Search results for: fuzzy rule

Authors: Nurulhikma Md Isa, Intan Elya Suka, Nur Farhana Roslan, Chew Bee Lynn

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The evolutionarily conserved N-end rule pathway marks proteins for degradation by the Ubiquitin Proteosome System (UPS) based on the nature of their N-terminal residue. Proteins with a destabilizing N-terminal residue undergo a series of condition-dependent N-terminal modifications, resulting in their ubiquitination and degradation. Intensive research has been carried out in Arabidopsis previously. The group VII Ethylene Response Factor (ERFs) transcription factors are the first N-end rule pathway substrates found in Arabidopsis and their role in regulating oxygen sensing. ERFs also function as central hubs for the perception of gaseous signals in plants and control different plant developmental including germination, stomatal aperture, hypocotyl elongation and stress responses. However, nothing is known about the role of this pathway during fruit development and ripening aspect. The plant model system Arabidopsis cannot represent fleshy fruit model system therefore tomato is the best model plant to study. PROTEOLYSIS6 (PRT6) is an E3 ubiquitin ligase of the N-end rule pathway. Two homologs of PRT6 sequences have been identified in tomato genome database using the PRT6 protein sequence from model plant Arabidopsis thaliana. Homology search against Ensemble Plant database (tomato) showed Solyc09g010830.2 is the best hit with highest score of 1143, e-value of 0.0 and 61.3% identity compare to the second hit Solyc10g084760.1. Further homology search was done using NCBI Blast database to validate the data. The result showed best gene hit was XP_010325853.1 of uncharacterized protein LOC101255129 (Solanum lycopersicum) with highest score of 1601, e-value 0.0 and 48% identity. Both Solyc09g010830.2 and uncharacterized protein LOC101255129 were genes located at chromosome 9. Further validation was carried out using BLASTP program between these two sequences (Solyc09g010830.2 and uncharacterized protein LOC101255129) to investigate whether they were the same proteins represent PRT6 in tomato. Results showed that both proteins have 100 % identity, indicates that they were the same gene represents PRT6 in tomato. In addition, we used two different RNAi constructs that were driven under 35S and Polygalacturonase (PG) promoters to study the function of PRT6 during tomato developmental stages and ripening processes.

Keywords: ERFs, PRT6, tomato, ubiquitin

Procedia PDF Downloads 226

Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang

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An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Keywords: distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone

Procedia PDF Downloads 372

Authors: Izadi Banafsheh, Sedaghat Reza

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Maintenance, Repair, and Overhaul (MRO) of machinery are a key recent issue concerning the automotive industry. It has always been a debated question what order or priority should be adopted for the MRO of machinery. This study attempts to examine several criteria including process sensitivity, average time between machine failures, average duration of repair, availability of parts, availability of maintenance personnel and workload through a literature review and experts survey so as to determine the condition of the machine. According to the mentioned criteria, the machinery were ranked in four modes below: A) Need for inspection, B) Need for minor repair, C) Need for part replacement, and D) Need for major repair. The Fuzzy AHP was employed to determine the weighting of criteria. At the end, the obtained weights were ranked through the AHP for each criterion, three groups were specified: shaving machines, assembly and painting in four modes. The statistical population comprises the elite in the Iranian automotive industry at IKCO covering operation managers, CEOs and maintenance professionals who are highly specialized in MRO and perfectly knowledgeable in how the machinery function. The information required for this study were collected from both desk research and field review, which eventually led to construction of a questionnaire handed out to the sample respondents in order to collect information on the subject matter. The results of the AHP for weighting the criteria revealed that the availability of maintenance personnel was the top priority at coefficient of 0.206, while the process sensitivity took the last priority at coefficient of 0.066. Furthermore, the results of TOPSIS for prioritizing the IKCO machinery suggested that at the mode where there is need for inspection, the assembly machines took the top priority while paining machines took the third priority. As for the mode where there is need for minor repairs, the assembly machines took the top priority while the third priority belonged to the shaving machines. As for the mode where there is need for parts replacement, the assembly machines took the top priority while the third belonged to the paining machinery. Finally, as for the mode where there is need for major repair, the assembly machines took the top priority while the third belonged to the paining machinery.

Keywords: maintenance, repair, overhaul, MRO, prioritization of machinery, fuzzy logic, AHP, TOPSIS

Procedia PDF Downloads 271

Authors: Seada Hussen, Frie Ayalew

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Integrating different energy resources, like solar PV and hydro, is used to ensure reliable power to rural communities like Hara village in Ethiopia. Hybrid power system offers power supply for rural villages by providing an alternative supply for the intermittent nature of renewable energy resources. The intermittent nature of renewable energy resources is a challenge to electrifying rural communities in a sustainable manner with solar resources. Major rural villages in Ethiopia are suffering from a lack of electrification, that cause our people to suffer deforestation, travel for long distance to fetch water, and lack good services like clinic and school sufficiently. The main objective of this project is to provide a balanced, stable, reliable supply for Hara village, Ethiopia using solar power with a pumped hydro energy storage system. The design of this project starts by collecting data from villages and taking solar irradiance data from NASA. In addition to this, geographical arrangement and location are also taken into consideration. After collecting this, all data analysis and cost estimation or optimal sizing of the system and comparison of solar with pumped hydro and solar with battery storage system is done using Homer Software. And since solar power only works in the daytime and pumped hydro works at night time and also at night and morning, both load will share to cover the load demand; this need controller designed to control multiple switch and scheduling in this project fuzzy logic controller is used to control this scenario. The result of the simulation shows that solar with pumped hydro energy storage system achieves good results than with a battery storage system since the comparison is done considering storage reliability, cost, storage capacity, life span, and efficiency.

Keywords: pumped hydro storage, solar energy, solar PV, battery energy storage, fuzzy logic controller

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Authors: Jyothi P. Phatak, L. Venkatesha, C. S. Raviprasad

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The performance improvement of Hybrid Energy Storage System (HESS) in Electric Vehicle (EV) has been in discussion over the last decade. The important issues in terms of performance parameters addressed are, range of vehicle and battery (BA) peak current. Published literature has either addressed battery peak current reduction or range improvement in EV. Both the issues have not been specifically discussed and analyzed. This paper deals with both range improvement in EV and battery peak current reduction by applying a new Karnaugh Map (K-Map) constructed rule based energy management strategy to proposed HESS. The strategy allows Ultracapacitor (UC) to assist battery when the vehicle accelerates there by reducing the burden on battery. Simulation is carried out for various operating modes of EV considering both urban and highway driving conditions. Simulation is done for different values of UC by keeping battery rating constant for each driving cycle and results are presented. Feasible value of UC is selected based on simulation results. The results of proposed HESS show an improvement in performance parameters compared to Battery only Energy Storage System (BESS). Battery life is improved to considerable extent and there is an overall development in the performance of electric vehicle.

Keywords: electric vehicle, PID controller, energy management strategy, range, battery current, ultracapacitor

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Authors: Rika van Zyl

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South Africa’s racial discrimination past has led to the drafting of the Constitution with the Bill of Rights for the people of South Africa. The Bill of Rights prohibits the state from unfairly discriminating directly or indirectly on certain grounds, one of which is race and another is gender. This has forced changes to the law of succession. The customary law rule of male primogeniture was abolished to ensure that women were not excluded from the intestate succession of the male head of the family in 2005. It was said that this rule cannot be reconciled with the notions of equality and human dignity contained in the Bill of Rights. The freedom of testation has further come under fire in South Africa, where it was found to be unfair discrimination and against public policy to exclude a specific gender (women) from inheriting in a private will. Although no one has the right to inherit in South Africa, any person with an interest can approach the court alleging that a right in the Bill of Rights has been infringed. A will that is found inconsistent with the South African Bill of Rights then cannot be enforced. Recent case law found that to leave out a specific gender (women) from a will, based entirely on the fact that they are of said specific gender, is in contravention of the Constitution and should, therefore, be declared invalid. It was said that the courts should take a transformative constitutional approach when equality rights are affected. Otherwise, the historical and insidious unequal distribution of wealth in South Africa will continue along the fault lines such as gender. This decision has opened the debate on the extent to which the state can interfere with the private autonomy of an individual who is deceased. Some of these arguments will be discussed, including the ambit of public policy in this regard.

Keywords: equality, discrimination, succession, public policy

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Authors: Mohit Modi, Rajiv Kumar, Manojraj Saxena, G. Ravi Shankar

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Change detection of coastal ecosystem plays a vital role in monitoring and managing natural resources along the coastal regions. The present study mainly focuses on the decadal change in Kochi islands connecting the urban flatland areas and the coastal regions where sand deposits have taken place. With this, in view, the change detection has been monitored in the Kochi area to apprehend the urban growth and industrialization leading to decrease in the wetland ecosystem. The region lies between 76°11'19.134"E to 76°25'42.193"E and 9°52'35.719"N to 10°5'51.575"N in the south-western coast of India. The IRS LISS-IV satellite image has been processed using a rule-based algorithm to classify the LULC and to interpret the changes between 2005 & 2015. The approach takes two steps, i.e. extracting features as a single GIS vector layer using different parametric values and to dissolve them. The multi-resolution segmentation has been carried out on the scale ranging from 10-30. The different classes like aquaculture, agricultural land, built-up, wetlands etc. were extracted using parameters like NDVI, mean layer values, the texture-based feature with corresponding threshold values using a rule set algorithm. The objects obtained in the segmentation process were visualized to be overlaying the satellite image at a scale of 15. This layer was further segmented using the spectral difference segmentation rule between the objects. These individual class layers were dissolved in the basic segmented layer of the image and were interpreted in vector-based GIS programme to achieve higher accuracy. The result shows a rapid increase in an industrial area of 40% based on industrial area statistics of 2005. There is a decrease in wetlands area which has been converted into built-up. New roads have been constructed which are connecting the islands to urban areas as well as highways. The increase in coastal region has been visualized due to sand depositions. The outcome is well supported by quantitative assessments which will empower rich understanding of land use land cover change for appropriate policy intervention and further monitoring.

Keywords: land use land cover, multiresolution segmentation, NDVI, object based classification

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Authors: Cui Li, Xu Yuping

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Based on the question of, "Are short video creators who are digital workers controlled by platform rules?" this study discusses the specific ways of platform rules control and the impact on short video creators. Based on the theory of digital labor, this paper adopts the method of in-depth interview and participant observation and chooses 24 producers of short video content of Tiktok to conduct in-depth interview. At the same time, through entering the short video creation field, the author carries on the four-month field investigation, obtains the creation process related data, and analyzes how the short video creator, as the digital labor, is controlled by the platform rule, as well as the creator in this process of compromise and resistance, a more comprehensive presentation of the short video creators of the labor process. It is found that the short video creators are controlled by the platform rules, mainly in the control of traffic rules, and the creators create content, compromise and resist under the guidance of traffic. First, while the platform seems to offer a flexible and autonomous way for creators to monetize, the threshold for participating in the event is actually very high for creators, and the rules for monetizing the event are vague. Under the influence of the flow rule, the creator is faced unstable incomes and high costs. Therefore, creators have to follow the rules of traffic to guide their own creation, began to flow-oriented content production, mainly reflected in the need to keep up-to-date, the pursuit of traffic to ride on the hot spots, in order to flow regardless, set up people "Born for the show", by the label solidified content creation. Secondly, the irregular working hours lead to the extension and overwork of the working hours, which leads to the internal friction of the short video creators at the spiritual level, and finally leads to the Rat Race of video creation. Thirdly, the video creator has completed the internalization and compromise of the platform rules in practice, which promotes the creator to continue to create independently, and forms the intrinsic motive force of the creator. Finally, the rule-controlled short video creators resist and fight in flexible ways, make use of the mechanism and rules of the platform to carry on the second creation, carry on the routine production, purchase the false flow, transfer the creation position to maintain own creation autonomy.

Keywords: short videos, tiktok, production, digital labors

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Authors: Tauqir A. Moughal, Fusheng Yu, Abeer Mazher

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Land-cover and land-use change information are important because of their practical uses in various applications, including deforestation, damage assessment, disasters monitoring, urban expansion, planning, and land management. Therefore, developing change detection methods for remote sensing images is an important ongoing research agenda. However, detection of change through optical remote sensing images is not a trivial task due to many factors including the vagueness between the boundaries of changed and unchanged regions and spatial dependence of the pixels to its neighborhood. In this paper, we propose a binary change detection technique for bi-temporal optical remote sensing images. As in most of the optical remote sensing images, the transition between the two clusters (change and no change) is overlapping and the existing methods are incapable of providing the accurate cluster boundaries. In this regard, a methodology has been proposed which uses the fuzzy c-means clustering to tackle the problem of vagueness in the changed and unchanged class by formulating the soft boundaries between them. Furthermore, in order to exploit the neighborhood information of the pixels, the input patterns are generated corresponding to each pixel from bi-temporal images using 3×3, 5×5 and 7×7 window. The between images and within image spatial dependence of the pixels to its neighborhood is quantified by using Pearson product moment correlation and Moran’s I statistics, respectively. The proposed technique consists of two phases. At first, between images and within image spatial correlation is calculated to utilize the information that the pixels at different locations may not be independent. Second, fuzzy c-means technique is used to produce two clusters from input feature by not only taking care of vagueness between the changed and unchanged class but also by exploiting the spatial correlation of the pixels. To show the effectiveness of the proposed technique, experiments are conducted on multispectral and bi-temporal remote sensing images. A subset (2100×1212 pixels) of a pan-sharpened, bi-temporal Landsat 5 thematic mapper optical image of Los Angeles, California, is used in this study which shows a long period of the forest fire continued from July until October 2009. Early forest fire and later forest fire optical remote sensing images were acquired on July 5, 2009 and October 25, 2009, respectively. The proposed technique is used to detect the fire (which causes change on earth’s surface) and compared with the existing K-means clustering technique. Experimental results showed that proposed technique performs better than the already existing technique. The proposed technique can be easily extendable for optical hyperspectral images and is suitable for many practical applications.

Keywords: burned area, change detection, correlation, fuzzy clustering, optical remote sensing

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Authors: S. Niamkaeo, O. Robert, O. Chaowalit

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In this investigation, we focus on discovering spatial relationship of drug smuggling along the northern border of Thailand. Thailand is no longer a drug production site, but Thailand is still one of the major drug trafficking hubs due to its topographic characteristics facilitating drug smuggling from neighboring countries. Our study areas cover three districts (Mae-jan, Mae-fahluang, and Mae-sai) in Chiangrai city and four districts (Chiangdao, Mae-eye, Chaiprakarn, and Wienghang) in Chiangmai city where drug smuggling of methamphetamine crystal and amphetamine occurs mostly. The data on drug smuggling incidents from 2011 to 2017 was collected from several national and local published news. Geo-spatial drug smuggling database was prepared. Decision tree algorithm was applied in order to discover the spatial relationship of factors related to drug smuggling, which was converted into rules using rule-based system. The factors including land use type, smuggling route, season and distance within 500 meters from check points were found that they were related to drug smuggling in terms of rules-based relationship. It was illustrated that drug smuggling was occurred mostly in forest area in winter. Drug smuggling exhibited was discovered mainly along topographic road where check points were not reachable. This spatial relationship of drug smuggling could support the Thai Office of Narcotics Control Board in surveillance drug smuggling.

Keywords: decision tree, drug smuggling, Geographic Information System, GIS knowledge discovery, rule-based system

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Authors: Parveen Kundu, Nitika Chawla, Ruchi Agarwal, Swaran Kaur

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Background: Mature cystic teratoma is a benign, most common tumor of the ovary occurring mostly in young and middle-aged females. This study consists of 19 cases of mature cystic teratomas which were received in the Department Of Pathology over a period of two years. There were malignant transformations observed in three cases, which makes it very important for pathologists to thoroughly examine the entire specimen of mature cystic teratomas. Material and Methods: Nineteen reported cases of mature cystic teratomas were received in Deptt. Of Pathology, BPS GMC Khanpur Kalan, Sonepat, over a two-year period from November 2020 to October 2022 and reviewed retrospectively. Data regarding age, size, laterality, gross, morphological features, and surgery performed were retrieved from pathological archives. Results: In our study, the most common age of presentation was the 20-40 year age group. The most common presenting complaint was fullness in the abdomen or abdominal distension. Four out of 19 cases studied cases presented with bilateral ovarian cysts. Tumor size ranged from 6 to 20 cm in diameter. In seven cases, cysts were greater than or equal to 10 cm in diameter. Three cases showed malignant transformation. Conclusion: It is very important to thoroughly examine the contralateral ovary to rule out bilateral presentation. A furthermost thorough examination is advised in tumors of size >10 cm and in tumors with solid areas to rule out any malignant transformation.

Keywords: teratoma, ovary, malignant, transformation

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Authors: Zijiao Chai, Wangming Li

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Under the background of increasing aging population, the situation of city endowment resources shortage gradually revealed. And many villages in the metropolitan area with the good natural ecological environment and leisure tourism base, have become one of the main destinations of urban old people for the off-site pension. This paper is based on a survey of more than ten villages which are characterized by leisure and endowment in Hangzhou metropolitan area, China. The satisfaction degree of the two main groups in the villages, dwellers, and aged visitors, is researched using the method of fuzzy comprehensive evaluation. The statistics are obtained from 535 questionnaires and qualitative interview. According to the satisfaction scores, it could be determined whether the dwellers and aged visitors have reached the equilibrium state. The equilibrium state is the development target of the villages, and it`s defined by environmentally friendly, proper for employment and pension, facilities sharing and harmonious life for each other. Furthermore, this paper comes up with some planning countermeasures in order to avoid "imbalance between dwellers and aged visitors" and obtain sustainable development while maintaining the economic benefit.

Keywords: aged visitors, balance between dwellers and aged visitors, dwellers, fuzzy comprehensive evaluation, Hangzhou metropolitan area, leisure and endowment characteristic villages

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Authors: Lotfi Farah, Nadir Farah, Zaiem Kamar

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This paper achieves a maximum power point tracking (MPPT) controller using a high-efficiency reduced rules neuro-fuzzy inference system (HE2RNF) for a 100 kW stand-alone photovoltaic (PV) system connected to the grid. The suggested HE2RNF based MPPT seeks the optimal duty cycle for the boost DC-DC converter, making the designed PV system working at the maximum power point (MPP), then transferring this power to the grid via a three levels voltage source converter (VSC). PV current variation and voltage variation are chosen as HE2RNF-based MPPT controller inputs. By using these inputs with the duty cycle as the only single output, a six rules ANFIS is generated. The high performance of the proposed HE2RNF numerically in the MATLAB/Simulink environment is shown. The 0.006% steady-state error, 0.006s of tracking time, and 0.088s of starting time prove the robustness of this six reduced rules against the widely used twenty-five ones.

Keywords: PV, MPPT, ANFIS, HE2RNF-based MPPT controller, VSC, grid connection

Procedia PDF Downloads 167

Authors: Ahmad Mohsin, Syda Fatima, Falak Nawaz, Aman Ullah Khan

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Selection of an appropriate architectural style is vital to the success of target web service under development. The nature of architecture design and selection for service-oriented computing applications is quite different as compared to traditional software. Web Services have complex and rigorous architectural styles to choose. Due to this, selection for accurate architectural style for web services development has become a more complex decision to be made by architects. Architectural style selection is a multi-criteria decision and demands lots of experience in service oriented computing. Decision support systems are good solutions to simplify the selection process of a particular architectural style. Our research suggests a new approach using DSS for selection of architectural styles while developing a web service to cater FRs and NFRs. Our proposed DSS helps architects to select right web service architectural pattern according to the domain and non-functional requirements. In this paper, a rule base DSS has been developed using CLIPS (C Language Integrated Production System) to support decisions using multi-criteria requirements. This DSS takes architectural characteristics, domain requirements and software architect preferences for NFRs as input for different architectural styles in use today in service-oriented computing. Weighted sum model has been applied to prioritize quality attributes and domain requirements. Scores are calculated using multiple criterions to choose the final architecture style.

Keywords: software architecture, web-service, rule-based, DSS, multi-criteria requirements, quality attributes

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Authors: Simone Leonardi, Luca Ardito

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Micro-influencers are effective elements in the marketing strategies of companies and institutions because of their capability to create an hyper-engaged audience around a specific topic of interest. In recent years, many scientific approaches and commercial tools have handled the task of detecting this type of social media users. These strategies adopt solutions ranging from rule based machine learning models to deep neural networks and graph analysis on text, images, and account information. This work compares the existing solutions and proposes an ensemble method to generalize them with different input data and social media platforms. The deployed solution combines deep learning models on unstructured data with statistical machine learning models on structured data. We retrieve both social media accounts information and multimedia posts on Twitter and Instagram. These data are mapped into feature vectors for an eXtreme Gradient Boosting (XGBoost) classifier. Sixty different topics have been analyzed to build a rule based gold standard dataset and to compare the performances of our approach against baseline classifiers. We prove the effectiveness of our work by comparing the accuracy, precision, recall, and f1 score of our model with different configurations and architectures. We obtained an accuracy of 0.91 with our best performing model.

Keywords: deep learning, gradient boosting, image processing, micro-influencers, NLP, social media

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Authors: Suvankar Chakraborty

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Introduction: Corporate Social Responsibility means the obligations of business to act in a manner which will serve the best interests of the Society. The Companies Act , 2013 for the first time has emphasized on the fact that every company having net worth of rupees five hundred crore or more, or turnover of rupees one thousand crore or more or a net profit of rupees five crore or more during any financial year shall constitute a Corporate Social Responsibility Committee of the Board consisting of three or more directors, out of which at least one director shall be an independent director. In the previous Companies Act, 1956 there was no such compulsion for constituting a Corporate Social Responsibility Committee. Objective: This study examines the changes in the perception of corporate sectors so far as social responsibility is concerned. Methodology: The study is based on secondary data obtained from various websites of different corporate sectors and the Gazette of India related to Companies Act, 1956 and the new Companies Act, 2013. For capturing the perception of the corporate world regarding the provisions of CSR in the new Companies Act, 2013, primary data has been collected through structured questionnaire. Findings: Corporate Social Responsibility can put a company on a strong base of sustainable development and in facing the business risk of foreclosure or winding up. Shouldering social responsibility on a long-term basis can help a company not only in increasing its reputation in the business world but also helps in minimizing Government intervention. . But, there can hardly be any universal rule that the area of social responsibility being wholly and solely dependent on the ethical aspect of the corporate sectors. But having said that it may be asserted that business ethics may be a key driver of CSR activities rather than rule based CSR activities in the years to come.

Keywords: business ethics, corporate social responsibility, companies act, 2013, CSR committee

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Authors: Ren Moses, Jaqueline Masaki

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This paper addresses the need for accurate and updated vehicle classification system through a thorough evaluation of vehicle class categories to identify errors arising from the existing system and proposing modifications. The data collected from two permanent traffic monitoring sites in Florida were used to evaluate the performance of the existing vehicle classification table. The vehicle data were collected and classified by the automatic vehicle classifier (AVC), and a video camera was used to obtain ground truth data. The Federal Highway Administration (FHWA) vehicle classification definitions were used to define vehicle classes from the video and compare them to the data generated by AVC in order to identify the sources of misclassification. Six types of errors were identified. Modifications were made in the classification table to improve the classification accuracy. The results of this study include the development of updated vehicle classification table with a reduction in total error by 5.1%, a step by step procedure to use for evaluation of vehicle classification studies and recommendations to improve FHWA 13-category rule set. The recommendations for the FHWA 13-category rule set indicate the need for the vehicle classification definitions in this scheme to be updated to reflect the distribution of current traffic. The presented results will be of interest to States’ transportation departments and consultants, researchers, engineers, designers, and planners who require accurate vehicle classification information for planning, designing and maintenance of transportation infrastructures.

Keywords: vehicle classification, traffic monitoring, pavement design, highway traffic

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Authors: M. Karthigayan, M. Rizon, Sazali Yaacob, R. Nagarajan, M. Muthukumaran, Thinaharan Ramachandran, Sargunam Thirugnanam

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In this paper, using a set of irregular and regular ellipse fitting equations using Genetic algorithm (GA) are applied to the lip and eye features to classify the human emotions. Two South East Asian (SEA) faces are considered in this work for the emotion classification. There are six emotions and one neutral are considered as the output. Each subject shows unique characteristic of the lip and eye features for various emotions. GA is adopted to optimize irregular ellipse characteristics of the lip and eye features in each emotion. That is, the top portion of lip configuration is a part of one ellipse and the bottom of different ellipse. Two ellipse based fitness equations are proposed for the lip configuration and relevant parameters that define the emotions are listed. The GA method has achieved reasonably successful classification of emotion. In some emotions classification, optimized data values of one emotion are messed or overlapped to other emotion ranges. In order to overcome the overlapping problem between the emotion optimized values and at the same time to improve the classification, a fuzzy clustering method (FCM) of approach has been implemented to offer better classification. The GA-FCM approach offers a reasonably good classification within the ranges of clusters and it had been proven by applying to two SEA subjects and have improved the classification rate.

Keywords: ellipse fitness function, genetic algorithm, emotion recognition, fuzzy clustering

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Authors: Ahmet Kayabasi, Ali Akdagli

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In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.

Keywords: a-shaped compact microstrip antenna, artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM)

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Authors: M. Abbasi Layegh, S. Haghipour, K. Athari, R. Khosravi, M. Tafkikialamdari

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An approach to find the optimum mel-frequency cepstral coefficients (MFCCs) for the Radif of Mirzâ Ábdollâh, which is the principal emblem and the heart of Persian music, performed by most famous Iranian masters on two Iranian stringed instruments ‘Tar’ and ‘Setar’ is proposed. While investigating the variance of MFCC for each record in themusic database of 1500 gushe of the repertoire belonging to 12 modal systems (dastgâh and âvâz), we have applied the Fuzzy C-Mean clustering algorithm on each of the 12 coefficient and different combinations of those coefficients. We have applied the same experiment while increasing the number of coefficients but the clustering accuracy remained the same. Therefore, we can conclude that the first 7 MFCCs (V-7MFCC) are enough for classification of The Radif of Mirzâ Ábdollâh. Classical machine learning algorithms such as MLP neural networks, K-Nearest Neighbors (KNN), Gaussian Mixture Model (GMM), Hidden Markov Model (HMM) and Support Vector Machine (SVM) have been employed. Finally, it can be realized that SVM shows a better performance in this study.

Keywords: radif of Mirzâ Ábdollâh, Gushe, mel frequency cepstral coefficients, fuzzy c-mean clustering algorithm, k-nearest neighbors (KNN), gaussian mixture model (GMM), hidden markov model (HMM), support vector machine (SVM)

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Authors: Ana Neves

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The European Union’s multi-level constitutionalism is grounded in an intricate network of vertical and horizontal legal relationships among different levels and types of public authorities. In a very significant way since the 2008 crisis, evolving institutional arrangements and institutional dynamics in the European Union have been progressively impacting Member States and the terms under which national public authorities are organised, interact and exercise their powers. This impact occurs in both macro and micro dimensions. Several examples are relevant here, such as the involvement of national Parliaments in the activities of the European Union, the enhanced integration of public administrations, the side effects of the Council framework decision on the European Arrest Warrant, the European Union Justice Scoreboard, the protection of whistle-blowers regulation, the enhanced cooperation on the establishment of the European Public Prosecutor’s Office, the regime for the protection of the Union budget and the European Rule of Law Mechanism. A common trend or denominator underlies the deepening of institutional interdependence and the increased interactions between the European Union, Member States, and public authorities at different levels. This seems to be conditionality as a general principle. The European multi-level constitutionalism must be considered in the light of this conditionality principle, which does not “imply a relationship of command and obedience”. Nevertheless, it might be more effective or be a very compelling principle. It is as if the extension of the shared rule is being accompanied by a contrapuntal dialogue. The different public authorities at various levels are being called to rethink and readjust themselves within a broader and more plural framework concerning understanding the limitation of power.

Keywords: european union -, multi-level hierarchy, conditionality, separation of powers

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Authors: Aschalew C. Workneh, K. S. Hari Prasad, C. S. P. Ojha

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The crop water stress index (CWSI) is a cost-effective, non-destructive, and simple technique for tracking the start of crop water stress. This study investigated the feasibility of CWSI derived from canopy temperature to detect the water status of wheat crops. Artificial intelligence (AI) techniques have become increasingly popular in recent years for determining CWSI. In this study, the performance of two AI techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing maps (SOM), are compared while determining the CWSI of paddy crops. Field experiments were conducted for varying irrigation water applications during two seasons in 2022 and 2023 at the irrigation field laboratory at the Civil Engineering Department, Indian Institute of Technology Roorkee, India. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash-Sutcliffe efficiency (NSE), and coefficient of correlation (R²). Both models successfully estimated the CWSI of the paddy crop with higher correlation coefficients and lower statistical errors. However, the ANFIS (R²=0.81, NSE=0.73, d=0.94, RMSE=0.04, MAE= 0.00-1.76 and MBE=-2.13-1.32) outperformed the SOM model (R²=0.77, NSE=0.68, d=0.90, RMSE=0.05, MAE= 0.00-2.13 and MBE=-2.29-1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in wheat crops compared to SOM.

Keywords: adaptive neuro-fuzzy inference system, canopy temperature, crop water stress index, self-organizing map, wheat

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Authors: Isaac Alonge Olusola

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One of the major peculiarities of man is the ability to communicate and interact with language. The original Yoruba society, before the advent of the Europeans, was purely oral. That is the major means of inter- personal communication was through speaking. The abolition of slave trade by Britain marked the beginning of development of Yoruba alphabet and introduction of writing around 1800. However, most of the writing was Christian religion-focused. Later, the introduction of British colonial rule led to the introduction of writing that dwelt on political and economic emancipation. On October 1, 1960, Nigeria was granted independence by the British colonial masters and self-rule started in Nigeria. Unfortunately, the military and civilian administrations brought about political and economic oppression instead of comfort. The discomfort brought about by Nigerian political and military rulers turned the Yoruba poets to activists, reactionaries and critics. This paper will give a brief preamble on the history of Nigeria and how she got her political independence from the British in 1960. It will thereafter go further to mention some political and economic hardship brought about by Nigerian leaders. Using literary theories called semiotics and structuralism, the reactions and criticisms of some Yoruba poets will be mentioned and analyzed vis-à-vis the counter reactions of the governments in power. Moreover, the paper will bring about a conclusion on how to create a conducive atmosphere for the Yoruba poets to operate in Nigeria. Finally, suggestions will be offered on how the Nigerian government and Yoruba poets can co-exist positively to bring about a better standard of living to Nigerians and also promote good governance

Keywords: Yoruba, Yoruba language, Yoruba poets, political leaders

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Authors: Nodi Islam

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This paper critically reads Rumi’s poems in The Masnavi (Book One) and the philosophy of master-disciple relationship, as reflected as a medium to attain the higher consciousness in the poems which is considered as spiritual by the Sufi practitioners. This paper further applies the concept of collective consciousness introduced by Durkheim, which stands for a set of beliefs, ideas, moral attitudes that operate as a unifying force in a certain society, in reading Rumi’s poems. According to Sufi philosophy, in order to reach to the beloved who is the Higher Being, a lover has to be a disciple of a master and dedicate himself completely even if it means to give up the earthly desires. When the process is completed, he achieves the divinity which is the utmost happiness to be one with the beloved. As this process is considered spiritual by the Sufi practitioners, this paper suggests that, apart from being spiritual, this is a reflection of collective consciousness also. This process plays a part to construct the collectivity as a means to create masters and disciples. Collective consciousness operates in this particular belief system of Sufis who tend to follow this phenomenon as a rule of obedience and accepts the rule because this is how their particular community proceeds on. This paper offers a view of Rumi’s poems which reflect such relationship and tends to offer a general discussion on the hegemonic approach of the Sufi society especially of the Mevlevi order. Finally, this paper offers a constructive representation of Mevlevi society based upon the idea of spirituality which could be an outcome of psychological and social issues and practices.

Keywords: collective consciousness, divinity, master-disciple relationship, Mevlevi order

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Authors: Babak Safaei, A. M. Fattahi

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Polymer/carbon nanotube nanocomposites have a wide range of promising applications Due to their enhanced properties. In this work, free vibration analysis of single-walled carbon nanotube-reinforced composite plates is conducted in which carbon nanotubes are embedded in an amorphous polyethylene. The rule of mixture based on various types of plate model namely classical plate theory (CLPT), first-order shear deformation theory (FSDT), and higher-order shear deformation theory (HSDT) was employed to obtain fundamental frequencies of the nanocomposite plates. Generalized differential quadrature (GDQ) method was used to discretize the governing differential equations along with the simply supported and clamped boundary conditions. The material properties of the nanocomposite plates were evaluated using molecular dynamic (MD) simulation corresponding to both short-(10,10) SWCNT and long-(10,10) SWCNT composites. Then the results obtained directly from MD simulations were fitted with those calculated by the rule of mixture to extract appropriate values of carbon nanotube efficiency parameters accounting for the scale-dependent material properties. The selected numerical results are presented to address the influences of nanotube volume fraction and edge supports on the value of fundamental frequency of carbon nanotube-reinforced composite plates corresponding to both long- and short-nanotube composites.

Keywords: nanocomposites, molecular dynamics simulation, free vibration, generalized, differential quadrature (GDQ) method

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Authors: Mike Omilusi

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Since the Buhari administration came to power, it has gained the people’s confidence with its anti-corruption efforts. Making culprits account for their past unlawful deeds, in a very determined and aggressive manner ever witnessed in the nation’s political history, generates different reactions among Nigerians. However, some questions remain pertinent to this study: Are Nigerians really advocating persecution or prosecution in respect of the graft suspects? Do they want conviction without being convinced? Is their outburst propelled by emotions and revengeful anticipation of having suspected looters of the nation’s commonwealth behind bars? Can the war be successfully fought without resorting to impunity? Relying extensively on secondary sources with the aid of descriptive and narrative tools, this study seeks to interrogate the claim of fundamental human rights in the face of wanton looting of the nation’s resources. If, as opined by President Buhari, corruption is a crime against humanity, then it is argued that those who commit such crime should be subjected to penalties prescribed by law. Such crime -as corruption in this study- deprives the citizens of welfare, social amenities and good things of life. In this instance, it also poses threats to national security, having misappropriated funds meant for the war against the Boko Haram terrorism as revealed by the anti-corruption agency in the country. A theoretically-driven investigation, this essay raises some expectations within the context of good governance-propelled anti-corruption crusade, making modest recommendations as to how corruption should be prevented and combated within the confine of rule of law.

Keywords: corruption, rule of law, human rights, prosecution, commonwealth

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Authors: Ganesh B. Shinde, Vijaya B. Musande

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Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.

Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices

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Authors: Kyonghoon Kim, Wonyoung Park, Taeil Park

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In 1994, Korea experienced a national tragedy of Seongsu Bridge collapse. The accident was severe enough to alert governmental officers to the problem of existing management policy for national infrastructures. As a result, government legislated the ‘Guidelines for the safety inspection and test of infrastructure’ which have been utilized as the primary tool to make decision for the maintenance and rehabilitation of infrastructure for last twenty years. Although it is clear that the guideline established a basics how to evaluate and manage the condition of infrastructures in systematic manner, it is equally clear that the guideline needs improvements in order to obtain reasonable investment decisions for budget allocation. Because its inspection and evaluation procedures mainly focused on the structural condition of infrastructures, it was hard to make decision when the infrastructures were in same level of structural condition. In addition, it did not properly reflect various aspects of infrastructures such as performance, public demand, capacity, etc., which were more valuable to public. Regardless of the importance, these factors were commonly neglected in governmental decision-making process, because there factors were somewhat subjective and difficult to quantify in rational manner. Thus, this study proposes a framework to properly evaluate the serviceability indicators using AHP and Fuzzy approach. The framework is expected to assist governmental agency in establishing effective investment strategies for budget planning.

Keywords: infrastructure, evaluation, serviceability, fuzzy

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Authors: Ruby A. L. Espineli

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The study assessed the Philippine National Police strategies in the implementation of ‘Peace and Order Agenda for Transformation and Upholding of the Rule-of-Law’ P.A.T.R.O.L Plan 2030. Its operational roadmap presents four perspectives which include resource management, learning and growth, process excellence; and community. Focused group discussion, observation, and distribution of survey questionnaire to selected PNP officers and community members were done to identify and describe the implementation, problems encountered and measures to address the problems of the PNP P.A.T.R.O.L Plan 2030. In resource management, PNP allocates most sufficient funds in providing service firearms, patrol vehicle, and internet connections. In terms of learning and growth, the attitude of PNP officers is relatively higher than their knowledge and skills. Moreover, in terms of process excellence, the PNP use several crime preventions and crime solution strategies to deliver an immediate response to calls of the community. As regards, community perspective, PNP takes effort in establishing partnership with community. It is also interesting to note that PNP officers and community were both undecided on the existence of problems encountered in the implementation of P.A.T.R.O.L Plan 2030. But, they had proactive behavior as they agreed on all the specified measures to address the problems encountered in implementation of PNP P.A.T.R.O.L. Plan 2030. A strategic framework, based on the findings was formulated in this study that could improve and entrench the harmonious working relationship between the PNP and stakeholders in the enhancement of the implementation of PNP P.A.T.R.O.L. Plan 2030.

Keywords: community perspectives, learning and growth, process excellence, resource management

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Authors: Adele Pierre, Nadia Amoroso

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Changing climate patterns are resulting in increased in storm severity, challenging traditional methods of managing stormwater runoff. This research compares a system of bioswales to existing curb and gutter infrastructure in a post-industrial streetscape of Hamilton, Ontario. Using the geodesign process, including rule-based set parameters and an integrated approach combining geospatial information with stakeholder input, a section of Ottawa St. North was modelled to show how green infrastructure can ease the burden on aging, combined sewer systems. Qualitative data was gathered from residents of the neighbourhood through field notes, and quantitative geospatial data through GIS and site analysis. Parametric modelling was used to generate multiple design scenarios, each visualizing resulting impacts on stormwater runoff along with their calculations. The selected design scenarios offered both an aesthetically pleasing urban bioswale street-scape system while minimizing and controlling stormwater runoff. Interactive maps, videos and the 3D model were presented for stakeholder comment via ESRI’s (Environmental System Research Institute) web-scene. The results of the study demonstrate powerful tools that can assist landscape architects in designing, collaborating and communicating stormwater strategies.

Keywords: bioswale, geodesign, data-driven and rule-based design, geodesign, GIS, stormwater management

Procedia PDF Downloads 167