Search results for: problem space
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10319

Search results for: problem space

5009 Law, Regulatory Transformations and Evolving Paradigm: The Case of Corporate Social Responsibility in India

Authors: Shuchi Bharti

Abstract:

This article intends to analyse the transforming nature of state and corporate sector relationship in the light of evolving regulatory and institutional aspects pertaining to Corporate Social Responsibility (CSR) in India. The focus is on evaluating the accounts of law and decentred discourses, relevant within the changing regulatory and institutional paradigm that substantially goes ahead of formal legal control of state towards corporate actors. At this vantage point, it is important to understand the state’s posture towards a changing scenario particularly as the tone is set by regulatory parameters pertaining to CSR to drive process of engagement with the stakeholders. The tripartite framework of the article intends to focus on finding on the vital interconnected aspects of the CSR provisions (Section 135) of The Companies Act 2013 (The Act), rise of new institutions and the emergence of the decentred regulatory space. Thus is earmarked in a neo-liberal paradigm; state is witnessed to perform a responsive function in engendering enhanced public role for the corporate sector. In this overarching framework the aim is to undertake a causal, exploratory and relational analysis of aspects pertaining law, regulation and institutional transformations. Firstly, focus is drawn on to investigate the relational facets of the advent of law and regulatory framework of CSR. Secondly, in the light of the historical evolution, a causal connection is attempted between globalization, emergence of international soft law framework and the Indian case of CSR. Finally, I look into how the new Companies Act mandates CSR expenditure vis- a -vis multiple parameters and guidelines.

Keywords: corporate social responsibility, stakeholders, soft law, decentred regulation

Procedia PDF Downloads 290
5008 Low-Cost Embedded Biometric System Based on Fingervein Modality

Authors: Randa Boukhris, Alima Damak, Dorra Sellami

Abstract:

Fingervein biometric authentication is one of the most popular and accurate technologies. However, low cost embedded solution is still an open problem. In this paper, a real-time implementation of fingervein recognition process embedded in Raspberry-Pi has been proposed. The use of Raspberry-Pi reduces overall system cost and size while allowing an easy user interface. Implementation of a target technology has guided to opt some specific parallel and simple processing algorithms. In the proposed system, we use four structural directional kernel elements for filtering finger vein images. Then, a Top-Hat and Bottom-Hat kernel filters are used to enhance the visibility and the appearance of venous images. For feature extraction step, a simple Local Directional Code (LDC) descriptor is applied. The proposed system presents an Error Equal Rate (EER) and Identification Rate (IR), respectively, equal to 0.02 and 98%. Furthermore, experimental results show that real-time operations have good performance.

Keywords: biometric, Bottom-Hat, Fingervein, LDC, Rasberry-Pi, ROI, Top-Hat

Procedia PDF Downloads 193
5007 Optimization Model for Support Decision for Maximizing Production of Mixed Fresh Fruit Farms

Authors: Andrés I. Ávila, Patricia Aros, César San Martín, Elizabeth Kehr, Yovana Leal

Abstract:

Planning models for fresh products is a very useful tool for improving the net profits. To get an efficient supply chain model, several functions should be considered to get a complete simulation of several operational units. We consider a linear programming model to help farmers to decide if it is convenient to choose what area should be planted for three kinds of export fruits considering their future investment. We consider area, investment, water, productivity minimal unit, and harvest restrictions to develop a monthly based model to compute the average income in five years. Also, conditions on the field as area, water availability, and initial investment are required. Using the Chilean costs and dollar-peso exchange rate, we can simulate several scenarios to understand the possible risks associated to this market. Also, this tool help to support decisions for government and individual farmers.

Keywords: mixed integer problem, fresh fruit production, support decision model, agricultural and biosystems engineering

Procedia PDF Downloads 422
5006 Multi-objective Rationality Optimisation for Robotic-fabrication-oriented Free-form Timber Structure Morphology Design

Authors: Yiping Meng, Yiming Sun

Abstract:

The traditional construction industry is unable to meet the requirements for novel fabrication and construction. Automated construction and digital design have emerged as industry development trends that compensate for this shortcoming under the backdrop of Industrial Revolution 4.0. Benefitting from more flexible working space and more various end-effector tools compared to CNC methods, robot fabrication and construction techniques have been used in irregular architectural design. However, there is a lack of a systematic and comprehensive design and optimisation workflow considering geometric form, material, and fabrication methods. This paper aims to propose a design optimisation workflow for improving the rationality of a free-form timber structure fabricated by the robotic arm. Firstly, the free-form surface is described by NURBS, while its structure is calculated using the finite element analysis method. Then, by considering the characteristics and limiting factors of robotic timber fabrication, strain energy and robustness are set as optimisation objectives to optimise structural morphology by gradient descent method. As a result, an optimised structure with axial force as the main force and uniform stress distribution is generated after the structure morphology optimisation process. With the decreased strain energy and the improved robustness, the generated structure's bearing capacity and mechanical properties have been enhanced. The results prove the feasibility and effectiveness of the proposed optimisation workflow for free-form timber structure morphology design.

Keywords: robotic fabrication, free-form timber structure, Multi-objective optimisation, Structural morphology, rational design

Procedia PDF Downloads 181
5005 Optimal Analysis of Structures by Large Wing Panel Using FEM

Authors: Byeong-Sam Kim, Kyeongwoo Park

Abstract:

In this study, induced structural optimization is performed to compare the trade-off between wing weight and induced drag for wing panel extensions, construction of wing panel and winglets. The aerostructural optimization problem consists of parameters with strength condition, and two maneuver conditions using residual stresses in panel production. The results of kinematic motion analysis presented a homogenization based theory for 3D beams and 3D shells for wing panel. This theory uses a kinematic description of the beam based on normalized displacement moments. The displacement of the wing is a significant design consideration as large deflections lead to large stresses and increased fatigue of components cause residual stresses. The stresses in the wing panel are small compared to the yield stress of aluminum alloy. This study describes the implementation of a large wing panel, aerostructural analysis and structural parameters optimization framework that couples a three-dimensional panel method.

Keywords: wing panel, aerostructural optimization, FEM, structural analysis

Procedia PDF Downloads 571
5004 Optimal Placement and Sizing of Distributed Generation in Microgrid for Power Loss Reduction and Voltage Profile Improvement

Authors: Ferinar Moaidi, Mahdi Moaidi

Abstract:

Environmental issues and the ever-increasing in demand of electrical energy make it necessary to have distributed generation (DG) resources in the power system. In this research, in order to realize the goals of reducing losses and improving the voltage profile in a microgrid, the allocation and sizing of DGs have been used. The proposed Genetic Algorithm (GA) is described from the array of artificial intelligence methods for solving the problem. The algorithm is implemented on the IEEE 33 buses network. This study is presented in two scenarios, primarily to illustrate the effect of location and determination of DGs has been done to reduce losses and improve the voltage profile. On the other hand, decisions made with the one-level assumptions of load are not universally accepted for all levels of load. Therefore, in this study, load modelling is performed and the results are presented for multi-levels load state.

Keywords: distributed generation, genetic algorithm, microgrid, load modelling, loss reduction, voltage improvement

Procedia PDF Downloads 135
5003 Fashion, Art and Culture in the Anthropological Management Model

Authors: Lucia Perez, Maria Gaton y Santa Palella

Abstract:

Starting from the etymology of the word culture, the Latin term ‘colere’, whose meaning is to cultivate, we understand that the society that cultivates its knowledge is laying the foundations for new possibilities. In this sense, art and fashion contain the same attributes: concept, aesthetic principles, and refined techniques. Both play a crucial role, communication, and this implies a sense of community, relationship with tradition, and innovation. This is the mirror in which to contemplate, but also the space that helps to grow. This is the framework where our object of study opens up: the anthropological management or the mission management model applied to fashion exhibitions in museums and cultural institutions. For this purpose, a bibliographic review has been carried out with its subsequent analysis, a case study of three successful exhibitions: ‘Christian Dior: designer of dreams’, ‘Balenciaga and the Spanish painting’, and ‘China: Through the Looking Glass’. The methodology has been completed with interviews focused on the curators. Amongst the results obtained, it is worth highlighting the fundamental role of transcendent leadership, which, in addition to being results-oriented, must align the motivations of the collaborators with the mission. The anthropological management model conceives management as a service, and it is oriented to the interests of the staff and the public, in short, of the person; this is what enables the objectives of effectiveness, efficiency, and social value to be achieved; dimensions, all necessary for the proper development of the mission of the exhibitions. Fashion, understood as art, is at the service of culture, and therefore of the human being, which defines a transcendent mission. We conclude that the profile of an anthropological management model applied to fashion exhibitions in museums is the ideal one to achieve the purpose of these institutions.

Keywords: art, culture, fashion, anthropological model, fashion exhibitions

Procedia PDF Downloads 90
5002 A Ratio-Weighted Decision Tree Algorithm for Imbalance Dataset Classification

Authors: Doyin Afolabi, Phillip Adewole, Oladipupo Sennaike

Abstract:

Most well-known classifiers, including the decision tree algorithm, can make predictions on balanced datasets efficiently. However, the decision tree algorithm tends to be biased towards imbalanced datasets because of the skewness of the distribution of such datasets. To overcome this problem, this study proposes a weighted decision tree algorithm that aims to remove the bias toward the majority class and prevents the reduction of majority observations in imbalance datasets classification. The proposed weighted decision tree algorithm was tested on three imbalanced datasets- cancer dataset, german credit dataset, and banknote dataset. The specificity, sensitivity, and accuracy metrics were used to evaluate the performance of the proposed decision tree algorithm on the datasets. The evaluation results show that for some of the weights of our proposed decision tree, the specificity, sensitivity, and accuracy metrics gave better results compared to that of the ID3 decision tree and decision tree induced with minority entropy for all three datasets.

Keywords: data mining, decision tree, classification, imbalance dataset

Procedia PDF Downloads 108
5001 Mechanical Tension Control of Winding Systems for Paper Webs

Authors: Glaoui Hachemi

Abstract:

In this paper, a scheme based on multi-input multi output Fuzzy Sliding Mode control (MIMO-FSMC) for linear speed regulation of winding system is proposed. Once the uncoupled model of the winding system was obtained, a smooth control function with a threshold was selected to indicate how far away the case was from the sliding surface. nevertheless, this control function depends closely on the higher bound of the uncertainties, which generates overlap. So, this size has to be chosen with broad care to obtain high performances. Usually, the upper bound of uncertainties is difficult to know before motor operation, so, a Fuzzy Sliding Mode controller is investigated to resolve this problem, a simple Fuzzy inference mechanism is used to decrease the chattering phenomenon by simple adjustments. A simulation study is achieved and that the indicate fuzzy sliding mode controllers have great potential for use as an alternative to the conventional sliding mode control.

Keywords: Winding system, induction machine, Mechanical tension, Proportional-integral (PI), sliding mode control, Fuzzy logic

Procedia PDF Downloads 75
5000 Passive Neutralization of Acid Mine Drainage Using Locally Produced Limestone

Authors: Reneiloe Seodigeng, Malwandla Hanabe, Haleden Chiririwa, Hilary Rutto, Tumisang Seodigeng

Abstract:

Neutralisation of acid-mine drainage (AMD) using limestone is cost effective, and good results can be obtained. However, this process has its limitations; it cannot be used for highly acidic water which consists of Fe(III). When Fe(III) reacts with CaCO3, it results in armoring. Armoring slows the reaction, and additional alkalinity can no longer be generated. Limestone is easily accessible, so this problem can be easily dealt with. Experiments were carried out to evaluate the effect of PVC pipe length on ferric and ferrous ions. It was found that the shorter the pipe length the more these dissolved metals precipitate. The effect of the pipe length on the hydrogen ions was also studied, and it was found that these two have an inverse relationship. Experimental data were further compared with the model prediction data to see if they behave in a similar fashion. The model was able to predict the behaviour of 1.5m and 2 m pipes in ferric and ferrous ion precipitation.

Keywords: acid mine drainage, neutralisation, limestone, mathematical modelling

Procedia PDF Downloads 352
4999 Effect of a Stepwise Discontinuity on a 65 Degree Delta Wing

Authors: Nishit L. Sanil, Raza M. Khan

Abstract:

Increasing lift effectively at higher angles of attack has always been a daunting challenge in aviation especially on a delta wing. These are used on military jet fighter planes and has some undesirable characteristics, notably flow separation at high angles of attack and high drag at low speeds. In order to solve this problem, a design modification is modeled on a delta wing which would increase the lift so that we can improve maneuverability. To attain an increase in the lift of a 65 degree delta wing at higher angles of attack, a step-wise discontinuity is created at the upper surface of the delta wing. A normal delta wing is validated for comparison which would thereby give us a measure of flow separation and coefficient of lift affected by the modification. The results obtained deliver a significant increase in lift at higher angles of attack thereby delaying stall. Hence the benefits of the modification would aid the potential designs of aircraft’s in the time to come.

Keywords: coefficient of lift, delta wing, flow separation, step-wise discontinuity

Procedia PDF Downloads 289
4998 Force Measurement for E-Cadherin-Mediated Intercellular Adhesion Probed by Protein Micropattern and Traction Force Microscopy

Authors: Chieh-Chung Tsou, Chun-Min Lo, Yeh-Shiu Chu

Abstract:

Cell’s mechanical forces provide important physical cues in regulation of proper cellular functions, such as cell differentiation, proliferation and migration. It is believed that adhesive forces generated by cell-cell interaction are able to transmit to the interior of cell through filamentous cortical cytoskeleton. Prominent among other membrane receptors, Cadherins are prototypical adhesive molecules able to generate remarkable forces to regulate intercellular adhesion. However, the mechanistic steps of mechano-transduction in Cadherin-mediated adhesion remain very controversial. We are interested in understanding how Cadherin protein complexes enable force generation and transmission at cell-cell contact in the initial stage of intercellular adhesion. For providing a better control of time, space, and substrate stiffness, in this study, a combination of protein micropattern, micropipette manipulation, and traction force microscopy is used. Pair micropattern with different forms confines cell spreading area and the gaps in pairs varied from 2 to 8 microns are applied for monitoring the forces that cell pairs generated, measured by traction force microscopy. Moreover, cell clones obtained from epithelial cells undergone genome editing are used to score the importance for known components of Cadherin complexes in force generation. We believe that our results from this combinatory mechanobiological method will provide deep insights on understanding the biophysical principle governing mechano- transduction of Cadherin-mediated intercellular adhesion.

Keywords: cadherin, intercellular adhesion, protein micropattern, traction force microscopy

Procedia PDF Downloads 239
4997 Back Stepping Sliding Mode Control of Blood Glucose for Type I Diabetes

Authors: N. Tadrisi Parsa, A. R. Vali, R. Ghasemi

Abstract:

Diabetes is a growing health problem in worldwide. Especially, the patients with Type 1 diabetes need strict glycemic control because they have deficiency of insulin production. This paper attempts to control blood glucose based on body mathematical body model. The Bergman minimal mathematical model is used to develop the nonlinear controller. A novel back-stepping based sliding mode control (B-SMC) strategy is proposed as a solution that guarantees practical tracking of a desired glucose concentration. In order to show the performance of the proposed design, it is compared with conventional linear and fuzzy controllers which have been done in previous researches. The numerical simulation result shows the advantages of sliding mode back stepping controller design to linear and fuzzy controllers.

Keywords: bergman model, nonlinear control, back stepping, sliding mode control

Procedia PDF Downloads 368
4996 Object Tracking in Motion Blurred Images with Adaptive Mean Shift and Wavelet Feature

Authors: Iman Iraei, Mina Sharifi

Abstract:

A method for object tracking in motion blurred images is proposed in this article. This paper shows that object tracking could be improved with this approach. We use mean shift algorithm to track different objects as a main tracker. But, the problem is that mean shift could not track the selected object accurately in blurred scenes. So, for better tracking result, and increasing the accuracy of tracking, wavelet transform is used. We use a feature named as blur extent, which could help us to get better results in tracking. For calculating of this feature, we should use Harr wavelet. We can look at this matter from two different angles which lead to determine whether an image is blurred or not and to what extent an image is blur. In fact, this feature left an impact on the covariance matrix of mean shift algorithm and cause to better performance of tracking. This method has been concentrated mostly on motion blur parameter. transform. The results reveal the ability of our method in order to reach more accurately tracking.

Keywords: mean shift, object tracking, blur extent, wavelet transform, motion blur

Procedia PDF Downloads 198
4995 BigCrypt: A Probable Approach of Big Data Encryption to Protect Personal and Business Privacy

Authors: Abdullah Al Mamun, Talal Alkharobi

Abstract:

As data size is growing up, people are became more familiar to store big amount of secret information into cloud storage. Companies are always required to need transfer massive business files from one end to another. We are going to lose privacy if we transmit it as it is and continuing same scenario repeatedly without securing the communication mechanism means proper encryption. Although asymmetric key encryption solves the main problem of symmetric key encryption but it can only encrypt limited size of data which is inapplicable for large data encryption. In this paper we propose a probable approach of pretty good privacy for encrypt big data using both symmetric and asymmetric keys. Our goal is to achieve encrypt huge collection information and transmit it through a secure communication channel for committing the business and personal privacy. To justify our method an experimental dataset from three different platform is provided. We would like to show that our approach is working for massive size of various data efficiently and reliably.

Keywords: big data, cloud computing, cryptography, hadoop, public key

Procedia PDF Downloads 306
4994 Detection Method of Federated Learning Backdoor Based on Weighted K-Medoids

Authors: Xun Li, Haojie Wang

Abstract:

Federated learning is a kind of distributed training and centralized training mode, which is of great value in the protection of user privacy. In order to solve the problem that the model is vulnerable to backdoor attacks in federated learning, a backdoor attack detection method based on a weighted k-medoids algorithm is proposed. First of all, this paper collates the update parameters of the client to construct a vector group, then uses the principal components analysis (PCA) algorithm to extract the corresponding feature information from the vector group, and finally uses the improved k-medoids clustering algorithm to identify the normal and backdoor update parameters. In this paper, the backdoor is implanted in the federation learning model through the model replacement attack method in the simulation experiment, and the update parameters from the attacker are effectively detected and removed by the defense method proposed in this paper.

Keywords: federated learning, backdoor attack, PCA, k-medoids, backdoor defense

Procedia PDF Downloads 93
4993 Optimization of Switched Reluctance Motor for Drive System in Automotive Applications

Authors: A. Peniak, J. Makarovič, P. Rafajdus, P. Dúbravka

Abstract:

The purpose of this work is to optimize a Switched Reluctance Motor (SRM) for an automotive application, specifically for a fully electric car. A new optimization approach is proposed. This unique approach transforms automotive customer requirements into an optimization problem, based on sound knowledge of a SRM theory. The approach combines an analytical and a finite element analysis of the motor to quantify static nonlinear and dynamic performance parameters, as phase currents and motor torque maps, an output power and power losses in order to find the optimal motor as close to the reality as possible, within reasonable time. The new approach yields the optimal motor which is competitive with other types of already proposed motors for automotive applications. This distinctive approach can also be used to optimize other types of electrical motors, when parts specifically related to the SRM are adjusted accordingly.

Keywords: automotive, drive system, electric car, finite element method, hybrid car, optimization, switched reluctance motor

Procedia PDF Downloads 501
4992 Flow Conservation Framework for Monitoring Software Defined Networks

Authors: Jesús Antonio Puente Fernández, Luis Javier Garcia Villalba

Abstract:

New trends on streaming videos such as series or films require a high demand of network resources. This fact results in a huge problem within traditional IP networks due to the rigidity of its architecture. In this way, Software Defined Networks (SDN) is a new concept of network architecture that intends to be more flexible and it simplifies the management in networks with respect to the existing ones. These aspects are possible due to the separation of control plane (controller) and data plane (switches). Taking the advantage of this separated control, it is easy to deploy a monitoring tool independent of device vendors since the existing ones are dependent on the installation of specialized and expensive hardware. In this paper, we propose a framework that optimizes the traffic monitoring in SDN networks that decreases the number of monitoring queries to improve the network traffic and also reduces the overload. The performed experiments (with and without the optimization) using a video streaming delivery between two hosts demonstrate the feasibility of our monitoring proposal.

Keywords: optimization, monitoring, software defined networking, statistics, query

Procedia PDF Downloads 314
4991 Predicting Seoul Bus Ridership Using Artificial Neural Network Algorithm with Smartcard Data

Authors: Hosuk Shin, Young-Hyun Seo, Eunhak Lee, Seung-Young Kho

Abstract:

Currently, in Seoul, users have the privilege to avoid riding crowded buses with the installation of Bus Information System (BIS). BIS has three levels of on-board bus ridership level information (spacious, normal, and crowded). However, there are flaws in the system due to it being real time which could provide incomplete information to the user. For example, a bus comes to the station, and on the BIS it shows that the bus is crowded, but on the stop that the user is waiting many people get off, which would mean that this station the information should show as normal or spacious. To fix this problem, this study predicts the bus ridership level using smart card data to provide more accurate information about the passenger ridership level on the bus. An Artificial Neural Network (ANN) is an interconnected group of nodes, that was created based on the human brain. Forecasting has been one of the major applications of ANN due to the data-driven self-adaptive methods of the algorithm itself. According to the results, the ANN algorithm was stable and robust with somewhat small error ratio, so the results were rational and reasonable.

Keywords: smartcard data, ANN, bus, ridership

Procedia PDF Downloads 154
4990 Study of Management of Waste Construction Materials in Civil Engineering Projects

Authors: Jalindar R. Patil, Harish P. Gayakwad

Abstract:

The increased economic growth across the globe as well as urbanization in developing countries have led into extensive construction activities that generate large amounts of wastes. Material wastage in construction projects resulted into huge financial setbacks to builders and contractors. In addition to this, it may also cause significant effects over aesthetics, health, and the general environment. However in many cities across the globe where construction wastes material management is still a problem. In this paper, the discussion is all about the method for the management of waste construction materials. The objectives of this seminar are to identify the significant source of construction waste globally, to improve the performance of by extracting the major barriers construction waste management and to determine the cost impact on the construction project. These wastes needs to be managed as well as their impacts needs to be ascertained to pave way for their proper management. The seminar includes the details of construction waste management with the reference to construction project. The application of construction waste management in the civil engineering projects is to describe the reduction in the construction wastes.

Keywords: civil engineering, construction materials, waste management, construction activities

Procedia PDF Downloads 503
4989 The Influence of Imposter Phenomenon on the Experiences of Intimacy in Non-Binary Young Adults

Authors: Muskan Jain, Baiju Gopal

Abstract:

Objectives: Intimacy in interpersonal relationships is integral to psychological health and everyday wellbeing; the focus is on intimacy, which can be described as feelings of closeness, connection, and belonging within relationships, which is influenced by an individual's gender identity as well as life experiences. The study aims to explore the experiences of intimacy of the non-binary gender; this marginalized community has increased risks of developing the imposter phenomenon. The study explores the influence of IP on the development and sustenance of intimacy in relationships. Methods: The present study accumulates detailed narratives from 10 non-binary young adults ages 18 to 25 in metropolitan cities of India. Thematic analysis was used for the data analysis. Results: Seven major themes have emerged revolving around internalized criticism and self-depreciating behavior, which causes distance between partners. The four themes that result in the internalization of criticism are lack of social stability, invalidation by social units, adverse life experiences, and estrangement due to gender identity. Three themes that encapsulate major difficulties in relationships are limited self-disclosure, inhibition of physical needs, and fear of taking space. The findings have been critically compared and contrasted with the existing body of literature in the domain, which sets the agenda for further inquiry. Conclusion: It is important for future studies to capture the experiences of non-binary genders in India to provide better therapeutic support in order to assist them in forming meaningful and authentic relationships, thus increasing overall wellbeing.

Keywords: imposter phenomenon, intimacy, internalized criticism, marginalized community

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4988 Exploring the Possibility of Islamic Banking as a Viable Alternative to the Conventional Banking Model

Authors: Lavan Vickneson

Abstract:

In today’s modern economy, the conventional banking model is the primary banking system used around the world. A significant problem faced by the conventional banking model is the recurring nature of banking crises. History’s record of the various banking crises, ranging from the Great Depression to the 2008 subprime mortgage crisis, is testament to the fact that banking crises continue to strike despite the preventive measures in place, such as bank’s minimum capital requirements and deposit guarantee schemes. If banking crises continue to occur despite these preventive measures, it necessarily follows that there are inherent flaws with the conventional banking model itself. In light of this, a possible alternative banking model to the conventional banking model is Islamic banking. To date, Islamic banking has been a niche market, predominantly serving Muslim investors. This paper seeks to explore the possibility of Islamic banking being more than just a niche market and playing a greater role in banking sectors around the world, by being a viable alternative to the conventional banking model.

Keywords: bank crises, conventional banking model, Islamic banking, niche market

Procedia PDF Downloads 260
4987 Synthesis, Crystal Structure Characterization, Hirshfeld Surface Analysis and Biological Activities of Two Schiff Base Polymorphs Derived From 2-Aminobenzonitrile

Authors: Nesrine Benarous, Hassiba Bougueria, Nabila Moussa Slimane, Aouatef Cherouana

Abstract:

Crystal polymorphism is important for the synthesis of more potent and bioactive pharmaceutical compounds, including their different properties, such as packing arrangement and conformation. In fact, polymorphism plays a vital role in drug development. Different parameters affect the crystallization and give their degree of freedom. Severalproperties affected polymorphism, like kinetics, thermodynamics, spectroscopy, and mechanical property. Various techniques are used for characterizing polymorphs, are crystallography, morphology, phase transitions, molecular motion, and chemical environment. In this work, crystal structures of two polymorphs (I and II) of the Schiff base (SB) title compound were prepared by condensation reaction. The crystal structures of both polymorphs were determined by single X-ray analysis. The two polymorphs crystallize in two different space groups: P21/c for I and Pbca for II. The dihedral angles between the two phenyl rings are 4.81º for I and 82.27º for II. Both crystal structures are built on the basis of moderate and weak hydrogen bonds, 𝜋-stacking, and halogen⋯halogeninteractions. On the other hand, Hirshfeld surface (HS) analysis indicates that the most important contributions to the crystal packing for the two polymorphs are from Cl⋯H/H⋯Cl, H⋯H, and N⋯H/H⋯N contacts. These are followed by C⋯H/H⋯C for compound I and C⋯C and by C⋯H/H⋯C contacts for compound II. Afterwards, the in vitro antibacterial activity revealed that the SB have been found effective against G- bacteria Klebsiella pneumonia andG+ bacteria Staphylococcus aureuswith MIC value of14.37μg/mL. Moreover, the SBexhibited moderate toxicity against Brine Shrimp with LC50 value of 44.19μg/mL.

Keywords: polymorph, crystal structure, hirshfeld surface analysis, in vitro antibacterial activity, toxicity

Procedia PDF Downloads 93
4986 Clothes Identification Using Inception ResNet V2 and MobileNet V2

Authors: Subodh Chandra Shakya, Badal Shrestha, Suni Thapa, Ashutosh Chauhan, Saugat Adhikari

Abstract:

To tackle our problem of clothes identification, we used different architectures of Convolutional Neural Networks. Among different architectures, the outcome from Inception ResNet V2 and MobileNet V2 seemed promising. On comparison of the metrices, we observed that the Inception ResNet V2 slightly outperforms MobileNet V2 for this purpose. So this paper of ours proposes the cloth identifier using Inception ResNet V2 and also contains the comparison between the outcome of ResNet V2 and MobileNet V2. The document here contains the results and findings of the research that we performed on the DeepFashion Dataset. To improve the dataset, we used different image preprocessing techniques like image shearing, image rotation, and denoising. The whole experiment was conducted with the intention of testing the efficiency of convolutional neural networks on cloth identification so that we could develop a reliable system that is good enough in identifying the clothes worn by the users. The whole system can be integrated with some kind of recommendation system.

Keywords: inception ResNet, convolutional neural net, deep learning, confusion matrix, data augmentation, data preprocessing

Procedia PDF Downloads 171
4985 Cyber Victimization: School Experience of Malaysian Cyberbullied Teenagers

Authors: Shireen Simon

Abstract:

Cyberbullying among schoolchildren and teenagers became a hot issue discussed by Malaysian society. Cyberbullying is a new age of bullying because it uses the modern digital technology intentionally to hurt and degrade someone in the cyber world. Cyberbullying is a problem affecting many teenagers as they embrace online communication and interaction whereby virtual world with no borders. By adopting a qualitative approach, this study has captured 8 cyberbullied victims’ school experience. Even years after leaving school, these 8 cyberbullied victims remember how it feels to be bullied in the cyber world. The principal investigator also tries to identify the possibility factors that contribute to cyberbullying among these 8 victims. The result shows that these victims were bullied differently in cyber world. This study not just primarily focuses on cyberbullying issues among schoolchildren and teenagers; it also addresses the motives and causes of cyberbullying. Lastly, this article will be served as guidance for school teachers, parents and teenagers to prepare to tackle cyberbullying together. Cyberbullying is no laughing matter in our community, and it is time to spread the seeds of peace inspires others to do the same.

Keywords: cyberbullying, cyber victimization, internet, school experience, teenagers

Procedia PDF Downloads 274
4984 Climate Change Based Frontier Research in Landscape Architecture

Authors: Xiaoyan Wang, Zhongde Wang

Abstract:

The issue of climate change, which originated in the middle of the twentieth century, has become a focus of international political, academic, and non-governmental organizations and public attention. In order to address the problems caused by climate change, the Chinese government has proposed a dual-carbon target and taken some national measures, such as ecological priority and green low-carbon development. These goals and measures are highly aligned with the values of the landscape architecture industry. This is an opportunity for the architectural discipline and the landscape architecture industry, so it is very necessary to summarize and analyze the hotspots related to climate change in the field of building science in China, which can assist the landscape architecture industry and related organizations in formulating more rational professional goals and taking actions that contribute to the betterment of societal, environmental development. Through the study, it is found as follows: firstly, after 20 years of rapid development, the research on climate change in the major architectural disciplines has shown a trend of diversification of research perspectives, interdisciplinary cross-cutting, and broadening of content; secondly, the research contents of landscape architecture focuses on the strategies to adapt to climate change, such as selection of urban tree species, the urban green infrastructure space layout, and the resilient city. Finally, in the future, climate change-based landscape architecture research will make the content system more diversified, but at the same time, it is still necessary to further deepen the research on quantitative methodology and construct scale systematic planning and design methods.

Keywords: climate change, landscape architecture, knowledge mapping, cites-pace

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4983 Landslide Hazard a Gigantic Problem in Indian Himalayan Region: Needs In-Depth Research to Minimize Disaster

Authors: Varun Joshi, M. S. Rawat

Abstract:

The Indian Himalayan Region (IHR) is inherently fragile and susceptible to landslide hazard due to its extremely weak geology, highly rugged topography and heavy monsoonal rainfall. One of the most common hazards in the IHR is landslide, and this event is particularly frequent in Himalayan states of India i.e. Jammu & Kashmir, Himachal Pradesh, Uttarakhand, Sikkim, Manipur and Arunachal Pradesh. Landslides are mostly triggered by extreme rainfall events but the incidence increases during monsoon months (June to September). Natural slopes which are otherwise stable but they get destabilized due to anthropogenic activities like construction of various developmental activities and deforestation. These activities are required to fulfill the developmental needs and upliftment of societal status in the region. Landslides also trigger during major earthquakes and reported most observable and damaging phenomena. Studies indicate that the landslide phenomenon has increased many folds due to developmental activities in Himalayan region. Gradually increasing and devastating consequences of landslides turned into one of the most important hydro-geological hazards in Himalayan states especially in Uttarakhand and Sikkim states of India. The recent most catastrophic rainfall in June 2013 in Uttarakhand lead to colossal loss of life and property. The societal damage due to this incident is still to be recovered even after three years. Sikkim earthquake of September 2011 is witnessed for triggering of large number of coseismic landslides. The rescue and relief team faced huge problem in helping the trapped villagers in remote locations of the state due to road side blockade by landslides. The recent past incidences of landslides in Uttarakhand, as well as Sikkim states, created a new domain of research in terms of understanding the phenomena of landslide and management of disaster in such situation. Every year at many locations landslides trigger which force dwellers to either evacuate their dwelling or lose their life and property. The communication and transportation networks are also severely affected by landslides at several locations. Many times the drinking water supply disturbed and shortage of daily need household items reported during monsoon months. To minimize the severity of landslide in IHR requires in-depth research and developmental planning. For most of the areas in the present study, landslide hazard zonation is done on 1:50,000 scale. The land use planning maps on extensive basis are not available. Therefore, there is a need of large-scale landslide hazard zonation and land use planning maps. If the scientist conduct research on desired aspects and their outcome of research is utilized by the government in developmental planning then the incidents of landslide could be minimized, subsequent impact on society, life and property would be reduced. Along with the scientific research, there is another need of awareness generation in the region for stake holders and local dwellers to combat with the landslide hazard, if triggered in their location.

Keywords: coseismic, Indian Himalayan Region, landslide hazard zonation, Sikkim, societal, Uttarakhand

Procedia PDF Downloads 238
4982 Nonlinear Analysis with Failure Using the Boundary Element Method

Authors: Ernesto Pineda Leon, Dante Tolentino Lopez, Janis Zapata Lopez

Abstract:

The current paper shows the application of the boundary element method for the analysis of plates under shear stress causing plasticity. In this case, the shear deformation of a plate is considered by means of the Reissner’s theory. The probability of failure of a Reissner’s plate due to a proposed index plastic behavior is calculated taken into account the uncertainty in mechanical and geometrical properties. The problem is developed in two dimensions. The classic plasticity’s theory is applied and a formulation for initial stresses that lead to the boundary integral equations due to plasticity is also used. For the plasticity calculation, the Von Misses criteria is used. To solve the non-linear equations an incremental method is employed. The results show a relatively small failure probability for the ranges of loads between 0.6 and 1.0. However, for values between 1.0 and 2.5, the probability of failure increases significantly. Consequently, for load bigger than 2.5 the plate failure is a safe event. The results are compared to those that were found in the literature and the agreement is good.

Keywords: boundary element method, failure, plasticity, probability

Procedia PDF Downloads 290
4981 Addressing the Exorbitant Cost of Labeling Medical Images with Active Learning

Authors: Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

Abstract:

Successful application of deep learning in medical image analysis necessitates unprecedented amounts of labeled training data. Unlike conventional 2D applications, radiological images can be three-dimensional (e.g., CT, MRI), consisting of many instances within each image. The problem is exacerbated when expert annotations are required for effective pixel-wise labeling, which incurs exorbitant labeling effort and cost. Active learning is an established research domain that aims to reduce labeling workload by prioritizing a subset of informative unlabeled examples to annotate. Our contribution is a cost-effective approach for U-Net 3D models that uses Monte Carlo sampling to analyze pixel-wise uncertainty. Experiments on the AAPM 2017 lung CT segmentation challenge dataset show that our proposed framework can achieve promising segmentation results by using only 42% of the training data.

Keywords: image segmentation, active learning, convolutional neural network, 3D U-Net

Procedia PDF Downloads 133
4980 Data Quality Enhancement with String Length Distribution

Authors: Qi Xiu, Hiromu Hota, Yohsuke Ishii, Takuya Oda

Abstract:

Recently, collectable manufacturing data are rapidly increasing. On the other hand, mega recall is getting serious as a social problem. Under such circumstances, there are increasing needs for preventing mega recalls by defect analysis such as root cause analysis and abnormal detection utilizing manufacturing data. However, the time to classify strings in manufacturing data by traditional method is too long to meet requirement of quick defect analysis. Therefore, we present String Length Distribution Classification method (SLDC) to correctly classify strings in a short time. This method learns character features, especially string length distribution from Product ID, Machine ID in BOM and asset list. By applying the proposal to strings in actual manufacturing data, we verified that the classification time of strings can be reduced by 80%. As a result, it can be estimated that the requirement of quick defect analysis can be fulfilled.

Keywords: string classification, data quality, feature selection, probability distribution, string length

Procedia PDF Downloads 306