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        A Novel Framework Based on CNN-LSTM Neural Network for Prediction of Missing Values in Electricity Consumption Time-Series Datasets

        Syed Nazir Hussain,Azlan Abd Aziz,Md. Jakir Hossen,Nor Azlina Ab Aziz,G. Ramana Murthy,Fajaruddin Bin Mustakim 한국정보처리학회 2022 Journal of information processing systems Vol.18 No.1

        Adopting Internet of Things (IoT)-based technologies in smart homes helps users analyze home applianceselectricity consumption for better overall cost monitoring. The IoT application like smart home system (SHS)could suffer from large missing values gaps due to several factors such as security attacks, sensor faults, orconnection errors. In this paper, a novel framework has been proposed to predict large gaps of missing valuesfrom the SHS home appliances electricity consumption time-series datasets. The framework follows a series ofsteps to detect, predict and reconstruct the input time-series datasets of missing values. A hybrid convolutionalneural network-long short term memory (CNN-LSTM) neural network used to forecast large missing valuesgaps. A comparative experiment has been conducted to evaluate the performance of hybrid CNN-LSTM withits single variant CNN and LSTM in forecasting missing values. The experimental results indicate a performancesuperiority of the CNN-LSTM model over the single CNN and LSTM neural networks.

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        Curcuma longa extract ameliorates motor and cognitive deficits of 6-hydroxydopamine-infused Parkinson’s disease model rats

        Sujan Bhowmick,Marzan Sarkar,Jakir Hussain,Mehedi Hassan,Mafroz Basunia,Taslima Nahar,Azizur Rahman,Borhan Uddin,Shahdat Hossain 경희대학교 융합한의과학연구소 2022 Oriental Pharmacy and Experimental Medicine Vol.22 No.4

        Parkinson’s disease (PD) results mostly from the degeneration of dopaminergic neurons in the substantia nigra pars compacta. It is characterized by the manifestations of anxiety, tremor, muscle rigidity, bradykinesia and cognitive impairments. Oxidative stress is attributed to the neurodegeneration of PD. Curcuma longa is a commonly used spice and has high levels of anti-oxidative phyto-constituents. Here, we evaluated whether the chronic oral administration of C. longa extract affects the degree of anxiety, neuromotor and cognitive deficits of 6-hydroxydopamine (6-OHDA)-infused PD model rats. Following the surgery, animals were orally administered with C. longa extract for twelve weeks. The degree of anxiety/depression, motor and cognitive performances were determined with a variety of neurobehavioral experimental paradigms, including elevated plus, Morris water maze task, rotarod, open field, forced swim, sucrose preference and tail suspension tests. Brain levels of lipid peroxide (LPO) were measured by standard method. Tumor necrosis factor-α (TNFα), α-synuclein, synaptosomeassociated protein-25 (SNAP25) and brain-derived neurotrophic factor (BDNF) of the brain tissues were measured by ELISA. Oral administration of C. longa significantly (P < 0.05) protected the deterioration of the motor activity, learning-related memory cognitions and the degree of anxiety- and depression-like behaviors in PD model rats. The preventive effects were accompanied with decreased brain levels of LPO, TNFα, α-synuclein and increased levels of cognition-related proteins SNAP-25 and BDNF. The experimental results suggest that C. longa ameliorates PD-like symptoms by suppressing the oxidative/pro-inflammatory stress and levels of α-synuclein and increasing the levels of SNAP-25 and BDNF.

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