Intelligent Intrusion Detection System for Industrial Internet of Things Environment

Rapid increase in the large quantity of industrial data, Industry 4.0/5.0 poses several challenging issues such as heterogeneous data generation, data sensing and collection, real-time data processing, and high request arrival rates. The classical intrusion detection system (IDS) is not a practical solution to the Industry 4.0 environment owing to the resource limitations and complexity. To resolve these issues, this paper designs a new Chaotic Cuckoo Search Optimization Algorithm (CCSOA) with optimal wavelet kernel extreme learning machine (OWKELM) named CCSOA-OWKELM technique for IDS on the Industry 4.0 platform. The CCSOA-OWKELM technique focuses on the design of feature selection with classification approach to achieve minimum computation complexity and maximum detection accuracy. The CCSOA-OWKELM technique involves the design of CCSOA based feature selection technique, which incorporates the concepts of chaotic maps with CSOA. Besides, the OWKELM technique is applied for the intrusion detection and classification process. In addition, the OWKELM technique is derived by the hyperparameter tuning of the WKELM technique by the use of sunflower optimization (SFO) algorithm. The utilization of CCSOA for feature subset selection and SFO algorithm based hyperparameter tuning leads to better performance. In order to guarantee the supreme performance of the CCSOA-OWKELM technique, a wide range of experiments take place on two benchmark datasets and the experimental outcomes demonstrate the promising performance of the CCSOA-OWKELM technique over the recent state of art techniques.     

Determination of methyl gallate in Bauhinia retusa extract by high-performance liquid and thin-layer chromatography

Two stability-indicating chromatographic methods are reported for the determination of methyl gallate in crude extracts of Bauhinia retusa. Separation by high performance thin layer chromatography was conducted on silica gel aluminum sheets using 9.5:0.5:0.2 (v/v/v) chloroform:methanol:acetic acid at 280 nm. The results from the 2–40 µg/band were used to prepare a linear calibration graph. The limits of detection and quantitation were 0.5 and 1.5 µg/band, respectively. The reverse phase high performance liquid chromatographic isolation of methyl gallate was performed at ambient temperature with an injection volume of 10 μL. The mobile phase consisted of 40:60 (v/v) methanol:0.1% ortho-phosphoric acid. The separation was performed at 1 mL/min using a detection wavelength of 280 nm. The calibration graph for methyl gallate was rectilinear from 0.02–40 µg/mL with limits of detection and quantitation of 0.004 and 0.010 µg/mL, respectively. For both methods, intra-day and inter-day precision were evaluated and the relative standard deviation was less than 2%, indicating good precision. The robustness was evaluated by making small and deliberate changes to appropriate parameters and the calculated relative standard deviation was less than 2%.The chromatographic methods were employed to determine methyl gallate in crude Bauhinia retusa extracts.     

Relative importance of informational units and their role in long-term recall by closed-head-injured patients and control groups.

Applied qualitative analysis to the information recalled by control Ss and closed-head-injured (CHI) patients. The Logical Memory subtest of the Wechsler Memory Scale (WMS) was administered to 40 CHI and 40 control Ss. Recall was tested immediately after administration, 40 min later, and 24 hrs later. The analysis took into account the importance of recalled information as determined by a prior rating according to 3 levels of importance. Results suggest that CHI patients have difficulty selectively retrieving the most important information after a long delay. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Hybrid Metaheuristics with Deep Learning Enabled Automated Deception Detection and Classification of Facial Expressions

Automatic deception recognition has received considerable attention from the machine learning community due to recent research on its vast application to social media, interviews, law enforcement, and the military. Video analysis-based techniques for automated deception detection have received increasing interest. This study develops a new self-adaptive population-based firefly algorithm with a deep learning-enabled automated deception detection (SAPFF-DLADD) model for analyzing facial cues. Initially, the input video is separated into a set of video frames. Then, the SAPFF-DLADD model applies the MobileNet-based feature extractor to produce a useful set of features. The long short-term memory (LSTM) model is exploited for deception detection and classification. In the final stage, the SAPFF technique is applied to optimally alter the hyperparameter values of the LSTM model, showing the novelty of the work. The experimental validation of the SAPFF-DLADD model is tested using the Miami University Deception Detection Database (MU3D), a database comprised of two classes, namely, truth and deception. An extensive comparative analysis reported a better performance of the SAPFF-DLADD model compared to recent approaches, with a higher accuracy of 99%.     

Peak-Average-Power Ratio Techniques for 5G Waveforms Using D-SLM and D-PTS

Multicarrier Waveform (MCW) has several advantages and plays a very important role in cellular systems. Fifth generation (5G) MCW such as Non-Orthogonal Multiple Access (NOMA) and Filter Bank Multicarrier (FBMC) are thought to be important in 5G implementation. High Peak to Average Power Ratio (PAPR) is seen as a serious concern in MCW since it reduces the efficiency of amplifier use in the user devices. The paper presents a novel Divergence Selective Mapping (DSLM) and Divergence Partial Transmission Sequence (D-PTS) for 5G waveforms. It is seen that the proposed D-SLM and PTS lower PAPR with low computational complexity. The work highlighted a combination of multi-data block partial transmit schemes along with tone reservation. In this, an overlapping factor is used to determine the number of data blocks for every group. Here, considering only those data blocks that have minimum signal power, the use of DSLM and DPTS are required to eliminate the segment’s peaks. Simulation results reveal that the suggested hybrid technique proves to be better than the conventional PTS scheme. Furthermore, the power saving performance of FBMC and NOMA is compared with the Orthogonal Frequency Division Multiplexing (OFDM) waveform.     

Optimal design of the inspection buffer for an unreliable process

Placing an inspection buffer immediately after an unreliable process subject to failure protects the process customers from receiving non-conforming products. Such protection is achieved by screening the buffer contents whenever a shift in the process is detected. Previous studies have suggested that, if properly designed, such buffers can reduce overall costs. In this paper we make two types of contributions to the study of inspection buffers. First, we refine the model proposed by Klastorin et al. (1993), by incorporating a more efficient way of sampling, a more realistic objective function and more accurate cost expressions. Second, we provide analytical results to assist in the calculation of the economically optimal buffer size. Specifically, these include conditions for determining whether an inspection buffer is at all justified and a theorem for bounding the search for the optimal buffer size. The performance of the search bound and the sensitivity of the model are examined computationally.     

Autonomous motivation for teaching: How self-determined teaching may lead to self-determined learning.

This study examined teachers' experience of autonomous motivation for teaching and its correlates in teachers and students. It was hypothesized that teachers would perceive various motivations posited by E. L. Deci and R. M. Ryan's (2000) self-determination theory as falling along a continuum of autonomous motivation for teaching. Autonomous motivation for teaching was predicted to be associated positively with teachers' sense of personal accomplishment and negatively with emotional exhaustion. Most important, teachers' self-reported autonomous motivation for teaching was expected to promote students' self-reported autonomous motivation for learning by enhancing teachers' autonomy-supportive behavior, as indicated by students' reports. Results from a sample of 132 Israeli teachers and their 1,255 students were consistent with the hypotheses. Discussion focuses on the importance of the experience of autonomous motivation for teaching for teachers and students. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The conceptual framing,design and evaluation of device ecologies for collaborative activities

A variety of computing technologies, in addition to the personal computer, are now commonly used in many settings. As networking infrastructures mature, it is increasingly feasible and affordable to consider closer integration and use of these heterogeneous devices in tandem. However, little is known about how best to design or evaluate such ‘device ecologies’; in particular, how best to combine devices to achieve a desired type of collaborative user experience. A central concern is how users switch their attention between devices, to utilize the various elements to best effect. We describe here the development of an ecology of devices for groups of students to use when engaged in collaborative inquiry-learning activities. This included a multi-touch tabletop, laptops, projections, video streams and telephone. In situ studies of students and tutors using it in three different settings showed how individuals and groups switched their foci between the multiple devices. We present our findings, using a novel method for analysing users’ transitions between foci, identifying patterns and emergent characteristics. We then discuss the importance of designing for transitions that enable groups to appropriately utilise an ecology of devices, using the concepts of seams, bridges, niches and focal character.