Online Class Incremental Learning on Stochastic Blurry Task Boundary via Mask and Visual Prompt Tuning

Continual learning aims to learn a model from a continuous stream of data, but it mainly assumes a fixed number of data and tasks with clear task boundaries. However, in real-world scenarios, the number of input data and tasks is constantly changing in a statistical way, not a static way. Although recently introduced incremental learning scenarios having blurry task boundaries somewhat address the above issues, they still do not fully reflect the statistical properties of real-world situations because of the fixed ratio of disjoint and blurry samples. In this paper, we propose a new Stochastic incremental Blurry task boundary scenario, called Si-Blurry, which reflects the stochastic properties of the real-world. We find that there are two major challenges in the Si-Blurry scenario: (1) inter- and intra-task forgettings and (2) class imbalance problem. To alleviate them, we introduce Mask and Visual Prompt tuning (MVP). In MVP, to address the inter- and intra-task forgetting issues, we propose a novel instance-wise logit masking and contrastive visual prompt tuning loss. Both of them help our model discern the classes to be learned in the current batch. It results in consolidating the previous knowledge. In addition, to alleviate the class imbalance problem, we introduce a new gradient similarity-based focal loss and adaptive feature scaling to ease overfitting to the major classes and underfitting to the minor classes. Extensive experiments show that our proposed MVP significantly outperforms the existing state-of-the-art methods in our challenging Si-Blurry scenario

3,3′-Dimethyl-1,1′-[2,2′-bipyridine-5,5′-diylbis(methyl­ene)]diimidazol-3-ium bis­(hexa­fluoro­phosphate)

The title compound, C20H22N6 2+·2PF6 −, was prepared by the reaction of 5,5′-bis­(bromo­meth­yl)-2,2′-bipyridine with 1-methyl­imidazole. The main mol­ecule lies on an inversion center located at the mid-point of the C—C bond joining the two pyridine rings. The asymmetric unit therefore contains one half-mol­ecule and one hexa­fluoro­phosphate anion. The dihedral angle between the pyridine and imidazole rings is 76.93 (7)°. In the crystal, weak inter­molecular C—H⋯F hydrogen bonds contribute to the stabilization of the packing

Bis[μ-N-(pyridin-2-ylmeth­yl)pyridin-2-amine-κ2 N:N′]disilver(I) bis(trifluoro­methane­sulfonate)

In the binuclear title compound, [Ag2(C11H11N3)2](CF3O3S)2, the complex cation is centrosymmetric, with the unique Ag+ cation coordinated by two pyridine N atoms from two symmetry-related N-(pyridin-2-ylmeth­yl)pyridin-2-amine ligands in a geometry slightly distorted from linear [N—Ag—N 161.02 (7)°]. This set-up leads to the formation of a 14-membered cyclic dimer. The two pyridine rings coordinated to the Ag+ cation are tilted by 80.19 (7)° with respect to each other. Inter­molecular N—H⋯O hydrogen-bonding inter­actions between the cyclic dimer and the anion exist. A two-dimensional network parallel to the ac plane is constructed by three weak Ag⋯(O,N) inter­actions as well as an F⋯F contact of 2.890 (4) Å

Methyl 9-diethyl­amino-2,2-bis­(4-meth­oxy­phen­yl)-2H-benzo[h]chromene-5-carboxyl­ate

In the title compound, C31H29NO5, the methyl carboxyl­ate and dimethyl­amino groups on the naphtho­pyran group are almost coplanar with the naphtho­pyran ring system [r.m.s. deviations = 0.08 (2) and 0.161 (2) Å, respectively]. The dihedral angle between the methyl carboxyl­ate and dimethyl­amino groups is 4.9 (1)°. The pyran ring has an envelope conformation with the quaternary C atom out of plane by 0.4739 (13) Å. The meth­oxy­phenyl substituent forms a dihedral angle of 16.6 (1)° with the plane of the benzene ring, while the other meth­oxy­phenyl group is almost coplanar, making a dihedral angle of 1.4 (1)°

1,4-Bis(4-pyridylsulfanylmeth­yl)benzene

In the title compound, C18H16N2S2, a crystallographic inversion centre lies at the centre of the benzene ring, and the two terminal 4-mercaptopyridyl groups adopt an anti geometry. Each benzene ring makes a dihedral angle of 55.4 (1)° with the plane of the benzene fragment. The crystal structure is stabilized by C—H⋯π inter­actions between a benzene H atom and a pyridyl ring of a neighbouring mol­ecule. In addition, the crystal structure exhibits inter­molecular C—H⋯N inter­actions

Improvisation of classification performance based on feature optimization for differentiation of Parkinson’s disease from other neurological diseases using gait characteristics

Most neurological disorders that include Parkinson’s disease (PD) as well as other neurological diseases such as Amyotrophic Lateral Sclerosis (ALS) and Huntington’s disease (HD) have some common abnormalities regarding the movement, vocal, and cognitive behaviors of sufferers. Variations in the manifestation of these types of abnormality help distinguish one disorder from another. In this study, differentiation was performed based on the gait characteristics of patients afflicted by different neurological disorders. In the recent past, many researchers have applied different machine learning and feature selection techniques to the classification of different groups of patients based on common abnormalities. However, in an era of modernization where the focus is on timely low-cost automatization and pattern recognition, such techniques require improvisation to provide high performance. We attempted to improve the performance of such techniques using different feature optimization methods, such as a genetic algorithm (GA) and principal component analysis (PCA), and applying different classification approaches, i.e., linear, nonlinear, and probabilistic classifiers. In this study, gait dynamics data of patients suffering with PD, ALS, and HD were collated from a public database, and a binary classification approach was used by taking PD as one group and adopting ALS+HD as another group. Performance comparison was achieved using different classification techniques that incorporated optimized feature sets obtained from GA and PCA. In comparison with other classifiers using different feature sets, the highest accuracy (97.87%) was obtained using random forest combined with GA-based feature sets. The results provide evidence that could assist medical practitioners in differentiating PD from other neurological diseases using gait characteristics

N,N-Diethyl-4-[9-meth­oxy-6-(4-methoxy­phen­yl)-5-methyl-2-phenyl-2H-benzo[h]chromen-2-yl]aniline

In the title compound, C38H37NO3, the pyran ring has an envelope conformation with the quaternary Cq atom as the flap atom. The dihedral angle formed between the meth­oxy­phenyl group and the naphthalene ring system is 67.32 (6)°. The ethyl­amino groups lie to the same side of the plane through the phenyl ring and form dihedral angles of 84.6 (3) and 75.8 (2)° with it