Search results for: projection operations

Authors: M. Kamal, Y. Wang, R. Kennon

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Quality Function Deployment is a useful tool in product development with the application of voice of customer. In this paper, it aims to be applied as a product development tool in redesigning fashion and textile product. The purpose of these studies is to apply the effective use of Voice of Customer in redesigning cultural fashion product. The data collection from Voice of Customer or consumers’ feedback might help the producer to improve the quality of merchandise ahead. Voice of Customer could give a specific detailing for quality which needs to be redesigned according to customers’ requirements. Meanwhile, the next objective is to differentiate design specifications and characteristics using House of Quality. In product designing phase, it is very important to distinguish each specification and characteristic which translated from Voice of Customer to House of Quality matrix. This matrix would help designers to development according to qualities that customer wants for the better and successful product in the market. It is hope this research would indicate the customers’ requirements and production team idea might be measured and translated to a systematic data. The specific technical data could be planned ahead with specific design details as well. This could be a sustainable approach for a traditional product which could control the material that they use and sustain the quality as the past production. As a conclusion, this study would benefit the Small Medium Enterprises design team or the designers to style an item from customers view with organised projection of the product. The finding also could assist designers or batik producers’ to recognise specific details Batik sarong from consumers as well as in in advertising and marketing strategy plan.

Keywords: house of quality, Malaysia batik sarong, quality function deployment, voice of customer

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Authors: Nyashadzashe Chiraga, Anthony Walker, Glen Bright

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The manufacturing industry is currently experiencing a paradigm shift into the Fourth Industrial Revolution in which customers are increasingly at the epicentre of production. The high degree of production customization and personalization requires a flexible manufacturing system that will rapidly respond to the dynamic and volatile changes driven by the market. They are a gap in technology that allows for the optimal flow of information and optimal manufacturing operations on the shop floor regardless of the rapid changes in the fixture and part demands. Information is the reduction of uncertainty; it gives meaning and context on the state of each cell. The amount of information needed to describe cellular manufacturing systems is investigated by two measures: the structural entropy and the operational entropy. Structural entropy is the expected amount of information needed to describe scheduled states of a manufacturing system. While operational entropy is the amount of information that describes the scheduled states of a manufacturing system, which occur during the actual manufacturing operation. Using Anylogic simulator a typical manufacturing job shop was set-up with a cellular manufacturing configuration. The cellular make-up of the configuration included; a Material handling cell, 3D Printer cell, Assembly cell, manufacturing cell and Quality control cell. The factory shop provides manufactured parts to a number of clients, and there are substantial variations in the part configurations, new part designs are continually being introduced to the system. Based on the normal expected production schedule, the schedule adherence was calculated from the structural entropy and operation entropy of varying the amounts of information communicated in simulated runs. The structural entropy denotes a system that is in control; the necessary real-time information is readily available to the decision maker at any point in time. For contractive analysis, different out of control scenarios were run, in which changes in the manufacturing environment were not effectively communicated resulting in deviations in the original predetermined schedule. The operational entropy was calculated from the actual operations. From the results obtained in the empirical study, it was seen that increasing, the efficiency of a factory communication system increases the degree of adherence of a job to the expected schedule. The performance of downstream production flow fed from the parallel upstream flow of information on the factory state was increased.

Keywords: information entropy, communication in manufacturing, mass customisation, scheduling

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Authors: Taeho Park, Ming Zhou, Sangryul Shim

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With the emergence of the global economy, today’s business environment is getting more competitive than ever in the past. And many supply chain (SC) strategies and operations have significantly been altered over the past decade to overcome more complexities and risks imposed onto the global business. First, offshoring and outsourcing are more adopted as operational strategies. Manufacturing continues to move to better locations for enhancing competitiveness. Second, international operations are a challenge to a company’s SC system. Third, the products traded in the SC system are not just physical goods, but also digital goods (e.g., software, e-books, music, video materials). There are three main flows involved in fulfilling the activities in the SC system: physical flow, information flow, and financial flow. An advance of the Internet and electronic communication technologies has enabled companies to perform the flows of SC activities in electronic formats, resulting in the advent of an electronic supply chain management (e-SCM) system. A SC system for digital goods is somewhat different from the supply chain system for physical goods. However, it involves many similar or identical SC activities and flows. For example, like the production of physical goods, many third parties are also involved in producing digital goods for the production of components and even final products. This research aims at identifying process flows of both physical and digital goods in a SC system, and then investigating all risk elements involved in the physical, information, and financial flows during the fulfilment of SC activities. There are many risks inherent in the e-SCM system. Some risks may have severe impact on a company’s business, and some occur frequently but are not detrimental enough to jeopardize a company. Thus, companies should assess the impact and frequency of those risks, and then prioritize them in terms of their severity, frequency, budget, and time in order to be carefully maintained. We found risks involved in the global trading of physical and digital goods in four different categories: environmental risk, strategic risk, technological risk, and operational risk. And then the significance of those risks was investigated through a survey. The survey asked companies about the frequency and severity of the identified risks. They were also asked whether they had faced those risks in the past. Since the characteristics and supply chain flows of digital goods are varying industry by industry and country by country, it is more meaningful and useful to analyze risks by industry and country. To this end, more data in each industry sector and country should be collected, which could be accomplished in the future research.

Keywords: digital goods, e-SCM, risk analysis, supply chain flows

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Authors: Canapi Patricia Joy, Canlas Tracy Gabriella, Canseco Teresa, Capistrano Reena Marie, Carandang Vernon, Carbonel Khiara Claudine

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Research problem: The main problem of the study was to determine the effect of Projecting the Reflection of the Individual’s Self-esteem (PRIDE) therapy on the level of self-esteem of physically challenged adolescents. Objectives of the Study: The study determined the effect of PRIDE (Projecting the Reflection of the Individuals Self-esteem) therapy on the level of self-esteem among physically challenged adolescents. Methodology: A quasi-experimental study was used which involved 30 randomly-assigned subjects, 15 in the experimental group and 15 in the control group. The Projecting the reflection of the Individuals’ Self-Esteem (PRDIE) therapy was administered to the experimental group. The researchers utilized the Sorensen Self-Esteem test tool as a pretest and posttest questionnaire and yielded a Cronbach’s alpha of .912. Paired T-test was used to analyze the gathered data. Results: The results showed that after the administration of PRIDE therapy, there was an increase on the level of self-esteem. The experimental group had a value of 3.590, which was significant and meant that the level of self-esteem is significantly increased. On the other hand, the control group, had a value of -2.207 which was also significant, therefore, the level of self esteem significantly decreased. Conclusion: the PRIDE Therapy is effective in increasing the level of self-esteem among physically challenged adolescent. Recommendations: The researchers recommend the use of PRIDE Therapy as an intervention in handling physically challenged patients, especially adolescents, in order to enhance their self-esteem. Also, the researchers recommend that nursing students be informed on the efficacy of PRIDE Therapy in enhancing the self-esteem of physically challenged patients. Furthermore, the inclusion of a psychologist during the implementation of PRIDE Therapy, specifically art therapy, to be able to have a more focused interpretation of the drawings and really be able to see the projection of their self-esteem is also recommended.

Keywords: adolescents, PRIDE therapy, physically challenged, self-esteem

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Authors: Thea Freese, Michael Gille, Andrew Hursthouse, John Struthers

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Ship operators on the North and Baltic Sea have been experiencing increased political interest in marine environmental protection and cleaner vessel operations. Stricter legislation on SO2 and NOx emissions, ballast water management and other measures of protection are currently being phased in or will come into force in the coming years. These measures benefit the health of the marine environment, while increasing company’s operational costs. In times of excess shipping capacity and linked consolidation in the industry non-compliance with environmental rules is one way companies might hope to stay competitive with both intra- and inter-modal trade. Around 5-15% of industry participants are believed to neglect laws on vessel-source pollution willingly or unwillingly. Exploratory in-depth interviews conducted with 12 experts from various stakeholder groups informed the researchers about variables influencing compliance levels, including awareness and apprehension, willingness to comply, ability to comply and effectiveness of controls. Semi-structured expert interviews were evaluated using qualitative content analysis. A model of determinants of compliance was developed and is presented here. While most vessel operators endeavour to achieve full compliance with environmental rules, a lack of availability of technical solutions, expediency of implementation and operation and economic feasibility might prove a hindrance. Ineffective control systems on the other hand foster willing non-compliance. With respect to motivations, lacking time, lacking financials and the absence of commercial advantages decrease compliance levels. These and other variables were inductively developed from qualitative data and integrated into a model on environmental compliance. The outcomes presented here form part of a wider research project on economic effects of maritime environmental legislation. Research on determinants of compliance might inform policy-makers about actual behavioural effects of shipping companies and might further the development of a comprehensive legal system for environmental protection.

Keywords: compliance, marine environmental protection, exploratory qualitative research study, clean vessel operations, North and Baltic Sea area

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Authors: Emin Gundogar, Burak Erkayman, Aysegul Yilmaz, Nusret Sazak

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When considering current competition conditions on the world, satisfying customer demands on time has become an important factor that enables the firms take a step further. Therefore, production process must be completed faster to take the competitive advantage. A balanced assembly line is the one of most important factors affecting the speed of production lines. The aim of this study is to build an assembly line to balance the assembly line and to simulate it for different scenarios through a refrigerator factory. The times of the operations is analyzed and grouped by the priorities. First, a Kilbridge & Wester heuristics is put to the model then a simulation approach is implemented to the model and the differences are observed.

Keywords: assembly line design, assembly line balancing, simulation modelling, refrigeration industry

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Authors: Swee Kun Yap, Sachin Jangam, Suraj Vasudevan

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Experiential learning is dubbed as a highly effective way to enhance learning. Virtual reality (VR) is thus a helpful tool in providing a safe, memorable, and interactive learning environment. A class of 49 fluid mechanics students participated in starting up a pump, one of the most used equipment in the chemical industry, in VR. They experience the process in VR to familiarize themselves with the safety training and the standard operating procedure (SOP) in guided mode. Students subsequently observe their peers (in groups of 4 to 5) complete the same training. The training first brings each user through the personal protection equipment (PPE) selection, before guiding the user through a series of steps for pump startup. One of the most common feedback given by industries include the weakness of our graduates in pump design and operation. Traditional fluid mechanics is a highly theoretical module loaded with engineering equations, providing limited opportunity for visualization and operation. With VR pump, students can now learn to startup, shutdown, troubleshoot and observe the intricacies of a centrifugal pump in a safe and controlled environment, thereby bridging the gap between theory and practical application. Following the completion of the guided mode operation, students then individually complete the VR assessment for pump startup on the same day, which requires students to complete the same series of steps, without any cues given in VR to test their recollection rate. While most students miss out a few minor steps such as the checking of lubrication oil and the closing of minor drain valves before pump priming, all the students scored full marks in the PPE selection, and over 80% of the students were able to complete all the critical steps that are required to startup a pump safely. The students were subsequently tested for their recollection rate by means of an online quiz 3 weeks later, and it is again found that over 80% of the students were able to complete the critical steps in the correct order. In the survey conducted, students reported that the VR experience has been enjoyable and enriching, and 79.5% of the students voted to include VR as a positive supplementary exercise in addition to traditional teaching methods. One of the more notable feedback is the higher ease of noticing and learning from mistakes as an observer rather than as a VR participant. Thus, the cycling between being a VR participant and an observer has helped tremendously in their knowledge retention. This reinforces the positive impact VR has on learning.

Keywords: experiential learning, learning by doing, pump, unit operations, virtual reality

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Authors: Hussain K. Chaiel

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The development in the field of the digital signal processing (DSP) and the microelectronics technology reduces the complexity of the iterative algorithms that need large number of arithmetic operations. Virtex-Field Programmable Gate Arrays (FPGAs) are programmable silicon foundations which offer an important solution for addressing the needs of high performance DSP designer. In this work, Virtex-7 FPGA technology is used to implement an iterative algorithm to estimate the earthquake location. Simulation results show that an implementation based on block RAMB36E1 and DSP48E1 slices of Virtex-7 type reduces the number of cycles of the clock frequency. This enables the algorithm to be used for earthquake prediction.

Keywords: DSP, earthquake, FPGA, iterative algorithm

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Authors: Albert Kwabena Osei Konadu

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Pterocarpus erinaceus, also known as Rosewood, is tropical wood, endemic in forest savannah transition zones within the middle and northern portion of Ghana. Its economic viability has made it increasingly popular and in high demand, leading to widespread conservation concerns. Ghana’s forest resource management regime for these ecozones is mainly on conservation and very little on resource utilization. Consequently, commercial logging management standards are at teething stage and not fully developed, leading to a deficiency in the monitoring of logging operations and quantification of harvested trees volumes. Tree information form (TIF); a volume estimation and tracking regime, has proven to be an effective, sustainable management tool for regulating timber resource extraction in the high forest zones of the country. This work aims to generate TIF that can track and capture requisite parameters to accurately estimate the volume of harvested rosewood within forest savannah transition zones. Tree information forms were created on three scenarios of individual billets, stacked billets and conveying vessel basis. These TIFs were field-tested to deduce the most viable option for the tracking and estimation of harvested volumes of rosewood using the smallian and cubic volume estimation formula. Overall, four districts were covered with individual billets, stacked billets and conveying vessel scenarios registering mean volumes of 25.83m3,45.08m3 and 32.6m3, respectively. These adduced volumes were validated by benchmarking to assigned volumes of the Forestry Commission of Ghana and known standard volumes of conveying vessels. The results did indicate an underestimation of extracted volumes under the quotas regime, a situation that could lead to unintended overexploitation of the species. The research revealed conveying vessels route is the most viable volume estimation and tracking regime for the sustainable management of the Pterocarpous erinaceus species as it provided a more practical volume estimate and data extraction protocol.

Keywords: convention on international trade in endangered species, cubic volume formula, forest transition savannah zones, pterocarpus erinaceus, smallian’s volume formula, tree information form

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Authors: Jamie Wong, Daisy Sang, Chang-Shyh Peng

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Geofence is a virtual fence defined by a preset physical radius around a target location. Geofencing App provides location-based services which define the actionable operations upon the crossing of a geofence. Geofencing requires continual location tracking, which can consume noticeable amount of battery power. Additionally, location updates need to be frequent and accurate or order so that actions can be triggered within an expected time window after the mobile user navigate through the geofence. In this paper, we build an Android mobile geofencing Application to remotely and autonomously control a power switch.

Keywords: location based service, geofence, autonomous, remote switch

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Authors: Nayira Ahmed GalalElden Hassan

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The management of Intellectual Property (IP) in museums can be complex and challenging, as it requires balancing access and control. On the one hand, museums must ensure that they have balanced permissions to display works in their collections and make them accessible to the public. On the other hand, they must also protect the rights of creators and owners of works and ensure that they are not infringing on IP rights. Intellectual property has become an increasingly important aspect of museum operations in the digital age. Museums hold a vast array of cultural assets in their collections, many of which have significant value as IP assets. The balanced management of IP in museums can help generate additional revenue and promote cultural heritage while also protecting the rights of the museum and its collections. Digital technologies have greatly impacted the way museums manage IP, providing new opportunities for revenue generation through e-commerce and licensing while also presenting new challenges related to IP protection and management. Museums must take a comprehensive approach to IP management, leveraging digital technologies, protecting IP rights, and engaging in licensing and e-commerce activities to maximize income and the economy of countries through the strong management of cultural institutions. Overall, the balanced management of IP in museums is crucial for ensuring the sustainability of museum operations and for preserving cultural heritage for future generations. By taking a balanced approach to identifying museum IP assets, museums can generate revenues and secure their financial sustainability to ensure the long-term preservation of their cultural heritage. We can divide IP assets in museums into two kinds: collection IP and museum-generated IP. Certain museums become confused and lose sight of their mission when trying to leverage collections-based IP. This was the case at the German State Museum in Berlin when the museum made 100 replicas from the Nefertiti bust and wrote under the replicas all rights reserved to the Berlin Museum and issued a certificate to prevent any person or Institution from reproducing any replica from this bust. The implications of IP in museums are far-reaching and can have significant impacts on the preservation of cultural heritage, the dissemination of information, and the development of educational programs. As such, it is important for museums to have a comprehensive understanding of IP laws and regulations and to properly manage IP to avoid legal liability, damage to reputation, and loss of revenue. The research aims to highlight the importance and role of intellectual property in museums and provide some illustrative examples of this.

Keywords: intellectual property, museum, cultural assets, sustainability, IP management

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Authors: Assad Maalouf, Lunjin Lu, James Lynott

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We present a taint analysis that can automatically detect when string operations result in a string that is free of taints, where all the tainted patterns have been removed. This is an improvement on the conservative behavior of previous taint analyzers, where a string operation on a tainted string always leads to a tainted string unless the operation is manually marked as a sanitizer. The taint analysis is built on top of a string analysis that uses finite state automata to approximate the sets of values that string variables can take during the execution of a program. The proposed approach has been implemented as an extension of FlowDroid and experimental results show that the resulting taint analyzer is much more precise than the original FlowDroid.

Keywords: android, static analysis, string analysis, taint analysis

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Authors: Elhussaien Elshiekh

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A study was performed to management and compare radiation doses and image quality during Lumbar spine PA and Lumbar spine LAT, x- ray radiography using Computed Radiography (CR) and Digital Radiography (DR). Standard exposure factors such as kV, mAs and FFD used for imaging the Lumbar spine anthropomorphic phantom obtained from average exposure factors that were used with CR in five radiology centres. Lumbar spine phantom was imaged using CR and DR systems. Entrance surface air kerma (ESAK) was calculated X-ray tube output and patient exposure factor. Images were evaluated using visual grading system based on the European Guidelines on Quality Criteria for diagnostic radiographic images. The ESAK corresponding to each image was measured at the surface of the phantom. Six experienced specialists evaluated hard copies of all the images, the image score (IS) was calculated for each image by finding the average score of the Six evaluators. The IS value also was used to determine whether an image was diagnostically acceptable. The optimum recommended exposure factors founded here for Lumbar spine PA and Lumbar spine LAT, with respectively (80 kVp,25 mAs at 100 cm FFD) and (75 kVp,15 mAs at 100 cm FFD) for CR system, and (80 kVp,15 mAs at100 cm FFD) and (75 kVp,10 mAs at 100 cm FFD) for DR system. For Lumbar spine PA, the lowest ESAK value required to obtain a diagnostically acceptable image were 0.80 mGy for DR and 1.20 mGy for CR systems. Similarly for Lumbar spine LAT projection, the lowest ESAK values to obtain a diagnostically acceptable image were 0.62 mGy for DR and 0.76 mGy for CR systems. At standard kVp and mAs values, the image quality did not vary significantly between the CR and the DR system, but at higher kVp and mAs values, the DR images were found to be of better quality than CR images. In addition, the lower limit of entrance skin dose consistent with diagnostically acceptable DR images was 40% lower than that for CR images.

Keywords: image quality, dosimetry, radiation protection, optimization, digital radiography, computed radiography

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Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin

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Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.

Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network

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Authors: S. Malisuwan, J. Sivaraks, N. Madan, N. Suriyakrai

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The ever going evolution of advanced wireless technologies makes it financially impossible for military operations to completely manufacture their own equipment. Therefore, Commercial-Off-The-Shelf (COTS) and Modified-Off-The-Shelf (MOTS) are being considered in military mission with low-cost modifications. In this paper, we focus on the LTE multicast systems for military communication systems under tactical environments with jamming condition. We examine the influence of the colored noise jamming on the performance of the LTE multicast systems in terms of the average throughput. The simulation results demonstrate the degradation of the average throughput for different dynamic ranges of the colored noise jamming versus average SNR.

Keywords: performance, LTE, multicast, jamming, throughput

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Authors: Chakrit Chotamonsak, Eric P. Salathé Jr, Jiemjai Kreasuwan

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Dynamical downscaling of the ECHAM5 global climate model is applied at 20-km horizontal resolution using the WRF regional climate model (WRF-ECHAM5), to project changes from 1990–2009 to 2045–2064 of temperature and precipitation over the Upper Ping River Basin. The analysis found that monthly changes in daily temperature and precipitation over the basin for the 2045-2064 compared to the 1990-2009 are revealed over the basin all months, with the largest warmer in December and the smallest warmer in February. The future simulated precipitation is smaller than that of the baseline value in May, July and August, while increasing of precipitation is revealed during pre-monsoon (April) and late monsoon (September and October). This means that the rainy season likely becomes longer and less intensified during the rainy season. During the cool-dry season and hot-dry season, precipitation is substantial increasing over the basin. For the annual cycle of changes in daily temperature and precipitation over the upper Ping River basin, the largest warmer in the mean temperature over the basin is 1.93 °C in December and the smallest is 0.77 °C in February. Increase in nighttime temperature (minimum temperature) is larger than that of daytime temperature (maximum temperature) during the dry season, especially in wintertime (November to February), resulted in decreasing the diurnal temperature range. The annual and seasonal changes in daily temperature and precipitation averaged over the basin. The annual mean rising are 1.43, 1.54 and 1.30 °C for mean temperature, maximum temperature and minimum temperature, respectively. The increasing of maximum temperature is larger than that of minimum temperature in all months during the dry season (November to April).

Keywords: climate change, regional climate model, upper Ping River basin, WRF

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Authors: Alsnosy Balbaa, Mohamed Nabil Elnabawi, Yasmin El Meladi

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With the ever-growing concerns of climate change, Mediterranean ports, as vital economic and transport hubs face unique challenges in maintaining operations and infrastructure. This empirical study seeks to understand the current adaptations and preparedness levels of Egyptian Mediterranean ports against climate-induced disruptions. Drawing from a structured questionnaire, the research gathers insights on observed climate impacts, infrastructure adaptations, operational changes, and stakeholder engagement, aiming to shed light on the resilience of these ports in the face of a changing climate.

Keywords: climate, infrastructures, port, mediterranean

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Authors: Djelloul Chafia, Demagh Rafik, Kareche Toufik

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Human activities, made without precautions, accelerate the degradation of the soil structure and reduces its resistance. Operations, such as tunnel construction may exercise an influence more or less permanent on the grounds which surrounded them, these structures alter soil it is necessary to predict their impacts by suitable measures. This research is a numerical analysis that deals the risks and effects due to the weakening of the soil after digging two parallel vertical circular tunnels in urban areas, and suggests forecasting techniques based essentially on the organization of underground space. The simulations are performed using the finite-difference code FLAC in a two-dimensional case and with an elasto-plastic behavior of the soil.

Keywords: sol, weakening, degradation, prevention, tunnel

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Authors: Xianwei Zheng, Yuan Yan Tang

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Classical window Fourier transform has been widely used in signal processing, image processing, machine learning and pattern recognition. The related Gabor transform is powerful enough to capture the texture information of any given dataset. Recently, in the emerging field of graph signal processing, researchers devoting themselves to develop a graph signal processing theory to handle the so-called graph signals. Among the new developing theory, windowed graph Fourier transform has been constructed to establish a time-frequency analysis framework of graph signals. The windowed graph Fourier transform is defined by using the translation and modulation operators of graph signals, following the similar calculations in classical windowed Fourier transform. Specifically, the translation and modulation operators of graph signals are defined by using the Laplacian eigenvectors as follows. For a given graph signal, its translation is defined by a similar manner as its definition in classical signal processing. Specifically, the translation operator can be defined by using the Fourier atoms; the graph signal translation is defined similarly by using the Laplacian eigenvectors. The modulation of the graph can also be established by using the Laplacian eigenvectors. The windowed graph Fourier transform based on these two operators has been applied to obtain time-frequency representations of graph signals. Fundamentally, the modulation operator is defined similarly to the classical modulation by multiplying a graph signal with the entries in each Fourier atom. However, a single Laplacian eigenvector entry cannot play a similar role as the Fourier atom. This definition ignored the relationship between the translation and modulation operators. In this paper, a new definition of the modulation operator is proposed and thus another time-frequency framework for graph signal is constructed. Specifically, the relationship between the translation and modulation operations can be established by the Fourier transform. Specifically, for any signal, the Fourier transform of its translation is the modulation of its Fourier transform. Thus, the modulation of any signal can be defined as the inverse Fourier transform of the translation of its Fourier transform. Therefore, similarly, the graph modulation of any graph signal can be defined as the inverse graph Fourier transform of the translation of its graph Fourier. The novel definition of the graph modulation operator established a relationship of the translation and modulation operations. The new modulation operation and the original translation operation are applied to construct a new framework of graph signal time-frequency analysis. Furthermore, a windowed graph Fourier frame theory is developed. Necessary and sufficient conditions for constructing windowed graph Fourier frames, tight frames and dual frames are presented in this paper. The novel graph signal time-frequency analysis framework is applied to signals defined on well-known graphs, e.g. Minnesota road graph and random graphs. Experimental results show that the novel framework captures new features of graph signals.

Keywords: graph signals, windowed graph Fourier transform, windowed graph Fourier frames, vertex frequency analysis

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Authors: Nishi Bhuvandas, P. V. Timbadiya, P. L. Patel, P. D. Porey

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Recent perceived climate variability raises concerns with unprecedented hydrological phenomena and extremes. Distribution and circulation of the waters of the Earth become increasingly difficult to determine because of additional uncertainty related to anthropogenic emissions. According to the sixth Intergovernmental Panel on Climate Change (IPCC) Technical Paper on Climate Change and water, changes in the large-scale hydrological cycle have been related to an increase in the observed temperature over several decades. Although many previous research carried on effect of change in climate on hydrology provides a general picture of possible hydrological global change, new tools and frameworks for modelling hydrological series with nonstationary characteristics at finer scales, are required for assessing climate change impacts. Of the downscaling techniques, dynamic downscaling is usually based on the use of Regional Climate Models (RCMs), which generate finer resolution output based on atmospheric physics over a region using General Circulation Model (GCM) fields as boundary conditions. However, RCMs are not expected to capture the observed spatial precipitation extremes at a fine cell scale or at a basin scale. Statistical downscaling derives a statistical or empirical relationship between the variables simulated by the GCMs, called predictors, and station-scale hydrologic variables, called predictands. The main focus of the paper is on the need for using statistical downscaling techniques for projection of local hydrometeorological variables under climate change scenarios. The projections can be then served as a means of input source to various hydrologic models to obtain streamflow, evapotranspiration, soil moisture and other hydrological variables of interest.

Keywords: climate change, downscaling, GCM, RCM

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Authors: Karima Menad, Ahmed Feddag

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In this study, large crystals of the zeolite NaA were synthesized by hydrothermal way. By following this zeolite was used to recover two heavy metals that are allowing the most dangerous toxic, lead and cadmium. The synthesized zeolite was analyzed by XRD and SEM aims to verify its purity and its good morphology; after it was undergoing ion exchange operations by aqueous solution with lead and cadmium in two salts Pb(CH3COOH)2 and CdCl2 at different concentrations. The exchange was carried out under the effect of two temperatures (25 °C and 60 °C). The contents of Pb++, Cd++ and Na+ were analyzed by atomic absorption and the results are given in the form of exchange rates. At the end the samples are analyzed by XRD exchanged to confirm their conservation of their zeolite framework. It is found that the exchange rate increases with the increase of initial concentration and the best results are found for the temperature of 60 °C.

Keywords: exchange rate, ion exchange, LTA zeolite, zeolite NaA

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Authors: Selim M. Khan, Dustin D. Pearson, Tryggve Rönnqvist, Markus E. Nielsen, Joshua M. Taron, Aaron A. Goodarzi

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Accumulation of radioactive radon gas in indoor air poses a serious risk to human health by increasing the lifetime risk of lung cancer and is classified by IARC as a category one carcinogen. Radon exposure risks are a function of geologic, geographic, design, and human behavioural variables and can change over time. Using time series and deep machine learning modelling, we analyzed long-term radon test outcomes as a function of building metrics from 25,489 Canadian and 38,596 Swedish residential properties constructed between 1945 to 2020. While Canadian and Swedish properties built between 1970 and 1980 are comparable (96–103 Bq/m³), innate radon risks subsequently diverge, rising in Canada and falling in Sweden such that 21st Century Canadian houses show 467% greater average radon (131 Bq/m³) relative to Swedish equivalents (28 Bq/m³). These trends are consistent across housing types and regions within each country. The introduction of energy efficiency measures within Canadian and Swedish building codes coincided with opposing radon level trajectories in each nation. Deep machine learning modelling predicts that, without intervention, average Canadian residential radon levels will increase to 176 Bq/m³ by 2050, emphasizing the importance and urgency of future building code intervention to achieve systemic radon reduction in Canada.

Keywords: radon health risk, time-series, deep machine learning, lung cancer, Canada, Sweden

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Authors: M. Chumburidze, N. Salia, T. Namchevadze

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This work deal with case processing problems in business. The task of strategic credit requirements management of cases portfolio is discussed. The information model of credit requirements in a binary tree diagram is considered. The algorithms to solve issues of prioritizing clusters of cases in business have been investigated. An implementation of priority queues to support case management operations has been presented. The corresponding pseudo codes for the programming application have been constructed. The tools applied in this development are based on binary tree ordering algorithms, optimization theory, and business management methods.

Keywords: credit network, case portfolio, binary tree, priority queue, stack

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Authors: José Eduardo García-Mendiola

Abstract:

In this work, a phenomenological approach to computational modeling of analogy processing is carried out. The paper goes through the consideration of the structure of the analogy, based on the possibility of sustaining the genesis of its elements regarding Husserl's genetic theory of association. Among particular processes which take place in order to get analogical inferences, there is one which arises crucial for enabling efficient base cases retrieval through long-term memory, namely analogical transference grounded on familiarity. In general, it has been argued that analogical reasoning is a way by which a conscious agent tries to determine or define a certain scope of objects and relationships between them using previous knowledge of other familiar domain of objects and relations. However, looking for a complete description of analogy process, a deeper consideration of phenomenological nature is required in so far, its simulation by computational programs is aimed. Also, one would get an idea of how complex it would be to have a fully computational account of the analogy elements. In fact, familiarity is not a result of a mere chain of repetitions of objects or events but generated insofar as the object/attribute or event in question is integrable inside a certain context that is taking shape as functionalities and functional approaches or perspectives of the object are being defined. Its familiarity is generated not by the identification of its parts or objective determinations as if they were isolated from those functionalities and approaches. Rather, at the core of such a familiarity between entities of different kinds lays the way they are functionally encoded. So, and hoping to make deeper inroads towards these topics, this essay allows us to consider that cognitive-computational perspectives can visualize, from the phenomenological projection of the analogy process reviewing achievements already obtained as well as exploration of new theoretical-experimental configurations towards implementation of analogy models in specific as well as in general purpose machines.

Keywords: analogy, association, encoding, retrieval

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Authors: Aena Iqbal

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The lack of access to maternal and reproductive health in Pakistan poses a great threat to global public health. Obstetric issues, including vesicovaginal fistulas (VVF), are the most common in South Asian countries, leaving women in a more vulnerable state. Koohi Goth Women’s Hospital offers free VVF operations, which draws in women from all over Pakistan. Although reproductive health is being handled, mental health is often neglected in these scenarios. Using a series of questions inspired by the Warwick Edinburgh Model, this paper builds on the results from interviewing women who have received vesicovaginal fistula repair surgery on their mental health, a taboo topic in Pakistan.

Keywords: obstetrics, VVF, Pakistan, reproductive health

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Authors: Albert W. K. Tan

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This research consolidates a comprehensive array of publications from peer-reviewed journals, case studies, and seminar reports focused on reverse logistics and network design. By synthesizing this secondary knowledge, our objective is to identify and articulate key decision factors crucial to reverse logistics network design for e-commerce. Through this exploration, we aim to present a refined mathematical model that offers valuable insights for companies seeking to optimize their reverse logistics operations. The primary goal of this research endeavor is to develop a comprehensive framework tailored to advising organizations and companies on crafting effective networks for their reverse logistics operations, thereby facilitating the achievement of their organizational goals. This involves a thorough examination of various network configurations, weighing their advantages and disadvantages to ensure alignment with specific business objectives. The key objectives of this research include: (i) Identifying pivotal factors pertinent to network design decisions within the realm of reverse logistics across diverse supply chains. (ii) Formulating a structured framework designed to offer informed recommendations for sound network design decisions applicable to relevant industries and scenarios. (iii) Propose a mathematical model to optimize its reverse logistics network. A conceptual framework for designing a reverse logistics network has been developed through a combination of insights from the literature review and information gathered from company websites. This framework encompasses four key stages in the selection of reverse logistics operations modes: (1) Collection, (2) Sorting and testing, (3) Processing, and (4) Storage. Key factors to consider in reverse logistics network design: I) Centralized vs. decentralized processing: Centralized processing, a long-standing practice in reverse logistics, has recently gained greater attention from manufacturing companies. In this system, all products within the reverse logistics pipeline are brought to a central facility for sorting, processing, and subsequent shipment to their next destinations. Centralization offers the advantage of efficiently managing the reverse logistics flow, potentially leading to increased revenues from returned items. Moreover, it aids in determining the most appropriate reverse channel for handling returns. On the contrary, a decentralized system is more suitable when products are returned directly from consumers to retailers. In this scenario, individual sales outlets serve as gatekeepers for processing returns. Considerations encompass the product lifecycle, product value and cost, return volume, and the geographic distribution of returns. II) In-house vs. third-party logistics providers: The decision between insourcing and outsourcing in reverse logistics network design is pivotal. In insourcing, a company handles the entire reverse logistics process, including material reuse. In contrast, outsourcing involves third-party providers taking on various aspects of reverse logistics. Companies may choose outsourcing due to resource constraints or lack of expertise, with the extent of outsourcing varying based on factors such as personnel skills and cost considerations. Based on the conceptual framework, the authors have constructed a mathematical model that optimizes reverse logistics network design decisions. The model will consider key factors identified in the framework, such as transportation costs, facility capacities, and lead times. The authors have employed mixed LP to find the optimal solutions that minimize costs while meeting organizational objectives.

Keywords: reverse logistics, supply chain management, optimization, e-commerce

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Authors: Sejin Jung, Dongho Kang, Byungsik Kim

Abstract:

Assessing the impact of climate change requires the use of a multi-model ensemble (MME) to quantify uncertainties between scenarios and produce downscaled outlines for simulation of climate under the influence of different factors, including topography. This study decreases climate change scenarios from the 13 global climate models (GCMs) to assess the impacts of future climate change. Unlike South Korea, North Korea lacks in studies using climate change scenarios of the CoupledModelIntercomparisonProject (CMIP5), and only recently did the country start the projection of extreme precipitation episodes. One of the main purposes of this study is to predict changes in the average climatic conditions of North Korea in the future. The result of comparing downscaled climate change scenarios with observation data for a reference period indicates high applicability of the Multi-Model Ensemble (MME). Furthermore, the study classifies climatic zones by applying the Köppen-Geiger climate classification system to the MME, which is validated for future precipitation and temperature. The result suggests that the continental climate (D) that covers the inland area for the reference climate is expected to shift into the temperate climate (C). The coefficient of variation (CVs) in the temperature ensemble is particularly low for the southern coast of the Korean peninsula, and accordingly, a high possibility of the shifting climatic zone of the coast is predicted. This research was supported by a grant (MOIS-DP-2015-05) of Disaster Prediction and Mitigation Technology Development Program funded by Ministry of Interior and Safety (MOIS, Korea).

Keywords: MME, North Korea, Koppen–Geiger, climatic zones, coefficient of variation, CV

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Authors: Jaime A. Palma-Mendoza

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A supply chain consists of different processes and when conducting supply chain re-design is necessary to identify the relevant processes and select a target for re-design. A solution was developed which consists to identify first the relevant processes using the Supply Chain Operations Reference (SCOR) model, then to use Analytical Hierarchy Process (AHP) for target process selection. An application was conducted in an Airline MRO supply chain re-design project which shows this combination can clearly aid the identification of relevant supply chain processes and the selection of a target process for re-design.

Keywords: decision support systems, multiple criteria analysis, supply chain management

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Authors: Bashayer Al-Enezi, Budoor Al-Sabti, Eman Al-Durai, Fatmah Kalban, Meshael Ahmed

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Production planning and control principles are concerned with planning, controlling and balancing all aspects of manufacturing including raw materials, finished goods, production schedules, and equipment requirements. Hence, an effective production planning and control system is very critical to the success of any factory. This project will focus on the application of production planning and control principles on “The National Canned Food Production and Trading Company (NCFP)” factory to find problems or areas for improvement.

Keywords: production planning, operations improvement, inventory management, National Canned Food Production and Trading Company (NCFP)

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Authors: S. M. Ishtiaque, V. K. Yadav, S. D. Joshi, J. K. Chatterjee

Abstract:

The DIAMETRIC FAULTS system has been developed that captures a bi-directional image of yarn continuously in sequentially manner and provides the detailed classification of faults. A novel mathematical framework developed on the acquired bi-directional images forms the basis of fault classification in four broad categories, namely, Thick1, Thick2, Thin and Normal Yarn. A discretised version of Radon transformation has been used to convert the bi-directional images into one-dimensional signals. Images were divided into training and test sample sets. Karhunen–Loève Transformation (KLT) basis is computed for the signals from the images in training set for each fault class taking top six highest energy eigen vectors. The fault class of the test image is identified by taking the Euclidean distance of its signal from its projection on the KLT basis for each sample realization and fault class in the training set. Euclidean distance applied using various techniques is used for classifying an unknown fault class. An accuracy of about 90% is achieved in detecting the correct fault class using the various techniques. The four broad fault classes were further sub classified in four sub groups based on the user set boundary limits for fault length and fault volume. The fault cross-sectional area and the fault length defines the total volume of fault. A distinct distribution of faults is found in terms of their volume and physical dimensions which can be used for monitoring the yarn faults. It has been shown from the configurational based characterization and classification that the spun yarn faults arising out of mass variation, exhibit distinct characteristics in terms of their contours, sizes and shapes apart from their frequency of occurrences.

Keywords: Euclidean distance, fault classification, KLT, Radon Transform

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