IMPROVED DESIGN OF DTW AND GMM CASCADED ARABIC SPEAKER

In this paper, we discuss about the design, implementation and assessment of a two-stage Arabic speaker recognition system, which aims to recognize a target Arabic speaker among several people. The first stage uses improved DTW (Dynamic Time Warping) algorithm and the second stage uses SA-KM-based GMM (Gaussian Mixture Model). MFCC (Mel Frequency Cepstral Coefficients) and its differences form, as acoustic feature, are extracted from the sample speeches. DTW provides three most possible speakers and then the recognition results are conveyed to GMM training processes. A specified similarity assessment algorithm, KL distance, is applied to find the best match with the target speaker. Experimental results show that text-independent recognition rate of the cascaded system reaches 90 percent

Self-Correctable and Adaptable Inference for Generalizable Human Pose Estimation

A central challenge in human pose estimation, as well as in many other machine learning and prediction tasks, is the generalization problem. The learned network does not have the capability to characterize the prediction error, generate feedback information from the test sample, and correct the prediction error on the fly for each individual test sample, which results in degraded performance in generalization. In this work, we introduce a self-correctable and adaptable inference (SCAI) method to address the generalization challenge of network prediction and use human pose estimation as an example to demonstrate its effectiveness and performance. We learn a correction network to correct the prediction result conditioned by a fitness feedback error. This feedback error is generated by a learned fitness feedback network which maps the prediction result to the original input domain and compares it against the original input. Interestingly, we find that this self-referential feedback error is highly correlated with the actual prediction error. This strong correlation suggests that we can use this error as feedback to guide the correction process. It can be also used as a loss function to quickly adapt and optimize the correction network during the inference process. Our extensive experimental results on human pose estimation demonstrate that the proposed SCAI method is able to significantly improve the generalization capability and performance of human pose estimation.Comment: Accepted by CVPR 202

Neuro-Modulated Hebbian Learning for Fully Test-Time Adaptation

Fully test-time adaptation aims to adapt the network model based on sequential analysis of input samples during the inference stage to address the cross-domain performance degradation problem of deep neural networks. We take inspiration from the biological plausibility learning where the neuron responses are tuned based on a local synapse-change procedure and activated by competitive lateral inhibition rules. Based on these feed-forward learning rules, we design a soft Hebbian learning process which provides an unsupervised and effective mechanism for online adaptation. We observe that the performance of this feed-forward Hebbian learning for fully test-time adaptation can be significantly improved by incorporating a feedback neuro-modulation layer. It is able to fine-tune the neuron responses based on the external feedback generated by the error back-propagation from the top inference layers. This leads to our proposed neuro-modulated Hebbian learning (NHL) method for fully test-time adaptation. With the unsupervised feed-forward soft Hebbian learning being combined with a learned neuro-modulator to capture feedback from external responses, the source model can be effectively adapted during the testing process. Experimental results on benchmark datasets demonstrate that our proposed method can significantly improve the adaptation performance of network models and outperforms existing state-of-the-art methods.Comment: CVPR2023 accepte

Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information), Vol 6, No 2 June 2013

IMPROVED DESIGN OF DTW AND GMM CASCADED ARABIC SPEAKER Shuoshuo Chen, Junbo Zhao, Ruiqi Yang EAODV: A*-BASED ENHANCEMENT AD-HOC ON DEMAND VECTOR PROTOCOL TO PREVENT BLACK HOLE ATTACKS Khalil I Ghathwan, Abdul Razak Yaakub, Rahmat Budiarto PRESERVING LOCAL ORNAMENT THROUGH ALGORITHM Aswin Indraprastha, Zulhadi Sahputra, Agus Suharjono DDOS ATTACK DETECTION SIMULATION AND HANDLING MECHANISM Ahmad Sanmorino, Setiadi Yazid BUILDING MONITORING SYSTEM BASED ON ZIGBEE Firdaus Kurniawan, Hira Meidia IMPLEMENTATION OF GENETIC ALGORITHM FOR STUDENT PLACEMENT PROCESS OF COMMUNITY DEVELOPMENT PROGRAM IN UNIVERSITAS GADJAH MADA Nanang Arfandi, Faizah SIMULATION OF QUANTUM SEARCH ALGORITHM Rina Refianti, Achmad Benny Mutiar

Synergistic tribological effect between polyisobutylene succinimide-modified molybdenum oxide nanoparticle and zinc dialkyldithiophosphate for reducing friction and wear of diamond-like carbon coating under boundary lubrication

Abstract Organic molybdenum lubricant additive like molybdenum dialkyl dithiocarbamate (MoDTC) can cause wear acceleration of diamond-like carbon (DLC) coating coupled with steel under boundary lubrication, which hinders its industrial application. Therefore, polyisobutylene succinimide (PIBS), an organo molybdenum amide, was adopted to modify molybdenum oxide affording molybdenum polyisobutylene succinimide-molybdenum oxide nanoparticles (MPIBS-MONPs) with potential to prevent the wear acceleration of DLC coating. The thermal stability of MPIBS-MONPs was evaluated by thermogravimetric analysis. Their tribological properties as the additives in di-isooctyl sebacate (DIOS) were evaluated with MoDTC as a control; and their tribomechanism was investigated in relation to their tribochemical reactions and synergistic tribological effect with zinc dialkyldithiophosphate (ZDDP) as well as worn surface characterizations. Findings indicate that MPIBS-MONPs/ZDDP added in DIOS can significantly reduce the friction and wear of DLC coating, being much superior to MoDTC. This is because MPIBS-MONPs and ZDDP jointly take part in tribochemical reactions to form a composite tribofilm that can increase the wear resistance of DLC coating. Namely, the molybdenum amide on MPIBS-MONPs surface can react with ZDDP to form MoS2 film with excellent friction-reducing ability; and MPIBS-MONPs can release molybdenum oxide nanoparticle to form deposited lubrication layer on worn surfaces. The as-formed composite tribofilm consisting of molybdenum oxide nanocrystal, amorphous polyphosphate, and molybdenum disulfide as well as a small amount of Mo2C accounts for the increase in the wear resistance of DLC coating under boundary lubrication

Spatio-Temporal Patterns and Source Identification of Water Pollution in Lake Taihu (China)

Various multivariate methods were used to analyze datasets of river water quality for 11 variables measured at 20 different sites surrounding Lake Taihu from 2006 to 2010 (13,200 observations), to determine temporal and spatial variations in river water quality and to identify potential pollution sources. Hierarchical cluster analysis (CA) grouped the 12 months into two periods (May to November, December to the next April) and the 20 sampling sites into two groups (A and B) based on similarities in river water quality characteristics. Discriminant analysis (DA) was important in data reduction because it used only three variables (water temperature, dissolved oxygen (DO) and five-day biochemical oxygen demand (BOD5)) to correctly assign about 94% of the cases and five variables (petroleum, volatile phenol, dissolved oxygen, ammonium nitrogen and total phosphorus) to correctly assign >88.6% of the cases. In addition, principal component analysis (PCA) identified four potential pollution sources for Clusters A and B: industrial source (chemical-related, petroleum-related or N-related), domestic source, combination of point and non-point sources and natural source. The Cluster A area received more industrial and domestic pollution-related agricultural runoff, whereas Cluster B was mainly influenced by the combination of point and non-point sources. The results imply that comprehensive analysis by using multiple methods could be more effective for facilitating effective management for the Lake Taihu Watershed in the future

HSDL2 knockdown promotes the progression of cholangiocarcinoma by inhibiting ferroptosis through the P53/SLC7A11 axis

Abstract Background Human hydroxysteroid dehydrogenase-like 2 (HSDL2), which regulates cancer progression, is involved in lipid metabolism. However, the role of HSDL2 in cholangiocarcinoma (CCA) and the mechanism by which it regulates CCA progression by modulating ferroptosis are unclear. Methods HSDL2 expression levels in CCA cells and tissues were determined by quantitative real-time polymerase chain reaction (qRT-PCR), western blotting, and immunohistochemistry. The overall survival and disease-free survival of patients with high vs. low HSDL2 expression were evaluated using Kaplan-Meier curves. The proliferation, migration, and invasion of CCA cells were assessed using Cell Counting Kit-8, colony formation, 5-ethynyl-2′-deoxyuridine DNA synthesis, and transwell assays. The effect of p53 on tumor growth was explored using a xenograft mouse model. The expression of SLC7A11 in patients with CCA was analyzed using immunofluorescence. Ferroptosis levels were measured by flow cytometry, malondialdehyde assay, and glutathione assay. HSDL2-regulated signaling pathways were analyzed by transcriptome sequencing. The correlation between p53 and SLC7A11 was assessed using bioinformatics and luciferase reporter assays. Results HSDL2 expression was lower in primary human CCA tissues than in matched adjacent non-tumorous bile duct tissues. HSDL2 downregulation was a significant risk factor for shorter overall survival and disease-free survival in patients with CCA. In addition, HSDL2 knockdown enhanced the proliferation, migration, and invasion of CCA cells. The transcriptome analysis of HSDL2 knockdown cells showed that differentially expressed genes were significantly enriched in the p53 signaling pathway, and HSDL2 downregulation increased SLC7A11 levels. These findings were consistent with the qRT-PCR and western blotting results. Other experiments showed that p53 expression modulated the effect of HSDL2 on CCA proliferation in vivo and in vitro and that p53 bound to the SLC7A11 promoter to inhibit ferroptosis. Conclusions HSDL2 knockdown promotes CCA progression by inhibiting ferroptosis through the p53/SLC7A11 axis. Thus, HSDL2 is a potential prognostic marker and therapeutic target for CCA