Search results for: Fraudulent pattern recognition

Authors: Kevin Wongleedee

Abstract:

This research paper was aimed to examine the reasons associated with hotel employees’ loyalty. This was a case study of 200 hotel employees in Bangkok, Thailand. The population of this study included all hotel employees who were working in Bangkok during January to March, 2014. Based on 200 respondents who answered the questionnaire, the data were complied by using SPSS. Mean and standard deviation were utilized in analyzing the data. The findings revealed that the average mean of importance was 4.40, with 0.7585 of standard deviation. Moreover, the mean average can be used to rank the level of importance from each factor as follows: 1) salary, service charge cut, and benefits, 2) career development and possible advancement, 3) freedom of working, thinking, and ability to use my initiative, 4) training opportunities, 5) social involvement and positive environment, 6) fair treatment in the workplace and fair evaluation of job performance, and 7) personal satisfaction, participation, and recognition.

Keywords: hotel employees, loyalty, reasons, case study

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Authors: Arun Prabhakar

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Threat modeling is an important activity carried out in the initial stages of the development lifecycle that helps in building proactive security measures in the product. Though there are many techniques and tools available today, one of the common challenges with the traditional methods is the lack of a systematic approach in identifying security threats. The proposed solution describes an organized model by defining ontologies that help in building patterns to enumerate threats. The concepts of graph theory are applied to build the pattern for discovering threats for any given scenario. This graph-based solution also brings in other benefits, making it a customizable and scalable model.

Keywords: directed acyclic graph, ontology, patterns, threat identification, threat modeling

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Authors: Elena Kokkoni, Prasanna Kannappan, Ashkan Zehfroosh, Effrosyni Mavroudi, Kristina Strother-Garcia, James C. Galloway, Jeffrey Heinz, Rene Vidal, Herbert G. Tanner

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Early immobility affects the motor, cognitive, and social development. Current pediatric rehabilitation lacks the technology that will provide the dosage needed to promote mobility for young children at risk. The addition of socially assistive robots in early interventions may help increase the mobility dosage. The aim of this study is to examine the feasibility of an early intervention paradigm where non-walking infants experience independent mobility while socially interacting with robots. A dynamic environment is developed where both the child and the robot interact and learn from each other. The environment involves: 1) a range of physical activities that are goal-oriented, age-appropriate, and ability-matched for the child to perform, 2) the automatic functions that perceive the child’s actions through novel activity recognition algorithms, and decide appropriate actions for the robot, and 3) a networked visual data acquisition system that enables real-time assessment and provides the means to connect child behavior with robot decision-making in real-time. The environment was tested by bringing a two-year old boy with Down syndrome for eight sessions. The child presented delays throughout his motor development with the current being on the acquisition of walking. During the sessions, the child performed physical activities that required complex motor actions (e.g. climbing an inclined platform and/or staircase). During these activities, a (wheeled or humanoid) robot was either performing the action or was at its end point 'signaling' for interaction. From these sessions, information was gathered to develop algorithms to automate the perception of activities which the robot bases its actions on. A Markov Decision Process (MDP) is used to model the intentions of the child. A 'smoothing' technique is used to help identify the model’s parameters which are a critical step when dealing with small data sets such in this paradigm. The child engaged in all activities and socially interacted with the robot across sessions. With time, the child’s mobility was increased, and the frequency and duration of complex and independent motor actions were also increased (e.g. taking independent steps). Simulation results on the combination of the MDP and smoothing support the use of this model in human-robot interaction. Smoothing facilitates learning MDP parameters from small data sets. This paradigm is feasible and provides an insight on how social interaction may elicit mobility actions suggesting a new early intervention paradigm for very young children with motor disabilities. Acknowledgment: This work has been supported by NIH under grant #5R01HD87133.

Keywords: activity recognition, human-robot interaction, machine learning, pediatric rehabilitation

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Authors: Arshia Aflaki, Hadis Karimipour, Anik Islam

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Generative Adversarial Attacks (GAAs) threaten critical sectors, ranging from fingerprint recognition to industrial control systems. Existing Deep Learning (DL) algorithms are not robust enough against this kind of cyber-attack. As one of the most critical industries in the world, the power grid is not an exception. In this study, a Deep Reinforcement Learning-based (DRL) framework assisting the DL model to improve the robustness of the model against generative adversarial attacks is proposed. Real-world smart grid stability data, as an IIoT dataset, test our method and improves the classification accuracy of a deep learning model from around 57 percent to 96 percent.

Keywords: generative adversarial attack, deep reinforcement learning, deep learning, IIoT, generative adversarial networks, power system

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Authors: Min-Ah Woo, Min-Cheol Lim, Hyun-Joo Chang, Sung-Wook Choi

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We developed a paper-based colorimetric sensor utilizing magnetic nanoparticles conjugated with aptamers (MNP-Apts) against E. coli O157:H7. The MNP-Apts were applied to a test sample solution containing the target cells, and the solution was simply dropped onto PVDF (polyvinylidene difluoride) membrane. The membrane moves the sample radially to form the sample spots of different compounds as concentric rings, thus the MNP-Apts on the membrane enabled specific recognition of the target cells through a color ring generation by MNP-promoted colorimetric reaction of TMB (3,3',5,5'-tetramethylbenzidine) and H₂O₂. This method could be applied to rapidly and visually detect various bacterial pathogens in less than 1 h without cell culturing.

Keywords: aptamer, colorimetric sensor, E. coli O157:H7, magnetic nanoparticle, polyvinylidene difluoride

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Authors: Elmira Ghanbari, Jan Van Esch, Stephen J. Picken, Sahil Aggarwal

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Low-molecular-weight organogelators form gels by self-assembly into the crystalline network which immobilizes the organic solvent. For single bisamide organogelator systems, the effect of the molecular structure on the molecular interaction and their self-assembly behavior has been explored. The spatial arrangement of bisamide molecules in the gel-state is driven by a combination of hydrogen bonding and Van der Waals interactions. The hydrogen-bonding pattern between the amide groups of bisamide molecules is regulated by the number of methylene spacers; the even number of methylene spacers between two amide groups, in even-spaced bisamides, leads to the antiparallel position of amide groups within a molecule. An even-spaced bisamide molecule with antiparallel amide groups can make two pairs of hydrogen bonding with the molecules on the same plane. The odd-spaced bisamide with a parallel directionality of amide groups can form four independent hydrogen bonds with four other bisamide molecules on different planes. The arrangement of bisamide molecules in the crystalline state and the interaction of these molecules depends on the molecular structure, particularly the parity of the spacer length between the amide groups in the bisamide molecule. In this study, the directionality of amide groups has been exploited as a structural characteristic to affect the arrangement of molecules in the crystalline state and produce different binary bisamide gelators with different degrees of crystallinities. Single odd- and even-spaced single bisamides were synthesized and blended to produce binary bisamide organogelators to be characterized in order to understand the effect of the different directionality of amide groups on the molecular interaction in the crystalline state. The pattern of molecular interactions between these blended molecules, mixing or phase separation, has been monitored via differential scanning calorimetry (DSC) and crystallography techniques; X-ray powder diffraction (XRD) and Small-angle X-ray scattering (SAXS). The formation of lamellar structures for odd- and even-spaced bisamide gelators was confirmed by using SAXS and XRD techniques. DSC results have shown that binary bisamide organogelators with different parity of methylene spacers (odd-even binary blends) have a higher tendency for phase separation compared to the binary bisamides with the same parity (odd-odd or even-even binary blends). Phase separation in binary odd-even bisamides was confirmed by the presence of individual (100) reflections of odd and even lamellar structures. The structural characteristic of bisamide organogelators, the parity of spacer length in binary systems, is a promising tool to control the arrangement of molecules and their crystalline structure.

Keywords: binary bisamide organogelators, crystalline structure, phase separation, self-assembly behavior

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Authors: Nguyen Van Loi, Le Thanh Son, Tran Trung Kien

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The paper deals with the problem of the formation of range profiles (RPs) for an X-band coastal surveillance radar. Two popular methods, the difference operator method, and the window-based method, are reviewed and analyzed via two tests with different datasets. The test results show that although the original window-based method achieves a better performance than the difference operator method, it has three main drawbacks that are the use of 3 or 4 peaks of an RP for creating the windows, the extension of the window size using the power sum of three adjacent cells in the left and the right sides of the windows and the same threshold applied for all types of vessels to finish the formation process of RPs. These drawbacks lead to inaccurate RPs due to the low signal-to-clutter ratio. Therefore, some suggestions are proposed to improve the original window-based method.

Keywords: range profile, difference operator method, window-based method, automatic target recognition

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Authors: Fátima R. Zan, Daniela C. Guimarães, Rosângela O. Soares, Suzana L. Russo

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The wine until it reaches the consumer has a long way to go, from planting the wine to the bottling and the placing on the market, bringing many years of experimentation, and through several generations to have recognition for quality and excellence. The winemaking grew dramatically and are today many brands, including the associated locations, demonstrating their origin and cultural order that is associated with their production. The production, circulation and marketing of wines and products of grape and wine in Brazil is regulated by Law 7.678/88, amended by Law 10970/04, and adjusting the legislation to Regulation Wine Mercosur. This study was based on a retrospective study, and aimed to identify and characterize the modalities of industrial property used in wine production in Brazil. The wineries were selected from the 2014 ranking list, drawn up by the World Association of Journalists and Writers of Wines and Spirits (WAWWJ). The results show that the registration with INPI, regarding Patents, Trademarks, Industrial Designs and Geographical Indications, is not used by the wineries analyzed.

Keywords: counterfeiting, industrial property, protection, wine production

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Authors: D. Beziakina, E. Bulgakova

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This study continues the research on Tuvinian intonation and presents a general cross-dialect analysis of intonation of Tuvinian declarative utterances, specifically the character of the tone movement in order to test the hypothesis about the prevalence of level tone in some Tuvinian dialects. The results of the analysis of basic pitch characteristics of Tuvinian speech (in general and in comparison with two other Turkic languages - Uzbek and Azerbaijani) are also given in this paper. The goal of our work was to obtain the ranges of pitch parameter values typical for Tuvinian speech. Such language-specific values can be used in speaker identification systems in order to get more accurate results of ethnic speech analysis. We also present the results of a cross-dialect analysis of declarative intonation in the poorly studied Tuvinian language.

Keywords: speech analysis, statistical analysis, speaker recognition, identification of person

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Authors: S. Tehsin, S. Kausar

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The ultimate aim of machine intelligence is to explore and materialize the human capabilities, one of which is the ability to detect various text objects within one or more images displayed on any canvas including prints, videos or electronic displays. Multimedia data has increased rapidly in past years. Textual information present in multimedia contains important information about the image/video content. However, it needs to technologically testify the commonly used human intelligence of detecting and differentiating the text within an image, for computers. Hence in this paper feature set based on anatomical study of human text detection system is proposed. Subsequent examination bears testimony to the fact that the features extracted proved instrumental to text detection.

Keywords: biologically inspired vision, content based retrieval, document analysis, text extraction

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Authors: Chinmayee Nanda

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In this modern era, India is still chained up with the idea of ‘Heteronormativity’. As a result, homonormativity, transgressions, preconceived notions, and bigotry add to many raised eyebrows, the majority being the norm and overpowering the voices of the minority. In this country an undeniable space is the need of the hour to identify those unheard voices. Media can be considered as the most powerful space for the same. This paper aims to examine the representation as well as transition (if any) of the varied figments of the imagination and alternative facts relating to the LGBTQ+ community in celluloid in Hindi. This paper will also explore the visibility of the queer aspirations through this media. The portrayal of the LGBTQ community as the ‘other’ and ‘not normal’ is a matter of concern about any individual’s sexuality. The years 2014 and 2018 turned out to be remarkable in the Indian Legal System pertaining to the recognition of the ‘Third Gender’ and ‘Decriminalization of Homosexuality,’ respectively. In relation to that, this paper will also explore the impression of these dynamics on the subsequent depiction.

Keywords: sexuality, hindi cinema, gender fluidity, legal framework

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Authors: Anatoly D. Pluzhnikov, Elena N. Pribludova, Alexander G. Ryndyk

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In conjunction with the problem of the target selection on a clutter background, the analysis of the scanning rate influence on the spatial-temporal signal structure, the generalized multivariate correlation function and the quality of the resolution with the increase pulse repetition frequency is made. The possibility of the object space-distance resolution, which is conditioned by the range-to-angle conversion with an increased scanning rate, is substantiated. The calculations for the real cylindrical array at high scanning rate are presented. The high scanning rate let to get the signal to noise improvement of the order of 10 dB for the space-time signal processing.

Keywords: antenna pattern, array, signal processing, spatial resolution

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Authors: Kuralay Kenzhekanova, Akmaral Dalelbekkyzy

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The article is devoted to the problem of political discourse and its reflection on mass cognition. This article is dedicated to describe the myth as one of the main features of political discourse. The dominance of an expressional and emotional component in the myth is shown. Precedent phenomenon plays an important role in distinguishing the myth from the linguistic point of view. Precedent phenomena show the linguistic cognition, which is characterized by their fame and recognition. Four types of myths such as master myths, a foundation myth, sustaining myth, eschatological myths are observed. The myths about the national idea are characterized by national specificity. The main aim of the political discourse with the help of myths is to influence on the mass consciousness in order to motivate the addressee to certain actions so that the target purpose is reached owing to unity of forces.

Keywords: cognition, myth, linguistic consciousness, types of myths, political discourse, political myth, precedent phenomena

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Authors: Ankit Tyagi, Reet Kamal Tiwari, Naveen James

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Landslide is the major geo-environmental problem of Himalaya because of high ridges, steep slopes, deep valleys, and complex system of streams. They are mainly triggered by rainfall and earthquake and causing severe damage to life and property. In Uttarakhand, the Tehri reservoir rim area, which is situated in the lesser Himalaya of Garhwal hills, was selected for landslide hazard zonation (LHZ). The study utilized different types of data, including geological maps, topographic maps from the survey of India, Landsat 8, and Cartosat DEM data. This paper presents the use of a weighted overlay method in LHZ using fourteen causative factors. The various data layers generated and co-registered were slope, aspect, relative relief, soil cover, intensity of rainfall, seismic ground shaking, seismic amplification at surface level, lithology, land use/land cover (LULC), normalized difference vegetation index (NDVI), topographic wetness index (TWI), stream power index (SPI), drainage buffer and reservoir buffer. Seismic analysis is performed using peak horizontal acceleration (PHA) intensity and amplification factors in the evaluation of the landslide hazard index (LHI). Several digital image processing techniques such as topographic correction, NDVI, and supervised classification were widely used in the process of terrain factor extraction. Lithological features, LULC, drainage pattern, lineaments, and structural features are extracted using digital image processing techniques. Colour, tones, topography, and stream drainage pattern from the imageries are used to analyse geological features. Slope map, aspect map, relative relief are created by using Cartosat DEM data. DEM data is also used for the detailed drainage analysis, which includes TWI, SPI, drainage buffer, and reservoir buffer. In the weighted overlay method, the comparative importance of several causative factors obtained from experience. In this method, after multiplying the influence factor with the corresponding rating of a particular class, it is reclassified, and the LHZ map is prepared. Further, based on the land-use map developed from remote sensing images, a landslide vulnerability study for the study area is carried out and presented in this paper.

Keywords: weighted overlay method, GIS, landslide hazard zonation, remote sensing

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Authors: Chen Xi, Liu Xuebing, Lao Xueru, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behavior recognition models, to provide empirical data such as 'pedestrian flow data and human behavioral characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, sustainable development

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Authors: Nouredine Benouzza, Ahmed Hamida Boudinar, Azeddine Bendiabdellah

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An algorithm for Eccentricity Fault Detection (EFD) applied to a squirrel cage induction machine is proposed in this paper. This algorithm employs the behavior of the stator current spectral analysis and the localization of the Rotor Slot Harmonic (RSH) frequency to detect eccentricity faults in three phase induction machine. The RHS frequency once obtained is used as a key parameter into a simple developed expression to directly compute the eccentricity fault frequencies in the induction machine. Experimental tests performed for both a healthy motor and a faulty motor with different eccentricity fault severities illustrate the effectiveness and merits of the proposed EFD algorithm.

Keywords: squirrel cage motor, diagnosis, eccentricity faults, current spectral analysis, rotor slot harmonic

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Authors: Tiee-Jian Wu, Chih-Yuan Hsu

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Mode estimation is an important task, because it has applications to data from a wide variety of sources. We propose a semi-parametric approach to estimate the mode of an unknown continuous multivariate density function. Our approach is based on a weighted average of a parametric density estimate using the Box-Cox transform and a non-parametric kernel density estimate. Our semi-parametric mode estimate improves both the parametric- and non-parametric- mode estimates. Specifically, our mode estimate solves the non-consistency problem of parametric mode estimates (at large sample sizes) and reduces the variability of non-parametric mode estimates (at small sample sizes). The performance of our method at practical sample sizes is demonstrated by simulation examples and two real examples from the fields of climatology and image recognition.

Keywords: Box-Cox transform, density estimation, mode seeking, semiparametric method

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Authors: Kwan Hee Han, Jun Woo Lee, Sung Moon Bae, Twae Kyung Park

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ECA (Event-Condition-Action) languages are largely adopted for event processing since they are an intuitive and powerful paradigm for programming reactive systems. However, there are some limitations about ECA rules for processing of complex events such as coupling of event producer and consumer. The objective of this paper is to propose an ECA rule pattern to improve the current limitations of ECA rule, and to develop a prototype system. In this paper, conventional ECA rule is separated into 3 parts and each part is extended to meet the requirements of CEP. Finally, event processing logic is established by combining the relevant elements of 3 parts. The usability of proposed extended ECA rule is validated by a test scenario in this study.

Keywords: complex event processing, ECA rule, Event processing system, event-driven architecture, internet of things

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Authors: Miloud Abid Brahim

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Herpetic gingivostomatitis is a prevalent viral infection in children, predominantly caused by herpes simplex virus type 1 (HSV-1). This case report details the clinical presentation and management of a 9-year-old patient diagnosed with this condition. The child exhibited fever, oral pain, and vesicular lesions that progressed to painful erosions affecting the inner cheeks, tongue, lips, and gums. The diagnosis was established based on clinical findings. Treatment included symptomatic care with analgesics and antipyretics, antimicrobial therapy with antibiotics and antiseptics, and early administration of antiviral medication (aciclovir). The comprehensive approach led to complete resolution of symptoms within 10 days. This case underscores the significance of early recognition and prompt treatment to mitigate the impact of this condition on the patient’s quality of life and to prevent complications.

Keywords: gingivostomatitis, case report, pediatric oral health, herpes simplex virus (HSV-1)

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Authors: Tayba Akram

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our main objective of this study is to work on the etiology of liver cirrhosis, to find basic reasons and causes of liver damage, and to find the pattern of liver cirrhosis in hepatic patients either suffering from hepatitis B/C or simple jaundice. We can evaluate medical treatment and the latest trends in patients suffering from liver cirrhosis. We can evaluate the side effects and adverse effects induced by drug therapy used to treat liver cirrhosis. The conclusion is based on the etiology of liver cirrhosis. The most common cause of liver cirrhosis is the viral Hepatitis C virus. Other common causes of liver cirrhosis that are estimated from our research are Hepatitis B virus, Diabetes Mellitus, Ascites, and very rarely found Hepatitis D virus.

Keywords: etiology, liver, cirrhosis, co-morbid diseases

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Authors: Chen Xi, Kuan Sinman, LI Haofeng, Huang Hongming, Zeng Chengyu, Tong Zhiyuan

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Stray animals are on the rise in mainland China's cities. There are legal reasons for this, namely the lack of protection for domestic pets in mainland China, where only wildlife protection laws exist. At a social level, the ease with which families adopt pets and the lack of a social view of animal nature has led to the frequent abandonment and loss of stray animals. If left unmanaged, conflicts between humans and stray animals can also increase. This project provides an inexpensive and widely applicable management tool for urban management by collecting videos and pictures of stray animals captured by surveillance or transmitted by humans and using artificial intelligence technology (mainly using YOLOv5 recognition technology) and recording and managing them in a database.

Keywords: urban planning, urban governance, artificial intelligence, convolutional neural network

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Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

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Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: few-shot learning, triplet network, adaptive margin, deep learning

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Authors: Sheldon McCall, Miao Yu, Liyun Gong, Shigang Yue, Stefanos Kollias

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Falls are a significant health concern for older adults globally, and prompt identification is critical to providing necessary healthcare support. Our study proposes a new fall detection method using computer vision based on modern deep learning techniques. Our approach involves training a trans- former model on a large 2D pose dataset for general action recognition, followed by transfer learning. Specifically, we freeze the first few layers of the trained transformer model and train only the last two layers for fall detection. Our experimental results demonstrate that our proposed method outperforms both classical machine learning and deep learning approaches in fall/non-fall classification. Overall, our study suggests that our proposed methodology could be a valuable tool for identifying falls.

Keywords: healthcare, fall detection, transformer, transfer learning

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Authors: Khaled M. Khan, Armstrong Nhlabatsi

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This article attempts to analyse behavioural traits of lone-wolves who struck and killed innocents in six different attacks in Europe in last nine months. The main objective of this study is to develop a profiling template in order to capture commonality of characteristics of these attackers. This study tries to understand the homogeneity of lone-wolves in terms of their social background and state of mind. The commonality among them can possibly be used to build a profiling template that could help detecting vulnerable persons who are prone to be self-radicalised or radicalised by someone else. The result of this study provides us an understanding of their commonality in terms of their state of mind and social characteristics.

Keywords: behavioral pattern, terrorism, profiling, commonality

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Authors: Dayo Samuel Banjo, Connice Trimmingham, Niloofar Yousefi, Nitin Agarwal

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Technological advancement and its omnipresent connection have pushed humans past the boundaries and limitations of a computer screen, physical state, or geographical location. It has provided a depth of avenues that facilitate human-computer interaction that was once inconceivable such as audio and body language detection. Given the complex modularities of emotions, it becomes vital to study human-computer interaction, as it is the commencement of a thorough understanding of the emotional state of users and, in the context of social networks, the producers of multimodal information. This study first acknowledges the accuracy of classification found within multimodal emotion detection systems compared to unimodal solutions. Second, it explores the characterization of multimedia content produced based on their emotions and the coherence of emotion in different modalities by utilizing deep learning models to classify emotion across different modalities.

Keywords: affective computing, deep learning, emotion recognition, multimodal

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Authors: Keivan Jamshidi, Fateme Behbahani, Sara Omidi, Nadia Shahi, Alireza Farkhonde

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Amyloidosis represents a heterogenous group of diseases that have in common the deposition of fibrils composed of proteins of beta-pleated sheet structure, which can be specifically identified by histochemistry using the Congo red or similar stains. Between October 2013 to April 2014 (6 months) different patterns of renal amyloidosis was diagnosed on histopathological examination of kidneys belong to 196 out of 7065 slaughtered sheep subjected to postmortem examination. Microscopic examination of renal tissue sections stained with H&E and CR staining techniques revealed 3 patterns of renal amyloid deposition; including glomerular (22.72%), medullary (68.18%), and vascular (9.09%) were recognized. Renal medullary amyloidosis (RMA) was detected as the most prevalence pattern of renal amyloidosis in domestic sheep.

Keywords: sheep, amyloidosis, kidney, slaughterhouse

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Authors: Jahanshah Saleh, Hossein Ghasemi, Ali Shahriari, Faezeh Alizadeh, Yaaghoob Hosseini

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Cadmium and chromium are toxic to most organisms and different mechanisms have been developed for overcoming with the toxic effects of these heavy metals. We studied the uptake and distribution of cadmium and chromium in different organs of tomato (Lycopersicon esculentum L.) plants in nine heavy metal polluted soils in western Hormozgan province, Iran. The accumulation of chromium was in increasing pattern of fruit peel

Keywords: cadmium, chromium, phytoextraction, phytostabilization, tomato

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Authors: Rui Mao, Heming Ji, Xiaoyu Wang

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Keystroke dynamics are widely used in identity recognition. It has the advantage that the individual typing rhythm is difficult to imitate. It also supports continuous authentication through the keyboard without extra devices. The existing keystroke dynamics authentication methods based on machine learning have a drawback in supporting relatively complex scenarios with massive data. There are drawbacks to both feature extraction and model optimization in these methods. To overcome the above weakness, an authentication model of keystroke dynamics based on deep learning is proposed. The model uses feature vectors formed by keystroke content and keystroke time. It ensures efficient continuous authentication by cooperating attention mechanisms with the combination of CNN and Bi-LSTM. The model has been tested with Open Data Buffalo dataset, and the result shows that the FRR is 3.09%, FAR is 3.03%, and EER is 4.23%. This proves that the model is efficient and accurate on continuous authentication.

Keywords: keystroke dynamics, identity authentication, deep learning, CNN, LSTM

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Authors: Ebenezer Obaloluwa Olaniyi

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In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.

Keywords: image processing, neural network, apple, intelligent system

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Authors: Adian Fatchur Rochim, Abdul Muis, Riri Fitri Sari

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H-index has been widely used as a performance indicator of researchers around the world especially in Indonesia. The Government uses Scopus and Google scholar as indexing references in providing recognition and appreciation. However, those two indexing services yield to different H-index values. For that purpose, this paper evaluates the difference of the H-index from those services. Researchers indexed by Webometrics, are used as reference’s data in this paper. Currently, Webometrics only uses H-index from Google Scholar. This paper observed and compared corresponding researchers’ data from Scopus to get their H-index score. Subsequently, some researchers with huge differences in score are observed in more detail on their paper’s publisher. This paper shows that the H-index of researchers in Google Scholar is approximately 2.45 times of their Scopus H-Index. Most difference exists due to the existence of uncertified publishers, which is considered in Google Scholar but not in Scopus.

Keywords: Google Scholar, H-index, Scopus, performance indicator

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