Calendar

Calendar

May
6
Thu
Robotics department Students Projects Presentations
May 6 @ 2:00 pm – 4:00 pm
Robotics department Students Projects Presentations

Nazarbayev University School of Engineering and Digital Sciences is delighted to invite you to the Group Project Presentations of the students of the Robotics department. Our final year students developed in the groups their projects during 2 semesters of studies. The students will show their problem-solving and communication skills.

Date: May 6th, 2021,

Time: 14:00 (Nur-Sultan time)

The presentations will be provided in online format by the following schedule:

Time slot                         Group members                                                            Project title
14:05 –14:20 1) Anuar Nurlybayev
2) Shyngyskhan Abilkassov
Autonomous Navigation of a Skid-Steering Mobile Robot in Human Present Environment
14:25 –14:40 1) Merey Kairgaliyev
2) Bauyrzhan Zhakanov
3) Serzhan Safin
Video Lecture Synthesis from Audio: Towards AI-based Instructors
14:45 – 15:00 1) Jabrail Chumakov
2) Dimash Mukashev
3) Nurlan Zhaniyar
Integrated Event-based Tactile Sense in Haptic Physical Interactions for Augmented Reality
15:05 – 15:20 1) Madi Nurmanov A Neuromorphic Control System for an Aquatic Robot
15:25 – 15:40 1) Aigerim Keutayeva
2) Biinur Boranbay
3) Saltanat Aidarova
Shoulder Rehabilitation Exoskeleton: Biomechanics, Design and Control.
15:45 – 16:00 1) Rustam Chibar
2) Shamil Sarmonov
3) Ulugbek Alibekov
Fine Indoor Localization Using IMU and WiFi Fusion

Register here to participate: 

May
11
Tue
Computer Science Department Students Project Presentations
May 11 @ 2:00 pm – 4:30 pm

Nazarbayev University School of Engineering and Digital Sciences is delighted to invite you to the Group Project Presentations of the students of the Computer Science department. Our final year students developed in the groups their projects during 2 semester of studies. The students will show their problem-solving and communication skills.

Date: May 11th, 2021,

Time: 14:00 (Nur-Sultan time)

The presentations will be provided in online format by the following schedule:

Time slot                         Group members                                                            Project title
14:00-14:20 Maxat Nurgazin, Akzhol Nabiolla, Akezhan Mussa A Distributed Localisation and Proximity Analysis System for Pandemics
14:20-14:40 Diana Murzagaliyeva, Nuray Nabiyeva A Software Framework for the Modeling and Analysis of Interactive Systems
14:40-15:00 Abylay Toktassyn, Aidyn Ubingazhibov Continuous sign language recognition
15:00-15:20 Izat Khamiyev, Nurtas Ilyas Face detection with the positioning of 3d model of glasses for web application
15:20-15:40 Askhat Kenenbay, Denis Kim, Kamila Zhanuzak Modeling and Development of a Learning Management System
15:40-16:00 Farkhad Kuanyshkereyev,    Rauan Amangeldiyev Optimal and Full Coverage Path Planning for the Agricultural Sector
16:00-16:20 Allan Dyussenbayev, Miras Bakhytbek, Alibek Seksenali Pose based action recognition project
16:20-16:40 Alisher Sultanov, Daulet Amirkhanov, Ablan Abkenov, Zhalgas Khassenov Home Security System
16:40-17:00 Saadat Nursultan, Valeriy Novossyolov The Synthesis and Visualization Tool for Design of Quantum Circuits
17:00-17:20 Aiya Yegenberdiyeva, Talgat Omarov, Lyailya Mussakhanova Web Application for Competitive Debates

 

Register here to participate: 

May
12
Wed
Chemical and Materials Engineering Department Students Presentations
May 12 @ 2:00 pm – 4:15 pm

Nazarbayev University School of Engineering and Digital Sciences is delighted to invite you to the Group Project Presentations of the students of the Chemical and Materials Engineering department. Our final year students developed in the groups their projects during 2 semesters of studies. The students will show their problem-solving and communication skills.

Date: May 12th, 2021,

Time: 14:00 (Nur-Sultan time)

The presentations will be provided in online format by the following schedule:

Time slot Students Project title
Undergraduate Students Project Presentations
14:10-14:30 Aimambet Abylaiuly, Miriam Absalyamova, Maksat Maratov, Rustam Abubakirov, Amirsana Kiykbay Sulfur from natural gas fuel processing
14:30-14:50 Rakhat Baitubayev, Kulyan Karipbayeva, Adil Abduakhanov, Magzhan Amze, Nurdaulet Mukhtarov Design a chemical plant of acetaminophen starting from phenol
14:50-15:10 Nursaule Batyrgali, Aisholpan Kaziullayeva, Miras Kaliyakhmet,Zhassulan Nurmukhan, Alibi Aitenov Dimethyl sulfate production
Master Thesis Presentations
15:10-15:30 Aidana Boribayeva, MSc in Chemical and Materials Engineering Program Packing structure of powder compacts
15:30-15:50 Yerbolat Kakimov, MSc in Chemical and Materials Engineering Program Evaluation of Decoupling of GDP, Energy, and CO2 Emissions in EU-15
15:50-16:10 Nurdaulet Suleimen, MSc in Biomedical Engineering Program Visualizing and quantifying the mechanism of the microtubule inhibitor ELR510444 in cell populations using multimodal imaging techniques

 

Register here to participate: 

May
13
Thu
Civil and Environmental Engineering Department Student Presentations
May 13 @ 2:00 pm – 3:00 pm

Nazarbayev University School of Engineering and Digital Sciences is delighted to invite you to the Group Project Presentations of the students of the Civil and Environmental Engineering department. Our final year students developed in the groups their projects during 2 semesters of studies. The students will show their problem-solving and communication skills.

Date: May 13th, 2021,

Time: 14:00 (Nur-Sultan time)

The presentations will be provided in online format by the following schedule:

Time slot Students Presentation titles
14:00-14:30 Sultan Kobeyev, Tileuzhan Mukhamet, Alimzhan Oteuil, Farnush Nazipov, Adilbek Oralbek Design of a High-rise Hotel in Los Angeles, California, USA
14:30-15:00 Almat Abilez, Iliyas Omarov, Ayana Ospanova and Diana Khussainova Design of Multi-story Apartment Building in San Francisco, California, USA

 

Register here to participate: 

We look forward to seeing you during the online presentations.

May
19
Wed
PhD Thesis Defense by Yerzhigit Bapin, NU PhD Program in Science, Engineering and Technology
May 19 @ 7:00 pm – 8:00 pm

Nazarbayev University’s PhD Program in Science, Engineering and Technology is delighted to invite you to the PhD Thesis Defense:

Candidate: Yerzhigit Bapin, 5th year PhD student

Thesis Title: APPLICATION OF PROBABILISTIC METHODS FOR EFFECTIVE AND RELIABLE OPERATION OF ELECTRICAL AND ELECTROMECHANICAL SYSTEMS

Date and time: May 19, 2021 (Wednesday) at 7:00 PM (Nur-Sultan time)

Lead Supervisor: Prof. Vasileios Zarikas, Dept. of Mechanical and Aerospace Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Kazakhstan.

Co-Supervisor:  Prof. Mehdi Bagheri, Dept. of Electrical and Computer Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Kazakhstan.

External Supervisor: Prof. Nick Papanikolaou, Democritus University of Thrace, Greece.

Chair-Internal Examiner: Prof. Luis Rojas-Solórzano, Dept. of  Mechanical and Aerospace Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Kazakhstan.

Internal Examiner: Prof. Dimitrios Emiris, Dept. of Civil and Environmental Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Kazakhstan.

External Examiner: Prof. Eduardo Cotilla-Sánchez, Oregon State University, USA.

Join Zoom Meeting – https://nu-edu-kz.zoom.us/j/95655992175

Abstract:

This PhD thesis presents novel system control methods that can be utilized for effective and reliable operation of electric grids and passenger elevators. First of all, this study introduces a new spinning reserve allocation optimization technique that takes into account load and renewable power generation, inter-zonal conventional power generating capacity and demand response. Using the bivariate Farlie-Gumbel-Morgenstern probability density function, the framework presented in this thesis utilizes a new method to simulate the power generation of wind farms. In addition, the presented framework uses a Bayesian Network (BN) algorithm to fine-tune the spinning reserve allocation based on previous hours’ actual unit commitment, as well as the hour and day types.

The model proposed in this study has been tested on the IEEE Two-Area Reliability Test System (RTS) to quantify the effect of the bivariate wind prediction model and the Bayesian network-based Reserve Allocation Adjustment Algorithm (RAAA) on reliability and cost-effectiveness of the power grid. The findings show that combining a bivariate wind forecast model with RAAA improves power grid stability by 2.66 percent while lowering overall system running costs by 1.12 percent.

Secondly, the present work introduces an algorithm with an objective of optimal dispatching control of passenger lifts. The algorithm utilizes the data received from video cameras and dispatches the elevator cars based on the passenger count. The proposed algorithm utilizes the information on the number of people and dispatches the lifts with an objective to move the maximum number of passengers to the desired building levels within the minimum amount of time. In addition, the algorithm considers each person’s size and whether or not they have luggage. To account for uncertainty in image acquisition, the algorithm assigns the probability weights to the number of people who are waiting for a lift and riding the lifts. The main purpose of the algorithm is to minimize the following performance metrics: average travel time (ATT), average journey time (AJT) and average waiting time (AWT).

The suggested algorithm works well in situations of limited traffic sizes, according to a test case scenario conducted on a ten-story office building having four elevator cars (less than 200 people). In a scenario with large up-peak high intensity traffic, the proposed algorithm primarily underperforms. The proposed algorithm’s best output was seen in situations with random inter-floor passenger movement. In scenarios of changing traffic intensity and size ATT increased by 39.94 percent and 19.53 percent, respectively.