Search results for: tensor deep stacking neural networks

Authors: Sofia Dokuka, Liz Lockhart, Alex Furman

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Organizational hierarchy, traditionally composed of individual contributors, middle management, and executives, is enhanced by the understanding of informal social roles. These roles, identified with organizational network analysis (ONA), might have an important effect on organizational functioning. In this paper, we identify three social roles – influencers, bridges, and soloists, and provide empirical analysis based on real-world organizational networks. Influencers are employees with broad networks and whose contacts also have rich networks. Influence is calculated using PageRank, initially proposed for measuring website importance, but now applied in various network settings, including social networks. Influencers, having high PageRank, become key players in shaping opinions and behaviors within an organization. Bridges serve as links between loosely connected groups within the organization. Bridges are identified using betweenness and Burt’s constraint. Betweenness quantifies a node's control over information flows by evaluating its role in the control over the shortest paths within the network. Burt's constraint measures the extent of interconnection among an individual's contacts. A high constraint value suggests fewer structural holes and lesser control over information flows, whereas a low value suggests the contrary. Soloists are individuals with fewer than 5 stable social contacts, potentially facing challenges due to reduced social interaction and hypothetical lack of feedback and communication. We considered social roles in the analysis of real-world organizations (N=1,060). Based on data from digital traces (Slack, corporate email and calendar) we reconstructed an organizational communication network and identified influencers, bridges and soloists. We also collected employee engagement data through an online survey. Among the top-5% of influencers, 10% are members of the Executive Team. 56% of the Executive Team members are part of the top influencers group. The same proportion of top influencers (10%) is individual contributors, accounting for just 0.6% of all individual contributors in the company. The majority of influencers (80%) are at the middle management level. Out of all middle managers, 19% hold the role of influencers. However, individual contributors represent a small proportion of influencers, and having information about these individuals who hold influential roles can be crucial for management in identifying high-potential talents. Among the bridges, 4% are members of the Executive Team, 16% are individual contributors, and 80% are middle management. Predominantly middle management acts as a bridge. Bridge positions of some members of the executive team might indicate potential micromanagement on the leader's part. Recognizing the individuals serving as bridges in an organization uncovers potential communication problems. The majority of soloists are individual contributors (96%), and 4% of soloists are from middle management. These managers might face communication difficulties. We found an association between being an influencer and attitude toward a company's direction. There is a statistically significant 20% higher perception that the company is headed in the right direction among influencers compared to non-influencers (p < 0.05, Mann-Whitney test). Taken together, we demonstrate that considering social roles in the company might indicate both positive and negative aspects of organizational functioning that should be considered in data-driven decision-making.

Keywords: organizational network analysis, social roles, influencer, bridge, soloist

Procedia PDF Downloads 105

Authors: Syed Romat Ali Shah, Bilal Shoaib, Saleem Akhtar, Munib Ahmad, Shahan Sadiqui

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Classification is a data mining technique, which is recognizedon Machine Learning (ML) algorithm. It is used to classifythe individual articlein a knownofinformation into a set of predefinemodules or group. Web mining is also a portion of that sympathetic of data mining methods. The main purpose of this paper to analysis and compare the performance of Naïve Bayse Algorithm, Decision Tree, K-Nearest Neighbor (KNN), Artificial Neural Network (ANN)and Support Vector Machine (SVM). This paper consists of different ML algorithm and their advantages and disadvantages and also define research issues.

Keywords: Data Mining, Web Mining, classification, ML Algorithms

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Authors: Sourav Biswas, Goutam Prasanna Kar, Suryasarathi Bose

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In order to obtain better materials, control in the precise location of nanoparticles is indispensable. It was shown here that ordered arrangement of nanoparticles, possessing different characteristics (electrical/magnetic dipoles), in the blend structure can result in excellent microwave absorption. This is manifested from a high reflection loss of ca. -67 dB for the best blend structure designed here. To attenuate electromagnetic radiations, the key parameters i.e. high electrical conductivity and large dielectric/magnetic loss are targeted here using a conducting inclusion [multiwall carbon nanotubes, MWNTs]; ferroelectric nanostructured material with associated relaxations in the GHz frequency [barium titanate, BT]; and a loss ferromagnetic nanoparticles [nickel ferrite, NF]. In this study, bi-continuous structures were designed using 50/50 (by wt) blends of polycarbonate (PC) and polyvinylidene fluoride (PVDF). The MWNTs was modified using an electron acceptor molecule; a derivative of perylenediimide, which facilitates π-π stacking with the nanotubes and stimulates efficient charge transport in the blends. The nanoscopic materials have specific affinity towards the PVDF phase. Hence, by introducing surface-active groups, ordered arrangement can be tailored. To accomplish this, both BT and NF was first hydroxylated followed by introducing amine-terminal groups on the surface. The latter facilitated in nucleophilic substitution reaction with PC and resulted in their precise location. In this study, we have shown for the first time that by compartmentalized approach, superior EM attenuation can be achieved. For instance, when the nanoparticles were localized exclusively in the PVDF phase or in both the phases, the minimum reflection loss was ca. -18 dB (for MWNT/BT mixture) and -29 dB (for MWNT/NF mixture), and the shielding was primarily through reflection. Interestingly, by adopting the compartmentalized approach where in, the lossy materials were in the PC phase and the conducting inclusion (MWNT) in PVDF, an outstanding reflection loss of ca. -57 dB (for BT and MWNT combination) and -67 dB (for NF and MWNT combination) was noted and the shielding was primarily through absorption. Thus, the approach demonstrates that nanoscopic structuring in the blends can be achieved under macroscopic processing conditions and this strategy can further be explored to design microwave absorbers.

Keywords: barium titanate, EMI shielding, MWNTs, nickel ferrite

Procedia PDF Downloads 447

Authors: Kriddikorn Kaewwongsri, Nikom Suvonvorn

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In the deep south of Thailand, checkpoints for people verification are necessary for the security management of risk zones, such as official buildings in the conflict area. In this paper, we propose an automatic checkpoint system that verifies persons using information from ID cards and facial features. The methods for a person’s information abstraction and verification are introduced based on useful information such as ID number and name, extracted from official cards, and facial images from videos. The proposed system shows promising results and has a real impact on the local society.

Keywords: face comparison, card recognition, OCR, checkpoint system, authentication

Procedia PDF Downloads 321

Authors: Emanuel Teixeira, Anderson Ramos, Marisa Lourenço, Fernando J. Velez, Jon M. Peha

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This article discusses the benefit cost analysis aspects of millimetre wavebands (mmWaves) and Super High Frequency (SHF). The devaluation along the distance of the carrier-to-noise-plus-interference ratio with the coverage distance is assessed by considering two different path loss models, the two-slope urban micro Line-of-Sight (UMiLoS) for the SHF band and the modified Friis propagation model, for frequencies above 24 GHz. The equivalent supported throughput is estimated at the 5.62, 28, 38, 60 and 73 GHz frequency bands and the influence of carrier-to-noise-plus-interference ratio in the radio and network optimization process is explored. Mostly owing to the lessening caused by the behaviour of the two-slope propagation model for SHF band, the supported throughput at this band is higher than at the millimetre wavebands only for the longest cell lengths. The benefit cost analysis of these pico-cellular networks was analysed for regular cellular topologies, by considering the unlicensed spectrum. For shortest distances, we can distinguish an optimal of the revenue in percentage terms for values of the cell length, R ≈ 10 m for the millimeter wavebands and for longest distances an optimal of the revenue can be observed at R ≈ 550 m for the 5.62 GHz. It is possible to observe that, for the 5.62 GHz band, the profit is slightly inferior than for millimetre wavebands, for the shortest Rs, and starts to increase for cell lengths approximately equal to the ratio between the break-point distance and the co-channel reuse factor, achieving a maximum for values of R approximately equal to 550 m.

Keywords: millimetre wavebands, SHF band, SINR, cost benefit analysis, 5G

Procedia PDF Downloads 141

Authors: Wedad Albalawi

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The mathematical inequalities have been the core of mathematical study and used in almost all branches of mathematics as well in various areas of science and engineering. The inequalities by Hardy, Littlewood and Polya were the first significant composition of several science. This work presents fundamental ideas, results and techniques, and it has had much influence on research in various branches of analysis. Since 1934, various inequalities have been produced and studied in the literature. Furthermore, some inequalities have been formulated by some operators; in 1989, weighted Hardy inequalities have been obtained for integration operators. Then, they obtained weighted estimates for Steklov operators that were used in the solution of the Cauchy problem for the wave equation. They were improved upon in 2011 to include the boundedness of integral operators from the weighted Sobolev space to the weighted Lebesgue space. Some inequalities have been demonstrated and improved using the Hardy–Steklov operator. Recently, a lot of integral inequalities have been improved by differential operators. Hardy inequality has been one of the tools that is used to consider integrity solutions of differential equations. Then, dynamic inequalities of Hardy and Coposon have been extended and improved by various integral operators. These inequalities would be interesting to apply in different fields of mathematics (functional spaces, partial differential equations, mathematical modeling). Some inequalities have been appeared involving Copson and Hardy inequalities on time scales to obtain new special version of them. A time scale is an arbitrary nonempty closed subset of the real numbers. Then, the dynamic inequalities on time scales have received a lot of attention in the literature and has become a major field in pure and applied mathematics. There are many applications of dynamic equations on time scales to quantum mechanics, electrical engineering, neural networks, heat transfer, combinatorics, and population dynamics. This study focuses on Hardy and Coposon inequalities, using Steklov operator on time scale in double integrals to obtain special cases of time-scale inequalities of Hardy and Copson on high dimensions. The advantage of this study is that it uses the one-dimensional classical Hardy inequality to obtain higher dimensional on time scale versions that will be applied in the solution of the Cauchy problem for the wave equation. In addition, the obtained inequalities have various applications involving discontinuous domains such as bug populations, phytoremediation of metals, wound healing, maximization problems. The proof can be done by introducing restriction on the operator in several cases. The concepts in time scale version such as time scales calculus will be used that allows to unify and extend many problems from the theories of differential and of difference equations. In addition, using chain rule, and some properties of multiple integrals on time scales, some theorems of Fubini and the inequality of H¨older.

Keywords: time scales, inequality of hardy, inequality of coposon, steklov operator

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Authors: Monica Plechero

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Many firms belonging to Italian industrial districts faced a crisis starting from 2000 and upsurging during 2008-2014. To remain competitive in the global market, these firms and their local systems need to renovate their traditional competitive advantages, strengthen their link with global flows of knowledge. This may be particularly relevant in sectors such as the mechatronics, that combine traditional knowledge domain with new knowledge domains (e.g. mechanics, electronics, and informatics). This sector is nowadays one of the key sectors within the so-called ‘smart specialization strategy’ that can lead part of the Italian traditional industry towards new economic developmental opportunities. This paper, by investigating the mechatronics district of the Veneto region, wants to shed new light on how firms of a local system can gain from the globalization of innovation and innovation networks. Methodologically, the paper relies on primary data collected through a survey targeting firms of the local system, as well as on a number of qualitative case studies. The relevant role of medium size companies in the district emerges as evident, as they have wider opportunities to be involved in different processes of globalization of innovation. Indeed, with respect to small companies, the size of medium firms allows them to exploit strategically international markets and globally distributed knowledge. Supporting medium firms’ global innovation strategies, and incentivizing their role as district gatekeepers, may strengthen the competitive capability of the local system and provide new opportunities to positively face global competition.

Keywords: global innovation network, industrial district, internationalization, innovation, mechatronics, Veneto region

Procedia PDF Downloads 230

Authors: R. Geetha, J. Arunkumar, P. Gopal, D. Loganathan, K. Pavithra, C. Vikashini

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Mobile Number Portability is an attempt to switch over from one network to another network facility for mobile based on applications. This facility is currently not available for mobile handsets. This application is intended to assist the mobile network and its service customers in understanding the criteria; this will serve as a universal set of requirements which must be met by the customers. This application helps the user's network portability. Accessing permission from the network provider to enable services to the user and utilizing the available network signals. It is enabling the user to make a temporary switch over to other network. The main aim of this research work is to adapt multiple networks at the time of no network coverage. It can be accessed at rural and geographical areas. This can be achieved by this mobile application. The application is capable of temporary switch over between various networks. With this application both the service provider and the network user are benefited. The service provider is benefited by charging a minimum cost for utilizing other network. It provides security in terms of password that is unique to avoid unauthorized users and to prevent loss of balance. The goal intended to be attained is a complete utilization of available network at significant situations and to provide feature that satisfy the customer needs. The temporary switch over is done to manage emergency calls when user is in rural or geographical area, where there will be a very low network coverage. Since people find it trend in using Android mobile, this application is designed as an Android applications, which can be freely downloaded and installed from Play store. In the current scenario, the service provider enables the user to change their network without shifting their mobile network. This application affords a clarification for users while they are jammed in a critical situation. This application is designed by using Android 4.2 and SQLite Version3.

Keywords: mobile number, random number, alarm, imei number, call

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Authors: Gunasekaran Raja, Ramkumar Jayaraman

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In this paper, we consider CCL-N (Cooperative Cross Layer Network) topology based on the cross layer (both centralized and distributed) environment to form network communities. Various performance metrics related to the IEEE 802.16 networks are discussed to design CCL-N Topology. In CCL-N topology, nodes are classified as master nodes (Master Base Station [MBS]) and serving nodes (Relay Station [RS]). Nodes communities are organized based on the networking terminologies. Based on CCL-N Topology, various simulation analyses for both transparent and non-transparent relays are tabulated and throughput efficiency is calculated. Weighted load balancing problem plays a challenging role in IEEE 802.16 network. CoTS (Concurrent Transmission Scheduling) Scheme is formulated in terms of three aspects – transmission mechanism based on identical communities, different communities and identical node communities. CoTS scheme helps in identifying the weighted load balancing problem. Based on the analytical results, modularity value is inversely proportional to that of the error value. The modularity value plays a key role in solving the CoTS problem based on hop count. The transmission mechanism for identical node community has no impact since modularity value is same for all the network groups. In this paper three aspects of communities based on the modularity value which helps in solving the problem of weighted load balancing and CoTS are discussed.

Keywords: cross layer network topology, concurrent scheduling, modularity value, network communities and weighted load balancing

Procedia PDF Downloads 265

Authors: Martin Pellon Consunji

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Due to the rise in popularity of Bitcoin and other crypto assets as a store of wealth and speculative investment, there is an ever-growing demand for automated trading tools, such as bots, in order to gain an advantage over the market. Traditionally, trading in the stock market was done by professionals with years of training who understood patterns and exploited market opportunities in order to gain a profit. However, nowadays a larger portion of market participants are at minimum aided by market-data processing bots, which can generally generate more stable signals than the average human trader. The rise in trading bot usage can be accredited to the inherent advantages that bots have over humans in terms of processing large amounts of data, lack of emotions of fear or greed, and predicting market prices using past data and artificial intelligence, hence a growing number of approaches have been brought forward to tackle this task. However, the general limitation of these approaches can still be broken down to the fact that limited historical data doesn’t always determine the future, and that a lot of market participants are still human emotion-driven traders. Moreover, developing markets such as those of the cryptocurrency space have even less historical data to interpret than most other well-established markets. Due to this, some human traders have gone back to the tried-and-tested traditional technical analysis tools for exploiting market patterns and simplifying the broader spectrum of data that is involved in making market predictions. This paper proposes a method which uses neuro evolution techniques on both sentimental data and, the more traditionally human-consumed, technical analysis data in order to gain a more accurate forecast of future market behavior and account for the way both automated bots and human traders affect the market prices of Bitcoin and other cryptocurrencies. This study’s approach uses evolutionary algorithms to automatically develop increasingly improved populations of bots which, by using the latest inflows of market analysis and sentimental data, evolve to efficiently predict future market price movements. The effectiveness of the approach is validated by testing the system in a simulated historical trading scenario, a real Bitcoin market live trading scenario, and testing its robustness in other cryptocurrency and stock market scenarios. Experimental results during a 30-day period show that this method outperformed the buy and hold strategy by over 260% in terms of net profits, even when taking into consideration standard trading fees.

Keywords: neuro-evolution, Bitcoin, trading bots, artificial neural networks, technical analysis, evolutionary algorithms

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Authors: Demet Ozgur-Unluakin, Busenur Turkali, Ayse Karacaorenli

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Maintenance strategies can be classified into two types, which are reactive and proactive, with respect to the time of the failure and maintenance. If the maintenance activity is done after a breakdown, it is called reactive maintenance. On the other hand, proactive maintenance, which is further divided as preventive and predictive, focuses on maintaining components before a failure occurs to prevent expensive halts. Recently, the number of interacting components in a system has increased rapidly and therefore, the structure of the systems have become more complex. This situation has made it difficult to provide the right maintenance decisions. Herewith, determining effective decisions has played a significant role. In multi-component systems, many methodologies and strategies can be applied when a component or a system has already broken down or when it is desired to identify and avoid proactively defects that could lead to future failure. This study focuses on the comparison of various maintenance strategies on a multi-component dynamic system. Components in the system are hidden, although there exists partial observability to the decision maker and they deteriorate in time. Several predefined policies under corrective, preventive and predictive maintenance strategies are considered to minimize the total maintenance cost in a planning horizon. The policies are simulated via Dynamic Bayesian Networks on a multi-component system with different policy parameters and cost scenarios, and their performances are evaluated. Results show that when the difference between the corrective and proactive maintenance cost is low, none of the proactive maintenance policies is significantly better than the corrective maintenance. However, when the difference is increased, at least one policy parameter for each proactive maintenance strategy gives significantly lower cost than the corrective maintenance.

Keywords: decision making, dynamic Bayesian networks, maintenance, multi-component systems, reliability

Procedia PDF Downloads 129

Authors: Johannes Dregger, Michael Schmidt, Christian Prasse, Michael ten Hompel

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Most of the today’s companies face increasing need to operate efficiently. Driven by global trends like shorter product cycles, mass customization and the rising speed of delivery, manufacturing value chains are becoming more and more distributed. Manufacturing processes are becoming highly integrated, e.g. 3D printing. All these changes are affecting companies´ organization. They are leading towards individual, small scale, and ad-hoc logistics processes and structures, and finally, towards a significant increase in the importance of logistics itself since traditional value chains transform into agile value networks. In the past logistics has been following manufacturing but in the future industry, this role allocation might change. With this increase in the logistics practice of companies and businesses, the relevance of logistics research as the methodological foundation of logistics networks and processes is gaining importance. Logistics research is evolving into a central and highly interdisciplinary science for the future industry. Using the example of Germany, this paper discusses ways to establish logistics as a central scientific discipline of the future industry. About three million people work in the logistics sector in Germany. Only automotive and retail industry have more employees. Even though there is a bunch of logistics degree programs at more than 100 institutions of higher education, a common understanding of logistics as a research discipline is missing. In this paper an innovative approach will be presented, including; identified perspectives on logistics, such as process orientation, IT orientation or employees orientation, relevant scientific disciplines for logistics science, a concept for interdisciplinary research approaches to unify the perspectives of the different scientific disciplines on logistics and the methodological base of logistics science.

Keywords: logistics, logistics science, logistics management, future challenges

Procedia PDF Downloads 314

Authors: Alaa Allakany, Koji Okamura

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Multicast technology is an efficient and scalable technology for data distribution in order to optimize network resources. However, in the IP network, the responsibility for management of multicast groups is distributed among network routers, which causes some limitations such as delays in processing group events, high bandwidth consumption and redundant tree calculation. Software Defined Networking (SDN) represented by OpenFlow presented as a solution for many problems, in SDN the control plane and data plane are separated by shifting the control and management to a remote centralized controller, and the routers are used as a forwarder only. In this paper we will proposed fast switching mechanism for solving the problem of link failure in multicast tree based on Tabu Search heuristic algorithm and modifying the functions of OpenFlow switch to fasts switch to the pack up sub tree rather than sending to the controller. In this work we will implement multicasting OpenFlow controller, this centralized controller is a core part in our multicasting approach, which is responsible for 1- constructing the multicast tree, 2- handling the multicast group events and multicast state maintenance. And finally modifying OpenFlow switch functions for fasts switch to pack up paths. Forwarders, forward the multicast packet based on multicast routing entries which were generated by the centralized controller. Tabu search will be used as heuristic algorithm for construction near optimum multicast tree and maintain multicast tree to still near optimum in case of join or leave any members from multicast group (group events).

Keywords: multicast tree, software define networks, tabu search, OpenFlow

Procedia PDF Downloads 263

Authors: Brahim Bellali, Fatima Bellali

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The integration of information technology systems (ITS) into a company's human resources processes seems to be the appropriate solution to the problem of evolving and adapting its human resources management practices in order to be both more strategic and more efficient in terms of costs and service quality. In this context, the aim of this work is to study the impact of information technology systems (ITS) on the recruitment process. In this study, we targeted candidates who had recruited using IT tools. The target population consists of 34 candidates based in Casablanca, Morocco. In order to collect the data, a questionnaire had to be drawn up. The survey is based on a data sheet and a questionnaire that is divided into several sections to make it more structured and comprehensible. The results show that the majority of respondents say that companies are making greater use of online CV libraries and social networks as digital solutions during the recruitment process. The results also show that 50% of candidates say that the use of digital tools by companies would not slow them down when applying for a job and that these IT tools improve manual recruitment processes, while 44.1% think that they facilitate recruitment without any human intervention. The majority of respondents (52.9%) think that social networks are the digital solutions most often used by recruiters in the sourcing phase. The constraints of digital recruitment encountered are the dehumanization of human resources (44.1%) and the limited interaction during remote interviews (44.1%), which leaves no room for informal exchanges. Digital recruitment can be a highly effective strategy for finding qualified candidates in a variety of fields. Here are a few recommendations for optimizing your digital recruitment process: (1) Use online recruitment platforms: LinkedIn, Twitter, and Facebook ; (2) Use applicant tracking systems (ATS) ; (3) Develop a content marketing strategy.

Keywords: IT systems, recruitment, challenges, constraints

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Authors: Mahmood Niroobakhsh

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This article deals with special structuralism approaches to explain a certain kind of social problem. Widespread presence of poverty is a reminder of deep-rooted unresolved problems of social relations. The expected role from an individual for the social system recognizes poverty derived from an interrelated social structure. By the time, enabled to act on his role in the course of social interaction, reintegration of the poor in society may take place. Poverty and housing type are reflections of the underlying social structure, primarily structure’s elements, systemic interrelations, and the overall strength or weakness of that structure. Poverty varies based on social structure in that the stronger structures are less likely to produce poverty.

Keywords: absolute poverty, relative poverty, social structure, urban poverty

Procedia PDF Downloads 679

Authors: Chapman Eze Nnadozie

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Cloud computing, a technology that is made possible through virtualization within networks represents a shift from the traditional ownership of infrastructure and other resources by distinct organization to a more scalable pattern in which computer resources are rented online to organizations on either as a pay-as-you-use basis or by subscription. In other words, cloud computing entails the renting of computing resources (such as storage space, memory, servers, applications, networks, etc.) by a third party to its clients on a pay-as-go basis. It is a new innovative technology that is globally embraced because of its renowned benefits, profound of which is its cost effectiveness on the part of organizations engaged with its services. In Nigeria, the services are provided either directly to companies mostly by the key IT players such as Microsoft, IBM, and Google; or in partnership with some other players such as Infoware, Descasio, and Sunnet. This action enables organizations to rent IT resources on a pay-as-you-go basis thereby salvaging them from wastages accruable on acquisition and maintenance of IT resources such as ownership of a separate data centre. This paper intends to appraise the challenges of cloud computing adoption in Nigeria, bearing in mind the country’s peculiarities’ in terms of infrastructural development. The methodologies used in this paper include the use of research questionnaires, formulated hypothesis, and the testing of the formulated hypothesis. The major findings of this paper include the fact that there are some addressable challenges to the adoption of cloud computing in Nigeria. Furthermore, the country will gain significantly if the challenges especially in the area of infrastructural development are well addressed. This is because the research established the fact that there are significant gains derivable by the adoption of cloud computing by organizations in Nigeria. However, these challenges can be overturned by concerted efforts in the part of government and other stakeholders.

Keywords: cloud computing, data centre, infrastructure, it resources, virtualization

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Authors: Amitkumar R. Shelar, B. P. Ronge, Sridevi Seshabhattar, R. M. Wabale

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This paper gives knowledge about the behavior of cold rolled steel IS 513_2008 CR2_D having grade D for the reduction of ductile damage. CR specifies Cold Rolled and D for Drawing grade. Problems encountered during sheet metal forming operations are dent, wrinkles, thinning, spring back, insufficient stretching etc. In this paper, wrinkle defect was studied experimentally and by using FE software on one of the auto components due to which its functionality was decreased. Experimental result and simulation result were found to be in agreement.

Keywords: deep drawing, FE software-LS DYNA, friction, wrinkling

Procedia PDF Downloads 488

Authors: Fatima Al-Aswadi, Chan Yong

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With the large volume of unstructured data that increases day by day on the web, the motivation of representing the knowledge in this data in the machine processable form is increased. Ontology is one of the major cornerstones of representing the information in a more meaningful way on the semantic Web. The goal of Ontology learning from text is to elicit and represent domain knowledge in the machine readable form. This paper aims to give a follow-up review on the ontology learning systems from text and some of their defects. Furthermore, it discusses how far the ontology learning process will enhance in the future.

Keywords: concept discovery, deep learning, ontology learning, semantic relation, semantic web

Procedia PDF Downloads 523

Authors: A. Anastasopoulou, A. Kolios, T. Somorin, A. Sowale, Y. Jiang, B. Fidalgo, A. Parker, L. Williams, M. Collins, E. J. McAdam, S. Tyrrel

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Developing countries are nowadays confronted with great challenges related to domestic sanitation services in view of the imminent water scarcity. Contemporary sanitation technologies established in these countries are likely to pose health risks unless waste management standards are followed properly. This paper provides a solution to sustainable sanitation with the development of an innovative toilet system, called Nano Membrane Toilet (NMT), which has been developed by Cranfield University and sponsored by the Bill & Melinda Gates Foundation. The particular technology converts human faeces into energy through gasification and provides treated wastewater from urine through membrane filtration. In order to evaluate the environmental profile of the NMT system, a deterministic life cycle assessment (LCA) has been conducted in SimaPro software employing the Ecoinvent v3.3 database. The particular study has determined the most contributory factors to the environmental footprint of the NMT system. However, as sensitivity analysis has identified certain critical operating parameters for the robustness of the LCA results, adopting a stochastic approach to the Life Cycle Inventory (LCI) will comprehensively capture the input data uncertainty and enhance the credibility of the LCA outcome. For that purpose, Monte Carlo simulations, in combination with an artificial neural network (ANN) model, have been conducted for the input parameters of raw material, produced electricity, NO_X emissions, amount of ash and transportation of fertilizer. The given analysis has provided the distribution and the confidence intervals of the selected impact categories and, in turn, more credible conclusions are drawn on the respective LCIA (Life Cycle Impact Assessment) profile of NMT system. Last but not least, the specific study will also yield essential insights into the methodological framework that can be adopted in the environmental impact assessment of other complex engineering systems subject to a high level of input data uncertainty.

Keywords: sanitation systems, nano-membrane toilet, lca, stochastic uncertainty analysis, Monte Carlo simulations, artificial neural network

Procedia PDF Downloads 225

Authors: Yasin Tadayonrad

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Most of the supply chain networks have many nodes starting from the suppliers’ side up to the customers’ side that each node sends/receives the raw materials/products from/to the other nodes. One of the major concerns in this kind of supply chain network is finding the best schedule for loading /unloading the shipments through the whole network by which all the constraints in the source and destination nodes are met and all the shipments are delivered on time. One of the main constraints in this problem is loading/unloading capacity in each source/ destination node at each time slot (e.g., per week/day/hour). Because of the different characteristics of different products/groups of products, the capacity of each node might differ based on each group of products. In most supply chain networks (especially in the Fast-moving consumer goods industry), there are different planners/planning teams working separately in different nodes to determine the loading/unloading timeslots in source/destination nodes to send/receive the shipments. In this paper, a mathematical problem has been proposed to find the best timeslots for loading/unloading the shipments minimizing the overall delays subject to respecting the capacity of loading/unloading of each node, the required delivery date of each shipment (considering the lead-times), and working-days of each node. This model was implemented on python and solved using Python-MIP on a sample data set. Finally, the idea of a heuristic algorithm has been proposed as a way of improving the solution method that helps to implement the model on larger data sets in real business cases, including more nodes and shipments.

Keywords: supply chain management, transportation, multiple-multiple network, timeslots management, mathematical modeling, mixed integer programming

Procedia PDF Downloads 91

Authors: Himanshu Sharma, Karthik Kumar, Harish Kumar

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The major problem in crop cultivation is the occurrence of multiple crop diseases. During the growth stage, timely identification of crop diseases is paramount to ensure the high yield of crops, lower production costs, and minimize pesticide usage. In most cases, crop diseases produce observable characteristics and symptoms. The Surveyors usually diagnose crop diseases when they walk through the fields. However, surveyor inspections tend to be biased and error-prone due to the nature of the monotonous task and the subjectivity of individuals. In addition, visual inspection of each leaf or plant is costly, time-consuming, and labour-intensive. Furthermore, the plant pathologists and experts who can often identify the disease within the plant according to their symptoms in early stages are not readily available in remote regions. Therefore, this study specifically addressed early detection of leaf scald, red rot, and eyespot types of diseases within sugarcane plants. The study proposes a computer vision-based approach using a convolutional neural network (CNN) for automatic identification of crop diseases. To facilitate this, firstly, images of sugarcane diseases were taken from google without modifying the scene, background, or controlling the illumination to build the training dataset. Then, the testing dataset was developed based on the real-time collected images from the sugarcane field from India. Then, the image dataset is pre-processed for feature extraction and selection. Finally, the CNN-based Visual Geometry Group (VGG) model was deployed on the training and testing dataset to classify the images into diseased and healthy sugarcane plants and measure the model's performance using various parameters, i.e., accuracy, sensitivity, specificity, and F1-score. The promising result of the proposed model lays the groundwork for the automatic early detection of sugarcane disease. The proposed research directly sustains an increase in crop yield.

Keywords: automatic classification, computer vision, convolutional neural network, image processing, sugarcane disease, visual geometry group

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Authors: Raúl García de la Cruz

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In the state of Hidalgo and to the vicinity to the state of Mexico, there is a network of people who also share a valley bordered by hills with agave landscape of cacti and shared a bond of building traditions inherited from pre-Hispanic times and according to their material resources, habits and needs have been adapted in time. Weather has played an important role in the way buildings and roofs are constructed. Throughout the centuries, the population has developed very sophisticated building techniques like the flat roof, made out of a layer of earth; that is usually identified as belonging to architecture of the desert, but it can also be found in other climates, such as semi-arid and even template climates. It is an example of a constructive logic applied efficiently to various cultures proving its thermal isolation. So far it has done a review and analysis of the use of the roof in different areas, from pre-Hispanic architecture to traditional Moroccan architecture , finding great similarities in the elements of the system to be incorporated into the contemporary architecture. The rescue of a lore that dissolves with the changing environment, depends in principle on the links created towards the use of environmental resources as the anchor of the people to retain and preserve a building tradition which has viability deep league with the possibility of obtaining the raw material from the immediate environment. The objective of the research is the documentation of existing earth flat roofs in the state of Hidalgo and Mexico, as evidence of the importance of constructive system and its historical value in the area, considering its environmental, social aspects, also understanding the process of transformation of public housing at the time replaced the traditional techniques for industrial materials on a path towards urbanization. So far it has done a review and analysis of the use of the roof in different areas, from pre-Hispanic architecture to traditional Moroccan architecture, finding great similarities in the elements of the system to be incorporated into the contemporary architecture. The rescue of a lore that dissolves with the changing environment, depends in principle on the links created towards the use of environmental resources as the anchor of the people to retain and preserve a building tradition which has viability deep league with the possibility of obtaining the raw material from the immediate environment.

Keywords: earth roof, low impact building system, sustainable architecture, vernacular architecture

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Authors: Joseph Fitoussi, Mohammadali Shirinbayan, Abbas Tcharkhtchi

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Due to material flow during processing, short fiber reinforced composites structures obtained by injection or compression molding generally present strong spatial microstructure variation. On the other hand, quasi-static, dynamic, and fatigue behavior of these materials are highly dependent on microstructure parameters such as fiber orientation distribution. Indeed, because of complex damage mechanisms, SFRC structures design is a key challenge for safety and reliability. In this paper, we propose a micromechanical model allowing prediction of damage behavior of real structures as a function of microstructure spatial distribution. To this aim, a statistical damage criterion including strain rate and fatigue effect at the local scale is introduced into a Mori and Tanaka model. A critical local damage state is identified, allowing fatigue life prediction. Moreover, the multi-scale model is coupled with an experimental intrinsic link between damage under monotonic loading and fatigue life in order to build an abacus giving Tsai-Wu failure criterion parameters as a function of microstructure and targeted fatigue life. On the other hand, the micromechanical damage model gives access to the evolution of the anisotropic stiffness tensor of SFRC submitted to complex thermomechanical loading, including quasi-static, dynamic, and cyclic loading with temperature and amplitude variations. Then, the latter is used to fill out microstructure dependent material cards in finite element analysis for design optimization in the case of complex loading history. The proposed methodology is illustrated in the case of a real automotive component made of sheet molding compound (PSA 3008 tailgate). The obtained results emphasize how the proposed micromechanical methodology opens a new path for the automotive industry to lighten vehicle bodies and thereby save energy and reduce gas emission.

Keywords: short fiber reinforced composite, structural design, damage, micromechanical modelling, fatigue, strain rate effect

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Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

Abstract:

Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

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Authors: Brahim Bellali, Fatima Bellali

Abstract:

The integration of information technology systems (ITS) into a company's ‘human resources processes seems to be the appropriate solution to the problem of evolving and adapting its human resources management practices in order to be both more strategic and more efficient in terms of costs and service quality. In this context, the aim of this work is to study the impact of information technology systems (ITS) on the recruitment process. In this study, we targeted candidates who had recruited using IT tools. The target population consists of 34 candidates based in Casablanca, Morocco. In order to collect the data, a questionnaire had to be drawn up. The survey is based on a data sheet and a questionnaire that is divided into several sections to make it more structured and comprehensible. The results show that the majority of respondents say that companies are making greater use of online CV libraries and social networks as digital solutions during the recruitment process. The results also show that 50% of candidates say that the use of digital tools by companies would not slow them down when applying for a job and that these IT tools improve manual recruitment processes, while 44.1% think that they facilitate recruitment without any human intervention. The majority of respondents (52.9%) think that social networks are the digital solutions most often used by recruiters in the sourcing phase. The constraints of digital recruitment encountered are the dehumanization of human resources (44.1%) and the limited interaction during remote interviews (44.1%), which leaves no room for informal exchanges. Digital recruitment can be a highly effective strategy for finding qualified candidates in a variety of fields. Here are a few recommendations for optimizing your digital recruitment process: (1) Use online recruitment platforms: LinkedIn, Twitter, and Facebook ; (2) Use applicant tracking systems (ATS) ; (3) Develop a content marketing strategy.

Keywords: IT systems, recruitment, challenges, constraints

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Authors: Bellali Brahim, Bellali Fatima

Abstract:

The integration of information technology systems (ITS) into a company's ‘human resources processes seems to be the appropriate solution to the problem of evolving and adapting its human resources management practices in order to be both more strategic and more efficient in terms of costs and service quality. In this context, the aim of this work is to study the impact of nformation technology systems (ITS) on the recruitment process. In this study, we targeted candidates who had recruited using IT tools. The target population consists of 34 candidates based in Casablanca, Morocco. In order to collect the data, a questionnaire had to be drawn up. The survey is based on a data sheet and a questionnaire that is divided into several sections to make it more structured and comprehensible. The results show that the majority of respondents say that companies are making greater use of online CV libraries and social networks as digital solutions during the recruitment process. The results also show that 50% of candidates say that the use of digital tools by companies would not slow them down when applying for a job and that these IT tools improve manual recruitment processes, while 44.1% think that they facilitate recruitment without any human intervention. The majority of respondents (52.9%) think that social networks are the digital solutions most often used by recruiters in the sourcing phase. The constraints of digital recruitment encountered are the dehumanization of human resources (44.1%) and the limited interaction during remote interviews (44.1%), which leaves no room for informal exchanges. Digital recruitment can be a highly effective strategy for finding qualified candidates in a variety of fields. Here are a few recommendations for optimizing your digital recruitment process: (1) Use online recruitment platforms: LinkedIn, Twitter, and Facebook ; (2) Use applicant tracking systems (ATS) ; (3) Develop a content marketing strategy.

Keywords: IT systems, recruitment, challenges, constraints

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Authors: Jose Daniel Giraldo Arias, Camilo Rojas Gomez, David Villegas Delgado, Gullermo Idarraga Alarcon, Juan Meza Meza

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The reverse engineering processes are widely used in the industry with the main goal to determine the materials and the manufacture used to produce a component. There are a lot of characterization techniques and computational tools that are used in order to get this information. A study case of a reverse engineering applied to a secondary sandwich- hybrid type structure used in a helicopter is presented. The methodology used consists of five main steps, which can be applied to any other similar component: Collect information about the service conditions of the part, disassembly and dimensional characterization, functional characterization, material properties characterization and manufacturing processes characterization, allowing to obtain all the supports of the traceability of the materials and processes of the aeronautical products that ensure their airworthiness. A detailed explanation of each step is covered. Criticality and comprehend the functionalities of each part, information of the state of the art and information obtained from interviews with the technical groups of the helicopter’s operators were analyzed,3D optical scanning technique, standard and advanced materials characterization techniques and finite element simulation allow to obtain all the characteristics of the materials used in the manufacture of the component. It was found that most of the materials are quite common in the aeronautical industry, including Kevlar, carbon, and glass fibers, aluminum honeycomb core, epoxy resin and epoxy adhesive. The stacking sequence and volumetric fiber fraction are a critical issue for the mechanical behavior; a digestion acid method was used for this purpose. This also helps in the determination of the manufacture technique which for this case was Vacuum Bagging. Samples of the material were manufactured and submitted to mechanical and environmental tests. These results were compared with those obtained during reverse engineering, which allows concluding that the materials and manufacture were correctly determined. Tooling for the manufacture was designed and manufactured according to the geometry and manufacture process requisites. The part was manufactured and the mechanical, and environmental tests required were also performed. Finally, a geometric characterization and non-destructive techniques allow verifying the quality of the part.

Keywords: reverse engineering, sandwich-structured composite parts, helicopter, mechanical properties, prototype

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Authors: D. Y. Fong, C. Y. Kuo, Y. T. Chiang, W. C. Lin

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Objectives: Qigong is an ancient Chinese practice in pursuit of a healthier body and a more peaceful mindset. It emphasizes on the restoration of vital energy (Qi) in body, mind, and spirit. The practice is the combination of gentle movements and mild breathing which help the doers reach the condition of tranquility. On account of the features of Qigong, first, we use cross-sectional methodology to compare the differences among the varied levels of Qigong practitioners on cognitive function with event-related potential (ERP) and electroencephalography (EEG). Second, we use the longitudinal methodology to explore the effects on the Qigong trainees for pretest and posttest on ERP and EEG. Current study adopts Attentional Network Test (ANT) task to examine the participants’ cognitive function, and aging-related researches demonstrated a declined tread on the cognition in older adults and exercise might ameliorate the deterioration. Qigong exercise integrates physical posture (muscle strength), breathing technique (aerobic ability) and focused intention (attention) that researchers hypothesize it might improve the cognitive function in aging adults. Method: Sixty participants were involved in this study, including 20 young adults (21.65±2.41 y) with normal physical activity (YA), 20 Qigong experts (60.69 ± 12.42 y) with over 7 years Qigong practice experience (QE), and 20 normal and healthy adults (52.90±12.37 y) with no Qigong practice experience as experimental group (EG). The EG participants took Qigong classes 2 times a week and 2 hours per time for 24 weeks with the purpose of examining the effect of Qigong intervention on cognitive function. ANT tasks (alert network, orient network, and executive control) were adopted to evaluate participants’ cognitive function via ERP’s P300 components and P300 amplitude topography. Results: Behavioral data: 1.The reaction time (RT) of YA is faster than the other two groups, and EG was faster than QE in the cue and flanker conditions of ANT task. 2. The RT of posttest was faster than pretest in EG in the cue and flanker conditions. 3. No difference among the three groups on orient, alert, and execute control networks. ERP data: 1. P300 amplitude detection in QE was larger than EG at Fz electrode in orient, alert, and execute control networks. 2. P300 amplitude in EG was larger at pretest than posttest on the orient network. 3. P300 Latency revealed no difference among the three groups in the three networks. Conclusion: Taken together these findings, they provide neuro-electrical evidence that older adults involved in Qigong practice may develop a more overall compensatory mechanism and also benefit the performance of behavior.

Keywords: Qigong, cognitive function, aging, event-related potential (ERP)

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Authors: Nur Bella Octoria Bella, Ayomi Dita Rarasati

Abstract:

DKI Jakarta is Indonesia's capital city with the 10th highest congestion rate in the world based on the 2019 traffic index. Other than that based on World Air Quality Report in 2019 showed DKI Jakarta's air pollutant concentrate 49.4 µg and the 5th highest air pollutant in the world. In the urban city nowadays, the mobility rate is high enough and the efficiency for sustainability assessment in transport infrastructure development is needed. This efficiency is the important key for sustainable infrastructure development. DKI Jakarta is nowadays in the process of constructing the railway infrastructure to support the transportation system. The problems appearing are the railway infrastructure networks and the service in DKI Jakarta already planned based on sustainability factors or not. Therefore, the aim of this research is to make the evaluation of railways infrastructure networks performance and services in DKI Jakarta regards on the railway sustainability key factors. Further, this evaluation will be used to make the railway sustainability assessment framework and to offer some of the alternative solutions to improve railway transportation sustainability in DKI Jakarta. Firstly a very detailed literature review of papers that have focused on railway sustainability factors and their improvements of railway sustainability, published in the scientific journal in the period 2011 until 2021. Regarding the sustainability factors from the literature review, further, it is used to assess the current condition of railway infrastructure in DKI Jakarta. The evaluation will be using a Likert rate questionnaire and directed to the transportation railway expert and the passenger. Furthermore, the mapping and evaluation rate based on the sustainability factors will be compared to the effect factors using the Analytical Hierarchical Process (AHP). This research offers the network's performance and service rate impact on the sustainability aspect and the passenger willingness for using the rail public transportation in DKI Jakarta.

Keywords: transportation sustainability, railway transportation, sustainability, DKI Jakarta

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Authors: Ahmad Lutfi, Nikolas Dhega

Abstract:

The Malala deposit in northwest Sulawesi is the only known porphyry molybdenum and the only source for rhenium, occurrence in Indonesia. The neural network method produces results that correspond very closely to those of the knowledge-based fuzzy logic method and weights of evidence method. This method required data of solid geology, regional faults, airborne magnetic, gamma-ray survey data and GIS data. This interpretation of the network output fits with the intuitive notion that a prospective area has characteristics that closely resemble areas known to contain mineral deposits. Contrasts with the weights of evidence and fuzzy logic methods, where, for a given grid location, each input-parameter value automatically results in an increase in the prospective estimated. Malala District indicated molybdenum anomalies in stream sediments from in excess of 15 km2 were obtained, including the Takudan Fault as most prominent structure with striking 40̊ to 60̊ over a distance of about 30 km and in most places weakly at anomaly B, developed over an area of 4 km2, with a ‘shell’ up to 50 m thick at the intrusive contact with minor mineralization occurring in the Tinombo Formation. Series of NW trending, steeply dipping fracture zones, named the East Zone has an estimated resource of 100 Mt at 0.14% MoS2 and minimum target of 150 Mt 0.25%. The Malala porphyries occur as stocks and dykes with predominantly granitic, with fluorine-poor class of molybdenum deposits and belongs to the plutonic sub-type. Unidirectional solidification textures consisting of subparallel, crenulated layers of quartz that area separated by layers of intrusive material textures. The deuteric nature of the molybdenum mineralization and the dominance of carbonate alteration.The nature of the Stage I with alteration barren quartz K‐feldspar; and Stage II with alteration quartz‐K‐feldspar‐apatite-molybdenite veins combined with the presence of disseminated molybdenite with primary biotite in the host intrusive.

Keywords: molybdenite, Malala, porphyries, anomaly B

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