Search results for: conventionally manufacturing techniques

Authors: Nor Diana Ahmad, Eric Atwell, Brandon Bennett

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Text processing techniques for English have been developed for several decades. But for the Malay language, text processing methods are still far behind. Moreover, there are limited resources, tools for computational linguistic analysis available for the Malay language. Therefore, this research presents the use of natural language processing (NLP) in processing Malay translated Qur’an text. As the result, a new language resource for Malay translated Qur’an was created. This resource will help other researchers to build the necessary processing tools for the Malay language. This research also develops a simple question-answer prototype to demonstrate the use of the Malay Qur’an resource for text processing. This prototype has been developed using Python. The prototype pre-processes the Malay Qur’an and an input query using a stemming algorithm and then searches for occurrences of the query word stem. The result produced shows improved matching likelihood between user query and its answer. A POS-tagging algorithm has also been produced. The stemming and tagging algorithms can be used as tools for research related to other Malay texts and can be used to support applications such as information retrieval, question answering systems, ontology-based search and other text analysis tasks.

Keywords: language resource, Malay translated Qur'an, natural language processing (NLP), text processing

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Authors: Hakim Aguedal, Abdelkader Iddou, Abdallah Aziz, Djillali Reda Merouani, Ferhat Bensaleh, Saleh Bensadek

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The textile industry produces high amount of colored effluent each year. The management or treatment of these discharges depends on the applied techniques. Adsorption is one of wastewater treatment techniques destined to treat this kind of pollution, and the performance and efficiency predominantly depend on the nature of the adsorbent used. Therefore, scientific research is directed towards the development of new materials using different physical and chemical treatments to improve their adsorption capacities. In the same perspective, we looked at the effect of the heat treatment on the effectiveness of diatomite, which is found in abundance in Algeria. The textile dye Orange Bezaktiv (SRL-150) which is used as organic pollutants in this study is provided by the textile company SOITEXHAM in Oran city (west Algeria). The effect of different physicochemical parameters on the adsorption of SRL-150 on natural and modified diatomite is studied, and the results of the kinetics and adsorption isotherms were modeled.

Keywords: wastewater treatment, diatomite, adsorption, dye pollution, kinetic, isotherm

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Authors: Priyadarshini Kiran, Gulshan Kumar

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: Social media are becoming the most important tools for interaction among learners, pedagogues and parents where everybody can share, exchange, comment, discuss and create information and knowledge in a collaborative way. The present case study attempts to highlight the role of social media (WhatsApp) in nurturing learning habits in toddlers with the help of parents in primary education. The Case study is based on primary data collected from a primary school situated in a small town in the northern state of Uttar Pradesh, India. In research methodology, survey and structured interviews have been used as a tool collected from parents and pedagogues. The findings Suggest: - To nurture learning habits in toddlers, parents and pedagogues use social media site (WhatsApp) in real-time and that too is convenient and handy; - Skill enhancement on the part of Pedagogues as a result of employing innovative teaching-learning techniques; - Social media sites serve as a social connectivity tool to ward off negativity and monotony on the part of parents and pedagogues in the wake of COVID- 19

Keywords: innovative teaching-learning techniques, pedagogues, social media, nurture, toddlers

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Authors: Usman Ghani

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Feedback is a vital element for improving student learning in a simulation-based training as it guides and refines learning through scaffolding. A number of studies in literature have shown that students’ learning is enhanced when feedback is provided with personalized tutoring that offers specific guidance and adapts feedback to the learner in a one-to-one environment. Thus, emulating these adaptive aspects of human tutoring in simulation provides an effective methodology to train individuals. This paper presents the results of a study that investigated the effectiveness of automating different types of feedback techniques such as Knowledge-of-Correct-Response (KCR) and Answer-Until- Correct (AUC) in software simulation for learning basic information technology concepts. For the purpose of comparison, techniques like simulation with zero or no-feedback (NFB) and traditional hands-on (HON) learning environments are also examined. The paper presents the summary of findings based on quantitative analyses which reveal that the simulation based instructional strategies are at least as effective as hands-on teaching methodologies for the purpose of learning of IT concepts. The paper also compares the results of the study with the earlier studies and recommends strategies for using feedback mechanism to improve students’ learning in designing and simulation-based IT training.

Keywords: simulation, feedback, training, hands-on, labs

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Authors: Abdulkader Helwan

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Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

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Authors: Pratima Kumari, Sukha Ranjan Samadder

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This research aims to contribute to the sustainable production of graphene materials by exploring the extraction of graphite from spent primary and secondary batteries. The increasing demand for graphene materials, a versatile and high-performance material, necessitates environmentally friendly methods for its synthesis. The process involves a well-planned methodology, beginning with the gathering and categorization of batteries, followed by the disassembly and careful removal of graphite from anode structures. The use of environmentally friendly solvents and mechanical techniques ensures an efficient and eco-friendly extraction of graphite. Advanced approaches such as the modified Hummers' method and chemical reduction process are utilized for the synthesis of graphene materials, with a focus on optimizing parameters. Various analytical techniques such as Fourier-transform infrared spectroscopy, X-ray diffraction, scanning electron microscopy, thermogravimetric analysis, and Raman spectroscopy were employed to validate the quality and structure of the produced graphene materials. The major findings of this study reveal the successful implementation of the methodology, leading to the production of high-quality graphene materials suitable for advanced material applications. Thorough characterization using various advanced techniques validates the structural integrity and purity of the graphene. The economic viability of the process is demonstrated through a comprehensive economic analysis, highlighting the potential for large-scale production. This research contributes to the field of sustainable production of graphene materials by offering a systematic methodology that efficiently transforms spent batteries into valuable graphene resources. Furthermore, the findings not only showcase the potential for upcycling electronic waste but also address the pressing need for environmentally conscious processes in advanced material synthesis.

Keywords: spent primary batteries, spent secondary batteries, graphite extraction, advanced material synthesis, circular economy approach

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Authors: O. Kahraman, M. S. Alatas, O. B. Citil

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In determination of values of feeds which, are used in ruminant nutrition, different methods are used like in vivo, in vitro, in situ or in sacco. Generally, the most reliable results are taken from the in vivo studies. But because of the disadvantages like being hard, laborious and expensive, time consuming, being hard to keep the experiment conditions under control and too much samples are needed, the in vitro techniques are more preferred. The most widely used in vitro techniques are two-staged digestion technique and gas production technique. In vitro gas production technique is based on the measurement of the CO2 which is released as a result of microbial fermentation of the feeds. In this review, the factors affecting the results obtained from in vitro gas production technique (Hohenheim Feed Test) were discussed. Some factors must be taken into consideration when interpreting the findings obtained in these studies and also comparing the findings reported by different researchers for the same feeds. These factors were discussed in 3 groups: factors related to animal, factors related to feeds and factors related with differences in the application of method. These factors and their effects on the results were explained. Also it can be concluded that the use of in vitro gas production technique in feed evaluation routinely can be contributed to the comprehensive feed evaluation, but standardization is needed in this technique to attain more reliable results.

Keywords: In vitro, gas production technique, Hohenheim feed test, standardization

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Authors: Luís R. Silva, Catarina Bento, Ana C. Gonçalves, Fábio Jesus, Branca M. Silva

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Nowadays, the general population is more and more concerned about nutrition and the health implications of an unbalanced diet. Current knowledge regarding the health benefits and antioxidant properties of certain foods such as fruits and vegetables has gained the interest of both the general public and scientific community. Peach (Prunus persica (L.) Batsch) is one of the most consumed fruits worldwide, with low sugar contents and a broad range of nutrients essential to the normal functioning of the body. Six different peach cultivars from the Fundão region in Portugal were evaluated regarding their phenolic composition by LC-DAD and biological activity. The prepared extracts’ capacity to scavenge free-radicals was tested through the stable free radical DPPH• and nitric oxide (•NO). Additionally, antidiabetic potential and protective effects against peroxyl radical (ROO•) induced damage to erythrocytes were also tested. LC-DAD analysis allowed the identification of 17 phenolic compounds, among which 5-O-caffeoylquinic acids and 3-O-caffeoylquinic acids are pointed out as the most abundant. Regarding the antioxidant activity, all cultivars displayed concentration-dependent free-radical scavenging activity against both nitrogen species and DPPH•. In respect to α-glucosidase inhibitory activity, Royal Magister and Royal Glory presented the highest inhibitory activity (IC50 = 11.7 ± 1.4 and 17.1 ± 1.7 μg/mL, respectively), nevertheless all six cultivars presented higher activity than the control acarbose. As for the protective effect of Royal Lu extract on the oxidative damage induced in erythrocytes by ROO•, the results were quite promising showing inhibition IC50 values of 110.0 ± 4.5 μg/mL and 83.8 ± 6.5 μg/mL for hemolysis and hemoglobin oxidation, respectively. The demonstrated activity is of course associated to the peaches’ phenolic profile, rich in phenolic acids and flavonoids with high hydrogen donating capacity. These compounds have great industrial interest for the manufacturing of natural products. The following step would naturally be the extraction and isolation from the plant tissues and large-scale production through biotechnology techniques.

Keywords: antioxidants, functional food, phenolic compounds, peach

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Authors: Thomas Wimmer, Bernhard Weigand

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The improvement of gas turbine efficiency is one of the main drivers of research and development in the gas turbine market. This has led to elevated gas turbine inlet temperatures beyond the melting point of the utilized materials. The turbine parts need to be actively cooled in order to withstand these harsh environments. However, the usage of compressor air as coolant decreases the overall gas turbine efficiency. Thus, coolant consumption needs to be minimized in order to gain the maximum advantage from higher turbine inlet temperatures. Therefore, sophisticated cooling designs for gas turbine parts aim to minimize coolant mass flow. New design space is accessible as additive manufacturing is maturing to industrial usage for the creation of hot gas flow path parts. By making use of this technology more efficient cooling schemes can be manufacture. In order to find such cooling schemes a generative design method is being developed. It generates cooling schemes randomly which adhere to a set of rules. These assure the sanity of the design. A huge amount of different cooling schemes are generated and implemented in a simulation environment where it is validated. Criteria for the fitness of the cooling schemes are coolant mass flow, maximum temperature and temperature gradients. This way the whole design space is sampled and a Pareto optimum front can be identified. This approach is applied to a flat plate, which resembles a simplified section of a hot gas flow path part. Realistic boundary conditions are applied and thermal barrier coating is accounted for in the simulation environment. The resulting cooling schemes are presented and compared to representative conventional cooling schemes. Further development of this method can give access to cooling schemes with an even better performance having higher complexity, which makes use of the available design space.

Keywords: additive manufacturing, cooling, gas turbine, heat transfer, heat transfer design, optimization

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Authors: Atish Bagchi, Siva Chandrasekaran

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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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Authors: Abdelhadi Adam Salih Denei

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Silver nanoparticles (AgNPs) have been used in cancer therapy, and the area of nanomedicine has made unheard-of strides in recent years. A thorough summary of the development and assessment of AgNPs for their possible use in the fight against cancer is the goal of this review. Targeted delivery methods have been designed to optimise therapeutic efficacy by using AgNPs' distinct physicochemical features, such as their size, shape, and surface chemistry. Firstly, the study provides an overview of the several synthesis routes—both chemical and green—that are used to create AgNPs. Natural extracts and biomolecules are used in green synthesis techniques, which are becoming more and more popular since they are biocompatible and environmentally benign. It is next described how synthesis factors affect the physicochemical properties of AgNPs, emphasising how crucial it is to modify these parameters for particular therapeutic uses. An extensive analysis is conducted on the anticancer potential of AgNPs, emphasising their capacity to trigger apoptosis, impede angiogenesis, and alter cellular signalling pathways. The analysis also investigates the potential benefits of combining AgNPs with currently used cancer treatment techniques, including radiation and chemotherapy. AgNPs' safety profile for use in clinical settings is clarified by a comprehensive evaluation of their cytotoxicity and biocompatibility.

Keywords: silver nanoparticles, cancer, nanocarrier system, targeted delivery

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Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: classification algorithms, data mining, knowledge discovery, tourism

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Authors: Surajo Isa

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In as much as mathematics is important to national development, it is regrettable to note that in Nigeria Students academic achievement especially in public examinations remains poor. Among the several factors responsible for such a poor performance is the lack of bringing cultural elements into the conventional school mathematics. The design for this study is triangulation in nature which is set to examined 800 students From 20 School (40 each from male and female schools). Ten (10) male and ten (10) female schools consisting of 400 male and 400 female students to formed the experiment and control groups with a further sub-groping of samples to represent urban and rural settings for both male and female groups. While the experimental groups were taught using ethnomathematics techniques, the control groups were taught using conventional techniques, the results of a t-test for independent samples at p =0.05 level of significance with tcritical = 1.968 showed that (a) boys performed significantly better than girls (b) there is no significantly difference in performance between urban and rural girls (c) significant difference in academic performance was obtained between urban and rural boys. Generally, it was observed that teaching mathematics with ethnomathematics technique would help in great achievement in mathematics.

Keywords: ethnomathematics, achievement, gender, settlement

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Authors: Monisha Isaac

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Biotechnology is a discipline which explains the use of living organisms and systems to construct a product, or we can define it as an application or technology developed to use biological systems and organisms processes for a specific use. Particularly, it includes cells and its components use for new technologies and inventions. The tools developed can be further used in diverse fields such as agriculture, industry, research and hospitals etc. The 21^st century has seen a drastic development and advancement in biotechnology in India. Significant increase in Government of India’s outlays for biotechnology over the past decade has been observed. A sectoral break up of biotechnology-based companies in India shows that most of the companies are agriculture-based companies having interests ranging from tissue culture to biopesticides. Major attention has been given by the companies in health related activities and in environmental biotechnology. The biopharmaceutical, which comprises of vaccines, diagnostic, and recombinant products is the most reliable and largest segment of the Indian Biotech industry. India has developed its vaccine markets and supplies them to various countries. Then there are the bio-services, which mainly comprise of contract researches and manufacturing services. India has made noticeable developments in the field of bio industries including manufacturing of enzymes, biofuels and biopolymers. Biotechnology is also playing a crucial and significant role in the field of agriculture. Traditional methods have been replaced by new technologies that mainly focus on GM crops, marker assisted technologies and the use of biotechnological tools to improve the quality of fertilizers and soil. It may only be a small contributor but has shown to have huge potential for growth. Bioinformatics is a computational method which helps to store, manage, arrange and design tools to interpret the extensive data gathered through experimental trials, making it important in the design of drugs.

Keywords: biotechnology, advancement, agriculture, bio-services, bio-industries, bio-pharmaceuticals

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Authors: Ozoemelam Ikechukwu Lazarus, Nizamuddin B. Zainuddi, Abdul Kafi

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Numerous studies have been carried out on Green Logistics Management Practices (GLMPs) across the globe. The study on the practices and performance of green chain practices in Africa in particular has not gained enough scholarly attention. Again, the majority of supply chain sustainability research being conducted focus on environmental sustainability. Logistics has been a major cause of supply chain resource waste and environmental damage. Many sectors of the economy that engage in logistical operations significantly rely on vehicles, which emit pollutants into the environment. Due to urbanization and industrialization, the logistical operations of manufacturing companies represent a serious hazard to the society and human life, making the sector one of the fastest expanding in the world today. Logistics companies are faced with numerous difficulties when attempting to implement logistics practices along their supply chains. In Nigeria, manufacturing companies aspire to implement reverse logistics in response to stakeholders’ requirements to reduce negative environmental consequences. However, implementing this is impeded by a criteria framework, and necessitates the careful analysis of how such criteria interact with each other in the presence of uncertainty. This study integrates most of the green logistics management practices (GLMPs) into the Nigerian firms to improve generalizability, and credibility. It examines the effect of Green Logistics Management Practices on environmental performance, social performance, market performance, and financial performance in the logistics industries. It seeks to identify the critical success factors in order to develop a model that incorporates different factors from the perspectives of the technology, organization, human and environment to inform the adoption and use of technologies for logistics supply chain social sustainability in Nigeria. It uses exploratory research approach to collect and analyse the data.

Keywords: logistics, management, sustainability, environment, operations

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Authors: A. Achour L. Chekour, A. Mekroud

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Tribology, the science of lubrication, friction and wear, plays an important role in science "crossroads" initiated by the recent developments in the industry. Its multidisciplinary nature reinforces its scientific interest. It covers all the sciences that deal with the contact between two solids loaded and relative motion. It is thus one of the many intersections more clearly established disciplines such as solid mechanics and the fluids, rheological, thermal, materials science and chemistry. As for his experimental approach, it is based on the physical and processing signals and images. The optimization of operating conditions by cutting tool must contribute significantly to the development and productivity of advanced automation of machining techniques because their implementation requires sufficient knowledge of how the process and in particular the evolution of tool wear. In addition, technological advances have developed the use of very hard materials, refractory difficult machinability, requiring highly resistant materials tools. In this study, we present the behavior wear a machining tool during the roughing operation according to the cutting parameters. The interpretation of the experimental results is based mainly on observations and analyzes of sharp edges e tool using the latest techniques: scanning electron microscopy (SEM) and optical rugosimetry laser beam.

Keywords: friction, wear, tool, cutting

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Authors: Derssie Mebratu

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As a large variety of micro services, web services, social graphic applications, and media applications are continuously developed, it is substantially vital to design and build a reliable, efficient, and faster memory tiering system. Despite limited design, implementation, and deployment in the last few years, several techniques are currently developed to improve a memory tiering system in a cloud. Some of these techniques are to develop an optimal scanning frequency; improve and track pages movement; identify pages that recently accessed; store pages across each tiering, and then identify pages as a hot, warm, and cold so that hot pages can store in the first tiering Dynamic Random Access Memory (DRAM) and warm pages store in the second tiering Compute Express Link(CXL) and cold pages store in the third tiering Non-Volatile Memory (NVM). Apart from the current proposal and implementation, we also develop a new technique based on a machine learning algorithm in that the throughput produced 25% improved performance compared to the performance produced by the baseline as well as the latency produced 95% improved performance compared to the performance produced by the baseline.

Keywords: machine learning, bayesian optimization, memory tiering, CXL, DRAM

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Authors: Layaly Ayoub, Mariana Ribeiro

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Introduction: Breast cancer is currently considered the leading cause of cancer-related deaths among women in Brazil. Mastectomy, essential in this treatment, often necessitates subsequent breast reconstruction to restore physical appearance and aid in the emotional and psychological recovery of patients. The choice between immediate or delayed reconstruction is influenced by factors such as the type and stage of cancer, as well as the patient's overall health. The decision between autologous breast reconstruction or implant-based reconstruction requires a detailed analysis of individual conditions and needs. Objectives: This study analyzes the techniques and indications used in post-mastectomy breast reconstruction. Methodology: Literature review conducted in the PubMed and SciELO databases, focusing on articles that met the inclusion and exclusion criteria and descriptors. Results: After mastectomy, breast reconstruction is commonly performed. It is necessary to determine the type of technique to be used in each case depending on the specific characteristics of each patient. The tissue expander technique is indicated for patients with sufficient skin and tissue post-mastectomy, who do not require additional radiotherapy, and who opt for a less complex surgery with a shorter recovery time. This procedure promotes the gradual expansion of soft tissues where the definitive implant will be placed. Both temporary and permanent expanders offer flexibility, allowing for adjustment in the expander size until the desired volume is reached, enabling the skin and tissues to adapt to the breast implant area. Conversely, autologous reconstruction is indicated for patients who will undergo radiotherapy, have insufficient tissue, and prefer a more natural solution. This technique uses the transverse rectus abdominis muscle (TRAM) flap, the latissimus dorsi muscle flap, the gluteal flap, and local muscle flaps to shape a new breast, potentially combined with a breast implant. Conclusion: In this context, it is essential to conduct a thorough evaluation regarding the technique to be applied, as both have their benefits and challenges.

Keywords: indications, post-mastectomy, breast reconstruction, techniques

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Authors: Mohammed Hasan Salahat, Stave Wade

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This paper presents an application of a “Systematic Soft Domain Driven Design Framework” as a soft systems approach to domain-driven design of information systems development. The framework combining techniques from Soft Systems Methodology (SSM), the Unified Modeling Language (UML), and an implementation pattern knows as ‘Naked Objects’. This framework have been used in action research projects that have involved the investigation and modeling of business processes using object-oriented domain models and the implementation of software systems based on those domain models. Within this framework, Soft Systems Methodology (SSM) is used as a guiding methodology to explore the problem situation and to develop the domain model using UML for the given business domain. The framework is proposed and evaluated in our previous works, and a real case study ‘Information Retrieval System for Academic Research’ is used, in this paper, to show further practice and evaluation of the framework in different business domain. We argue that there are advantages from combining and using techniques from different methodologies in this way for business domain modeling. The framework is overviewed and justified as multi-methodology using Mingers Multi-Methodology ideas.

Keywords: SSM, UML, domain-driven design, soft domain-driven design, naked objects, soft language, information retrieval, multimethodology

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Authors: Ozoemelam Ikechukwu Lazarus, Nizamuddin B. Zainuddin, Abdul Kafi

Abstract:

Numerous studies have been carried out on Green Logistics Management Practices (GLMPs) across the globe. The study on the practices and performance of green chain practices in Africa in particular has not gained enough scholarly attention. Again, the majority of supply chain sustainability research being conducted focus on environmental sustainability. Logistics has been a major cause of supply chain resource waste and environmental damage. Many sectors of the economy that engage in logistical operations significantly rely on vehicles, which emit pollutants into the environment. Due to urbanization and industrialization, the logistical operations of manufacturing companies represent a serious hazard to the society and human life, making the sector one of the fastest expanding in the world today. Logistics companies are faced with numerous difficulties when attempting to implement logistics practices along their supply chains. In Nigeria, manufacturing companies aspire to implement reverse logistics in response to stakeholders’ requirements to reduce negative environmental consequences. However, implementing this is impeded by a criteria framework, and necessitates the careful analysis of how such criteria interact with each other in the presence of uncertainty. This study integrates most of the green logistics management practices (GLMPs) into the Nigerian firms to improve generalizability, and credibility. It examines the effect of Green Logistics Management Practices on environmental performance, social performance, market performance, and financial performance in the logistics industries. It seeks to identify the critical success factors in order to develop a model that incorporates different factors from the perspectives of the technology, organization, human and environment to inform the adoption and use of technologies for logistics supply chain social sustainability in Nigeria. It uses exploratory research approach to collect and analyse the data.

Keywords: logistics, managemernt, suatainability, environment, operations

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Authors: Ramoshweu Melvin Sethobya, Emmanuel Chirenje, Mihlali Hobo, Simon Sebothoma

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The recent surge in residential infrastructure development around the metropolitan areas of South Africa has necessitated conditions for thorough geotechnical assessments to be conducted prior to site developments to ensure human and infrastructure safety. This paper appraises the success in the application of multi-method geophysical techniques for the delineation of sinkhole vulnerability in a residential landscape. Geophysical techniques ERT, MASW, VES, Magnetics and gravity surveys were conducted to assist in mapping sinkhole vulnerability, using an existing sinkhole as a constraint at Venterspost town, West of Johannesburg city. A combination of different geophysical techniques and results integration from those proved to be useful in the delineation of the lithologic succession around sinkhole locality, and determining the geotechnical characteristics of each layer for its contribution to the development of sinkholes, subsidence and cavities at the vicinity of the site. Study results have also assisted in the determination of the possible depth extension of the currently existing sinkhole and the location of sites where other similar karstic features and sinkholes could form. Results of the ERT, VES and MASW surveys have uncovered dolomitic bedrock at varying depths around the sites, which exhibits high resistivity values in the range 2500-8000ohm.m and corresponding high velocities in the range 1000-2400 m/s. The dolomite layer was found to be overlain by a weathered chert-poor dolomite layer, which has resistivities between the range 250-2400ohm.m, and velocities ranging from 500-600m/s, from which the large sinkhole has been found to collapse/ cave in. A compiled 2.5D high resolution Shear Wave Velocity (Vs) map of the study area was created using 2D profiles of MASW data, offering insights into the prevailing lithological setup conducive for formation various types of karstic features around the site. 3D magnetic models of the site highlighted the regions of possible subsurface interconnections between the currently existing large sinkhole and the other subsidence feature at the site. A number of depth slices were used to detail the conditions near the sinkhole as depth increases. Gravity surveys results mapped the possible formational pathways for development of new karstic features around the site. Combination and correlation of different geophysical techniques proved useful in delineation of the site geotechnical characteristics and mapping the possible depth extend of the currently existing sinkhole.

Keywords: resistivity, magnetics, sinkhole, gravity, karst, delineation, VES

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Authors: Simon Komesker, Achim Wagner, Martin Ruskowski

Abstract:

In times of volatile markets with fluctuating demand and the uncertainty of global supply chains, flexible production systems are the key to an efficient implementation of a desired production program. In this publication, the authors present a holistic information concept taking into account various influencing factors for operating towards the global optimum. Therefore, a strategy for the implementation of multi-level planning for a flexible, reconfigurable production system with an alternative production concept in the automotive industry is developed. The main contribution of this work is a system structure mixing central and decentral planning and control evaluated in a simulation framework. The information system structure in current production systems in the automotive industry is rigidly hierarchically organized in monolithic systems. The production program is created rule-based with the premise of achieving uniform cycle time. This program then provides the information basis for execution in subsystems at the station and process execution level. In today's era of mixed-(car-)model factories, complex conditions and conflicts arise in achieving logistics, quality, and production goals. There is no provision for feedback loops of results from the process execution level (resources) and process supporting (quality and logistics) systems and reconsideration in the planning systems. To enable a robust production flow, the complexity of production system control is artificially reduced by the line structure and results, for example in material-intensive processes (buffers and safety stocks - two container principle also for different variants). The limited degrees of freedom of line production have produced the principle of progress figure control, which results in one-time sequencing, sequential order release, and relatively inflexible capacity control. As a result, modularly structured production systems such as modular production according to known approaches with more degrees of freedom are currently difficult to represent in terms of information technology. The remedy is an information concept that supports cross-system and cross-level information processing for centralized and decentralized decision-making. Through an architecture of hierarchically organized but decoupled subsystems, the paradigm of hybrid control is used, and a holonic manufacturing system is offered, which enables flexible information provisioning and processing support. In this way, the influences from quality, logistics, and production processes can be linked holistically with the advantages of mixed centralized and decentralized planning and control. Modular production systems also require modularly networked information systems with semi-autonomous optimization for a robust production flow. Dynamic prioritization of different key figures between subsystems should lead the production system to an overall optimum. The tasks and goals of quality, logistics, process, resource, and product areas in a cyber-physical production system are designed as an interconnected multi-agent-system. The result is an alternative system structure that executes centralized process planning and decentralized processing. An agent-based manufacturing control is used to enable different flexibility and reconfigurability states and manufacturing strategies in order to find optimal partial solutions of subsystems, that lead to a near global optimum for hybrid planning. This allows a robust near to plan execution with integrated quality control and intralogistics.

Keywords: holonic manufacturing system, modular production system, planning, and control, system structure

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Authors: Johannes Barlang

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Adhesive bonding plays a pivotal role in various industrial applications, ranging from automotive manufacturing to aerospace engineering. The peel strength of adhesives, a critical parameter reflecting the ability of an adhesive to withstand external forces, is crucial for ensuring the integrity and durability of bonded joints. This study provides a synopsis of the methodologies, influencing factors, and significance of peel testing in the evaluation of adhesive performance. Peel testing involves the measurement of the force required to separate two bonded substrates under controlled conditions. This study systematically reviews the different testing techniques commonly applied in peel testing, including the widely used 180-degree peel test and the T-peel test. Emphasis is placed on the importance of selecting an appropriate testing method based on the specific characteristics of the adhesive and the application requirements. The influencing factors on peel strength are multifaceted, encompassing adhesive properties, substrate characteristics, environmental conditions, and test parameters. Through an in-depth analysis, this study explores how factors such as adhesive formulation, surface preparation, temperature, and peel rate can significantly impact the peel strength of adhesively bonded joints. Understanding these factors is essential for optimizing adhesive selection and application processes in real-world scenarios. Furthermore, the study highlights the role of peel testing in quality control and assurance, aiding manufacturers in maintaining consistent adhesive performance and ensuring the reliability of bonded structures. The correlation between peel strength and long-term durability is discussed, shedding light on the predictive capabilities of peel testing in assessing the service life of adhesive bonds. In conclusion, this study underscores the significance of peel testing as a fundamental tool for characterizing adhesive performance. By delving into testing methodologies, influencing factors, and practical implications, this study contributes to the broader understanding of adhesive behavior and fosters advancements in adhesive technology across diverse industrial sectors.

Keywords: adhesively bonded joints, cleavage resistance, elastic adhesives, peel strength

Procedia PDF Downloads 69

Authors: Ling Liyun

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In the field of contemporary architecture, complex forms of architectural works continue to emerge in the world, along with some new terminology emerged: digital architecture, parametric design, algorithm generation, building information modeling, CNC construction and so on. Architects gradually mastered the new skills of mathematical logic in the form of exploration, virtual simulation, and the entire design and coordination in the construction process. Digital construction technology has a greater degree in controlling construction, and ensure its accuracy, creating a series of new construction techniques. As a result, the use of digital technology is an improvement and expansion of the practice of digital architecture design revolution. We worked by reading and analyzing information about the digital architecture development process, a large number of cases, as well as architectural design and construction as a whole process. Thus current developments were introduced and discussed in our paper, such as architectural discourse, design theory, digital design models and techniques, material selecting, as well as artificial intelligence space design. Our paper also pays attention to the representative three cases of digital design and construction experiment at great length in detail to expound high-informatization, high-reliability intelligence, and high-technique in constructing a humane space to cope with the rapid development of urbanization. We concluded that the opportunities and challenges of the shift existed in architectural paradigms, such as the cooperation methods, theories, models, technologies and techniques which were currently employed in digital design research and digital praxis. We also find out that the innovative use of space can gradually change the way people learn, talk, and control information. The past two decades, digital technology radically breaks the technology constraints of industrial technical products, digests the publicity on a particular architectural style (era doctrine). People should not adapt to the machine, but in turn, it’s better to make the machine work for users.

Keywords: artificial intelligence, collaboration, digital architecture, digital design theory, material selection, space construction

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Authors: Sertac Arslan, Sezer Kefeli

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In this paper, firstly supercavitating phenomenon and supercavity shape design parameters are explained and then drag force calculation methods of high speed supercavitating torpedoes are investigated with numerical techniques and verified with empirical studies. In order to reach huge speeds such as 200, 300 knots for underwater vehicles, hydrodynamic hull drag force which is proportional to density of water (ρ) and square of speed should be reduced. Conventional heavy weight torpedoes could reach up to ~50 knots by classic underwater hydrodynamic techniques. However, to exceed 50 knots and reach about 200 knots speeds, hydrodynamic viscous forces must be reduced or eliminated completely. This requirement revives supercavitation phenomena that could be implemented to conventional torpedoes. Supercavitation is the use of cavitation effects to create a gas bubble, allowing the torpedo to move at huge speed through the water by being fully developed cavitation bubble. When the torpedo moves in a cavitation envelope due to cavitator in nose section and solid fuel rocket engine in rear section, this kind of torpedoes could be entitled as Supercavitating Torpedoes. There are two types of cavitation; first one is natural cavitation, and second one is ventilated cavitation. In this study, disk cavitator is modeled with natural cavitation and supercavitation phenomenon parameters are studied. Moreover, drag force calculation is performed for disk shape cavitator with numerical techniques and compared via empirical studies. Drag forces are calculated with computational fluid dynamics methods and different empirical methods. Numerical calculation method is developed by comparing with empirical results. In verification study cavitation number (σ), drag coefficient (CD) and drag force (D), cavity wall velocity (U

Keywords: cavity envelope, CFD, high speed underwater vehicles, supercavitation, supercavity flows

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Authors: Zhang Xingnan, Huang Jingjia, Feng Yue, Burra Venkata Durga Kumar

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This paper proposes a comprehensive approach to mitigate ROP (Return-Oriented Programming) attacks by combining internal operating system protection mechanisms and hardware-assisted techniques. Through extensive literature review, we identify the effectiveness of ASLR (Address Space Layout Randomization) and LBR (Last Branch Record) in preventing ROP attacks. We present a process involving buffer overflow detection, hardware-assisted ROP attack detection, and the use of Turing detection technology to monitor control flow behavior. We envision a specialized tool that views and analyzes the last branch record, compares control flow with a baseline, and outputs differences in natural language. This tool offers a graphical interface, facilitating the prevention and detection of ROP attacks. The proposed approach and tool provide practical solutions for enhancing software security.

Keywords: operating system, ROP attacks, returning-oriented programming attacks, ASLR, LBR, CFI, DEP, code randomization, hardware-assisted CFI

Procedia PDF Downloads 79

Authors: Wided Bakari, Patrice Bellot, Omar Trigui, Mahmoud Neji

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This article constitutes an opening to think of the modeling and analysis of Arabic texts in the context of a question-answer system. It is a question of exceeding the traditional approaches focused on morphosyntactic approaches. Furthermore, we present a new approach that analyze a text in order to extract correct answers then transform it to logical predicates. In addition, we would like to represent different levels of information within a text to answer a question and choose an answer among several proposed. To do so, we transform both the question and the text into logical forms. Then, we try to recognize all entailment between them. The results of recognizing the entailment are a set of text sentences that can implicate the user’s question. Our work is now concentrated on an implementation step in order to develop a system of question-answering in Arabic using techniques to recognize textual implications. In this context, the extraction of text features (keywords, named entities, and relationships that link them) is actually considered the first step in our process of text modeling. The second one is the use of techniques of textual implication that relies on the notion of inference and logic representation to extract candidate answers. The last step is the extraction and selection of the desired answer.

Keywords: NLP, Arabic language, question-answering, recognition text entailment, logic forms

Procedia PDF Downloads 324

Authors: Soumava Boral, Sanjay K. Chaturvedi, Ian Howard, Kristoffer McKee, V. N. A. Naikan

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Due to strict regulations from government to enhance the possibilities of sustainability practices in industries, and noting the advances in sustainable manufacturing practices, it is necessary that the associated processes are also sustainable. Maintenance of large scale and complex machines is a pivotal task to maintain the uninterrupted flow of manufacturing processes. Appropriate maintenance practices can prolong the lifetime of machines, and prevent associated breakdowns, which subsequently reduces different cost heads. Selection of the best maintenance strategies for such machines are considered as a burdensome task, as they require the consideration of multiple technical criteria, complex mathematical calculations, previous fault data, maintenance records, etc. In the era of the fourth industrial revolution, organizations are rapidly changing their way of business, and they are giving their utmost importance to sensor technologies, artificial intelligence, data analytics, automations, etc. In this work, the effectiveness of several maintenance strategies (e.g., preventive, failure-based, reliability centered, condition based, total productive maintenance, etc.) related to a large scale and complex gearbox, operating in a steel processing plant is evaluated in terms of economic, social, environmental and technical criteria. As it is not possible to obtain/describe some criteria by exact numerical values, these criteria are evaluated linguistically by cross-functional experts. Fuzzy sets are potential soft-computing technique, which has been useful to deal with linguistic data and to provide inferences in many complex situations. To prioritize different maintenance practices based on the identified sustainable criteria, multi-criteria decision making (MCDM) approaches can be considered as potential tools. Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) is a recent addition in the MCDM family and has proven its superiority over some well-known MCDM approaches, like TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and ELECTRE (ELimination Et Choix Traduisant la REalité). It has a simple but robust mathematical approach, which is easy to comprehend. On the other side, due to some inherent drawbacks of Intuitionistic Fuzzy Sets (IFS) and Pythagorean Fuzzy Sets (PFS), recently, the use of Fermatean Fuzzy Sets (FFSs) has been proposed. In this work, we propose the novel concept of FF-MAIRCA. We obtain the weights of the criteria by experts’ evaluation and use them to prioritize the different maintenance practices according to their suitability by FF-MAIRCA approach. Finally, a sensitivity analysis is carried out to highlight the robustness of the approach.

Keywords: Fermatean fuzzy sets, Fermatean fuzzy MAIRCA, maintenance strategy selection, sustainable manufacturing, MCDM

Procedia PDF Downloads 130

Authors: Sang Wook Park, Se Woon Choi, Yousok Kim, Byung Kwan Oh, Hyo Seon Park

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Various retrofit techniques for reinforced concrete frame with infill wall have been steadily developed. Among those techniques, strengthening methodology based on diagonal FRP strips (FRP bracings) has numerous advantages such as feasibility of implementing without interrupting the building under operation, reduction of cost and time, and easy application. Considering the safety of structure and retrofit cost, the most appropriate retrofit solution is needed. Thus, the objective of this study is to suggest pareto-optimal solution for existing building using FRP bracings. To find pareto-optimal solution analysis, NSGA-II is applied. Moreover, the seismic performance of retrofit building is evaluated. The example building is 5-storey, 3-bay RC frames with infill wall. Nonlinear static pushover analyses are performed with FEMA 356. The criterion of performance evaluation is inter-story drift ratio at the performance level IO, LS, CP. Optimal retrofit solutions is obtained for 32 individuals and 200 generations. Through the proposed optimal solutions, we confirm the improvement of seismic performance of the example building.

Keywords: retrofit, FRP bracings, reinforced concrete frame with infill wall, seismic performance evaluation, NSGA-II

Procedia PDF Downloads 420

Authors: Hasan Muslemani, Jeffrey Wilson, Xi Liang, Francisco Ascui, Katharina Kaesehage

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This paper aims to examine consumer behaviour towards, and the willingness to adopt, green steel use in the automotive sector, in order to identify potential barriers and opportunities for its widespread adoption. Semi-structured interviews were held with experts from global, regional and country-specific industry associations and automakers. The analysis shows there is a new shift towards lifecycle thinking in the sector, although these efforts have been voluntary and driven by customer and employee pressures rather than regulation. The paper further appraises possible demand for green steel within different vehicle types (based on size and powertrain), and shows that manufacturers of electric heavy-duty vehicles are most likely to adopt green steel in the first instance, given the amount of incorporated steel in the vehicles and the fact that lifecycle emissions lie predominantly in their manufacturing phase. A case for green advanced higher-strength steels (AHSS) can also be made in light-duty passenger vehicles, which may mitigate competition from light-weight alternative materials in terms of cost and greenness (depending on source and utilisation zones). This work builds on a wide sustainability-related literature in the automotive sector and highlights areas in need of urgent action if the sector as a whole were to meet its Paris Agreement climate targets, in particular a need to revisit current CO2 performance regulations to include Scope 1 and Scope 2 emissions, engage in educational green marketing campaigns, and explore innovative market-based mechanisms to bridge the gap between relatively-low carbon abatement costs of steelmaking and high abatement costs of vehicle manufacturing.

Keywords: Green steel, Consumer behaviour, Automotive industry, Environmental sustainability

Procedia PDF Downloads 151