THAPE: A Tunable Hybrid Associative Predictive Engine Approach for Enhancing Rule Interpretability in Association Rule Learning for the Retail Sector

Association rule learning(ARL)is a widely used technique for discovering relationships within datasets.However,it often generates excessive irrelevant or ambiguous rules.Therefore,post-processing is crucial not only for removing irrelevant or redundant rules but also for uncovering hidden associations that impact other factors.Recently,several post-processing methods have been proposed,each with its own strengths and weaknesses.In this paper,we propose THAPE(Tunable Hybrid Associative Predictive Engine),which combines descriptive and predictive techniques.By leveraging both techniques,our aim is to enhance the quality of analyzing generated rules.This includes removing irrelevant or redundant rules,uncovering interesting and useful rules,exploring hidden association rules that may affect other factors,and providing backtracking ability for a given product.The proposed approach offers a tailored method that suits specific goals for retailers,enabling them to gain a better understanding of customer behavior based on factual transactions in the target market.We applied THAPE to a real dataset as a case study in this paper to demonstrate its effectiveness.Through this application,we successfully mined a concise set of highly interesting and useful association rules.Out of the 11,265 rules generated,we identified 125 rules that are particularly relevant to the business context.These identified rules significantly improve the interpretability and usefulness of association rules for decision-making purposes.

Changes of learning and memory ability associated with neuronal nitric oxide synthase in brain tissues of rats with acute alcoholism

BACKGROUD： Ethanol can influence neural development and the ability of leaming and memory, but its mechanism of the neural toxicity is not clear till now. Endogenous nitric oxide （NO） as a gaseous messenger is proved to play an important role in the formation of synaptic plasticity, transference of neuronal information and the neural development, but excessive nitro oxide can result in neurotoxicity. OBJECTIVE ： To observe the effects of acute alcoholism on the learning and memory ability and the content of neuronal nitric oxide synthase （nNOS） in brain tissue of rats. DESIGN ： A randomized controlled animal experiment. SETTING ： Department of Physiology, Xinxiang Medical College MATERIALS： Eighteen male clean-degree SD rats of 18-22 weeks were raised adaptively for 2 days, and then randomly divided into control group （n = 8） and experimental group （n = 10）. The nNOS immunohistochemical reagent was provided by Beijing Zhongshan Golden Bridge Biotechnology Co.,Ltd. Y-maze was produced by Suixi Zhenghua Apparatus Plant. METHODS ： The experiment was carded out in the laboratory of the Department of Physiology, Xinxiang Medical College from June to October in 2005. ① Rats in the experimental group were intraperitoneally injected with ethanol （2.5 g/kg） which was dissolved in normal saline （20%）. The loss of righting reflex and ataxia within 5 minutes indicated the successful model. Whereas rats in the control group were given saline of the same volume. ② Examinations of learning and memory ability： The Y-maze tests for learning and memory ability were performed at 6 hours after the models establishment. The rats were put into the Y-maze separately. The test was performed in a quiet and dark room. There was a lamp at the end of each of three pathways in Y-maze and the base of maze had electric net. All the lamps of the three pathways were turned on for 3 minutes and then turned off. One lamp was turned on randomly, and the other two delayed automatically. In 5 seconds after alternation, pulsating electric current presented in the base of unsafe area to stimulate rat＇s feet to run to the safe area. The lighting lasted for 15 seconds as one test. Running from unsafe area to safe area at one time in 10 seconds was justified as successful. Such test was repeated for 10 times for each rat and the successful frequency was recorded. The qualified standard of maze test was that the rat ardved in the safe area g times during 10 experiments. The number of trainings for the qualified standard was used to represent the result of spatial learning. ③ Determination of the content of nNOS in brain tissue： After the Y-maze test, the rats were anaesthetized, and blood was let from the incision on right auricle, transcardially perfused via the left ventricle with about 200 mL saline, then fixed by perfusion of 40 g/L paraformaldehyde. Hippocampal CA1 region, corpus striatum and cerebellum were taken to prepare serial freezing coronal sections. The nNOS contents in the brain regions were determined with the immunohistochemical methods to reflect the changes of nitdc oxide in brain tissue. MAIN OUTCOME MEASURES ： The changes of learning and memory ability and the changes of the nNOS contents in the brain tissue of rats with acute alcoholism were observed. RESULTS ： One rat in the experimental group was excluded due to its slow reaction to electdc stimulation in the Y-maze test, and the other 17 rats were involved in the analysis of results. ① The training times to reach qualifying standards of Y-maze in the expedmental group was more than that in the control group [（34.33 ±13.04）, （27.50±8.79） times, P〈 0.05]. ② Forms and numbers of nNOS positive neurons in brain tissue： It could be observed under light microscope that in the hippocampal CA1 region, there were fewer nNOS positive neurons, which were lightly stained, and the processes were not clear enough; But the numbers of the positive neurons which were deeply stained as huffy were obviously increased in the experimental group, the cell body and cyloplasm of process were evenly stained, but the nucleus was not stained. The nNOS positive neurons in corpus stdatum had similar forms and size in the experimental group and control group. The form of the nNOS positive neurons in cerebellum were similar between the two groups. The numbers of nNOS positive neurons in hippocampal CA1 region and corpus striatum in the expedmental group [（18.22±7.47）, （11.38±5.00） cells/high power field] were obviously higher than those in the control group [（10.15±4.24）, （6.15±3.69） cells/high power field. The number of nNOS positive neurons in cerebellum had no significant difference between the two groups [（49.56±18.84）, （44.43±15.42） cells/high power field, P〉 0.05]. CONCLUSION ： Acute alcoholism may impair learning and memory ability, and nitric oxide may be involved in mediating the neurotoxic role of ethanol.

Amorphous gallium oxide homojunction-based optoelectronic synapse for multi-functional signal processing

In the era of accelerated development in artificial intelligence as well as explosive growth of information and data throughput,underlying hardware devices that can integrate perception and memory while simultaneously offering the bene-fits of low power consumption and high transmission rates are particularly valuable.Neuromorphic devices inspired by the human brain are considered to be one of the most promising successors to the efficient in-sensory process.In this paper,a homojunction-based multi-functional optoelectronic synapse(MFOS)is proposed and testified.It enables a series of basic electri-cal synaptic plasticity,including paired-pulse facilitation/depression(PPF/PPD)and long-term promotion/depression(LTP/LTD).In addition,the synaptic behaviors induced by electrical signals could be instead achieved through optical signals,where its sen-sitivity to optical frequency allows the MFOS to simulate high-pass filtering applications in situ and the perception capability integrated into memory endows it with the information acquisition and processing functions as a visual system.Meanwhile,the MFOS exhibits its performances of associative learning and logic gates following the illumination with two different wave-lengths.As a result,the proposed MFOS offers a solution for the realization of intelligent visual system and bionic electronic eye,and will provide more diverse application scenarios for future neuromorphic computing.

Image Enhancement via Associated Perturbation Removal and Texture Reconstruction Learning

Degradation under challenging conditions such as rain, haze, and low light not only diminishes content visibility, but also results in additional degradation side effects, including detail occlusion and color distortion. However, current technologies have barely explored the correlation between perturbation removal and background restoration, consequently struggling to generate high-naturalness content in challenging scenarios. In this paper, we rethink the image enhancement task from the perspective of joint optimization: Perturbation removal and texture reconstruction. To this end, we advise an efficient yet effective image enhancement model, termed the perturbation-guided texture reconstruction network(PerTeRNet). It contains two subnetworks designed for the perturbation elimination and texture reconstruction tasks, respectively. To facilitate texture recovery,we develop a novel perturbation-guided texture enhancement module(PerTEM) to connect these two tasks, where informative background features are extracted from the input with the guidance of predicted perturbation priors. To alleviate the learning burden and computational cost, we suggest performing perturbation removal in a sub-space and exploiting super-resolution to infer high-frequency background details. Our PerTeRNet has demonstrated significant superiority over typical methods in both quantitative and qualitative measures, as evidenced by extensive experimental results on popular image enhancement and joint detection tasks. The source code is available at https://github.com/kuijiang94/PerTeRNet.

Effects of cold narcosis on memory acquisition, consolidation and retrieval in honeybees （Apis mellifera）

In learning and memory studies on honeybees （Apis mellifera）, cold-induced narcosis has been widely used to temporarily immobilize honeybees. In this study, we investigated the effects of cold narcosis on the associative memories in honeybees by using the proboscis extension response （PER） paradigm. Severe impairments in memory acquisition was found when cold narcosis was performed 30 rain, instead of 1 h before training. Locomotor activities were reduced when honeybees were tested 15 min, instead of 30 rain after cold narcosis. These results indicate that cold narcosis impairs locomotor activities, as well as memory acquisition in a time-dependent manner, but by comparison no such effects on memory retrieval have yet been observed.[0]

A Survey on Methods and Applications of Intelligent Market Basket Analysis Based on Association Rule

The market trends rapidly changed over the last two decades.The primary reason is the newly created opportunities and the increased number of competitors competing to grasp market share using business analysis techniques.Market Basket Analysis has a tangible effect in facilitating current change in the market.Market Basket Analysis is one of the famous fields that deal with Big Data and Data Mining applications.MBA initially uses Association Rule Learning(ARL)as a mean for realization.ARL has a beneficial effect in providing a plenty benefit in analyzing the market data and understanding customers’behavior.An important motive of using such techniques is maximizing the business profit as well as matching the exact customer needs as closely as possible.In this survey paper,we discussed several applications and methods of MBA based on ARL.Also,we reviewed some association rule learning measurements including trust,lift,leverage,and others.Furthermore,we discuss some open issues and future topics in the area of market basket analysis and association rule learning.

A Study of Using Synthetic Data for Effective Association Knowledge Learning

Association,aiming to link bounding boxes of the same identity in a video sequence,is a central component in multi-object tracking(MOT).To train association modules,e.g.,parametric networks,real video data are usually used.However,annotating person tracks in consecutive video frames is expensive,and such real data,due to its inflexibility,offer us limited opportunities to evaluate the system performance w.r.t.changing tracking scenarios.In this paper,we study whether 3D synthetic data can replace real-world videos for association training.Specifically,we introduce a large-scale synthetic data engine named MOTX,where the motion characteristics of cameras and objects are manually configured to be similar to those of real-world datasets.We show that,compared with real data,association knowledge obtained from synthetic data can achieve very similar performance on real-world test sets without domain adaption techniques.Our intriguing observation is credited to two factors.First and foremost,3D engines can well simulate motion factors such as camera movement,camera view,and object movement so that the simulated videos can provide association modules with effective motion features.Second,the experimental results show that the appearance domain gap hardly harms the learning of association knowledge.In addition,the strong customization ability of MOTX allows us to quantitatively assess the impact of motion factors on MOT,which brings new insights to the community.

Chinese EFL Learners' Actual Word Processing and Lexical Learning in Performing a Collaborative Output Task

The word processing depth hypothesis implies a positive association between learners＇ word processing and their lexical learning. In research, learners＇ task-inherent involvement load （i.e., word processing） has not been found to be consistently associated with their lexical learning. Meanwhile, existing studies have not obtained consensus results, either, from directly associating learners＇ actual word processing and their lexical learning. Against this backdrop, this paper reports a study investigating the association between Chinese EFL learners＇ actual word processing and their lexical learning in performing a collaborative oral output task. Interactional and statistical analyses revealed that the participants engaged in four types of word processing; their overall word processing was significantly correlated with both their productive and receptive word acquisition and retention; their different types of word processing were significantly correlated with their productive word learning, but showed variances in correlations with their receptive word learning. The findings were discussed from the perspectives of word processing in collaborative output, word processing and lexical learning, and word processing and different modes of lexical learning.

Droid Detector:Android Malware Characterization and Detection Using Deep Learning

Smartphones and mobile tablets are rapidly becoming indispensable in daily life. Android has been the most popular mobile operating system since 2012. However, owing to the open nature of Android, countless malwares are hidden in a large number of benign apps in Android markets that seriously threaten Android security. Deep learning is a new area of machine learning research that has gained increasing attention in artificial intelligence. In this study, we propose to associate the features from the static analysis with features from dynamic analysis of Android apps and characterize malware using deep learning techniques. We implement an online deep-learning-based Android malware detection engine（Droid Detector） that can automatically detect whether an app is a malware or not. With thousands of Android apps, we thoroughly test Droid Detector and perform an indepth analysis on the features that deep learning essentially exploits to characterize malware. The results show that deep learning is suitable for characterizing Android malware and especially effective with the availability of more training data. Droid Detector can achieve 96.76% detection accuracy, which outperforms traditional machine learning techniques. An evaluation of ten popular anti-virus softwares demonstrates the urgency of advancing our capabilities in Android malware detection.

Ultrathin SrTiO_(3)-based oxide memristor with both drift and diffusive dynamics as versatile synaptic emulators for neuromorphic computing

Artificial synapses are electronic devices that simulate important functions of biological synapses,and therefore are the basic components of artificial neural morphological networks for brain-like computing.One of the most important objectives for developing artificial synapses is to simulate the characteristics of biological synapses as much as possible,especially their self-adaptive ability to external stimuli.Here,we have successfully developed an artificial synapse with multiple synaptic functions and highly adaptive characteristics based on a simple SrTiO_(3)/Nb:SrTiO_(3)heterojunction type memristor.Diverse functions of synaptic learning,such as short-term/long-term plasticity(STP/LTP),transition from STP to LTP,learning–forgetting–relearning behaviors,associative learning and dynamic filtering,are all bio-realistically implemented in a single device.The remarkable synaptic performance is attributed to the fascinating inherent dynamics of oxygen vacancy drift and diffusion,which give rise to the coexistence of volatile-and nonvolatile-type resistive switching.This work reports a multi-functional synaptic emulator with advanced computing capability based on a simple heterostructure,showing great application potential for a compact and low-power neuromorphic computing system.

In-depth analysis of core-shell filaments in nonvolatile NbO_(x) memristive device as an artificial synapse for multifunctional bionic applications

As a key building block of the biological cortex,synapses are powerful information processing units that enable highly complex nonlinear computations.The realization of artificial synapses with similar capabilities has important implications for building intelligent,neuromorphic systems.Here,we demonstrate an artificial synapse based on NbO_(x) nonvolatile memristor to mimic multifunctional bionic applications such as nociceptor and associative learning.Combined experimental characterization with COMSOL simulation,the traditional resistance switching characteristics,which are the decisive factor for the synapse properties are in-depth analyzed.It can be proposed that the I-V characteristics of Pt/NbO_(x)/TiN memristor are governed by core-shell filaments consisting of the shell region of sub-stoichiometric Nb_(2)O_(5-δ)and the core of NbO_(2).On the basis of the core-shell filament model,it can be reasonably explained that Ohmic conduction and Poole-Frenkel conduction take turns to dominate the current flowing in the memristive device,leading to the zigzag evolution of current during the operation process of NbO_(x)-based device.The simulations of synaptic plasticity,including long-term potentiation/depression(LTP/LTD),paired-pulse facilitation(PPF),and spike-timing-dependent plasticity(STDP),exhibiting that the NbO_(x) can be utilized for an artificial synapse.Furthermore,bionic functions such as hyperalgesia and allodynia of a nociceptor and a series of associative learning behaviors in Pavlovian dog experiment are mimicked,illustrating that the Pt/NbO_(x)/TiN have great potential for highly simplified artificial neural network applications.

Decrease of memory retention in a parasitic wasp： an effect of host manipulation by Wolbachia？

Several factors, such as cold exposure, aging, the number of experiences and viral infection, have been shown to affect learning ability in different organisms. Wol- bachia has been found worldwide as an arthropod parasite/mutualist symbiont in a wide range of species, including insects. Differing effects have been identified on physiology and behavior by Wolbachia. However, the effect of Wolbachia infection on the learning ability of their host had never previously been studied. The current study carried out to compare learning ability and memory duration in 2 strains of the parasitoid Trichogramma brassicae： 1 uninfected and I infected by Wolbachia. Both strains were able to associate the novel odors with the reward of an oviposition into a host egg. However, the percentage of females that responded to the experimental design and displayed an ability to learn in these conditions was higher in the uninfected strain. Memory duration was longer in uninfected wasps （23.8 and 21.4 h after conditioning with peppermint and lemon, respectively） than in infected wasps （18.9 and 16.2 h after conditioning with peppermint and lemon, respec- tively）. Memory retention increased in response to the number of conditioning sessions in both strains, but memory retention was always shorter in the infected wasps than in the uninfected ones. Wolbachia infection may select for reduced memory retention because shorter memory induces infected wasps to disperse in new environments and avoid compe- tition with uninfected wasps by forgetting cues related to previously visited environments, thus increasing transmission of Wolbachia in new environments.

Hippocampal Interneurons are Required for Trace Eyeblink Conditioning in Mice

While the hippocampus has been implicated in supporting the association among time-separated events,the underlying cellular mechanisms have not been fully clarified.Here,we combined in vivo multi-channel recording and optogenetics to investigate the activity of hippocampal interneurons in freely-moving mice performing a trace eyeblink conditioning(tEBC)task.We found that the hippocampal interneurons exhibited conditioned stimulus(CS)-evoked sustained activity,which predicted the performance of conditioned eyeblink responses(CRs)in the early acquisition of the tEBC.Consistent with this,greater proportions of hippocampal pyramidal cells showed CS-evoked decreased activity in the early acquisition of the tEBC.Moreover,optogenetic suppression of the sustained activity in hippocampal interneurons severely impaired acquisition of the tEBC.In contrast,suppression of the sustained activity of hippocampal interneurons had no effect on the performance of well-learned CRs.Our findings highlight the role of hippocampal interneurons in the tEBC,and point to a potential cellular mechanism subserving associative learning.

Evaluation and hedonic value in mate choice

Mating preferences can show extreme variation within and among individuals even when sensory inputs are conserved. This variation is a result of changes associated with evaluative mechanisms that assign positive, neutral, or negative hedonic value to stimuli--that is, label them as attractive, uninteresting, or unattractive. There is widespread behavioral evidence for differences in genes, environmental cues, or social experience leading to marked changes in the hedonic value of stimuli. Evaluation is accomplished through an array of mechanisms that are readily modifiable through genetic changes or environmental inputs, and that may often result in the rapid acquisition or loss of behavioral preferences. Reversals in preference arising from ＂flips＂ in hedonic value may be quite common. Incorporating such discontinuous changes into models of preference evolution may illuminate our understanding of processes like trait diversification, sexual conflict, and sympatric speciation.

An Overview of Data Mining and Knowledge Discovery

With massive amounts of data stored in databases, mining information and knowledge in databases has become an important issue in recent research. Researchers in many different fields have shown great interest in data mining and knowledge discovery in databases. Several emerging applications in information providing services, such as data warehousing and on-line services over the Internet, also call for various data mining and knowledge discovery techniques to understand user behavior better, to improve the service provided, and to increase the business opportunities. In response to such a demand, this article is to provide a comprehensive survey on the data mining and knowledge discovery techniques developed recently, and introduce some real application systems as well. In conclusion, this article also lists some problems and challenges for further research.