01.NU Schoolshttp://nur.nu.edu.kz:80/handle/123456789/672024-03-29T13:51:20Z2024-03-29T13:51:20ZANALYSIS OF INTERFERENCE IN LFM RADAR DETECTION AND IMAGING IN A MULTI-RADAR ENVIRONMENTNwigbo, Suanuhttp://nur.nu.edu.kz:80/handle/123456789/75902024-02-05T17:00:27Z2023-04-01T00:00:00ZANALYSIS OF INTERFERENCE IN LFM RADAR DETECTION AND IMAGING IN A MULTI-RADAR ENVIRONMENT
Nwigbo, Suanu
Because of the growing use of radio detection and ranging (radar) systems in multiple application sectors, the radars have to be operated on the same or adjacent frequency resources. This frequency overlap can cause interference and impacts the performance of the victim radar. Besides unintended interferences, there could also be intentional interferences. The interference can cause a reduction in the signal-to-noise ratio, introduce ghost targets, and lead to poor detection capabilities of the radar as well as false detections. Thus, interference effects should be compensated to operate the radar in a safe and secure environment.
In this thesis, different types of interference and their impact on traditional linear frequency modulation (LFM) based radio detection and ranging (radar) are investigated through numerical simulation and electronic radar-based experiments. The work has been extended to investigate the imaging of radar-detected objects with the help of the back-projection technique.
In the simulation environment, a multi-radar environment has been created to investigate the effect of external interference radar on the victim radar. Different types of interference waveforms such as LFM, triangular and pulsed waveforms are being considered. It is found that the LFM-based waveform suffers from coherent LFM interference, which can result in the appearance of ghost targets on the range profile. Whereas, non-coherent types of interference increase the noise level, reducing the signal-to-noise ratio, thus adversely impacting the detection accuracy. Thus, a random hopping LFM-based waveform as an alternative to the LFM-based waveform has been proposed as a robust waveform to mitigate interference in a multi-radar environment.
Experimental work with an mm-wave (77GHz-81GHz) radar sensor for detecting targets has been performed, and radar performance metrics such as range and range resolution have been evaluated with the theoretical values.
Through the back-projection algorithm, the imaging of the detected objects has been obtained. Through extensive iteration, it is found that the back-projection with weighting function provides enhanced resolution.
2023-04-01T00:00:00ZHEART SOUND CLASSIFICATION VIA VISION TRANSFORMER MODELSAdilkhanuly, Zhanathttp://nur.nu.edu.kz:80/handle/123456789/75862024-01-26T21:00:16Z2023-11-23T00:00:00ZHEART SOUND CLASSIFICATION VIA VISION TRANSFORMER MODELS
Adilkhanuly, Zhanat
The automatic heart sound classification is an integral part of the early diagnosis
of cardiovascular diseases(CVDs). Even though advances in medical technologies
allow us to diagnose many CVDs, it remains one of the leading causes of death
worldwide due to its absence of symptoms at the initial stages. Thus, there is a huge
demand to develop other methods of identifying heart sound abnormalities that are
less expensive, simple, and applicable. Several audio feature extraction methods, in
combination with classification models, have been developed over time. However,
existing feature extraction methods are sensitive to noise, which negatively impacts
the performance of the heart sound classification model. In addition, there is a strong
need to develop models more sensitive to heart sound abnormalities in patients. In this
work, we address the limitations of extracted features by using spectrogram images
that are taken from Discrete Fourier Transform, and introducing them to Vision
Transformer Model. Results of our experiments on the benchmark of PhysioNet Heart
Sound Dataset show that the proposed method outperforms existing methodologies
with an accuracy of 0.925 and with a sensitivity score of 0.955
2023-11-23T00:00:00ZTHE AXL INHIBITOR TP-0903 AND ARTESUNATE SYNERGISE TO INDUCE REACTIVE OXYGEN SPECIES, DNA DAMAGE AND APOPTOSIS IN TRIPLE NEGATIVE BREAST CANCER CELLSTerragno, Mirkohttp://nur.nu.edu.kz:80/handle/123456789/75852024-01-26T21:00:20Z2024-01-01T00:00:00ZTHE AXL INHIBITOR TP-0903 AND ARTESUNATE SYNERGISE TO INDUCE REACTIVE OXYGEN SPECIES, DNA DAMAGE AND APOPTOSIS IN TRIPLE NEGATIVE BREAST CANCER CELLS
Terragno, Mirko
Triple Negative Breast Cancer (TNBC) is an aggressive, often rapidly growing form of breast cancer. TNBC usually displays a basal molecular phenotype that associates with epithelial mesenchymal transition (EMT), a cellular program that confers chemoresistance and metastasis. Approximately 56% of TNBC cases show a basal-like gene expression profile and roughly 46% of TNBC patients have distant metastasis. In general, the absence of molecular targets in TNBC is the main obstacle for the development of an effective therapy. For example, TNBC does not respond to endocrine and anti-human epidermal receptor (HER2) treatments as it does not express estrogen and progesterone receptors (ESR/PgR) and human epidermal receptor 2 (HER2). In addition, though initially TNBC is more responsive to cytotoxic drugs compared to other subtypes, TNBC presents a higher relapse rate. Therefore, new anti-TNBC treatment strategies are urgently needed. Drug combination therapy for TNBC could rely on protocols whereby EMT reversal sensitizes TNBC to anti-cancer compounds that are effective against epithelial tumors. Recently, the anti-malaria compound Artesunate (ART) has been shown to exert cytotoxicity in breast cancer by generating reactive oxygen species (ROS) and DNA double strand breaks (DSBs). However, the effect was more pronounced in tumors of epithelial than mesenchymal origin. In this project, the hypothesis was to verify whether EMT inhibition could sensitize TNBC cell lines to ART cytotoxicity. To address this, two aims were pursued. Aim 1 verified whether receptor tyrosine kinase (RTK) AXL inhibitors TP-0903/R428 and AXL/ZEB1 knockdown sensitised TNBC cell lines to ART-generated ROS, DNA damage and apoptosis. Aim 2 was to test whether TP-0903 and AXL/ZEB1 knockout in TNBC cell lines suppressed expression of superoxide dismutase 1/2 (SOD1/2), glutathione peroxidase 8 (GPX8) and catalase (CAT)...
2024-01-01T00:00:00ZCOMING BACK HOME: POSTMEMORY IN NOVELS BY ALEXANDER CHUDAKOV, KATJA PETROWSKAJA, AND MARIA STEPANOVAMektepbayeva, Zhanelhttp://nur.nu.edu.kz:80/handle/123456789/75842024-01-19T12:29:56Z2023-11-27T00:00:00ZCOMING BACK HOME: POSTMEMORY IN NOVELS BY ALEXANDER CHUDAKOV, KATJA PETROWSKAJA, AND MARIA STEPANOVA
Mektepbayeva, Zhanel
This study explores postmemory as a way of “coming back home” to one’s roots and reimagined identity. It is particularly important within the context of the recent turn to prioritizing personal memories over the official, collective memory to process traumatic historical experiences of the 20th century, such as the war, Stalinist purges, and the Holocaust. The thesis presents a comprehensive analysis of three contemporary novels — Alexander Chudakov’s A Gloom Is Cast Upon the Ancient Steps (Lozhitsia mgla na starye stupeni, 2000), Maria Stepanova’s In Memory of Memory (Pamiati pamiati, 2017), and Katja Petrowskaja’s Maybe Esther (Vielleicht Esther, 2014). The study uses the theory of postmemory, developed by Marianne Hirsch, to research how different generations of survivors engage with stories and objects of memory, such as family photographs, letters and archival documents to access the experience of their ancestors. The thesis uses the methods of literary analysis and close reading to discuss, through the question of genre, connections between literature, memоry, and the enduring impact of catastrophic historical events on subsequent generations.
2023-11-27T00:00:00ZFABRICATION AND CHARACTERIZATION OF FUNCTIONALLY GRADED MATERIALS: STUDY OF MICROSTRUCTURE IN CENTRIFUGAL COMPACTION AND HOT PRESSING PROCESSESSariyev, Bakytzhanhttp://nur.nu.edu.kz:80/handle/123456789/75832024-02-12T04:21:54Z2023-08-31T00:00:00ZFABRICATION AND CHARACTERIZATION OF FUNCTIONALLY GRADED MATERIALS: STUDY OF MICROSTRUCTURE IN CENTRIFUGAL COMPACTION AND HOT PRESSING PROCESSES
Sariyev, Bakytzhan
In recent times, remarkable progress in science and technology has prompted scientists to create a new category CCP of structural materials with enhanced characteristics. Functionally graded materials (FGMs) are a new type of composite materials made up of two or more components that are continuously varied in their distribution. The idea of FGMs can be utilized to exploit the advantageous properties of each constituent phase and adjust the distribution of material properties to achieve the desired response to specific mechanical and thermal loads or to modify natural frequencies in a desired manner. To fully utilize the exceptional properties of FGMs in the development of new products, it is essential to conduct fundamental studies on the mechanics of these materials, as well as research on their processing.
The first study investigates the application of centrifugal force for the compaction of metal powders. Aluminium alloy powder with a particle size less than 100 µm and polymer binder were mixed and compacted in the centrifugal machine with varying degrees of centripetal acceleration. SEM micrographs of the green bodies' microstructure showed significant packing densities and an increase in median particle size at sites further from the centrifuge's centre of rotation. The segregation phenomena was not observed at 700 G, but clear particle segregation was found at higher centrifugal forces. This investigation focuses on the development of topologically complex FGM by controlling interfacial microstructure through CCP-based compaction.
The second study examines poly(ether-ether-ketone) (PEEK) and graphite-based high-performance laminate composite materials. The structural, thermal, and mechanical characteristics of the composites, which were created utilising the hot press technique at temperatures below 310°C, were carefully examined and described. SEM images indicated a strong interfacial contact between PEEK and graphite. This research focuses on the design of PEEK/graphite FGM with topologically complex multi-scale compositions and revealed improved mechanical and thermal properties due to the synergistic effect of incorporation of two dissimilar materials under high temperature and joining load.
Overall, this dissertation provides insights into the design and fabrication of materials with multi-scale topologies. The research focuses on understanding the interfacial behaviour of materials at various scales and developing fabrication methods to produce materials with desired properties.
2023-08-31T00:00:00ZGLULA: LINEAR ATTENTION BASED MODEL FOR EFFICIENT HUMAN ACTIVITY RECOGNITION FROM WEARABLE SENSORS AND SKELETON DATABolatov, Aldiyarhttp://nur.nu.edu.kz:80/handle/123456789/75822024-01-10T21:01:15Z2023-01-01T00:00:00ZGLULA: LINEAR ATTENTION BASED MODEL FOR EFFICIENT HUMAN ACTIVITY RECOGNITION FROM WEARABLE SENSORS AND SKELETON DATA
Bolatov, Aldiyar
Sensors’ data is used in monitoring patient activity during rehabilitation and also can
be extended to controlling rehabilitation devices based on the activity of the person.
Both wearable sensors and extracted skeleton data from the video can be used for that.
As there, exist similarities, a unified solution can be presented, which also focuses on
effectively capturing the spatiotemporal dependencies in the data collected by these
sensors and efficiently classifying human activities. With the increasing complexity
and size of models, there is a growing emphasis on optimizing their efficiency in terms
of memory usage and inference time for real-time usage and mobile computers. There
is an opportunity to develop a novel unified framework that incorporates recent advancements
to enhance speed and memory efficiency, specifically tailored for Human
Activity Recognition (HAR) tasks. In line with this approach, we present GLULA, a
unique architecture for human activity recognition. GLULA combines gated convolutional
networks, branched convolutions, and linear self-attention to achieve efficient
and powerful solutions. Extensive experiments showed its effectiveness both in wearable
sensors’ data and skeleton-based sets. Tests were conducted on five benchmark
IMU datasets: PAMAP2, SKODA, OPPORTUNITY, DAPHNET, and USC-HAD.
Our findings demonstrate that GLULA outperforms recent models in the literature
on the latter four datasets but also exhibits the lowest parameter count among stateof-
the-art models. In HAR for the human skeleton domain, examinations were done
on the NTU RGB+D dataset. While getting comparable results with recent work in
this field, it managed to be smaller and significantly faster.
2023-01-01T00:00:00Z