Search results for: international standard industrial classification

Authors: Aimite Jorge, Leenekela Usebiu

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In recent years the International Community has seen a rise of what can be termed as ‘actio popularis”;that is to say lawsuits brought by third parties in the interest of the public or the world community as a whole, such as in cases of genocide and terrorism prosecutions under international law. It is equally clear that under current globalized world the effect of multinational activities on the environment is often felt beyond the borders of the territories where they operate. Equally true is the fact that the correspondence of citizens self-determination with national government is increasingly upset by the increasing willingness of states to share some ‘sovereign powers’ in order to address new economic, environmental and security interdependencies. The ‘unbundling’ of functional governance from fixed territories sees continuously citizens give up their formal approval of key decisions in exchange for a more remote, indirect say in supra-national or international decision-making bodies. The efforts to address a growing transnational flow of ecological harm are at the forefront of such indirect transformations, as evidenced by a proliferation of multilateral environmental agreements (MEAs) over the past three decades. However, unlike the defence of the global commons in cases of terrorism and genocide, there is still to be a clear application of action popularis in the case of environment, despite acknowledgement that the effect of the activities of several multinationals on the environment is as destructive to the global commons as genocide or terrorism are. Thus, this paper looking at specific cases of harmful degradation of the environment by certain multinationals transcending national boundaries, argues that it is high-time for a serious consideration of the application of the actio-popularis to environmental concerns. Although it is acknowledged that in international environmental law the challenge to reach a “critical mass” of recognition and support for an ‘actio-popularis’ for environment damage is particularly demanding, it is worth the try.

Keywords: actio popularis in environment law, global commons, transnational environmental damage, law and environment

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Authors: Lottie Lane

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It is habitually assumed and stated that the World Bank should engage and comply with international human rights standards. However, the basis for holding the Bank to such standards is unclear. Most advocates of the idea invoke aspects of international law to argue that the Bank has existing obligations to act in compliance with human rights standards. The Bank itself, however, does not appear to accept such arguments, despite having endorsed the importance of human rights for a considerable length of time. A substantial challenge is that under the current international human rights law framework, the World Bank is considered a non-state actor, and as such, has no direct human rights obligations. In the absence of clear legal duties for the Bank, it is necessary to look at the tools available beyond the international human rights framework to encourage the Bank to comply with human rights standards. This article critically examines several bases for arguing that the Bank should comply and engage with human rights through its policies and practices. Drawing on the Bank’s own ‘good governance’ approach as well as the United Nations’ ‘human rights-based-approach’ to development, a new basis is suggested. First, the relationship between the World Bank and human rights is examined. Three perspectives are considered: (1) the legal position – what the status of the World Bank is under international human rights law, and whether it can be said to have existing legal human rights obligations; (2) the Bank’s own official position – how the Bank envisages its relationship with and role in the protection of human rights; and (3) the relationship between the Bank’s policies and practices and human rights (including how its attitudes are reflected in its policies and how the Bank’s operations impact human rights enjoyment in practice). Here, the article focuses on two examples – the (revised) 2016 Environmental and Social Safeguard Policies and the 2012 case-study regarding Gambella, Ethiopia. Both examples are widely considered missed opportunities for the Bank to actively engage with human rights. The analysis shows that however much pressure is placed on the Bank to improve its human rights footprint, it is extremely reluctant to do so explicitly, and the legal bases available are insufficient for requiring concrete, ex ante action by the Bank. Instead, the Bank’s own ‘good governance’ approach to development – which it has been advocating since the 1990s – can be relied upon. ‘Good governance’ has been used and applied by many actors in many contexts, receiving numerous different definitions. This article argues that human rights protection can now be considered a crucial component of good governance, at least in the context of development. In doing so, the article explains the relationship and interdependence between the two concepts, and provides three rationales for the Bank to take a ‘human rights-based approach’ to good governance. Ultimately, this article seeks to look beyond international human rights law and take a governance approach to provide a convincing basis upon which to argue that the World Bank should comply with human rights standards.

Keywords: World Bank, international human rights law, good governance, human rights-based approach

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Authors: Devendra Kr Tayal, Vrinda Gupta, Aastha Bansal, Khushi Singh, Sristi Sharma, Hunny Gaur

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In today's world, suicide is a serious problem. In order to save lives, early suicide attempt detection and prevention should be addressed. A good number of at-risk people utilize social media platforms to talk about their issues or find knowledge on related chores. Twitter and Reddit are two of the most common platforms that are used for expressing oneself. Extensive research has already been done in this field. Through supervised classification techniques like Nave Bayes, Bernoulli Nave Bayes, and Multiple Layer Perceptron on a Reddit dataset, we demonstrate the early recognition of suicidal ideation. We also performed comparative analysis on these approaches and used accuracy, recall score, F1 score, and precision score for analysis.

Keywords: machine learning, suicide ideation detection, supervised classification, natural language processing

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Authors: Rajaramamohanarao Chennu, S. Sudhakara Reddy, Gurudev T, Maroti

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With the invent of recent available technology and cost optimization, the switchgear assemblies are becoming more compact and designed to operate at critical levels of thermal and dielectric stress. At the same time, the switchgear assemblies shall be designed for protection of persons, met in the event of internal arc for specified installation conditions, according to the latest available national/international standards. These standards are revising regularly for better product design and personal safety. The switchgear assemblies design shall be modified in accordance with the change in requirements in the latest edition of the standards. This paper presents the signifying changes brought in the latest edition of 62271-200:2021 and effect of these changes and the necessitated design improvements for meeting internal arc test requirements is presented by carrying out the internal arc testing experiments on the switchgear assemblies at High Power Laboratory, Central Power Research Institute, Bangalore, India.

Keywords: internal arc, switchgear assembly, high speed videography, IEC 62271-200

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Authors: Soon-Mi Park, Ihn Sook Jeong

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This retrospective study was aimed to identify risk factors of intravenous (IV) infiltration for hospitalized children. The participants were 1,174 children for test and 424 children for validation, who admitted to a general hospital, received peripheral intravenous injection therapy at least once and had complete records. Data were analyzed with frequency and percentage or mean and standard deviation were calculated, and decision tree analysis was used to screen for the most important risk factors for IV infiltration for hospitalized children. The decision tree analysis showed that the most important traditional risk factors for IV infiltration were the use of ampicillin/sulbactam, IV insertion site (lower extremities), and medical department (internal medicine) both in the test sample and validation sample. The correct classification was 92.2% in the test sample and 90.1% in the validation sample. More careful attention should be made to patients who are administered ampicillin/sulbactam, have IV site in lower extremities and have internal medical problems to prevent or detect infiltration occurrence.

Keywords: decision tree analysis, intravenous infiltration, child, validation

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Authors: Filiz Ersoz, Taner Ersoz, Erkin Guler

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This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship.

Keywords: data mining, textile production, decision trees, classification

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Authors: Pramod Ghadge, Swadesh Srivastava

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Revenue generation of a logistics company depends on how the logistics cost of a shipment is calculated. Logistics cost of a shipment is a function of distance & speed of the shipment travel in a particular network, its volumetric size and dead weight. Logistics billing is based mainly on the consumption of the scarce resource (space or weight carrying capacity of a carrier). Shipment’s size or deadweight is a function of product and packaging weight, dimensions and flexibility. Hence, to arrive at a standard methodology to compute accurate cost to bill the customer, the interplay among above mentioned physical attributes along with their measurement plays a key role. This becomes even more complex for an ecommerce company, like Flipkart, which caters to shipments from both warehouse and marketplace in an unorganized non-standard market like India. In this paper, we will explore various methodologies to define a standard way of billing the non-standard shipments across a wide range of size, shape and deadweight. Those will be, usage of historical volumetric/dead weight data to arrive at a factor which can be used to compute the logistics cost of a shipment, also calculating the real/contour volume of a shipment to address the problem of irregular shipment shapes which cannot be solved by conventional bounding box volume measurements. We will also discuss certain key business practices and operational quality considerations needed to bring standardization and drive appropriate ownership in the ecosystem.

Keywords: contour volume, logistics, real volume, volumetric weight

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Authors: Ramin Mansouri

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The manhole is one of the types of structures that are installed at the site of change direction or change in the pipe diameter or sewage pipes as well as in step slope areas to reduce the flow velocity. In this study, the flow characteristics of hydraulic structures in a manhole structure have been investigated with a numerical model. In this research, the types of computational grid coarse, medium, and fines have been used for simulation. In order to simulate flow, k-ε model (standard, RNG, Realizable) and k-w model (standard SST) are used. Also, in order to find the best wall conditions, two types of standard and non-equilibrium wall functions were investigated. The turbulent model k-ε has the highest correlation with experimental results or all models. In terms of boundary conditions, constant speed is set for the flow input boundary, the output pressure is set in the boundaries which are in contact with the air, and the standard wall function is used for the effect of the wall function. In the numerical model, the depth at the output of the second manhole is estimated to be less than that of the laboratory and the output jet from the span. In the second regime, the jet flow collides with the manhole wall and divides into two parts, so hydraulic characteristics are the same as large vertical shaft hydraulic characteristics. In this situation, the turbulence is in a high range since it can be seen more energy loss in it. According to the results, energy loss in numerical is estimated at 9.359%, which is more than experimental data.

Keywords: manhole, energy, depreciation, turbulence model, wall function, flow

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Authors: Addin Osman, Anwar Ali Yahya, Mohammed Basit Kamal

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Datasets or collections are becoming important assets by themselves and now they can be accepted as a primary intellectual output of a research. The quality and usage of the datasets depend mainly on the context under which they have been collected, processed, analyzed, validated, and interpreted. This paper aims to present a collection of program educational objectives mapped to student’s outcomes collected from self-study reports prepared by 32 engineering programs accredited by ABET. The manual mapping (classification) of this data is a notoriously tedious, time consuming process. In addition, it requires experts in the area, which are mostly not available. It has been shown the operational settings under which the collection has been produced. The collection has been cleansed, preprocessed, some features have been selected and preliminary exploratory data analysis has been performed so as to illustrate the properties and usefulness of the collection. At the end, the collection has been benchmarked using nine of the most widely used supervised multiclass classification techniques (Binary Relevance, Label Powerset, Classifier Chains, Pruned Sets, Random k-label sets, Ensemble of Classifier Chains, Ensemble of Pruned Sets, Multi-Label k-Nearest Neighbors and Back-Propagation Multi-Label Learning). The techniques have been compared to each other using five well-known measurements (Accuracy, Hamming Loss, Micro-F, Macro-F, and Macro-F). The Ensemble of Classifier Chains and Ensemble of Pruned Sets have achieved encouraging performance compared to other experimented multi-label classification methods. The Classifier Chains method has shown the worst performance. To recap, the benchmark has achieved promising results by utilizing preliminary exploratory data analysis performed on the collection, proposing new trends for research and providing a baseline for future studies.

Keywords: ABET, accreditation, benchmark collection, machine learning, program educational objectives, student outcomes, supervised multi-class classification, text mining

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Authors: Ajish Sreedharan

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With the fast evolution of digital data exchange, security information becomes much important in data storage and transmission. Due to the increasing use of images in industrial process, it is essential to protect the confidential image data from unauthorized access. As encryption process is applied to the whole image in AES ,it is difficult to improve the efficiency. In this paper, wavelet decomposition is used to concentrate the main information of image to the low frequency part. Then, AES encryption is applied to the low frequency part. The high frequency parts are XORed with the encrypted low frequency part and a wavelet reconstruction is applied. Theoretical analysis and experimental results show that the proposed algorithm has high efficiency, and satisfied security suits for image data transmission.

Keywords: discrete wavelet transforms, AES, dynamic SBox

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Authors: Merve Begum Terzi, Orhan Arikan, Adnan Abaci, Mustafa Candemir

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Acute myocardial infarction is a major cause of death in the world. Therefore, its fast and reliable diagnosis is a major clinical need. ECG is the most important diagnostic methodology which is used to make decisions about the management of the cardiovascular diseases. In patients with acute myocardial ischemia, temporary chest pains together with changes in ST segment and T wave of ECG occur shortly before the start of myocardial infarction. In this study, a technique which detects changes in ST/T sections of ECG is developed for the early diagnosis of acute myocardial ischemia. For this purpose, a database of real ECG recordings that contains a set of records from 75 patients presenting symptoms of chest pain who underwent elective percutaneous coronary intervention (PCI) is constituted. 12-lead ECG’s of the patients were recorded before and during the PCI procedure. Two ECG epochs, which are the pre-inflation ECG which is acquired before any catheter insertion and the occlusion ECG which is acquired during balloon inflation, are analyzed for each patient. By using pre-inflation and occlusion recordings, ECG features that are critical in the detection of acute myocardial ischemia are identified and the most discriminative features for the detection of acute myocardial ischemia are extracted. A classification technique based on support vector machine (SVM) approach operating with linear and radial basis function (RBF) kernels to detect ischemic events by using ST-T derived joint features from non-ischemic and ischemic states of the patients is developed. The dataset is randomly divided into training and testing sets and the training set is used to optimize SVM hyperparameters by using grid-search method and 10fold cross-validation. SVMs are designed specifically for each patient by tuning the kernel parameters in order to obtain the optimal classification performance results. As a result of implementing the developed classification technique to real ECG recordings, it is shown that the proposed technique provides highly reliable detections of the anomalies in ECG signals. Furthermore, to develop a detection technique that can be used in the absence of ECG recording obtained during healthy stage, the detection of acute myocardial ischemia based on ECG recordings of the patients obtained during ischemia is also investigated. For this purpose, a Gaussian mixture model (GMM) is used to represent the joint pdf of the most discriminating ECG features of myocardial ischemia. Then, a Neyman-Pearson type of approach is developed to provide detection of outliers that would correspond to acute myocardial ischemia. Neyman – Pearson decision strategy is used by computing the average log likelihood values of ECG segments and comparing them with a range of different threshold values. For different discrimination threshold values and number of ECG segments, probability of detection and probability of false alarm values are computed, and the corresponding ROC curves are obtained. The results indicate that increasing number of ECG segments provide higher performance for GMM based classification. Moreover, the comparison between the performances of SVM and GMM based classification showed that SVM provides higher classification performance results over ECG recordings of considerable number of patients.

Keywords: ECG classification, Gaussian mixture model, Neyman–Pearson approach, support vector machine

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Authors: Ahmad Almaududy Amri

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Southeast Asia is considered as an area which is important in terms of piratical studies. There are several reasons to this argument: firstly, it has the second highest figure of piracy attacks in the world from 2008 to 2012. Only the African Region transcends the number of piracies that were committed in Southeast Asia. Secondly, the geographical location of the region is very important to world trade. There are several sea lanes and straits which are normally used for international navigation mainly for trade purposes. In fact, there are six out of 25 busiest ports all over the world located in Southeast Asia. In ancient times, the main drivers of piracy were raiding for plunder and capture of slaves; however, in modern times, developments in politics, economics and even military technology have drastically altered the universal crime of piracy. There are a variety of motives behind modern day piracy including economic gains from receiving ransoms from government or ship companies, political and even terrorist reasons. However, it cannot be denied that piratical attacks persist and continue. States have taken measures both at the international and regional level in order to eradicate piratical attacks. The United Nations Convention on the Law of the Sea and the Convention on the Suppression of Unlawful Act against the Safety of Navigation served as the two main international legal frameworks in combating piracy. At the regional level, Regional Cooperation Agreement against Piracy and Armed Robbery and ASEAN measures are regard as prominent in addressing the piracy problem. This paper will elaborate the problems of piracy in Southeast Asia and examine the adequacy of legal frameworks at both the international and regional levels in order address the current legal measures in combating piracy. Furthermore, it will discuss current challenges in the implementation of anti-piracy measures at the international and regional levels as well as the way forward in addressing the issue.

Keywords: piracy, Southeast Asia, maritime security, legal frameworks

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Authors: Andre C Jordaan

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The end of the Cold War and rivalry between super powers has changed the nature of military build-up in many countries. A call from international institutions like the United Nations, International Monetary Fund and the World Bank to reduce the levels of military expenditure was the order of the day. However, this bid to cut military expenditure has not been forthright. Recently, active armed conflicts occurred in at least 46 states in 2021 with 8 in the Americas, 9 in Asia and Oceania, 3 in Europe, 8 in the Middle East and North Africa and 18 in sub-Saharan Africa. Global military expenditure in 2022 was estimated to be US$2,2 trillion, representing 2.2 per cent of global gross domestic product. Particularly sharp rises in military spending have followed in African countries and the Middle East. Global military expenditure currently follows two divergent trends, either a declining trend in the West caused mainly by austerity, efforts to control budget deficits and the wrapping up of prolonged wars. However, some parts of the world shows an increasing trend on the back of security concerns, geopolitical ambitions and some internal political factors. Conflict related fatalities in sub-Saharan Africa alone increased by 19 per cent between 2020 and 2021. The interaction between military expenditure (read conflict) and international trade is generally the cause of much debate. Some argue that countries’ fear of losing trade opportunities causes political decision makers to refrain from engaging in conflict when important trading partners are involved. However, three main arguments are always present when discussing the relationship between military expenditure or conflicts and international trade: Free trade could promote peaceful cooperation, it could trigger tension between trading blocs and partners, and trade could have no effect because conflict is based on issues that are more important. Military expenditure remains an important element of the overall government expenditure in many African countries. On the other hand, numerous researchers perceive increased international trade to be one of the main factors promoting economic growth in these countries. The purpose of this paper is therefore to determine what effect, if any, exist between the level of military expenditure and international trade within a selection of 19 African countries. Applying an augmented gravity model to explore the relationship between military expenditure and international trade, evidence is found to confirm the existence of an inverse relationship between these two variables. It seems that the results are in line with the Liberal school of thought where trade is seen as an instrument of conflict prevention. Trade is therefore perceived as a symptom of peace and not a cause thereof. In general, conflict or rumors of conflict tend to reduce trade. If conflict did not impede trade, economic agents would be indifferent to risk. Many claim that trade brings peace, however, it seems that it is rather peace that brings trade. From the results, it appears that trade reduces the risk of conflict and that conflict reduces trade.

Keywords: African countries, conflict, international trade, military expenditure

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Authors: Gamal Shiha, Waleed Samir, Zahid Azam, Premashis Kar, Saeed Hamid, Shiv Sarin

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A simple, rapid and non-invasive electromagnetic sensor (C-FAST device) was- patented; for diagnosis of HCV RNA. Aim: To test the validity of the device compared to standard HCV PCR. Subjects and Methods: The first phase was done as pilot in Egypt on 79 participants; the second phase was done in five centers: one center from Egypt, two centers from Pakistan and two centers from India (800, 92 and 113 subjects respectively). The third phase was done nationally as multicenter study on (1600) participants for ensuring its representativeness. Results: When compared to PCR technique, C-FAST device revealed sensitivity 95% to 100%, specificity 95.5% to 100%, PPV 89.5% to 100%, NPV 95% to 100% and positive likelihood ratios 21.8% to 38.5%. Conclusion: It is practical evidence that HCV nucleotides emit electromagnetic signals that can be used for its identification. As compared to PCR, C-FAST is an accurate, valid and non-invasive device.

Keywords: C-FAST- a valid and reliable device, distant cellular interaction, electromagnetic signal detection, non-invasive diagnosis of HCV

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Authors: Agi Sunday, Agih Ukuru Agih

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In Nigeria, the food processing sector is dominated by small and medium enterprises, as well as multinational food companies. Quality standards are usually related to improving the safety of food products suitable for consumption in accordance to specifications by food regulatory bodies. These standards are essential elements for local and international businesses which contribute to economic progress through industrial development and trade. This review takes a critical look on the Nigerian food industry development in terms of quality standards that are necessary to be given consideration in the production of food and also ways of improving food production in Nigeria through the use of Total Quality Management (TQM) technique and the use of computerized systems to produce high quality and high value products while at the same time reducing production time and cost.

Keywords: food industry, quality assurance, Nigeria, TQM, computerized systems

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Authors: Shubhakar Gupta, Dhruv Prakash, Apoorv Mehta

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In this project, we design a modular robot capable of using and switching between multiple methods of propulsion and classifying terrain, based on an Inertial Measurement Unit (IMU) input. We wanted to make a robot that is not only intelligent in its functioning but also versatile in its physical design. The advantage of a modular robot is that it can be designed to hold several movement-apparatuses, such as wheels, legs for a hexapod or a quadpod setup, propellers for underwater locomotion, and any other solution that may be needed. The robot takes roughness input from a gyroscope and an accelerometer in the IMU, and based on the terrain classification from an artificial neural network; it decides which method of propulsion would best optimize its movement. This provides the bot with adaptability over a set of terrains, which means it can optimize its locomotion on a terrain based on its roughness. A feature like this would be a great asset to have in autonomous exploration or research drones.

Keywords: modular robotics, terrain detection, terrain classification, neural network

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Authors: Federico Pittino, Thomas Arnold

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The shredding of waste materials is a key step in the recycling process towards the circular economy. Industrial shredders for waste processing operate in very harsh operating conditions, leading to the need for frequent maintenance of critical components. Maintenance optimization is particularly important also to increase the machine’s efficiency, thereby reducing the operational costs. In this work, a monitoring system has been developed and deployed on an industrial shredder located at a waste recycling plant in Austria. The machine has been monitored for one year, and methods for predictive maintenance have been developed for two key components: the cutting knives and the drive belt. The large amount of collected data is leveraged by statistical machine learning techniques, thereby not requiring very detailed knowledge of the machine or its live operating conditions. The results show that, despite the wide range of operating conditions, a reliable estimate of the optimal time for maintenance can be derived. Moreover, the trade-off between the cost of maintenance and the increase in power consumption due to the wear state of the monitored components of the machine is investigated. This work proves the benefits of real-time monitoring system for the efficient operation of industrial shredders.

Keywords: predictive maintenance, circular economy, industrial shredder, cost optimization, statistical machine learning

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Authors: Jingpeng Gao, Xinrui Mao, Zhibin Deng

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Aiming at the low recognition rate on the composite signal modulation in low signal to noise ratio (SNR), this paper proposes a modulation recognition algorithm based on ICanny-CNN. Firstly, the radar signal is transformed into the time-frequency image by Choi-Williams Distribution (CWD). Secondly, we propose an image processing algorithm using the Guided Filter and the threshold selection method, which is combined with the hole filling and the mask operation. Finally, the shallow convolutional neural network (CNN) is combined with the idea of the depth-wise convolution (Dw Conv) and the point-wise convolution (Pw Conv). The proposed CNN is designed to complete image classification and realize modulation recognition of radar signal. The simulation results show that the proposed algorithm can reach 90.83% at 0dB and 71.52% at -8dB. Therefore, the proposed algorithm has a good classification and anti-noise performance in radar signal modulation recognition and other fields.

Keywords: modulation recognition, image processing, composite signal, improved Canny algorithm

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Authors: Nqobizwe Mvelo Ngema

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The right to equality has been accepted as one of the principles of jus cogens since the Second World War and it is protected in numerous international and regional human rights instruments. The convention on the elimination of all forms of discrimination against women (CEDAW) is a comprehensive document that serves as the international Bill of Rights for women and it prohibits polygamy. This paper examines whether the most unusual customary practice of polyandry would serve as a solution in elevating the status of women to be on par with that of man that are polygamists or not. This paper concludes by arguing that polyandry cannot solve the problem of inequalities that are confronted by women because even in polyandrous societies there is male domination that is detrimental to the equality rights of women.

Keywords: human rights, polygamy, polyandry, polygyny

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Authors: M. Tahir Demirsel, Mustafa Atsan

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Many elements of the environment in which businesses operate today leave them faced with unexpected threats and opportunities. One of the major threats is business crisis. The crisis is a state of affairs in a business wherein the executives must take urgent and unprecedented action to try to save the business from failure. In order to survive in the business environment, organizations should be prepared for the potential crises. Technological developments, uncertainty in the market and the intense competition increase the probability of encountering a crisis for organizations. Therefore, by acting proactively to predict crisis, to detect signals of crisis and be prepared for a crisis by taking necessary precautions accordingly, is of great importance for businesses. In this context, the objective of this study is to reveal that how much organizations are proactive and can predict the future crises and investigate whether they are prepared for possible crises or not. The research was conducted on 222 business executives in one of the major industrial zones of Turkey, Konya Organized Industrial Zone (KOS). The findings are analyzed through descriptive statistics and multiple regression analysis. According to the results, it has been observed that organizations cannot predict the crisis signals and are not prepared for potential crises.

Keywords: crisis preparedness, crisis signals, industrial organizations, proactivity

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Authors: Suraj Gururaj, Sumantha Udupa U.

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Browsing the Web has emerged as the de facto activity performed on the Internet. Although browsing gets tracked, the manageability aspect of Web browsing history is very poor. In this paper, we have a workable solution implemented by using machine learning and natural language processing techniques for efficient manageability of user’s browsing history. The significance of adding such a capability to a Web browser is that it ensures efficient and quick information retrieval from browsing history, which currently is very challenging. Our solution guarantees that any important websites visited in the past can be easily accessible because of the intelligent and automatic classification. In a nutshell, our solution-based paper provides an implementation as a browser extension by intelligently classifying the browsing history into most relevant category automatically without any user’s intervention. This guarantees no information is lost and increases productivity by saving time spent revisiting websites that were of much importance.

Keywords: adhoc retrieval, Chrome extension, supervised learning, tile, Web personalization

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Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

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Authors: Irfan Mohiuddin, Ahmad Al Mogren

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In recent years, cloud computing has earned substantial attention in the Oil and Gas Industry and provides services in all the phases of the industry lifecycle. Oil and gas supply infrastructure, in particular, is more vulnerable to accidental, natural and intentional threats because of its widespread distribution. Numerous surveys have been conducted on cloud security and privacy. However, to the best of our knowledge, hardly any survey is carried out that reviews cyber security in all phases with a cloud computing perspective. Moreover, a distinctive classification is performed for all the cloud-based cyber security measures based on the cloud component in use. The classification approach will enable researchers to identify the required technique used to enhance the security in specific cloud components. Also, the limitation of each component will allow the researchers to design optimal algorithms. Lastly, future directions are given to point out the imminent challenges that can pave the way for researchers to further enhance the resilience to cyber security threats in the oil and gas industry.

Keywords: cyber security, cloud computing, safety and security, oil and gas industry, security threats, oil and gas pipelines

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Authors: Zoltan Theisz, Gergely Mezei

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Modern industrial automation relies on service oriented concepts of Internet of Things (IoT) device modeling in order to provide a flexible and extendable environment for service meta-repository. However, state-of-the-art meta-modeling techniques prefer design-time modeling, which results in a heavy usage of class sometimes unnecessary static subtyping. Although this approach benefits from clear-cut object-oriented design principles, it also seals the model repository for further dynamic extensions. In this paper, a dynamic multi-level modeling approach is introduced that enables dynamic subtyping through a more relaxed partial instantiation mechanism. The approach is demonstrated on a simple sensor network example.

Keywords: meta-modeling, dynamic subtyping, DMLA, industrial automation, arrowhead

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Authors: Mary T. McKinley

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As socio-economic globalization impacts education and turns knowledge into a commodity, institutions of higher education are becoming more intentional about infusing a global and intercultural perspective into education via the recruitment of international students. Coming from dissimilar cultures, many of these students are evaluated and held accountable to Euro-American values of independence, self-reliance, and autonomy. Not surprisingly, these students often experience culture shock with deleterious effects on their mental health and academic functioning. Thus, it is critical to understand the experiences of international students with the hope that such knowledge will keep the field of psychology from promulgating Eurocentric ideals and values and prevent the training of these students as good-enough White therapists. Using a critical narrative inquiry framework, this study elicits stories about the challenges encountered by international students as they navigate their clinical training in the presence of acculturative stress and potentially different worldviews. With its emphasis on story-telling as meaning making, narrative research design is hinged on the assumption that people are interpretive beings who make meaning of themselves and their world through the language of stories. Also, dominant socially-constructed narratives play a central role in creating and maintaining hegemonic structures that privilege certain individuals and ideologies at the expense of others. On this premise, narrative inquiry begins with an exploration of the experiences of participants in their lived stories. Bounded narrative segments were read, interpreted, and analyzed using a critical events approach. Throughout the process, issues of reliability and researcher bias were addressed by keeping a reflective analytic memo, as well as triangulating the data using peer-reviewers and check-ins with participants. The findings situate culture at the epicenter of international students’ acculturation challenges as well as their resiliency in psychology doctoral programs. It was not uncommon for these international students to experience ethical dilemmas inherent in learning content that conflicted with their cultural beliefs and values. Issues of cultural incongruence appear to be further exacerbated by visible markers for differences like speech accent and clothing attire. These stories also link the acculturative stress reported by international students to the experiences of perceived racial discrimination and lack of support from the faculty, administration, peers, and the society at large. Beyond the impact on the international students themselves, there are implications for internationalization in psychology with the goal of equipping doctoral programs to be better prepared to meet the needs of their international students. More than ever before, programs need to liaise with international students’ services and work in tandem to meet the unique needs of this population of students. Also, there exists a need for multiculturally competent supervisors working with international students with varying degrees of acculturation. In addition to making social justice and advocacy salient in students’ multicultural training, it may be helpful for psychology doctoral programs to be more intentional about infusing cross-cultural theories, indigenous psychotherapies, and/or when practical, the possibility for geographically cross-cultural practicum experiences in the home countries of international students while taking into consideration the ethical issues for virtual supervision.

Keywords: decolonizing pedagogies, international students, multiculturalism, psychology doctoral programs

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Authors: Anne Camille P. Balabag, Via B. Cabarda, Ruffa Mae Lomboy, Aira Joyce Nesus

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Nowadays, Filipinos seem to dominate the outsourcing industry, one factor that affects quality service is organization mismanagement. Traditionally, Filipino promotions are based on tenure rather than competence. Seniority refers to a superior rank that an employee holds in an industrial setting based on a position withheld in a company. Yet, seniority also holds the paradigm for Filipino family structures. With this, the researchers believe that Filipinos have a deeper take on seniority, which became the motivation for this study. The researchers wanted to contextualize the Filipino concept of seniority, the perception, and reactions of Filipino employees to its existence, and uncover their relevant experiences within the industrial setting. Following a phenomenological research design, data collected from ten (10) participants with various demographic backgrounds, chosen through purposive sampling, and interviewed utilizing a semi-structured interview and analyzed using thematic analysis revealed seven primary themes: (1) Reality of Tenureship and Competence, (2) Disparity in Age Influence, (3) Special Power of Seniority, (4) Seniority is Necessity, (5) The Filipino Organizational Values, (6) Art of Seniority in Human Resource, and (7) Confessions of the Inner Child. The findings suggest that seniority exists based on a ranking system created through human resource management and mirrored from traditional Filipino values. Also, the researchers identified three Filipino industrial values: respect, pakikipagkapwa-tao (treating others as a fellow human being), and utang na loob (debt of gratitude). Lastly, birth order was found to have direct and indirect effects on their conduct in an industrial context.

Keywords: organizational psychology, human resource management, filipino psychology, industrial values

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Authors: A. van Staden, A. A. van Rhyn

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The numerous challenges South African, ESL learners experience were highlighted by the results of several literacy surveys and tests, which demonstrated that our learners’ literacy abilities are far below standard and very weak compared to other international countries. This study developed and implemented an interactive storybook intervention program to support the reading development of ESL learners. The researchers utilized an experimental pre-test/post-test research design, whereby 80 ESL learners from five participating schools, were purposively sampled to take part in this study. This paper, inter alia, discusses the key features of this intervention program whilst also reporting the results of the experimental investigation. Results are promising and show a significant improvement in the mean scores of the learners in the experimental group. Moreover, the results show the value of interactive storybook reading in creating responsive literacy environments to develop the literacy skills of ESL learners.

Keywords: ESL learners, reading comprehension, Interactive story book reading, South Africa

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Authors: Stefan Werrlich, Phuc-Anh Nguyen, Kai Nitsche, Gunther Notni

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Augmented Reality (AR) is a strong growing research topic. This innovative technology is interesting for several training domains like education, medicine, military, sports and industrial use cases like assembly and maintenance tasks. AR can help to improve the efficiency, quality and transfer of training tasks. Due to these reasons, AR becomes more interesting for big companies and researchers because the industrial domain is still an unexplored field. This paper presents the research proposal of a PhD thesis which is done in cooperation with the BMW Group, aiming to explore head-mounted display (HMD) based training in industrial environments. We give a short introduction, describing the motivation, the underlying problems as well as the five formulated research questions we want to clarify along this thesis. We give a brief overview of the current assembly training in industrial environments and present some AR-based training approaches, including their research deficits. We use the Design Science Research (DSR) framework for this thesis and describe how we want to realize the seven guidelines, mandatory from the DSR. Furthermore, we describe each methodology which we use within that framework and present our approach in a comprehensive figure, representing the entire thesis.

Keywords: assembly, augmented reality, research proposal, training

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Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

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An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

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Authors: Alberto Sanchidrián, José A. Parra, Jesús Alonso, Julián Pecharromán, Antonia Pacios, Consuelo Huerta

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Glass is a commonly used material in building; there is not a unique design solution as plates with a different number of layers and interlayers may be used. In most façades, a security glazing have to be used according to its performance in the impact pendulum. The European Standard EN 12600 establishes an impact test procedure for classification under the point of view of the human security, of flat plates with different thickness, using a pendulum of two tires and 50 kg mass that impacts against the plate from different heights. However, this test does not replicate the actual dimensions and border conditions used in building configurations and so the real stress distribution is not determined with this test. The influence of different boundary conditions, as the ones employed in construction sites, is not well taking into account when testing the behaviour of safety glazing and there is not a detailed procedure and criteria to determinate the glass resistance against human impact. To reproduce the actual boundary conditions on site, when needed, the pendulum test is arranged to be used "in situ", with no account for load control, stiffness, and without a standard procedure. Fracture stress of small and large glass plates fit a Weibull distribution with quite a big dispersion so conservative values are adopted for admissible fracture stress under static loads. In fact, test performed for human impact gives a fracture strength two or three times higher, and many times without a total fracture of the glass plate. Newest standards, as for example DIN 18008-4, states for an admissible fracture stress 2.5 times higher than the ones used for static and wing loads. Now two working areas are open: a) to define a standard for the ‘in situ’ test; b) to prepare a laboratory procedure that allows testing with more real stress distribution. To work on both research lines a laboratory that allows to test medium size specimens with different border conditions, has been developed. A special steel frame allows reproducing the stiffness of the glass support substructure, including a rigid condition used as reference. The dynamic behaviour of the glass plate and its support substructure have been characterized with finite elements models updated with modal tests results. In addition, a new portable impact machine is being used to get enough force and direction control during the impact test. Impact based on 100 J is used. To avoid problems with broken glass plates, the test have been done using an aluminium plate of 1000 mm x 700 mm size and 10 mm thickness supported on four sides; three different substructure stiffness conditions are used. A detailed control of the dynamic stiffness and the behaviour of the plate is done with modal tests. Repeatability of the test and reproducibility of results prove that procedure to control both, stiffness of the plate and the impact level, is necessary.

Keywords: glass plates, human impact test, modal test, plate boundary conditions

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