Financed Research Projects
- Artavazd Khachatryan/YSU
- Khachik Sahakyan/YSU
The main purpose of this project is to apply the latest developments in machine learning to medical databases. Although large databases of medical time-series data are freely available, they are largely ignored by the machine learning community. The main reason is that lots of medical expertise is required to understand and process these databases.During this project we will define several standardized benchmarks on MIMIC-III clinical database1 that are known to be useful for doctors (e.g. in-hospital mortality prediction, phenotype classification, length of stay prediction etc.), will apply various state-of-the-art machine learning models on these benchmarks and will develop new models.
The brain is integrity of billions of computational units from the point of view of information processing. The communication between these units is realized via electrical signals and each unit shows the ability of experience integration, i.e. the abilityof learning. The study of the mechanisms of information storage, encoding and conducting in this system is of great importance for application in brain machine interfaces and neuroprosthetics. The recording of the electrical activity of a brain is an irreplaceable method for studying the behavior of neural populations and athematical or physical patterns underlying this behavior. Recording of this signal makes it possible to detect the behavior of neural populations with high temporal and spatial resolution. An additional reason of interest in LFPs is that they provide stable signal for a longer period and therefore, are useful for long‐term chronic experiments and for clinical applicationssuch as Brain Machine Interfaces (BMI). However, as LFP captures a multitude of neural processes, the extraction of essential features is among the main problems of Computational euroscience.The investigation of neural activity underlying cognitive functions requires recording of activity in several brain regions and analytical methods that will give an opportunity to ombine multiple features of spatially and temporally separated complex signals to achieve a robust classification of brain states. The extraction of cognitive functions requires complex processing of information. We will continuously execute these steps in a cycle and at each iteration, we are going to improve further the placement methods and positioning of the electrodes, the LFP signal conditioning circuit and signal analyzing algorithms. So, one of the outcomes of the project will be the developed complete methodology for LFP recording and analysis. Another expected outcomeof this project is an analysis tool for LFP data which can also be used in the animal models of neurological and neurodegenerative disorders. As a result of our project, we will have a large amount of data of LFP recordings and video recordings, both in raw and processed versions. We are going to make this data available in the Internet. This community-driven data sharing may offer cross-validation of findings and refinement of interpretations of the data. After the achievement of solid results with LFP recording, we are planning to couple it with simultaneous recording of EEG in the same animal. This can lead to translation of our methods to human EEG data analysis, which is relevant as a non-invasive method.
- Serob Muradyan/RAU
- Lusine Hovhannisyan/YSMU
- Amalya Hakobyan/YSMU
- Ani Alaverdyan/YSMU
- Kristina Sargsyan/MSUIECS
- Arman Grigoryan/ERIICTA
- Eduard Khachatryan/ERIICTA
Main purpose of our project is to deliver a cloud-based service for white-hat penetration testers and security professionals for an advanced and automated shellcode obfuscation techniques, thus helping them to easily conduct social engineering based penetration vectors.The core of the problem and what are we trying to solve is that during social engineering vectors security professionals use no or very poor obfuscation for theirshellcodes and payloads, because this would take big amount of time, effort and research. In result – very low percentage of successful conducted vectors due to high risk for shellcodes and payloads to be caught by an end-point security system. This totally confronts with the point of penetration testing audits because they are ment to simulate real-world scenarions of cyberthreat and in real-world scenarios companies\organisations are being attacked not by white-hat security professionals but by black-hat hackers who do have access to illegal obfuscating programs. Summarizing all this we get that the black-hat hackers have serious advantages over legitimate white-hat professionals who help improve security.
- Vahe Karapetyan
- Sipan Vardanyan
Electronic Health Information Management System (e-HIMS) is an essential element of healthcare improvement and a vital component of strategies for healthcare system reform. A health information system that provides reliable, timely, high-quality information is a key prerequisite for healthcare system improvement in now days. Since 2010 Armenian government is working on development and implementation of integrational Integrated Health Information System of Armenia (IHISA). Currently the government is highlighting the need of e-HIMS implementation in the healthcare facilities. This fact enforcing and expanding the market for e-HIMS in Armenia. Having this vision and perspectives we developed Electronic Health Information Management System (e-HIMS) for the healthcare facilities which is intelligent instrument that supports health care services to compile and use health information for better clinical and financial performance. It has multiple modules that allows computerizing clinical workflow throughout the health care facility and adapt the system to reflect the way healthcare facility works. Moreover, one of the key components of our e-HIMS product is electronic quality control management system. The Quality of healthcare is comparatively new concept in healthcare and it is defined as level of value delivered by any healthcare resources. According to the US Institute of Medicine it is a degree to which health services for people increase the probability of targeted health outcomes and are consistent with existing medical knowledge. In other words, quality of health care services could be defined as doing the right thing, at the right time, in the right way, for the right person – and having the best possible results. Effective and efficient quality systems can promote good practice. The studies and scientific publications are showing that is very difficult to implement described e-Health projects. For doctors, patients, and the health care managers the implications of Electronic Health Information Management Systems are usually hard to understand, as are the likely pace and extent of adoption of e-HIMS.
- Karapet Davtyan/AUA
- Artashes Tadevosyan/YSMU
- Hayk Davtyan/AUA
Application of IBM® BPM Technology to Ensure and Measure BPM Project/Program Efficiency in Telecommunication Industry of Armenia.
The Project aims to make a deep analysis of three business processes in elecommunication sector companies of Armenia and to define efficiency growth measures via application of IBM® products with sufficient automation and control. The following business processes shall be considered: Training & Development, Compensation & Benefits (Reward Management), and Performance Management. The projects aim to link science with practice via connecting theoretic research with practical applications and output analyses.Purpose 1: Analyze telecommunication sector development trends and BPM challenges from customer excellence and shareholder expectations perspective. Purpose 2: Integrate IBM® products into the Training & Development, Reward Management, and Performance Management processes. Purpose 4: Test and prove efficiency of IBM® products application in telecommunication sector from BPM perspective.
- Marine Ghahramanyan/UJML
- Lilit Poghosyan/NUACA
- Irina Poghossian/AUA
Regional Analysis and Decision-Making Optimization through Technology Based Strategy in vayots Dzor Region
Research based decision making is a rare procedure for Armenian regional development. Technology based research and innovative solutions also are far from the development strategy. In this context the proposed interdisciplinary research (including statistics, economics, regional development and public administration) cloud integrate academic approach, business needs and community development through new technological solutions through development of computer-human interaction and knowledge-rich intervention. Economics, statistics and public administration are core components of the research that will be developed through SPSS modeling, GIS spatial managment and Cloud infrastructure managment tools. The objectives of the project are regional economic modeling and spatial development strategy based on inter-municipal cooperation and social entrepreneurship for the target region, as well as knowledge transfer and education. The expected results of the project will be (1) a developed course for higer education, (2) a five person research group, (3) a manual, (4) economic models and relevant academic papers, (5) a spatial development strategy and relevant academic paper.
- Sos Khachikyan/ASUE
- Arthur Dolmajian/École Polytechnique de Montréal
- Armen Ktoyan/ASUE
- Davit Shahnazaryan/YSU
The work is devoted to research in waveforms having opportunity and perspective of using in the fifth generation mobile communication networks. Through the analysis of existing modulation techniques, relative advantages and disadvantages will be detected. Taking into account the parameters of spectral efficiency, noise resistance, required signal to noise ratio, implementation simplicity, compatibility with data transmission MIMO (Multiple Input Multiple Output) technique, as well as arising new requirements in mm wave frequency range the best modulation technique for fifth generation mobile communication networks will be selected and suggested for use.
- Martin Aivazyan/PhD, Associate Professor NPUA
- Levon Grigoryan/PhD student NPUA
- Hayk Avetisyan /PhD student NPUA