Gestural musical interfaces using real time machine learning

Master of ScienceDepartment of Computer ScienceWilliam H. HsuWe present gestural music instruments and interfaces that aid musicians and audio engineers to express themselves efficiently. While we have mastered building a wide variety of physical instruments, the quest for virtual instruments and sound synthesis is on the rise. Virtual instruments are essentially software that enable musicians to interact with a sound module in the computer. Since the invention of MIDI (Musical Instrument Digital Interface), devices and interfaces to interact with sound modules like keyboards, drum machines, joysticks, mixing and mastering systems have been flooding the music industry. Research in the past decade gone one step further in interacting through simple musical gestures to create, shape and arrange music in real time. Machine learning is a powerful tool that can be smartly used to teach simple gestures to the interface. The ability to teach innovative gestures and shape the way a sound module behaves unleashes the untapped creativity of an artist. Timed music and multimedia programs such as Max/MSP/Jitter along with machine learning techniques open gateways to embodied musical experiences without physical touch. This master's report presents my research, observations and how this interdisciplinary field of research could be used to study wider neuroscience problems like embodied music cognition and human-computer interactions

Case series of clinical study and surgical management of atlanto axial dislocation our institute experience

Background: Atlantoaxial dislocation refers to a loss of stability between the atlas and axis (C1-C2), resulting in loss of normal articulation. Cervical spine C1-C2 motion segment is the most technically challenging.Methods: This is a prospective and retrospective Study which included 34 patients admitted in King George hospital, Andhra medical college, Visakhapatnam over the past two years (January 2014- January 2016) with AAD.Results: The age of the patients ranged from 3 to 60 years with mean age being 37.67 years. Commonest presenting sign is local tenderness at the back of upper cervical region in 91.17%. Most common procedure done was single sitting trans oral odontoid decompression with posterior occipito cervical fusion with occipital plate and C2, C4 polyaxial screws and lateral mass rods in 18 cases out of 34. The next common procedure performed was C1 lateral mass and C2 pars screw fixation 8 out of 34.Conclusions: Trans oral odentoidectomy and posterior ocipito cervical fusion is ideal and still holds good for irreducible AAD with  ventral compressive pathology

Directed Evolution in Live Coding Music Performance

This paper is presented and accepted as an In-Proceedings paper at the 2020 Joint Conference on AI and Musical Creativity, October 19-23, 2020, organized and hosted virtually by the Royal Institute of Technology (KTH), Stockholm, Sweden.Genetic algorithms are extensively used to understand, simulate, and create works of art and music. In this paper, a similar approach is taken to apply basic evolutionary algorithms to perform music live using code. Often considered an improvisational or experimental performance, live coding music comes with its own set of challenges. Genetic algorithms offer potential to address these long-standing challenges. Traditional evolutionary applications in music focused on novelty search to create new sounds, sequences of notes or chords, and effects. In contrast, this paper focuses on live performance to create directed evolving musical pieces. The paper also details some key design decisions, implementation, and usage of a novel genetic algorithm API created for a popular live coding language

An Effective Classification of DDoS Attacks in a Distributed Network by Adopting Hierarchical Machine Learning and Hyperparameters Optimization Techniques

Data privacy is essential in the financial sector to protect client’s sensitive information, prevent financial fraud, ensure regulatory compliance, and safeguard intellectual property. It has become a challenging task due to the increase in usage of the internet and digital transactions. In this scenario, DDoS attack is one of the major attacks that makes clients’ privacy questionable. It requires effective and robust attack detection and prevention techniques. Machine Learning (ML) is the most effective approach for employing cyber attack detection systems. It paves the way for a new era where human and scientific communities will benefit. This paper presents a hierarchical ML-based hyperparameter-optimization approach for classifying intrusions in a network. CICIDS 2017 standard dataset was considered for this work. Initially, data was preprocessed with the min-max scaling and SMOTE methods. The LASSO approach was used for feature selection, given as input to the hierarchical ML algorithms: XGboost, LGBM, CatBoost, Random Forest (RF), and Decision Tree (DT). All these algorithms are pretrained with hyperparameters to enhance the effectiveness of algorithms. Models performance was assessed in terms of recall, precision, accuracy, and F1-score metrics. Evaluated approaches have shown that the LGBM algorithm gives a proven performance in classifying DDoS attacks with 99.77% of classification accuracy

Low serum 1,25(OH) 2 D levels: A risk factor for periodontitis

Context: Vitamin D has been associated with bone health and it is well understood that vitamin D deficiency leads to various disorders. 1,25(OH) 2 D maintains oral health through its effect on bone and mineral metabolism and innate immunity. Aims: The aim was to evaluate the association between serum levels of 25-hydroxyvitamin D [25(OH)D] and 1,25(OH) 2 D and periodontal disease risk and also the effect of low serum levels on periodontal surgical outcomes in periodontitis patients. Settings and Design: The study was designed as a case control clinical trial that was conducted to identify the risk of low levels of serum vitamin D in progression of the disease and also in periodontal healing process. Materials and Methods: A total of 51 chronic periodontitis patients and 33 periodontally healthy subjects were included in the study. The serum levels of both 25(OH)D and 1,25(OH) 2 D were determined. Parameters, such as plaque index, bleeding on probing (BOP), clinical attachment level (CAL), and pocket depth (PD), were measured at baseline, 6 weeks, and 6 months to assess the periodontal status. Statistical Analysis Used: The data were analyzed using chi-square test, independent sample t-test, repeated measures analysis of variance (ANOVA) with post hoc Bonferroni test. Results: There was statistically significant association between serum 1,25(OH) 2 D level and periodontal health status (12.73 ± 4.19 vs. 20.36 ± 5.50). The subjects with chronic periodontitis showed low serum levels of 1,25(OH) 2 D, and individuals with severe deficiency have shown less clinical attachment gain and PD reduction when compared with minimal deficiency patients after the surgery. Conclusions: Analysis of these data suggest that low serum 1,25(OH) 2 D level seem to be associated with chronic periodontitis and 1,25(OH)2D deficiency negatively affects the periodontal surgical treatment outcome

Supramolecular Depolymerization in the Mixture of Two Poor Solvents: Mechanistic Insights and Modulation of Supramolecular Polymerization of Ionic π-Systems

Solvents are fundamentally essential for the synthesis and processing of soft materials. Supramolecular polymers (SPs), an emerging class of soft materials, are usually stable in single and mixtures of poor solvents. In contrast to these preconceived notions, here we report the depolymerization of SPs in the mixture of two poor solvents. This surprising behavior was observed for well-known cationic perylene diimides (cPDIs) in the mixtures of water and amphiphilic organic solvents such as isopropanol (IPA). cPDIs form stable SPs in water and IPA but readily depolymerize into monomers in 50–70 vol% IPA containing water. This is due to the selective solvation of the π-surface of cPDIs by alkyl chains of IPA and ionic side chains by water, as evidenced by molecular dynamic simulations. Moreover, by systematically changing the ratio between water and amphiphilic organic solvent, we could achieve an unprecedented supramolecular polymerization both by increasing and decreasing the solvent polarity

Supramolecular Depolymerization in the Mixture of Two Poor Solvents: Mechanistic Insights and Modulation of Supramolecular Polymerization of Ionic π‐Systems

Solvents are fundamentally essential for the synthesis and processing of soft materials. Supramolecular polymers (SPs), an emerging class of soft materials, are usually stable in single and mixtures of poor solvents. In contrast to these preconceived notions, here we report the depolymerization of SPs in the mixture of two poor solvents. This surprising behavior was observed for well-known cationic perylene diimides (cPDIs) in the mixtures of water and amphiphilic organic solvents such as isopropanol (IPA). cPDIs form stable SPs in water and IPA but readily depolymerize into monomers in 50–70 vol% IPA containing water. This is due to the selective solvation of the π-surface of cPDIs by alkyl chains of IPA and ionic side chains by water, as evidenced by molecular dynamic simulations. Moreover, by systematically changing the ratio between water and amphiphilic organic solvent, we could achieve an unprecedented supramolecular polymerization both by increasing and decreasing the solvent polarity. © 2020 Wiley-VCH Gmb

Supramolecular Depolymerization in the Mixture of Two Poor Solvents: Mechanistic Insights and Modulation of Supramolecular Polymerization of Ionic π‐Systems

Solvents are fundamentally essential for the synthesis and processing of soft materials. Supramolecular polymers (SPs), an emerging class of soft materials, are usually stable in single and mixtures of poor solvents. In contrast to these preconceived notions, here we report the depolymerization of SPs in the mixture of two poor solvents. This surprising behavior was observed for well-known cationic perylene diimides (cPDIs) in the mixtures of water and amphiphilic organic solvents such as isopropanol (IPA). cPDIs form stable SPs in water and IPA but readily depolymerize into monomers in 50–70 vol% IPA containing water. This is due to the selective solvation of the π-surface of cPDIs by alkyl chains of IPA and ionic side chains by water, as evidenced by molecular dynamic simulations. Moreover, by systematically changing the ratio between water and amphiphilic organic solvent, we could achieve an unprecedented supramolecular polymerization both by increasing and decreasing the solvent polarity. © 2020 Wiley-VCH Gmb

Anti mullerian hormone and antral follicle count for prediction of ovarian reserve in female infertile patients: A cross sectional study

Ovarian reserve (OR)determines the quantity and quality of follicles present in the ovary. It is independent of menstrual cycle in women of reproductive age. The chances of conceiving in infertile women can be predicted by understanding and determining the OR. The aim of the study was to assess and determine whether Anti-Mullerian Hormone (AMH) with Antral Follicle Count (AFC) or AMH alone is a better predictor of ovarian reserve in female infertile patients. Methods: In this prospective, cross-sectional study, a total of 60 patients were measured for AMH levels of which 30 patients was assessed along with AFC. The demographic details were collected and 5ml of venous blood samples were taken on day 2 of menstrual cycle. Serum was separated and stored at -20oC. Serum AMH levels were analysed using enzyme-linked immune sorbent assay (ELISA) whereas Antral Follicle Count with ultrasonography. Finally, 54 patients completed the analysis with the mean age of 26.32±3.95 years and body mass index of 24.09±4.62. The average AMH levels and AFC were found to be 2.49±4.05 ng/ml and 14.92±8.69 follicles respectively. AMH showed negative correlation with both FSH and LH and no correlation with estradiol

Cooperative Supramolecular Polymerization Guided by Dispersive Interactions

Cooperative supramolecular polymerization is important for the synthesis of functional supramolecular homo and block-copolymers of π-systems. Current strategies indicate the need of strong hydrogen bonding (H-bonding) and/or dipolar interactions in the π-systems to achieve cooperativity. In sharp contrast, here we report the cooperative supramolecular polymerization in alkyl chain substituted perylene diimides (alkyl PDIs) driven by dispersive interactions with molecular level understanding. Moreover, alkyl PDIs follow cooperative mechanism with cooperativity similar to the strong H-bonded π-systems (σ ∼10−5) despite the lack of strong H-bonding and dipolar interactions. Computer simulations show that this surprising phenomenon in alkyl PDIs is driven by the efficient dispersive interactions among the alkyl chains and π-cores due to their zigzag arrangement in the supramolecular polymer. Importantly, alkyl PDIs display cooperative supramolecular polymerization in both polar and non-polar solvents which is difficult for H-bonded/dipolar π-systems thus highlighting the advantages of dispersive interactions. © 2022 Wiley-VCH GmbH