and cost(economy).DFT and FFT are the most efficient mathematical technique to meet these challenges .To compute DFT using FFT is genius method ,in this method FFT decomposes DFT with N sample points, into N DFT each with single point. This paper focus on DFT, FFT and its approach to Digital signal processing

Human Activity Recognition Based on Multimodal Body Sensing

In the recent years, human activity recognition has been widely popularized by a lot of smartphone manufacturers and fitness tracking companies. It has allowed us to gain a deeper insight into our physical health on a daily basis. However, with the evolution of fitness tracking devices and smartphones, the amount of data that is being captured by these devices is growing exponentially. This paper aims at understanding the process of dimensionality reduction such as PCA so that the data can be used to make meaningful predictions along with novel techniques using autoencoders with different activation functions. The paper also looks into how using autoencoders allows us to better capture the relations between features in the data. It also covers some of the classification techniques such as k-Nearest Neighbors, SVM and Random forest that are currently being used for activity recognition that have shown promising results

HMR LOG ANALYZER: ANALYZE WEB APPLICATION LOGS OVER HADOOP MAPREDUCE

In today’s Internet world, log file analysis is becoming a necessary task for analyzing the customer’s behavior in order to improve advertising and sales as well as for datasets like environment, medical, banking system it is important to analyze the log data to get required knowledge from it. Web mining is the process of discovering the knowledge from the web data. Log files are getting generated very fast at the rate of 1-10 Mb/s per machine, a single data center can generate tens of terabytes of log data in a day. These datasets are huge. In order to analyze such large datasets we need parallel processing system and reliable data storage mechanism. Virtual database system is an effective solution for integrating the data but it becomes inefficient for large datasets. The Hadoop framework provides reliable data storage by Hadoop Distributed File System and MapReduce programming model which is a parallel processing system for large datasets. Hadoop distributed file system breaks up input data and sends fractions of the original data to several machines in hadoop cluster to hold blocks of data. This mechanism helps to process log data in parallel using all the machines in the hadoop cluster and computes result efficiently. The dominant approach provided by hadoop to “Store first query later”, loads the data to the Hadoop Distributed File System and then executes queries written in Pig Latin. This approach reduces the response time as well as the load on to the end system. This paper proposes a log analysis system using Hadoop MapReduce which will provide accurate results in minimum response time

Neurobrucellosis: a case report

Neurologic involvement of brucellosis is common but exact prevalence of it is unknown due to difficulty in diagnosis and inadequate reporting all over the world. Neurologic involvement may manifest as chronic meningitis, lymphocytic meningoencephalitis, a variety of cranial nerve deficits, or ruptured mycotic aneurysms. We report a case of young male who had history of fever and headache on and off for 2 years and later developed signs of meningitis, lateral rectus palsy, altered sensorium and bilateral papilledema. He did not respond to anti-tubercular therapy and antibiotics. CT scan and MRI brain were normal. He had hepato-splenomegaly with small hypoechoic lesions in the spleen. CSF culture grew gram negative bacilli. Brucella IgG antibodies in serum by EIA 7, IgM negative, Brucella antigen titer was positive, 1:160. Patient received inj. streptomycin 0.75 g for 21 days and doxycycline 100 mg twice daily doxycycline for 6 weeks. The complete improvement in patient’s condition after a long lasting illness motivated authors to report this case. Delay or failure in diagnosis of this treatable disease may lead to significant morbidity and mortality so high index of suspicion should be kept in such cases

Web service Recommendation by combining QOS and user comments

Due to well gaining experience of internet its user’s expectation from the search engines increases dramatically. Due to this search engines capability is not only limited to the providing desired URL’s to the users query. Moreover to this search engines are expected to provide information by analyzing in proper way like by doing surveys and recommendations. So many recommendation systems are existed which are working on some limited aspect of the parameters for recommending a web service. This paper represents a method of recommendation which considers users opinion and quality of the service parameter of the web service. The proposed idea captures the response time of the user transaction for a web service along with the users opinion comments about the web service. Then by combining both a new hybrid recommendation system is introduced which efficiently provides the recommendation that is more accurate and fine grained. This hybrid recommendation is powered with the Pearson correlation and strong NLP protocols to attain most accurate state. DOI: 10.17762/ijritcc2321-8169.15083