Search results for: heterogeneous computing

Authors: D. Zhang, H. Y. Du, G. W. Li, J. Zeng, D. W. Zuo, Y. P. You

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For the difficult issues of process selection, case-based reasoning technology is applied to computer aided process planning system for cold form tapping of internal threads on the basis of similarity in the process. A model is established based on the analysis of process planning. Case representation and similarity computing method are given. Confidence degree is used to evaluate the case. Rule-based reuse strategy is presented. The scheme is illustrated and verified by practical application. The case shows the design results with the proposed method are effective.

Keywords: case-based reasoning, internal thread, cold extrusion, process planning

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Authors: Zhiwen Pan, Jesus Pacheco, Salim Hariri, Yiqiang Chen, Bozhi Liu

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The Internet of Things (IoT) will lead to the development of advanced Smart Home services that are pervasive, cost-effective, and can be accessed by home occupants from anywhere and at any time. However, advanced smart home applications will introduce grand security challenges due to the increase in the attack surface. Current approaches do not handle cybersecurity from a holistic point of view; hence, a systematic cybersecurity mechanism needs to be adopted when designing smart home applications. In this paper, we present a generic intrusion detection methodology to detect and mitigate the anomaly behaviors happened in Smart Home Systems (SHS). By utilizing our Smart Home Context Data Structure, the heterogeneous information and services acquired from SHS are mapped in context attributes which can describe the context of smart home operation precisely and accurately. Runtime models for describing usage patterns of home assets are developed based on characterization functions. A threat-aware action management methodology, used to efficiently mitigate anomaly behaviors, is proposed at the end. Our preliminary experimental results show that our methodology can be used to detect and mitigate known and unknown threats, as well as to protect SHS premises and services.

Keywords: Internet of Things, network security, context awareness, intrusion detection

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

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Authors: Chahid K. Ghaddar

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The spreadsheet engine is exploited via a non-conventional mechanism to enable novel worksheet solver functions for computational calculus. The solver functions bypass inherent restrictions on built-in math and user defined functions by taking variable formulas as a new type of argument while retaining purity and recursion properties. The enabling mechanism permits integration of numerical algorithms into worksheet functions for solving virtually any computational problem that can be modelled by formulas and variables. Several examples are presented for computing integrals, derivatives, and systems of deferential-algebraic equations. Incorporation of the worksheet solver functions with the ubiquitous spreadsheet extend the utility of the latter as a powerful tool for computational mathematics.

Keywords: calculus, differential algebraic equations, solvers, spreadsheet

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Authors: Jinhyun Ryu, Chengliang Xie, Nal Ae Yoon, Dong Hoon Lee, Gu Seob Roh, Hyun Joon Kim, Gyeong Jae Cho, Wan Sung Choi, Sang Soo Kang

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Type 2 diabetes is a heterogeneous group of metabolic disorders featured by a deficit in or loss of insulin activity to maintain normal glucose homeostasis. Mainly, it results from the compromised insulin secretion and/or reduced insulin activity. The frequency of type 2 diabetes (T2D) has been increased rapidly in recent decades with the increase in the trend of obesity due to life style and food habit. Obesity is considered to be the primary risk factor for the development of insulin resistance and thereby developing T2D. Traditionally naturally occurring fruits, vegetables etc. are being used to treat many pathogenic conditions. In this study, we tried to find out the effect of a popularly used vegetable in Bangladesh and several other Asian countries, ‘bitter melon’ on high fat diet induced T2D. To investigate the effect, we used 70% ethanol extract of bitter melon (BME) as dietary supplement with chow. BME was found to attenuate the high fat diet (HFD) induced body weight and total fat mass significantly. We also observed that BME reduced the insulin resistance induced by HFD effectively. Furthermore, dietary supplementation of BME was highly effective in increasing insulin sensitivity, and reducing the hepatic fat and obesity. These results indicate that BME could be effective to attenuate T2D and could be a preventive measure against T2D.

Keywords: bitter melon, obesity, type 2 diabetes, high fat diet

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Authors: Francisco José Plácido da Cunha, Tassio Ferenzini Martins Sirqueira, Marx Leles Viana, Carlos José Pereira de Lucena

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Open Multiagent Systems (MASs) are societies in which heterogeneous and independently designed entities (agents) work towards similar, or different ends. Software agents are autonomous and the diversity of interests among different members living in the same society is a fact. In order to deal with this autonomy, these open systems use mechanisms of social control (norms) to ensure a desirable social order. This paper considers the following types of norms: (i) obligation — agents must accomplish a specific outcome; (ii) permission — agents may act in a particular way, and (iii) prohibition — agents must not act in a specific way. All of these characteristics mean to encourage the fulfillment of norms through rewards and to discourage norm violation by pointing out the punishments. Once the software agent decides that its priority is the satisfaction of its own desires and goals, each agent must evaluate the effects associated to the fulfillment of one or more norms before choosing which one should be fulfilled. The same applies when agents decide to violate a norm. This paper also introduces a framework for the development of MASs that provide support mechanisms to the agent’s decision-making, using norm-based reasoning. The applicability and validation of this approach is demonstrated applying a traffic intersection scenario.

Keywords: BDI agent, BDI4JADE framework, multiagent systems, normative agents

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Authors: Malihe Aliasgari, Yousef Nejatbakhsh

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The era of Big Data and the immensity of real-life datasets compels computation tasks to be performed in a distributed fashion, where the data is dispersed among many servers that operate in parallel. However, massive parallelization leads to computational bottlenecks due to faulty servers and stragglers. Stragglers refer to a few slow or delay-prone processors that can bottleneck the entire computation because one has to wait for all the parallel nodes to finish. The problem of straggling processors, has been well studied in the context of distributed computing. Recently, it has been pointed out that, for the important case of linear functions, it is possible to improve over repetition strategies in terms of the tradeoff between performance and latency by carrying out linear precoding of the data prior to processing. The key idea is that, by employing suitable linear codes operating over fractions of the original data, a function may be completed as soon as enough number of processors, depending on the minimum distance of the code, have completed their operations. The problem of matrix-matrix multiplication in the presence of practically big sized of data sets faced with computational and memory related difficulties, which makes such operations are carried out using distributed computing platforms. In this work, we study the problem of distributed matrix-matrix multiplication W = XY under storage constraints, i.e., when each server is allowed to store a fixed fraction of each of the matrices X and Y, which is a fundamental building of many science and engineering fields such as machine learning, image and signal processing, wireless communication, optimization. Non-secure and secure matrix multiplication are studied. We want to study the setup, in which the identity of the matrix of interest should be kept private from the workers and then obtain the recovery threshold of the colluding model, that is, the number of workers that need to complete their task before the master server can recover the product W. The problem of secure and private distributed matrix multiplication W = XY which the matrix X is confidential, while matrix Y is selected in a private manner from a library of public matrices. We present the best currently known trade-off between communication load and recovery threshold. On the other words, we design an achievable PSGPD scheme for any arbitrary privacy level by trivially concatenating a robust PIR scheme for arbitrary colluding workers and private databases and the proposed SGPD code that provides a smaller computational complexity at the workers.

Keywords: coded distributed computation, private information retrieval, secret sharing, stragglers

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Authors: Selma Sbit, Mohamed Bechir Dadi, Belgacem Chibani Rhaimi

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Incorporating Home eNodeB (HeNB) in cellular networks, e.g. Long Term Evolution Advanced (LTE-A), is beneficial for extending coverage and enhancing capacity at low price especially within the non-line-of sight (NLOS) environments such as homes. HeNB or femtocell is a small low powered base station which provides radio coverage to the mobile users in an indoor environment. This deployment results in a heterogeneous network where the available spectrum becomes shared between two layers. Therefore, a problem of Inter Cell Interference (ICI) appears. This issue is the main challenge in LTE-A. To deal with this challenge, various techniques based on frequency, time and power control are proposed. This paper deals with the impact of carrier aggregation and higher order MIMO (Multiple Input Multiple Output) schemes on the LTE-Advanced performance. Simulation results show the advantages of these schemes on the system capacity (4.10⁹ b/s/Hz when bandwidth B=100 MHz and when applying MIMO 8x8 for SINR=30 dB), maximum theoretical peak data rate (more than 4 Gbps for B=100 MHz and when MIMO 8x8 is used) and spectral efficiency (15 b/s/Hz and 30b/s/Hz when MIMO 4x4 and MIMO 8x8 are applying respectively for SINR=30 dB).

Keywords: capacity, carrier aggregation, LTE-Advanced, MIMO (Multiple Input Multiple Output), peak data rate, spectral efficiency

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Authors: Yiwei Li, Boyu Tian, Mingyu Gao

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Hybrid main memory systems combine both performance and capacity advantages from heterogeneous memory technologies. With larger capacities, higher associativities, and finer granularities, hybrid memory systems currently exhibit significant metadata storage and lookup overheads for flexibly remapping data blocks between the two memory tiers. To alleviate the inefficiencies of existing designs, we propose Trimma, the combination of a multi-level metadata structure and an efficient metadata cache design. Trimma uses a multilevel metadata table to only track truly necessary address remap entries. The saved memory space is effectively utilized as extra DRAM cache capacity to improve performance. Trimma also uses separate formats to store the entries with non-identity and identity mappings. This improves the overall remap cache hit rate, further boosting the performance. Trimma is transparent to software and compatible with various types of hybrid memory systems. When evaluated on a representative DDR4 + NVM hybrid memory system, Trimma achieves up to 2.4× and on average 58.1% speedup benefits, compared with a state-of-the-art design that only leverages the unallocated fast memory space for caching. Trimma addresses metadata management overheads and targets future scalable large-scale hybrid memory architectures.

Keywords: memory system, data cache, hybrid memory, non-volatile memory

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Authors: Dongjae Kang, Sokho Son, Jinmee Kim

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Cloud service brokering is a new service paradigm that provides interoperability and portability of application across multiple Cloud providers. In this paper, we designed cloud service brokerage system, any broker, supporting integrated service provisioning and SLA based service life cycle management. For the system design, we introduce the system concept and whole architecture, details of main components and use cases of primary operations in the system. These features ease the Cloud service provider and customer’s concern and support new Cloud service open market to increase cloud service profit and prompt Cloud service echo system in cloud computing related area.

Keywords: cloud service brokerage, multiple Clouds, Integrated service provisioning, SLA, network service

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Authors: Samia Dardouri, Ridha Bouallegue

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Scheduling is the process of dynamically allocating physical resources to User Equipment (UE) based on scheduling algorithms implemented at the LTE base station. Various algorithms have been proposed by network researchers as the implementation of scheduling algorithm which represents an open issue in Long Term Evolution (LTE) standard. This paper makes an attempt to study and compare the performance of PF, MLWDF and EXP/PF scheduling algorithms. The evaluation is considered for a single cell with interference scenario for different flows such as Best effort, Video and VoIP in a pedestrian and vehicular environment using the LTE-Sim network simulator. The comparative study is conducted in terms of system throughput, fairness index, delay, packet loss ratio (PLR) and total cell spectral efficiency.

Keywords: LTE, multimedia flows, scheduling algorithms, mobile computing

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Authors: Dawei Cai

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In this paper, we present a new wearable device that provide an automatic guidance servie for visitors. By combining the position information from NFC and the orientation information from a 6 axis acceleration and terrestrial magnetism sensor, the head's direction can be calculated. We developed an algorithm to calculate the device orientation based on the data from acceleration and terrestrial magnetism sensor. If visitors want to know some explanation about an exhibit in front of him, what he has to do is just lift up his mobile device. The identification program will automatically identify the status based on the information from NFC and MEMS, and start playing explanation content for him. This service may be convenient for old people or disables or children.

Keywords: wearable device, ubiquitous computing, guide sysem, MEMS sensor, NFC

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Authors: Xin-Yu Shih, Yue-Qu Liu, Hong-Ru Chou

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This paper presents a low-area and fully-reconfigurable Fast Fourier Transform (FFT) hardware design for 3GPP-LTE communication standard. It can fully support 32 different FFT sizes, up to 2048 FFT points. Besides, a special processing element is developed for making reconfigurable computing characteristics possible, while first-in first-out (FIFO) scheduling scheme design technique is proposed for hardware-friendly FIFO resource arranging. In a synthesis chip realization via TSMC 40 nm CMOS technology, the hardware circuit only occupies core area of 0.2325 mm² and dissipates 233.5 mW at maximal operating frequency of 250 MHz.

Keywords: reconfigurable, fast Fourier transform (FFT), single-path delay feedback (SDF), 3GPP-LTE

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Authors: Francis O. Nwawuru

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The convergence analysis of split monotone inclusion problems and fixed point problems of certain nonlinear mappings are investigated in the setting of real Hilbert spaces. Inertial extrapolation term in the spirit of Polyak is incorporated to speed up the rate of convergence. Under standard assumptions, a strong convergence of the proposed algorithm is established without computing the resolvent operator or involving Yosida approximation method. The stepsize involved in the algorithm does not depend on the spectral radius of the linear operator. Furthermore, applications of the proposed algorithm in solving some related optimization problems are also considered. Our result complements and extends numerous results in the literature.

Keywords: fixedpoint, hilbertspace, monotonemapping, resolventoperators

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Authors: Harleen Kaur, Richa

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Plants produce a large variety of secondary metabolites. Phenolics are the compounds that contain hydroxyl functional group on an aromatic ring. These are chemically heterogeneous compounds. Some are soluble only in organic solvents, some are water soluble and others are large insoluble polymers. Flavonoids are one of the largest classes of plant phenolics. The carbon skeleton of a flavonoid contains 15 carbons arranged in two aromatic rings connected by a three carbon ridge. Both phenolics and flavonoids are good natural antioxidants. Four Indian aromatic plants were selected for the study i.e, Achillea species, Jasminum primulinum, Leucas cephalotes and Leonotis nepetaefolia. All the plant species were collected from Chail region of Himachal Pradesh, India. The identifying features and anatomical studies were done of the part containing the essential oils. Phenolic cotent was estimated by Folin Ciocalteu’s method and flavonoids content by aluminium chloride method. Antioxidant property was checked by using DPPH method. Maximum antioxidant potential was found in Achillea species, followed by Leonotis nepetaefolia, Jaminum primulinum and Leucas cephalotes. Phenolics and flavonoids are important compounds that serve as defences against herbivores and pathogens. Others function in attracting pollinators and absorbing harmful radiations.

Keywords: antioxidants, DPPH, flavonoids, phenolics

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Authors: Vanshika Chutani, Priya Bhatnagar

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The pandemic has brought us to a standpoint where stress as a physical, cognitive, and behavioral construct is inevitable. The current research provides an overview of the relationship between stress and dysfunctional eating behavior during the challenging time of the COVID-19 pandemic. The present paper also aims to highlight the gender-specific differences in perception of stress and its correlation with dysfunctional eating behavior in the COVID-19 pandemic. Perceived Stress Scale-10 (PSS) and Adult Eating Behavior questionnaire (AEBQ) were used on a heterogeneous sample between 20-40 years. The research was conducted on 50 participants, 25 male, and 25 female. Quantitative analysis was done with SPSS 22.0. The results of the investigation revealed a significant difference in stress level, t(48)=2.01, p<0.01, with women (M=22.24. SD=5.23) having a higher stress level than men (M=19.04, SD=4.89). There was no significant difference in dysfunctional eating behavior between males and females. There was a significant positive correlation between stress and dysfunctional eating behavior in females, whereas, in males, there was no significant positive correlation between stress and dysfunctional eating behavior. The research extrapolates that the pandemic led to elevated stress levels in both genders and gender differences existed, and males & females responded differently on dysfunctional eating behavior. The research has also outlined intervention to help individuals cope with stress and dysfunctional eating behavior. The findings of the research propose the execution of different intervention programs and psychological first aid to help individuals who are predisposed to develop eating disorders.

Keywords: stress, dysfunctional eating behavior, gender-specific differences, COVID-19

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Authors: Miao Yang

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PPCPs (pharmaceutical and personal care products) in water, as an environmental pollutant, becomes an issue of increasing concern. Therefore, the techniques for degradation of PPCPs has been a hotspot in water pollution control field. Since there are several disadvantages for common degradation techniques of PPCPs, such as low degradation efficiency for certain PPCPs (ibuprofen and Carbamazepine) this proposal will adopt a combined technique by using CDs (carbon nanodots)/C₃N₄ composite and ultrasonic irradiation to mitigate or overcome these shortages. There is a significant scientific problem that the mechanism including PPCPs, major reactants, and interfacial active sites is not clear yet in the study of PPCPs degradation. This work aims to solve this problem by using both theoretical and experimental methodologies. Firstly, optimized parameters will be obtained by evaluating the kinetics and oxidation efficiency under different conditions. The competition between H₂O₂ and PPCPs with HO• will be elucidated, after which the degradation mechanism of PPCPs by the synergy of CDs/C₃N₄ composite and ultrasonic irradiation will be proposed. Finally, a sonolysis-adsorption-catalysis coupling mechanism will be established which is the theoretical basis and technical support for developing new efficient degradation techniques for PPCPs in the future.

Keywords: carbon nanodots/C₃N₄, pharmaceutical and personal care products, ultrasonic irradiation, hydroxyl radical, heterogeneous catalysis

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Authors: Min-Shiuan Liou, Yi Shan Yang, Yang-Zhan Huang, Chia-Wen Hsieh

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A high speed growing and butanol-tolerant Clostridium acetobutylicum HOL1 mutant was screened throughout continuous adaption culture with C. acetobutylicum ATCC 824. The HOL1 strain can grow well in 10 g/L butanol contained CGM medium and can produce about 12.8 g /L butanol during 24 hrs. The C. acetobutylicum HOL1 strain was able to produce 166 mM butanol with 21 mM acetone at pH 4.8, resulting in a butanol selectivity (a molar ratio of butanol to total solvents) of 0.79, which is much higher than that (0.6) of the wild-type strain C. acetobutylicum ATCC 824. The acetate and butyrate accumulation were not observed during fermentation of the HOL1 strain. A hyper-butanol producing C. acetobutylicum HOL1 (pBPHS-3), which was created to overexpress the Bacillus psychrosaccharolyticus originated specific heat-shock protein gene, hspX, from a clostridial phosphotransbutyrylase promoter, was studied for its potential to produce a high titer of butanol. Overexpression of hspX resulted in increased final butanol yield 47% and 30% higher than those of the the ATCC824 and the HOL1 strains, respectively. The remarkable high-speed growth and butanol tolerance of strain HOL1 (pBPHS-3) demonstrates that overexpression of heterogeneous stress protein-encoding gene, hspX, could help C. acetobutylicum to effectively produce a high concentration of butanol.

Keywords: Clostridium acetobutylicum, butanol, heat-shock protein, resistance

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Authors: Amandeep Singh Dhaliwal

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Networking solutions, particularly wireless local area networks have revolutionized the technological advancement. Wireless Local Area Networks (WLANs) have gained a lot of popularity as they provide location-independent network access between computing devices. There are a number of access methods used in Wireless Networks among which DCF and PCF are the fundamental access methods. This paper emphasizes on the impact of DCF and PCF access mechanisms on the performance of the IEEE 802.11a, 802.11b and 802.11g standards. On the basis of various parameters viz. throughput, delay, load etc performance is evaluated between these three standards using above mentioned access mechanisms. Analysis revealed a superior throughput performance with low delays for 802.11g standard as compared to 802.11 a/b standard using both DCF and PCF access methods.

Keywords: DCF, IEEE, PCF, WLAN

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Authors: Iulia Crisan

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Objective: The present study investigates the cross-cultural validity of three North-American performance validity indicators (PVTs) by comparing base rates of failure (BRF) in Romanian and Canadian disability applicants. Methods: Three PVTs (Test of Memory Malingering Trial 1 [TOMM-1], Rey Fifteen Item Test free recall [Rey-15 FR], and Rey FR+Recognition [Rey COMB]) were administered to a heterogeneous Romanian clinical sample (N Ro =54) and a similar Canadian sample (N Can = 52). Patients were referred for assessment to determine the severity of their cognitive deficits. Results: We compared the BRF in both samples at various cutoffs. BRF on TOMM-1 at ≤ 43 was similar (Ro = 33.3% vs. Can = 40.4%); at ≤40, Ro = 22.2% vs. Can = 25.0%. Likewise, comparable BRF were observed on Rey-15 FR at ≤ 8 (Ro = 7.4% vs. Can = 11.5%) and ≤ 11 (Ro = 27.8% vs. Can = 23.1%). However, the Romanian sample produced significantly higher failure rates on the Rey COMB at variable cutoffs (p <.05), possibly because Romanian patients were significantly older than the Canadian sample. Conclusion: Our findings offer proof of concept for the cross-cultural validity of the TOMM and Rey-15 FR. At the same time, they serve as a reminder that the generalizability of PVT cutoffs to different populations should not be assumed but verified empirically. Employing the TOMM as a criterion measure for newly developed PVTs is discussed.

Keywords: performance validity indicators, cross-cultural validity, failure base rates, clinical samples, cognitive dysfunction, TOMM-1, Rey-15, Rey COMB

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Authors: Palash Dey, Sudip Talukdar

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In this work, a cross-breed approach is presented for obtaining both the amount of the damage intensity and location of damage existing in thin-walled members. This cross-breed approach is developed based on response surface methodology (RSM) and genetic algorithm (GA). Theoretical finite element (FE) model of cracked angle section thin walled curved beam has been linked to the developed approach to carry out trial experiments to generate response surface functions (RSFs) of free, forced and heterogeneous dynamic response data. Subsequently, the error between the computed response surface functions and measured dynamic response data has been minimized using GA to find out the optimum damage parameters (amount of the damage intensity and location). A single crack of varying location and depth has been considered in this study. The presented approach has been found to reveal good accuracy in prediction of crack parameters and possess great potential in crack detection as it requires only the current response of a cracked beam.

Keywords: damage parameters, finite element, genetic algorithm, response surface methodology, thin walled curved beam

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Authors: Ivan Stanev, Maria Koleva

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A common platform for automated programming (CPAP) is defined in details. Two versions of CPAP are described: Cloud-based (including the set of components for classic programming, and the set of components for combined programming) and KBASE based (including the set of components for automated programming, and the set of components for ontology programming). Four KBASE products (module for automated programming of robots, intelligent product manual, intelligent document display, and intelligent form generator) are analyzed and CPAP contributions to automated programming are presented.

Keywords: automated programming, cloud computing, knowledge based software engineering, service oriented architecture

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Authors: M. Bevilacqua, F. E. Ciarapica, G. Marcucci

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Supply Chain Resilience has been broadly studied during the last decade, focusing the research on many aspects of Supply Chain performance. Consequently, different definitions of Supply Chain Resilience have been developed by the research community, drawing inspiration also from other fields of study such as ecology, sociology, psychology, economy et al. This way, the definitions so far developed in the extant literature are therefore very heterogeneous, and many authors have pointed out a lack of consensus in this field of analysis. The aim of this research is to find common points between these definitions, through the development of a framework of study: the Resilience Triangle. The Resilience Triangle is a tool developed in the field of civil engineering, with the objective of modeling the loss of resilience of a given structure during and after the occurrence of a disruption such as an earthquake. The Resilience Triangle is a simple yet powerful tool: in our opinion, it can summarize all the features that authors have captured in the Supply Chain Resilience definitions over the years. This research intends to recapitulate within this framework all these heterogeneities in Supply Chain Resilience research. After collecting a various number of Supply Chain Resilience definitions present in the extant literature, the methodology approach provides a taxonomy step with the scope of collecting and analyzing all the data gathered. The next step provides the comparison of the data obtained with the plotting of a disruption profile, in order to contextualize the Resilience Triangle in the Supply Chain context. The tool and the results developed in this research will allow to lay the foundation for future Supply Chain Resilience modeling and measurement work.

Keywords: supply chain resilience, resilience definition, supply chain resilience triangle

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Authors: Gurkirandeep Kaur, Rana Pratap Yadav

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This experimental study is aimed to examine the radiation characteristics of different plasma structures of a surface wave-driven plasma antenna by an automated measuring system. In this study, a 30 cm long plasma column of argon gas with a diameter of 3 cm is excited by surface wave discharge mechanism operating at 13.56 MHz with RF power level up to 100 Watts and gas pressure between 0.01 to 0.05 mb. The study reveals that a single structured plasma monopole can be modified into an array of plasma antenna elements by forming multiple striations or plasma blobs inside the discharge tube by altering the values of plasma properties such as working pressure, operating frequency, input RF power, discharge tube dimensions, i.e., length, radius, and thickness. It is also reported that plasma length, electron density, and conductivity are functions of operating plasma parameters and controlled by changing working pressure and input power. To investigate the antenna radiation efficiency for the far-field region, an automation-based radiation measuring system has been fabricated and presented in detail. This developed automated system involves a combined setup of controller, dc servo motors, vector network analyzer, and computing device to evaluate the radiation intensity, directivity, gain and efficiency of plasma antenna. In this system, the controller is connected to multiple motors for moving aluminum shafts in both elevation and azimuthal plane whereas radiation from plasma monopole antenna is measured by a Vector Network Analyser (VNA) which is further wired up with the computing device to display radiations in polar plot forms. Here, the radiation characteristics of both continuous and array plasma monopole antenna have been studied for various working plasma parameters. The experimental results clearly indicate that the plasma antenna is as efficient as a metallic antenna. The radiation from plasma monopole antenna is significantly influenced by plasma properties which provides a wider range in radiation pattern where desired radiation parameters like beam-width, the direction of radiation, radiation intensity, antenna efficiency, etc. can be achieved in a single monopole. Due to its wide range of selectivity in radiation pattern; this can meet the demands of wider bandwidth to get high data speed in communication systems. Moreover, this developed system provides an efficient and cost-effective solution for measuring the radiation pattern in far-field zone for any kind of antenna system.

Keywords: antenna radiation characteristics, dynamically reconfigurable, plasma antenna, plasma column, plasma striations, surface wave

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Authors: Golnush Masghati-Amoli, Paul Chin

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Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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Authors: Muhammad Ganda Wiratama

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XYZ company is one of the upstream chemical companies that produce chemical products such as NaOH, HCl, NaClO, VCM, EDC, and PVC for downstream companies. The products are shipped by land using trucks and sea lanes using ship mode. Especially for solid products such as flake caustic soda (F-NaOH) and PVC resin, the products are sold in loose bag packing and palletize packing (packed in pallet). The focus of this study is to increase the number of items that can be loaded in pallet packaging on the company's logistics vehicle. This is very difficult because on this packaging, the dimensions or size of the material to be loaded become larger and certainly much heavier than the loose bag packing. This factor causes the arrangement and handling of materials in the mode of transportation more difficult. In this case, it is difficult to load a different type of volume packing pallet dimension in one truck or container. By using the Cube-IQ software, it is hoped that the planning of stuffing activity material by pallet can become easier in optimizing the existing space with various possible combinations of possibilities. In addition, the output of this software can also be used as a reference for operators in the material handling include the order and orientation of materials contained in the truck or container. The more optimal contents of logistics cargo, then transportation costs can also be minimized.

Keywords: loading activity, container loading, palletize product, simulation

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Authors: Haneef Ur Rehman, Afsheen Aman, Abdul Hameed Baloch, Shah Ali Ul Qader

Abstract:

Pectinase is a heterogeneous group of enzymes that catalyze the hydrolysis of pectin substances and widely has been used in food and textile industries. In current study, pectinase from B. licheniformis KIBGE-IB21 was immobilized within different polymers (calcium alginate beads, polyacrylamide gel and agar-agar matrix) to enhance its catalytic properties. Polyacrylamide gel was found to be most promising one and gave maximum (89%) immobilization yield. While less immobilization yield was observed in case of calcium alginate beads that only retained 46 % activity. The reaction time for maximum pectinolytic activity was increased from 5.0 to 10 minutes after immobilization. The temperature of pectinase for maximum enzyme activity was increased from 45 °C to 50 °C and 55 °C when it was immobilized within agar-agar and calcium alginate beads, respectively. The optimum pH of pectinase didn’t alter when it was immobilized within polyacrylamide gel and calcium alginate beads, but in case of agar-agar it was changed from pH 10 to pH 9.0. Thermal stability of pectinase was improved after immobilization and immobilized pectinase showed higher toleration against different temperatures as compared to free enzyme. It can be concluded that the entrapment is a simple, single step and promising procedure to immobilized pectinase within different synthetic and non-synthetic polymers and enhanced its catalytic properties.

Keywords: pectinase, characterization immobilization, polyacrylamide, agar-agar, calcium alginate beads

Procedia PDF Downloads 593

Authors: Ali Zazi, Ouiza Cherifi

Abstract:

Natural gas currently represents a raw material of choice for the manufacture of a wide range of chemical products via synthesis gas, among the routes of transformation of methane into synthesis gas The reaction of the oxidation of methane by gas vapor 'water. This work focuses on the study of the effect of cerieum on the nickel-based catalyst supported by silica for the methane vapor reforming reaction, with a variation of certain parameters of the reaction. The reaction temperature, the H₂O / CH₄ ratio and the flow rate of the reaction mixture (CH₄-H₂O). Two catalysts were prepared by impregnation of Degussa silica with a solution of nickel nitrates and a solution of cerium nitrates [Ni (NO₃) 2 6H₂O and Ce (NO₃) 3 6H₂O] so as to obtain the 1.5% nickel concentrations. For both catalysts and plus 1% cerium for the second catalyst. These Catalysts have been characterized by physical and chemical analysis techniques: BET technique, Atomic Absorption, IR Spectroscopy, X-ray diffraction. These characterizations indicated that the nitrates had impregnated the silica. And that the NiO and Ce₂O3 phases are present and Ni°(after reaction). The BET surface of the silica decreases without being affected. The catalytic tests carried out on the two catalysts for the steam reforming reactions show that the addition of cerium to the nickel improves the catalytic performances of the nickel. And that these performances also depend on the parameters of the reaction, namely the temperature, the rate of the reaction mixture, and the ratio (H₂O / CH₄).

Keywords: heterogeneous catalysis, steam reforming, Methane, Nickel, Cerium, synthesis gas, hydrogen

Procedia PDF Downloads 148

Authors: Eunae Lee, Oh-Kuen Kwon, Ki-Sub Kim, Jeong Won Kang

Abstract:

We investigated the dynamic properties of graphene-nanoribbon (GNR) memory encapsulating graphene-nanoflake (GNF) shuttle in the potential to be applicable as a non-volatile random access memory via molecular dynamics simulations. This work explicitly demonstrates that the GNR encapsulating the GNF shuttle can be applied to nonvolatile memory. The potential well was originated by the increase of the attractive vdW energy between the GNRs when the GNF approached the edges of the GNRs. So the bistable positions were located near the edges of the GNRs. Such a nanoelectromechanical non-volatile memory based on graphene is also applicable to the development of switches, sensors, and quantum computing.

Keywords: graphene nanoribbon, graphene nanoflake, shuttle memory, molecular dynamics

Procedia PDF Downloads 439

Authors: Loulwah Bokhari, Jori Nazer, Hala Sultan

Abstract:

Nowadays, artificial intelligence (AI) is used as a foundation for many activities in modern computing applications at home, in vehicles, and in businesses. Many modern machines are built to carry out a specific activity or purpose. This is where the Amazon Alexa application comes in, as it is used as a virtual assistant. The purpose of this paper is to explore the use of Amazon Alexa among people and how it has improved and made simple daily tasks easier for many people. We gave our participants several questions regarding Amazon Alexa and if they had recently used or heard of it, as well as the different tasks it provides and whether it successfully satisfied their needs. Overall, we found that participants who have recently used Alexa have found it to be helpful in their daily tasks.

Keywords: artificial intelligence, Echo system, machine learning, feature for feature match

Procedia PDF Downloads 103