Multi-target tracking is facing the difficulties of modeling uncertain motion and observation noise.Traditional tracking algorithms are limited by specific models and priors that may mismatch a real-world scenario.In ...Multi-target tracking is facing the difficulties of modeling uncertain motion and observation noise.Traditional tracking algorithms are limited by specific models and priors that may mismatch a real-world scenario.In this paper,considering the model-free purpose,we present an online Multi-Target Intelligent Tracking(MTIT)algorithm based on a Deep Long-Short Term Memory(DLSTM)network for complex tracking requirements,named the MTIT-DLSTM algorithm.Firstly,to distinguish trajectories and concatenate the tracking task in a time sequence,we define a target tuple set that is the labeled Random Finite Set(RFS).Then,prediction and update blocks based on the DLSTM network are constructed to predict and estimate the state of targets,respectively.Further,the prediction block can learn the movement trend from the historical state sequence,while the update block can capture the noise characteristic from the historical measurement sequence.Finally,a data association scheme based on Hungarian algorithm and the heuristic track management strategy are employed to assign measurements to targets and adapt births and deaths.Experimental results manifest that,compared with the existing tracking algorithms,our proposed MTIT-DLSTM algorithm can improve effectively the accuracy and robustness in estimating the state of targets appearing at random positions,and be applied to linear and nonlinear multi-target tracking scenarios.展开更多
The unloading relaxation caused by excavation for construction of high arch dams is an important factor influencing the foundation’s integrity and strength.To evaluate the degree of unloading relaxation,the long-shor...The unloading relaxation caused by excavation for construction of high arch dams is an important factor influencing the foundation’s integrity and strength.To evaluate the degree of unloading relaxation,the long-short term memory(LSTM)network was used to estimate the depth of unloading relaxation zones on the left bank foundation of the Baihetan Arch Dam.Principal component analysis indicates that rock charac-teristics,the structural plane,the protection layer,lithology,and time are the main factors.The LSTM network results demonstrate the unloading relaxation characteristics of the left bank,and the relationships with the factors were also analyzed.The structural plane has the most significant influence on the distribution of unloading relaxation zones.Compared with massive basalt,the columnar jointed basalt experiences a more significant unloading relaxation phenomenon with a clear time effect,with the average unloading relaxation period being 50 d.The protection layer can effectively reduce the unloading relaxation depth by approximately 20%.展开更多
Deep learning plays a vital role in real-life applications, for example object identification, human face recognition, speech recognition, biometrics identification, and short and long-term forecasting of data. The ma...Deep learning plays a vital role in real-life applications, for example object identification, human face recognition, speech recognition, biometrics identification, and short and long-term forecasting of data. The main objective of our work is to predict the market performance of the Dhaka Stock Exchange (DSE) on day closing price using different Deep Learning techniques. In this study, we have used the LSTM (Long Short-Term Memory) network to forecast the data of DSE for the convenience of shareholders. We have enforced LSTM networks to train data as well as forecast the future time series that has differentiated with test data. We have computed the Root Mean Square Error (RMSE) value to scrutinize the error between the forecasted value and test data that diminished the error by updating the LSTM networks. As a consequence of the renovation of the network, the LSTM network provides tremendous performance which outperformed the existing works to predict stock market prices.展开更多
In this paper, a new class of three term memory gradient method with non-monotone line search technique for unconstrained optimization is presented. Global convergence properties of the new methods are discussed. Comb...In this paper, a new class of three term memory gradient method with non-monotone line search technique for unconstrained optimization is presented. Global convergence properties of the new methods are discussed. Combining the quasi-Newton method with the new method, the former is modified to have global convergence property. Numerical results show that the new algorithm is efficient.展开更多
Objective: To observe the effects on spatial long-term memory in the rats with vascular dementia(VD)treated with moxibustion for resolving stasis and promoting meridian circulation.Methods: The modified 2-vascular occ...Objective: To observe the effects on spatial long-term memory in the rats with vascular dementia(VD)treated with moxibustion for resolving stasis and promoting meridian circulation.Methods: The modified 2-vascular occlusion(2-VO) method was used to prepare VD animal model. The rats were randomized into a sham-operation group, a model group, a moxibustion group and a western medication group, 15 rats in each one. In the moxibustion group, mild warm moxibustion was applied to"Bǎihuì(百会 GV 20)" "DàZhuī(大椎 GV 14)" and "Shéntíng(神庭 GV 24)". 20 min at each point, once a day, for 3 weeks consecutively. In the western medicaion group, mouse nerve growth factor(NGF) was injected intraperitoneally, 0.18 mL/kg, once a day, for 3 weeks consecutively. Morris water maze test was used, the time of the first passing platform, the frequency of passing-platform and swimming speed in120 s were determined of the rats in each group. Western blot were used to test the protein expressions of hippocampal Nestin and DCX.Results: At the end of three courses of treatment, compared with sham-operation group, the difference was not significant statistically in swimming speed in the model group, the moxibustion group and the western medication group separately(all P>0.05). Three days after modeling, the mean of escape latency was prolonged obviously in the modeled rats compared with the rats in the shamoperation group(88.84 ± 19.94 vs 18.15 ±9.41, P< 0.01). At the end of three courses of treatment, compared with the sham-operation group(22.01 ± 10.07), the mean of escape latency was different statistically in the model group(89.18± 19.70), the moxibustion group(37.21 ±13.31) and the western medication group separately(51.50± 16.15), all P<0.01. Compared with the model group, the mean of escape latency was shortened in the moxibustion group and western medication group respectively(37.21 ± 13.31 vs89.18 ± 19.70, 51.50 ± 16.15 vs 89.18 ± 19.70, both P< 0.01). Compared with the western medication group,there was no statistical significant difference in the mean of escape latency in the moxibustion group(37.21 ± 13.31 vs 51.50 ±16.15, P> 0.05). Compared with the sham-operation group, the frequency of passing-platform was decreased in the model group(0.73 ±0.96 vs 2.60 ±1.45, P<0.01); compared with model group, the frequency of passing-platform was increased in the moxibustion group and the western medicine group and the statistically significant difference presented in the moxibustion group(2.06 ± 1.33 vs 0.73 ±0.96, P<0.01). Compared with the sham-operation group, the time of first passing-platform was prolonged in the model group(87.86 ± 33.25 vs 36.13 +29.76, P< 0.01). Compared with the model group,the time of first passing-platform was shortened in the moxibustion group and the western medicine group respectively(49.53 ±29.48 vs 87.86 ± 33.25.P< 0.01; 58.98 ± 36.22 vs 87.86 ±33.25, P< 0.05). After three courses of treatment, compared with the sham-operation group, Nestin expression was reduced in the model group,(0.33 ±0.12 vs 0.51 ±0.02, P<0.05) and was increased in the moxibustion group and the western medication group respectively(1.33 ± 0.17 vs 0.51 ± 0.02. 1.39 ± 0.10 vs 0.51 ±0.02, both P< 0.01).Compared with the model group, Nestin expression was increased in the moxibustion group and the western medication group, respectively(1.33 ± 0.17 vs 0.33±0.12. 1.39±0.10 vs 0.33 ±0.12, both P< 0.01).Compared with the western medication group, the difference was not significant statistically in the moxibustion group(1.33±0.17 vs 1.39±0.10, P>0.05). After three courses of treatment, compared with the sham-operation group, DCX expression was decreased in the model group, but without significant difference(0.44±0.20 vs 0.51 ±0.26, P> 0.05), the expression was increased in the moxibustion group and the western medication group respectively(0.98±0.25 vs 0.51±0.26. P< 0.05; 1.11±0.43 vs 0.51 ±0.26,P<0.01). Compared with the model group, DCX expression was obviously increased in the moxibustion group and the western medication group(0.98 ± 0.25 vs 0.44 ± 0.20. 1.11 ± 0.43 vs 0.44 ± 0.20, both P<0.01). The difference in DCX expression was not statistically significant between the western medication group and the moxibustion group(0.98 ± 0.25 vs 1.11 ± 0.43. P> 0.05).Conclusion: Moxibustion apparently improves the long-term memory in VD rats.展开更多
In dense pedestrian tracking,frequent object occlusions and close distances between objects cause difficulty when accurately estimating object trajectories.In this study,a conditional random field tracking model is es...In dense pedestrian tracking,frequent object occlusions and close distances between objects cause difficulty when accurately estimating object trajectories.In this study,a conditional random field tracking model is established by using a visual long short term memory network in the three-dimensional(3D)space and the motion estimations jointly performed on object trajectory segments.Object visual field information is added to the long short term memory network to improve the accuracy of the motion related object pair selection and motion estimation.To address the uncertainty of the length and interval of trajectory segments,a multimode long short term memory network is proposed for the object motion estimation.The tracking performance is evaluated using the PETS2009 dataset.The experimental results show that the proposed method achieves better performance than the tracking methods based on the independent motion estimation.展开更多
The healthy condition of the milling tool has a very high impact on the machining quality of the titanium components.Therefore,it is important to recognize the healthy condition of the tool and replace the damaged cut...The healthy condition of the milling tool has a very high impact on the machining quality of the titanium components.Therefore,it is important to recognize the healthy condition of the tool and replace the damaged cutter at the right time.In order to recognize the health condition of the milling cutter,a method based on the long short term memory(LSTM)was proposed to recognize tool health state in this paper.The various signals collected in the tool wear experiments were analyzed by time-domain statistics,and then the extracted data were generated by principal component analysis(PCA)method.The preprocessed data extracted by PCA is transmitted to the LSTM model for recognition.Compared with back propagation neural network(BPNN)and support vector machine(SVM),the proposed method can effectively utilize the time-domain regulation in the data to achieve higher recognition speed and accuracy.展开更多
In this paper,we study the blow-up of solutions to a semi-linear wave equation with a nonlinear memory term of derivative type.By using methods of an iteration argument and di erential inequalities,we obtain the blow-...In this paper,we study the blow-up of solutions to a semi-linear wave equation with a nonlinear memory term of derivative type.By using methods of an iteration argument and di erential inequalities,we obtain the blow-up result for the semi-linear wave equation when the exponent of p is under certain conditions.Meanwhile,we derive an upper bound of the lifespan of solutions to the Cauchy problem for the semi-linear wave equation.展开更多
Objective To evaluate whether the thermotaxis tracking model is suitable for assessing long-term memory （LTM） in the nematode Caenorhabditis elegans. Methods Animals were trained at 20℃ overnight in presence of foo...Objective To evaluate whether the thermotaxis tracking model is suitable for assessing long-term memory （LTM） in the nematode Caenorhabditis elegans. Methods Animals were trained at 20℃ overnight in presence of food. The percentage of animals performing isothermal tracking （IT） behavior was measured at different time intervals after the training. Results The percentage of animals performing IT behavior, the numbers of body bends inside and outside the training temperature, and the expression patterns of AFD and AIY neurons were similar to those in control animals at 36 and 48 h after training; whereas when extending to 60, 72, and 84 h, locomotory behavior defects were observed in the assayed animals, suggesting that this thermal tracking model is feasible for analyzing LTM at 36 and 48 h after training. Moreover, the percent-age of animals performing IT behavior was reduced at 18, 36, and 48 h after training in neuronal calcium sensor-1 gene （nsc-1） mutant animals compared with that in wild-type N2 animals. In addition, exposure to plumbum （Pb） significantly repressed the LTM at 18, 36, and 48 h after training in both wild-type N2 and ncs-1 mutant animals. Conclusion The thermotaxis tracking model is suitable for evaluating the LTM regulated by NCS-1, and can be employed for elucidating regulatory functions of specific genes or effects of stimuli on memory in C. elegans.展开更多
A Long Short-Term Memory(LSTM) Recurrent Neural Network(RNN) has driven tremendous improvements on an acoustic model based on Gaussian Mixture Model(GMM). However, these models based on a hybrid method require a force...A Long Short-Term Memory(LSTM) Recurrent Neural Network(RNN) has driven tremendous improvements on an acoustic model based on Gaussian Mixture Model(GMM). However, these models based on a hybrid method require a forced aligned Hidden Markov Model(HMM) state sequence obtained from the GMM-based acoustic model. Therefore, it requires a long computation time for training both the GMM-based acoustic model and a deep learning-based acoustic model. In order to solve this problem, an acoustic model using CTC algorithm is proposed. CTC algorithm does not require the GMM-based acoustic model because it does not use the forced aligned HMM state sequence. However, previous works on a LSTM RNN-based acoustic model using CTC used a small-scale training corpus. In this paper, the LSTM RNN-based acoustic model using CTC is trained on a large-scale training corpus and its performance is evaluated. The implemented acoustic model has a performance of 6.18% and 15.01% in terms of Word Error Rate(WER) for clean speech and noisy speech, respectively. This is similar to a performance of the acoustic model based on the hybrid method.展开更多
Objective To gain a better understanding of gene expression changes in the brain following microwave exposure in mice. This study hopes to reveal mechanisms contributing to microwave-induced learning and memory dysfun...Objective To gain a better understanding of gene expression changes in the brain following microwave exposure in mice. This study hopes to reveal mechanisms contributing to microwave-induced learning and memory dysfunction. Methods Mice were exposed to whole body 2100 MHz microwaves with specific absorption rates (SARs) of 0.45 W/kg, 1.8 W/kg, and 3.6 W/kg for 1 hour daily for 8 weeks. Differentially expressing genes in the brains were screened using high-density oligonucleotide arrays, with genes showing more significant differences further confirmed by RT-PCR. Results The gene chip results demonstrated that 41 genes (0.45 W/kg group), 29 genes (1.8 W/kg group), and 219 genes (3.6 W/kg group) were differentially expressed. GO analysis revealed that these differentially expressed genes were primarily involved in metabolic processes, cellular metabolic processes, regulation of biological processes, macromolecular metabolic processes, biosynthetic processes, cellular protein metabolic processes, transport, developmental processes, cellular component organization, etc. KEGG pathway analysis showed that these genes are mainly involved in pathways related to ribosome, Alzheimer's disease, Parkinson's disease, long-term potentiation, Huntington's disease, and Neurotrophin signaling. Construction of a protein interaction network identified several important regulatory genes including synbindin (sbdn), Crystallin (CryaB), PPP1CA, Ywhaq, Psap, Psmb1, Pcbp2, etc., which play important roles in the processes of learning and memory. Conclusion Long-term, low-level microwave exposure may inhibit learning and memory by affecting protein and energy metabolic processes and signaling pathways relating to neurological functions or diseases.展开更多
Statistics of languages are usually calculated by counting characters, words, sentences, word rankings. Some of these random variables are also the main “ingredients” of classical readability formulae. Revisiting th...Statistics of languages are usually calculated by counting characters, words, sentences, word rankings. Some of these random variables are also the main “ingredients” of classical readability formulae. Revisiting the readability formula of Italian, known as GULPEASE, shows that of the two terms that determine the readability index G—the semantic index , proportional to the number of characters per word, and the syntactic index GF, proportional to the reciprocal of the number of words per sentence—GF is dominant because GC is, in practice, constant for any author throughout seven centuries of Italian Literature. Each author can modulate the length of sentences more freely than he can do with the length of words, and in different ways from author to author. For any author, any couple of text variables can be modelled by a linear relationship y = mx, but with different slope m from author to author, except for the relationship between characters and words, which is unique for all. The most important relationship found in the paper is that between the short-term memory capacity, described by Miller’s “7 ? 2 law” (i.e., the number of “chunks” that an average person can hold in the short-term memory ranges from 5 to 9), and the word interval, a new random variable defined as the average number of words between two successive punctuation marks. The word interval can be converted into a time interval through the average reading speed. The word interval spreads in the same range as Miller’s law, and the time interval is spread in the same range of short-term memory response times. The connection between the word interval (and time interval) and short-term memory appears, at least empirically, justified and natural, however, to be further investigated. Technical and scientific writings (papers, essays, etc.) ask more to their readers because words are on the average longer, the readability index G is lower, word and time intervals are longer. Future work done on ancient languages, such as the classical Greek and Latin Literatures (or modern languages Literatures), could bring us an insight into the short-term memory required to their well-educated ancient readers.展开更多
Objective: This study aimed to compare the cortical topographic mapping while performing cognitive activities of standardized short-term memory. Materials and Methods: The sample consisted of 30 individuals of both ge...Objective: This study aimed to compare the cortical topographic mapping while performing cognitive activities of standardized short-term memory. Materials and Methods: The sample consisted of 30 individuals of both gender. Each individual participant of the survey was subjected to a short-term memory test for each sense. To carry out the EEG record, we used an electroencephalograph with 20 electrodes. The stimulus for the acquisition of short-term memory has always been made up of five items from different semantic classes. Results: The posterior right quadrant had a higher percentage of gamma rhythm during the tests of most senses. Conclusion: It was concluded that the right back quadrant has a higher gamma rhythms percentage during tests which involve somesthetic, olfactory and gustatory memory. On the other hand, the predominance of a gamma rhythm percentage in any quadrant when the auditory and visual memory was stimulated was not observed in this study.展开更多
Short-term memory allows individuals to recall stimuli, such as numbers or words, for several seconds to several minutes without rehearsal. Although the capacity of short-term memory is considered to be 7 ±?2 ...Short-term memory allows individuals to recall stimuli, such as numbers or words, for several seconds to several minutes without rehearsal. Although the capacity of short-term memory is considered to be 7 ±?2 items, this can be increased through a process called chunking. For example, in Japan, 11-digit cellular phone numbers and 10-digit toll free numbers are chunked into three groups of three or four digits: 090-XXXX-XXXX and 0120-XXX-XXX, respectively. We use probability theory to predict that the most effective chunking involves groups of three or four items, such as in phone numbers. However, a 16-digit credit card number exceeds the capacity of short-term memory, even when chunked into groups of four digits, such as XXXX-XXXX-XXXX-XXXX. Based on these data, 16-digit credit card numbers should be sufficient for security purposes.展开更多
Activity-regulated cytoskeleton-associated protein (Arc/Arg3.1) was originally identified in patients with seizures. It is densely distributed in the hip-pocampus and amygdala in particular. Because the expression of ...Activity-regulated cytoskeleton-associated protein (Arc/Arg3.1) was originally identified in patients with seizures. It is densely distributed in the hip-pocampus and amygdala in particular. Because the expression of Arc/Arg3.1 is regulated by nerve in-puts, it is thought to be an immediate early gene. As shown both in vitro and in vivo, Arc/Arg3.1 is in-volved in synaptic consolidation and regulates some forms of learning and memory in rats and mice [1,2]. Furthermore, a recent study suggests that Arc/Arg3.1 may play a significant role in signal transmission via AMPA-type glutamate receptors [3-5]. Therefore, we conducted a detailed analysis of fear memory in Arc/Arg3.1-deficient mice. As previously reported, the knockout animals exhib-ited impaired fear memory in both contextual and cued test situations. Although Arc/Arg3.1-deficient mice showed almost the same performance as wild-type littermates 4 hr after a conditioning trial, their performance was impaired in the retention test after 24 hr or longer, either with or without reconsolidation. Immunohistochemical analyses showed an abnormal density of GluR1 in the hip-pocampus of Arc/Arg3.1-deficient mice;however, an application of AMPA potentiator did not improve memory performance in the mutant mice. Memory impairment in Arc/Arg3.1-deficient mice is so ro-bust that the mice provide a useful tool for devel-oping treatments for memory impairment.展开更多
We consider a von Karman equation of memory type with a delay term . By introducing suitable energy and Lyapunov functional, we establish a general decay estimate for the energy, which depends on the behavior of g.
Mental workload plays a vital role in cognitive impairment. The impairment refers to a person’s difficulty in remembering, receiving new information, learning new things, concentrating, or making decisions that serio...Mental workload plays a vital role in cognitive impairment. The impairment refers to a person’s difficulty in remembering, receiving new information, learning new things, concentrating, or making decisions that seriously affect everyday life. In this paper, the simultaneous capacity (SIMKAP) experiment-based EEG workload analysis was presented using 45 subjects for multitasking mental workload estimation with subject wise attention loss calculation as well as short term memory loss measurement. Using an open access preprocessed EEG dataset, Discrete wavelet transforms (DWT) was utilized for feature extraction and Minimum redundancy and maximum relevancy (MRMR) technique was used to select most relevance features. Wavelet decomposition technique was also used for decomposing EEG signals into five sub bands. Fourteen statistical features were calculated from each sub band signal to form a 5 × 14 window size. The Neural Network (Narrow) classification algorithm was used to classify dataset for low and high workload conditions and comparison was made using some other machine learning models. The results show the classifier’s accuracy of 86.7%, precision of 84.4%, F1 score of 86.33%, and recall of 88.37% that crosses the state-of-the art methodologies in the literature. This prediction is expected to greatly facilitate the improved way in memory and attention loss impairments assessment.展开更多
In today’s world, there are many people suffering from mentalhealth problems such as depression and anxiety. If these conditions are notidentified and treated early, they can get worse quickly and have far-reachingne...In today’s world, there are many people suffering from mentalhealth problems such as depression and anxiety. If these conditions are notidentified and treated early, they can get worse quickly and have far-reachingnegative effects. Unfortunately, many people suffering from these conditions,especially depression and hypertension, are unaware of their existence until theconditions become chronic. Thus, this paper proposes a novel approach usingBi-directional Long Short-Term Memory (Bi-LSTM) algorithm and GlobalVector (GloVe) algorithm for the prediction and treatment of these conditions.Smartwatches and fitness bands can be equipped with these algorithms whichcan share data with a variety of IoT devices and smart systems to betterunderstand and analyze the user’s condition. We compared the accuracy andloss of the training dataset and the validation dataset of the two modelsnamely, Bi-LSTM without a global vector layer and with a global vector layer.It was observed that the model of Bi-LSTM without a global vector layer hadan accuracy of 83%,while Bi-LSTMwith a global vector layer had an accuracyof 86% with a precision of 86.4%, and an F1 score of 0.861. In addition toproviding basic therapies for the treatment of identified cases, our model alsohelps prevent the deterioration of associated conditions, making our methoda real-world solution.展开更多
Aimed at the problem that the traditional ART-2 neural network can not recognize a gradually changing course, an eternal term memory (ETM) vector is introduced into ART-2 to simulate the function of human brain, i.e. ...Aimed at the problem that the traditional ART-2 neural network can not recognize a gradually changing course, an eternal term memory (ETM) vector is introduced into ART-2 to simulate the function of human brain, i.e. the deep remembrance for the initial impression.. The eternal term memory vector is determined only by the initial vector that establishes category neuron node and is used to keep the remembrance for this vector for ever. Two times of vigilance algorithm are put forward, and the posterior input vector must first pass the first vigilance of this eternal term memory vector, only succeeded has it the qualification to begin the second vigilance of long term memory vector. The long term memory vector can be revised only when both of the vigilances are passed. Results of recognition examples show that the improved ART-2 overcomes the defect of traditional ART-2 and can recognize a gradually changing course effectively.展开更多
基金supported by the National Natural Science Foundation of China(No.62276204)Open Foundation of Science and Technology on Electronic Information Control Laboratory,Natural Science Basic Research Program of Shanxi,China(Nos.2022JM-340 and 2023-JC-QN-0710)China Postdoctoral Science Foundation(Nos.2020T130494 and 2018M633470).
文摘Multi-target tracking is facing the difficulties of modeling uncertain motion and observation noise.Traditional tracking algorithms are limited by specific models and priors that may mismatch a real-world scenario.In this paper,considering the model-free purpose,we present an online Multi-Target Intelligent Tracking(MTIT)algorithm based on a Deep Long-Short Term Memory(DLSTM)network for complex tracking requirements,named the MTIT-DLSTM algorithm.Firstly,to distinguish trajectories and concatenate the tracking task in a time sequence,we define a target tuple set that is the labeled Random Finite Set(RFS).Then,prediction and update blocks based on the DLSTM network are constructed to predict and estimate the state of targets,respectively.Further,the prediction block can learn the movement trend from the historical state sequence,while the update block can capture the noise characteristic from the historical measurement sequence.Finally,a data association scheme based on Hungarian algorithm and the heuristic track management strategy are employed to assign measurements to targets and adapt births and deaths.Experimental results manifest that,compared with the existing tracking algorithms,our proposed MTIT-DLSTM algorithm can improve effectively the accuracy and robustness in estimating the state of targets appearing at random positions,and be applied to linear and nonlinear multi-target tracking scenarios.
基金This work was supported by the National Key Research and Development Program of China(Grant No.2018YFC0407004)the Natural Science Foundation of China(Grants No.51939004 and 11772116).
文摘The unloading relaxation caused by excavation for construction of high arch dams is an important factor influencing the foundation’s integrity and strength.To evaluate the degree of unloading relaxation,the long-short term memory(LSTM)network was used to estimate the depth of unloading relaxation zones on the left bank foundation of the Baihetan Arch Dam.Principal component analysis indicates that rock charac-teristics,the structural plane,the protection layer,lithology,and time are the main factors.The LSTM network results demonstrate the unloading relaxation characteristics of the left bank,and the relationships with the factors were also analyzed.The structural plane has the most significant influence on the distribution of unloading relaxation zones.Compared with massive basalt,the columnar jointed basalt experiences a more significant unloading relaxation phenomenon with a clear time effect,with the average unloading relaxation period being 50 d.The protection layer can effectively reduce the unloading relaxation depth by approximately 20%.
文摘Deep learning plays a vital role in real-life applications, for example object identification, human face recognition, speech recognition, biometrics identification, and short and long-term forecasting of data. The main objective of our work is to predict the market performance of the Dhaka Stock Exchange (DSE) on day closing price using different Deep Learning techniques. In this study, we have used the LSTM (Long Short-Term Memory) network to forecast the data of DSE for the convenience of shareholders. We have enforced LSTM networks to train data as well as forecast the future time series that has differentiated with test data. We have computed the Root Mean Square Error (RMSE) value to scrutinize the error between the forecasted value and test data that diminished the error by updating the LSTM networks. As a consequence of the renovation of the network, the LSTM network provides tremendous performance which outperformed the existing works to predict stock market prices.
文摘In this paper, a new class of three term memory gradient method with non-monotone line search technique for unconstrained optimization is presented. Global convergence properties of the new methods are discussed. Combining the quasi-Newton method with the new method, the former is modified to have global convergence property. Numerical results show that the new algorithm is efficient.
基金Supported by National Natural Science Foundation of China:81473785Project of National Veteran TCM Expert Inheritance Studio
文摘Objective: To observe the effects on spatial long-term memory in the rats with vascular dementia(VD)treated with moxibustion for resolving stasis and promoting meridian circulation.Methods: The modified 2-vascular occlusion(2-VO) method was used to prepare VD animal model. The rats were randomized into a sham-operation group, a model group, a moxibustion group and a western medication group, 15 rats in each one. In the moxibustion group, mild warm moxibustion was applied to"Bǎihuì(百会 GV 20)" "DàZhuī(大椎 GV 14)" and "Shéntíng(神庭 GV 24)". 20 min at each point, once a day, for 3 weeks consecutively. In the western medicaion group, mouse nerve growth factor(NGF) was injected intraperitoneally, 0.18 mL/kg, once a day, for 3 weeks consecutively. Morris water maze test was used, the time of the first passing platform, the frequency of passing-platform and swimming speed in120 s were determined of the rats in each group. Western blot were used to test the protein expressions of hippocampal Nestin and DCX.Results: At the end of three courses of treatment, compared with sham-operation group, the difference was not significant statistically in swimming speed in the model group, the moxibustion group and the western medication group separately(all P>0.05). Three days after modeling, the mean of escape latency was prolonged obviously in the modeled rats compared with the rats in the shamoperation group(88.84 ± 19.94 vs 18.15 ±9.41, P< 0.01). At the end of three courses of treatment, compared with the sham-operation group(22.01 ± 10.07), the mean of escape latency was different statistically in the model group(89.18± 19.70), the moxibustion group(37.21 ±13.31) and the western medication group separately(51.50± 16.15), all P<0.01. Compared with the model group, the mean of escape latency was shortened in the moxibustion group and western medication group respectively(37.21 ± 13.31 vs89.18 ± 19.70, 51.50 ± 16.15 vs 89.18 ± 19.70, both P< 0.01). Compared with the western medication group,there was no statistical significant difference in the mean of escape latency in the moxibustion group(37.21 ± 13.31 vs 51.50 ±16.15, P> 0.05). Compared with the sham-operation group, the frequency of passing-platform was decreased in the model group(0.73 ±0.96 vs 2.60 ±1.45, P<0.01); compared with model group, the frequency of passing-platform was increased in the moxibustion group and the western medicine group and the statistically significant difference presented in the moxibustion group(2.06 ± 1.33 vs 0.73 ±0.96, P<0.01). Compared with the sham-operation group, the time of first passing-platform was prolonged in the model group(87.86 ± 33.25 vs 36.13 +29.76, P< 0.01). Compared with the model group,the time of first passing-platform was shortened in the moxibustion group and the western medicine group respectively(49.53 ±29.48 vs 87.86 ± 33.25.P< 0.01; 58.98 ± 36.22 vs 87.86 ±33.25, P< 0.05). After three courses of treatment, compared with the sham-operation group, Nestin expression was reduced in the model group,(0.33 ±0.12 vs 0.51 ±0.02, P<0.05) and was increased in the moxibustion group and the western medication group respectively(1.33 ± 0.17 vs 0.51 ± 0.02. 1.39 ± 0.10 vs 0.51 ±0.02, both P< 0.01).Compared with the model group, Nestin expression was increased in the moxibustion group and the western medication group, respectively(1.33 ± 0.17 vs 0.33±0.12. 1.39±0.10 vs 0.33 ±0.12, both P< 0.01).Compared with the western medication group, the difference was not significant statistically in the moxibustion group(1.33±0.17 vs 1.39±0.10, P>0.05). After three courses of treatment, compared with the sham-operation group, DCX expression was decreased in the model group, but without significant difference(0.44±0.20 vs 0.51 ±0.26, P> 0.05), the expression was increased in the moxibustion group and the western medication group respectively(0.98±0.25 vs 0.51±0.26. P< 0.05; 1.11±0.43 vs 0.51 ±0.26,P<0.01). Compared with the model group, DCX expression was obviously increased in the moxibustion group and the western medication group(0.98 ± 0.25 vs 0.44 ± 0.20. 1.11 ± 0.43 vs 0.44 ± 0.20, both P<0.01). The difference in DCX expression was not statistically significant between the western medication group and the moxibustion group(0.98 ± 0.25 vs 1.11 ± 0.43. P> 0.05).Conclusion: Moxibustion apparently improves the long-term memory in VD rats.
文摘In dense pedestrian tracking,frequent object occlusions and close distances between objects cause difficulty when accurately estimating object trajectories.In this study,a conditional random field tracking model is established by using a visual long short term memory network in the three-dimensional(3D)space and the motion estimations jointly performed on object trajectory segments.Object visual field information is added to the long short term memory network to improve the accuracy of the motion related object pair selection and motion estimation.To address the uncertainty of the length and interval of trajectory segments,a multimode long short term memory network is proposed for the object motion estimation.The tracking performance is evaluated using the PETS2009 dataset.The experimental results show that the proposed method achieves better performance than the tracking methods based on the independent motion estimation.
基金National Natural Science Foundation of China(No.51805079)Shanghai Natural Science Foundation,China(No.17ZR1400600)Fundamental Research Funds for the Central Universities,China(No.16D110309)
文摘The healthy condition of the milling tool has a very high impact on the machining quality of the titanium components.Therefore,it is important to recognize the healthy condition of the tool and replace the damaged cutter at the right time.In order to recognize the health condition of the milling cutter,a method based on the long short term memory(LSTM)was proposed to recognize tool health state in this paper.The various signals collected in the tool wear experiments were analyzed by time-domain statistics,and then the extracted data were generated by principal component analysis(PCA)method.The preprocessed data extracted by PCA is transmitted to the LSTM model for recognition.Compared with back propagation neural network(BPNN)and support vector machine(SVM),the proposed method can effectively utilize the time-domain regulation in the data to achieve higher recognition speed and accuracy.
基金Supported by the Natural Science Foundation of China(Grant No.11371175)Innovation Team Project in Colleges and Universities of Guangdong Province(Grant No.2020WCXTD008)+1 种基金Science Foundation of Huashang College Guangdong University of Finance&Economics(Grant No.2020HSDS01)Science Research Team Project in Guangzhou Huashang College(Grant No.2021HSKT01).
文摘In this paper,we study the blow-up of solutions to a semi-linear wave equation with a nonlinear memory term of derivative type.By using methods of an iteration argument and di erential inequalities,we obtain the blow-up result for the semi-linear wave equation when the exponent of p is under certain conditions.Meanwhile,we derive an upper bound of the lifespan of solutions to the Cauchy problem for the semi-linear wave equation.
文摘Objective To evaluate whether the thermotaxis tracking model is suitable for assessing long-term memory （LTM） in the nematode Caenorhabditis elegans. Methods Animals were trained at 20℃ overnight in presence of food. The percentage of animals performing isothermal tracking （IT） behavior was measured at different time intervals after the training. Results The percentage of animals performing IT behavior, the numbers of body bends inside and outside the training temperature, and the expression patterns of AFD and AIY neurons were similar to those in control animals at 36 and 48 h after training; whereas when extending to 60, 72, and 84 h, locomotory behavior defects were observed in the assayed animals, suggesting that this thermal tracking model is feasible for analyzing LTM at 36 and 48 h after training. Moreover, the percent-age of animals performing IT behavior was reduced at 18, 36, and 48 h after training in neuronal calcium sensor-1 gene （nsc-1） mutant animals compared with that in wild-type N2 animals. In addition, exposure to plumbum （Pb） significantly repressed the LTM at 18, 36, and 48 h after training in both wild-type N2 and ncs-1 mutant animals. Conclusion The thermotaxis tracking model is suitable for evaluating the LTM regulated by NCS-1, and can be employed for elucidating regulatory functions of specific genes or effects of stimuli on memory in C. elegans.
基金supported by the Ministry of Trade,Industry & Energy(MOTIE,Korea) under Industrial Technology Innovation Program (No.10063424,'development of distant speech recognition and multi-task dialog processing technologies for in-door conversational robots')
文摘A Long Short-Term Memory(LSTM) Recurrent Neural Network(RNN) has driven tremendous improvements on an acoustic model based on Gaussian Mixture Model(GMM). However, these models based on a hybrid method require a forced aligned Hidden Markov Model(HMM) state sequence obtained from the GMM-based acoustic model. Therefore, it requires a long computation time for training both the GMM-based acoustic model and a deep learning-based acoustic model. In order to solve this problem, an acoustic model using CTC algorithm is proposed. CTC algorithm does not require the GMM-based acoustic model because it does not use the forced aligned HMM state sequence. However, previous works on a LSTM RNN-based acoustic model using CTC used a small-scale training corpus. In this paper, the LSTM RNN-based acoustic model using CTC is trained on a large-scale training corpus and its performance is evaluated. The implemented acoustic model has a performance of 6.18% and 15.01% in terms of Word Error Rate(WER) for clean speech and noisy speech, respectively. This is similar to a performance of the acoustic model based on the hybrid method.
基金supported by the Foundation of Astronaut Research and Training Center of China(No.SN 02-3)
文摘Objective To gain a better understanding of gene expression changes in the brain following microwave exposure in mice. This study hopes to reveal mechanisms contributing to microwave-induced learning and memory dysfunction. Methods Mice were exposed to whole body 2100 MHz microwaves with specific absorption rates (SARs) of 0.45 W/kg, 1.8 W/kg, and 3.6 W/kg for 1 hour daily for 8 weeks. Differentially expressing genes in the brains were screened using high-density oligonucleotide arrays, with genes showing more significant differences further confirmed by RT-PCR. Results The gene chip results demonstrated that 41 genes (0.45 W/kg group), 29 genes (1.8 W/kg group), and 219 genes (3.6 W/kg group) were differentially expressed. GO analysis revealed that these differentially expressed genes were primarily involved in metabolic processes, cellular metabolic processes, regulation of biological processes, macromolecular metabolic processes, biosynthetic processes, cellular protein metabolic processes, transport, developmental processes, cellular component organization, etc. KEGG pathway analysis showed that these genes are mainly involved in pathways related to ribosome, Alzheimer's disease, Parkinson's disease, long-term potentiation, Huntington's disease, and Neurotrophin signaling. Construction of a protein interaction network identified several important regulatory genes including synbindin (sbdn), Crystallin (CryaB), PPP1CA, Ywhaq, Psap, Psmb1, Pcbp2, etc., which play important roles in the processes of learning and memory. Conclusion Long-term, low-level microwave exposure may inhibit learning and memory by affecting protein and energy metabolic processes and signaling pathways relating to neurological functions or diseases.
文摘Statistics of languages are usually calculated by counting characters, words, sentences, word rankings. Some of these random variables are also the main “ingredients” of classical readability formulae. Revisiting the readability formula of Italian, known as GULPEASE, shows that of the two terms that determine the readability index G—the semantic index , proportional to the number of characters per word, and the syntactic index GF, proportional to the reciprocal of the number of words per sentence—GF is dominant because GC is, in practice, constant for any author throughout seven centuries of Italian Literature. Each author can modulate the length of sentences more freely than he can do with the length of words, and in different ways from author to author. For any author, any couple of text variables can be modelled by a linear relationship y = mx, but with different slope m from author to author, except for the relationship between characters and words, which is unique for all. The most important relationship found in the paper is that between the short-term memory capacity, described by Miller’s “7 ? 2 law” (i.e., the number of “chunks” that an average person can hold in the short-term memory ranges from 5 to 9), and the word interval, a new random variable defined as the average number of words between two successive punctuation marks. The word interval can be converted into a time interval through the average reading speed. The word interval spreads in the same range as Miller’s law, and the time interval is spread in the same range of short-term memory response times. The connection between the word interval (and time interval) and short-term memory appears, at least empirically, justified and natural, however, to be further investigated. Technical and scientific writings (papers, essays, etc.) ask more to their readers because words are on the average longer, the readability index G is lower, word and time intervals are longer. Future work done on ancient languages, such as the classical Greek and Latin Literatures (or modern languages Literatures), could bring us an insight into the short-term memory required to their well-educated ancient readers.
文摘Objective: This study aimed to compare the cortical topographic mapping while performing cognitive activities of standardized short-term memory. Materials and Methods: The sample consisted of 30 individuals of both gender. Each individual participant of the survey was subjected to a short-term memory test for each sense. To carry out the EEG record, we used an electroencephalograph with 20 electrodes. The stimulus for the acquisition of short-term memory has always been made up of five items from different semantic classes. Results: The posterior right quadrant had a higher percentage of gamma rhythm during the tests of most senses. Conclusion: It was concluded that the right back quadrant has a higher gamma rhythms percentage during tests which involve somesthetic, olfactory and gustatory memory. On the other hand, the predominance of a gamma rhythm percentage in any quadrant when the auditory and visual memory was stimulated was not observed in this study.
文摘Short-term memory allows individuals to recall stimuli, such as numbers or words, for several seconds to several minutes without rehearsal. Although the capacity of short-term memory is considered to be 7 ±?2 items, this can be increased through a process called chunking. For example, in Japan, 11-digit cellular phone numbers and 10-digit toll free numbers are chunked into three groups of three or four digits: 090-XXXX-XXXX and 0120-XXX-XXX, respectively. We use probability theory to predict that the most effective chunking involves groups of three or four items, such as in phone numbers. However, a 16-digit credit card number exceeds the capacity of short-term memory, even when chunked into groups of four digits, such as XXXX-XXXX-XXXX-XXXX. Based on these data, 16-digit credit card numbers should be sufficient for security purposes.
文摘Activity-regulated cytoskeleton-associated protein (Arc/Arg3.1) was originally identified in patients with seizures. It is densely distributed in the hip-pocampus and amygdala in particular. Because the expression of Arc/Arg3.1 is regulated by nerve in-puts, it is thought to be an immediate early gene. As shown both in vitro and in vivo, Arc/Arg3.1 is in-volved in synaptic consolidation and regulates some forms of learning and memory in rats and mice [1,2]. Furthermore, a recent study suggests that Arc/Arg3.1 may play a significant role in signal transmission via AMPA-type glutamate receptors [3-5]. Therefore, we conducted a detailed analysis of fear memory in Arc/Arg3.1-deficient mice. As previously reported, the knockout animals exhib-ited impaired fear memory in both contextual and cued test situations. Although Arc/Arg3.1-deficient mice showed almost the same performance as wild-type littermates 4 hr after a conditioning trial, their performance was impaired in the retention test after 24 hr or longer, either with or without reconsolidation. Immunohistochemical analyses showed an abnormal density of GluR1 in the hip-pocampus of Arc/Arg3.1-deficient mice;however, an application of AMPA potentiator did not improve memory performance in the mutant mice. Memory impairment in Arc/Arg3.1-deficient mice is so ro-bust that the mice provide a useful tool for devel-oping treatments for memory impairment.
文摘We consider a von Karman equation of memory type with a delay term . By introducing suitable energy and Lyapunov functional, we establish a general decay estimate for the energy, which depends on the behavior of g.
文摘Mental workload plays a vital role in cognitive impairment. The impairment refers to a person’s difficulty in remembering, receiving new information, learning new things, concentrating, or making decisions that seriously affect everyday life. In this paper, the simultaneous capacity (SIMKAP) experiment-based EEG workload analysis was presented using 45 subjects for multitasking mental workload estimation with subject wise attention loss calculation as well as short term memory loss measurement. Using an open access preprocessed EEG dataset, Discrete wavelet transforms (DWT) was utilized for feature extraction and Minimum redundancy and maximum relevancy (MRMR) technique was used to select most relevance features. Wavelet decomposition technique was also used for decomposing EEG signals into five sub bands. Fourteen statistical features were calculated from each sub band signal to form a 5 × 14 window size. The Neural Network (Narrow) classification algorithm was used to classify dataset for low and high workload conditions and comparison was made using some other machine learning models. The results show the classifier’s accuracy of 86.7%, precision of 84.4%, F1 score of 86.33%, and recall of 88.37% that crosses the state-of-the art methodologies in the literature. This prediction is expected to greatly facilitate the improved way in memory and attention loss impairments assessment.
基金This research is funded by Vellore Institute of Technology,Chennai,India.
文摘In today’s world, there are many people suffering from mentalhealth problems such as depression and anxiety. If these conditions are notidentified and treated early, they can get worse quickly and have far-reachingnegative effects. Unfortunately, many people suffering from these conditions,especially depression and hypertension, are unaware of their existence until theconditions become chronic. Thus, this paper proposes a novel approach usingBi-directional Long Short-Term Memory (Bi-LSTM) algorithm and GlobalVector (GloVe) algorithm for the prediction and treatment of these conditions.Smartwatches and fitness bands can be equipped with these algorithms whichcan share data with a variety of IoT devices and smart systems to betterunderstand and analyze the user’s condition. We compared the accuracy andloss of the training dataset and the validation dataset of the two modelsnamely, Bi-LSTM without a global vector layer and with a global vector layer.It was observed that the model of Bi-LSTM without a global vector layer hadan accuracy of 83%,while Bi-LSTMwith a global vector layer had an accuracyof 86% with a precision of 86.4%, and an F1 score of 0.861. In addition toproviding basic therapies for the treatment of identified cases, our model alsohelps prevent the deterioration of associated conditions, making our methoda real-world solution.
基金Sponsored by the National Natural Science Foundation of China (Grant No. 50305005)
文摘Aimed at the problem that the traditional ART-2 neural network can not recognize a gradually changing course, an eternal term memory (ETM) vector is introduced into ART-2 to simulate the function of human brain, i.e. the deep remembrance for the initial impression.. The eternal term memory vector is determined only by the initial vector that establishes category neuron node and is used to keep the remembrance for this vector for ever. Two times of vigilance algorithm are put forward, and the posterior input vector must first pass the first vigilance of this eternal term memory vector, only succeeded has it the qualification to begin the second vigilance of long term memory vector. The long term memory vector can be revised only when both of the vigilances are passed. Results of recognition examples show that the improved ART-2 overcomes the defect of traditional ART-2 and can recognize a gradually changing course effectively.
