Search results for: machine resistance training

Authors: Oloruntegbe Kunle Oke, Alake Ese Monica, Odutuyi Olubu Musili

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This research explores the differing effectiveness of cascade and cluster models in professional development programs for educators in Ondo State, Nigeria. The cascade model emphasizes a top-down approach, where training is cascaded from expert trainers to lower levels of teachers. In contrast, the cluster model, a bottom-up approach, fosters collaborative learning among teachers within specific clusters. Through a review of the literature and empirical studies of the implementations of the former in two academic sessions followed by the cluster model in another two, the study examined their effectiveness on teacher development, productivity and students’ achievements. The study also drew a comparative analysis of the strengths and weaknesses associated with each model, considering factors such as scalability, cost-effectiveness, adaptability in various contexts, and sustainability. 2500 teachers from Ondo State Primary Schools participated in the cascade with intensive training in five zones for a week each in two academic sessions. On the other hand, 1,980 and 1,663 teachers in 52 and 34 clusters, respectively, were in the first and the following session. The programs were designed for one week of rigorous training of teachers by facilitators in the former while the latter was made up of four components: sit-in-observation, need-based assessment workshop, pre-cluster and the actual cluster meetings in addition to sensitization, and took place one day a week for ten weeks. Validated Cluster Impact Survey Instruments, CISI and Teacher’s Assessment Questionnaire (TAQ) were administered to ascertain the effectiveness of the models during and after implementation. The findings from the literature detailed specific effectiveness, strengths and limitations of each approach, especially the potential for inconsistencies and resistance to change. Findings from the data collected revealed the superiority of the cluster model. Response to TAQ equally showed content knowledge and skill update in both but were more sustained in the cluster model. Overall, the study contributes to the ongoing discourse on effective strategies for improving teacher training and enhancing student outcomes, offering practical recommendations for the development and implementation of future professional development projects.

Keywords: cascade model, cluster model, teachers’ development, productivity, students’ achievement

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Authors: Olga Mironiuk, Małgorzata Kossowska

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The aim of the present study was to investigate the influence of Situational Attribution Training on reducing automatic in-group stereotyping in females. The experiment was conducted with the control of age and level of prejudice. 90 female participants were randomly assigned to two conditions: experimental and control group (each group was also divided into younger- and older-aged condition). Participants from the experimental condition were subjected to more extensive training. In the first part of the experiment, the experimental group took part in the first session of Situational Attribution Training while the control group participated in the Grammatical Training Control. In the second part of the research both groups took part in the Situational Attribution Training (which was considered as the second training session for the experimental group and the first one for the control condition). The training procedure was based on the descriptions of ambiguous situations which could be explained using situational or dispositional attributions. The participant’s task was to choose the situational explanation from two alternatives, out of which the second one presented the explanation based on neutral or stereotypically associated with women traits. Moreover, the experimental group took part in the third training session after two- day time delay, in order to check the persistence of the training effect. The main hypothesis stated that among participants taking part in the more extensive training, the automatic in-group stereotyping would be less frequent after having finished training sessions. The effectiveness of the training was tested by measuring the response time and the correctness of answers: the longer response time for the examples where one of two possible answers was based on the stereotype trait and higher correctness of answers was considered to be a proof of the training effectiveness. As the participants’ level of prejudice was controlled (using the Ambivalent Sexism Inventory), it was also assumed that the training effect would be weaker for participants revealing a higher level of prejudice. The obtained results did not confirm the hypothesis based on the response time: participants from the experimental group responded faster in case of situations where one of the possible explanations was based on stereotype trait. However, an interesting observation was made during the analysis of the answers’ correctness: regardless the condition and age group affiliation, participants made more mistakes while choosing the situational explanations when the alternative was based on stereotypical trait associated with the dimension of warmth. What is more, the correctness of answers was higher in the third training session for the experimental group in case when the alternative of situational explanation was based on the stereotype trait associated with the dimension of competence. The obtained results partially confirm the effectiveness of the training.

Keywords: female, in-group stereotyping, prejudice, situational attribution training

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Authors: Masaya Yoshikawa, Toshiya Asai, Ryoma Matsuhisa, Yusuke Nozaki, Kensaku Asahi

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Recently, side-channel attacks, which estimate secret keys using side-channel information such as power consumption and compromising emanations of cryptography circuits embedded in hardware, have become a serious problem. In particular, electromagnetic analysis attacks against cryptographic circuits between information processing and electromagnetic fields, which are related to secret keys in cryptography circuits, are the most threatening side-channel attacks. Therefore, it is important to evaluate tamper resistance against electromagnetic analysis attacks for cryptography circuits. The present study performs basic examination of the tamper resistance of cryptography circuits using electromagnetic analysis attacks with noise resources.

Keywords: tamper resistance, cryptographic circuit, hardware security evaluation, noise resources

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Authors: Sibel Karacaoglu, Fatma Ç. Kayapinar

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The aim of the study is to investigate the effect of the core training program on physical fitness characteristics and body composition in male volleyball players. 26 male university volleyball team players aged between 19 to 24 years who had no health problems and injury participated in the study. Subjects were divided into training (TG) and control groups (CG) as randomly. Data from twenty-one players who completed all training sessions were used for statistical analysis (TG,n=11; CG,n=10). A core training program was applied to the training group three days a week for 10 weeks. On the other hand, the control group did not receive any training. Before and after the 10-week training program, pre- and post-testing comprised of body composition measurements (weight, BMI, bioelectrical impedance analysis) and physical fitness measurements including flexibility (sit and reach test), muscle strength (back, leg and grip strength by dynamometer), muscle endurance (sit-ups and push-ups tests), power (one-legged jump and vertical jump tests), speed (20m sprint, 30m sprint) and balance tests (one-legged standing test) were performed. Changes of pre- and post- test values of the groups were determined by using dependent t test. According to the statistical analysis of data, no significant difference was found in terms of body composition in the both groups for pre- and post- test values. In the training group, all physical fitness measurements improved significantly after core training program (p<0.05) except 30m speed and handgrip strength (p>0.05). On the hand, only 20m speed test values improved after post-test period (p<0.05), but the other physical fitness tests values did not differ (p>0.05) between pre- and post- test measurement in the control group. The results of the study suggest that the core training program has positive effect on physical fitness characteristics in male volleyball players.

Keywords: body composition, core training, physical fitness, volleyball

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Authors: Bjørn Salskov, Nicolaj Bang, Charlotte Falko

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Future labour markets demand employees that can carry out a non-linear task which is still not possible for computers. This means that employees must have well-developed soft-skills to perform at high levels in such a work environment. One of these soft-skills is presenting a message effectively. To be able to present a message effectively, one needs to practice this. To practice effectively, the trainee needs feedback on the current performance. Here VR environments can be used as a practice tool because it gives the trainee a sense of presence and reality. VR environments are becoming a cost-effective training method since it does not demand the presence of an expert to provide this feedback. The research article analysed in this study suggests that VR environment can be used and are able to provide the necessary feedback to the trainee which in turn will help the trainee become better at the task. The research analysed in this review does, however, show that there is a need for a study with larger sample size and a study which runs over a longer period.

Keywords: training, presentation, presentation skills, VR training, VR as a training tool, VR and presentation

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Authors: A. Gulbiniene, V. Jankauskaite

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Textile laminates with breathable membranes are used extensively in protective footwear. Such polymeric membranes act as a barrier to liquid water and soil entry from the environment, but are sufficiently permeable to water vapour to allow significant amounts of sweat to evaporate and affect the comfort of the wearer. In this paper the influence of absorbed humidity amount on the electrical properties of textiles lining laminates with and without polymeric membrane is presented. It was shown that textile laminate structure and its layers have a great influence on the water vapour absorption. Laminates with polyurethane foam layers show lower ability to absorb water vapour. Semi-permeable membrane increases absorbed humidity amount. The increase of water vapour absorption ability decreases textile laminates' electrical resistance. However, the intensity of the decrease in electrical resistance depends on the textile laminate layers' nature. Laminates with polyamide layers show significantly lower electrical resistance values.

Keywords: electrical resistance, humid atmosphere, textiles laminate, water vapour absorption

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Authors: Lavanya Madhuri Bollipo, K. V. Kadambari

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Objective: To discuss key issues in the diagnosis of Parkinson disease (PD), To discuss features influencing PD progression, To discuss importance of brain SPECT data in PD diagnosis, and To discuss the essentiality of machine learning techniques in early diagnosis of PD. An accurate and early diagnosis of PD is nowadays a challenge as clinical symptoms in PD arise only when there is more than 60% loss of dopaminergic neurons. So far there are no laboratory tests for the diagnosis of PD, causing a high rate of misdiagnosis especially when the disease is in the early stages. Recent neuroimaging studies with brain SPECT using 123I-Ioflupane (DaTSCAN) as radiotracer shown to be widely used to assist the diagnosis of PD even in its early stages. Machine learning techniques can be used in combination with image analysis procedures to develop computer-aided diagnosis (CAD) systems for PD. This paper addressed recent studies involving diagnosis of PD in its early stages using brain SPECT data with Machine Learning Techniques.

Keywords: Parkinson disease (PD), dopamine transporter, single-photon emission computed tomography (SPECT), support vector machine (SVM)

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Authors: Abdul Rauf, Xiaoxing Liu, Rizwan Qaisar Danish, Waqas Amin

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The core intention of this study is to analyze the linkage of training, job attitudes and motivation through a mediation model in the banking sector of Pakistan. Moreover, this study is executed to answer a range of queries regarding the consideration of employees about training, job satisfaction, motivation and organizational commitment. Hence, the association of training with job satisfaction, job satisfaction with motivation, organizational commitment with job satisfaction, organization commitment as independently with motivation and training directly related to motivation is determined in this course of study. A questionnaire crafted for comprehending the purpose of this study by including four variables such as training, job satisfaction, motivation and organizational commitment which have to measure. A sample of 450 employees from seventeen private (17) banks and two (2) public banks was taken on the basis of convenience sampling from Pakistan. However, 357 questionnaires, completely filled were received back. AMOS used for assessing the conformity factor analysis (CFA) model and statistical techniques practiced to scan the collected data (i.e.) descriptive statistics, regression analysis and correlation analysis. The empirical findings revealed that training and organizational commitment has a significant and positive impact directly on job satisfaction and motivation as well as through the mediator (job satisfaction) also the impact sensing in the same way on the motivation of employees in the financial Banks of Pakistan. In this research study, the banking sector is under discussion, so the findings could not generalize on other sectors such as manufacturing, textiles, telecom, and medicine, etc. The low sample size is also the limitation of this study. On the foundation of these results the management fascinates to make the revised strategies regarding training program for the employees as it enhances their motivation level, and job satisfaction on a regular basis.

Keywords: job satisfaction, motivation, organizational commitment, Pakistan, training

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Authors: Anne-Lena Kampen, Øivind Kure

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Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.

Keywords: central machine learning, embedded machine learning, energy consumption, local machine learning, wireless sensor networks, WSN

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Authors: Adamu Abdullahi, On Francisca, Saidu Isah Rambo, G. N. Obunadike, D. T. Chinyio

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The paper discusses the potential threat of Denial of Service (DoS) attacks in the Internet of Things (IoT) networks on constrained application protocols (CoAP). As billions of IoT devices are expected to be connected to the internet in the coming years, the security of these devices is vulnerable to attacks, disrupting their functioning. This research aims to tackle this issue by applying mixed methods of qualitative and quantitative for feature selection, extraction, and cluster algorithms to detect DoS attacks in the Constrained Application Protocol (CoAP) using the Machine Learning Algorithm (MLA). The main objective of the research is to enhance the security scheme for CoAP in the IoT environment by analyzing the nature of DoS attacks and identifying a new set of features for detecting them in the IoT network environment. The aim is to demonstrate the effectiveness of the MLA in detecting DoS attacks and compare it with conventional intrusion detection systems for securing the CoAP in the IoT environment. Findings: The research identifies the appropriate node to detect DoS attacks in the IoT network environment and demonstrates how to detect the attacks through the MLA. The accuracy detection in both classification and network simulation environments shows that the k-means algorithm scored the highest percentage in the training and testing of the evaluation. The network simulation platform also achieved the highest percentage of 99.93% in overall accuracy. This work reviews conventional intrusion detection systems for securing the CoAP in the IoT environment. The DoS security issues associated with the CoAP are discussed.

Keywords: algorithm, CoAP, DoS, IoT, machine learning

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Authors: Zainab Dashti, Leila Vali

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Background: The Middle East, in particular Kuwait, contains one of the highest rates of patients with Diabetes in the world. Generally, infections resistant to antibiotics among the diabetic population has been shown to be on the rise. This is the first study in Kuwait to compare the antibiotic resistance profiles and genotypic differences between the resistant isolates of Enterobacteriaceae obtained from diabetic and non-diabetic patients. Material/Methods: In total, 65 isolates were collected from diabetic patients consisting of 34 E. coli, 15 K. pneumoniae and 16 other Enterobacteriaceae species (including Salmonella spp. Serratia spp and Proteus spp.). In our control group, a total of 49 isolates consisting of 37 E. coli, 7 K. pneumoniae and 5 other species (including Salmonella spp. Serratia spp and Proteus spp.) were included. Isolates were identified at the species level and antibiotic resistance profiles, including Colistin, were determined using initially the Vitek system followed by double dilution MIC and E-test assays. Multi drug resistance (MDR) was defined as isolates resistant to a minimum of three antibiotics from three different classes. PCR was performed to detect ESBL genes (blaCTX-M, blaTEM & blaSHV), flouroquinolone resistance genes (qnrA, qnrB, qnrS & aac(6’)-lb-cr) and carbapenem resistance genes (blaOXA, blaVIM, blaGIM, blaKPC, blaIMP, & blaNDM) in both groups. Pulse field gel electrophoresis (PFGE) was performed to compare clonal relatedness of both E. coli and K.pneumonaie isolates. Results: Colistin resistance was determined in three isolates with MICs of 32-128 mg/L. A significant difference in resistance to ampicillin (Diabetes 93.8% vs control 72.5%, P value <0.002), augmentin (80% vs 52.5%, p value < 0.003), cefuroxime (69.2% vs 45%, p value < 0.0014), ceftazadime (73.8% vs 42.5%, p value <0.001) and ciprofloxacin (67.6% vs 40%, p value < 0.005) were determined. Also, a significant difference in MDR rates between the two groups (Diabetes 76.9%, control 57.5%, p value <0.036 were found. All antibiotic resistance genes showed a higher prevalence among the diabetic group, except for blaCTX-M, which was higher among the control group. PFGE showed a high rate of diversity between each group of isolates. Conclusions: Our results suggested an alarming rate of antibiotic resistance, in particular Colistin resistance (1.8%) among K. pneumoniea isolated from diabetic patients in Kuwait. MDR among Enterobacteriaceae infections also seems to be a worrying issue among the diabetics of Kuwait. More efforts are required to limit the issue of antibiotic resistance in Kuwait, especially among patients with diabetes mellitus.

Keywords: antibiotic resistance, diabetes, enterobacreriacae, multi antibiotic resistance

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Authors: Gabrielle Veloso, Welison Ty

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Trait anxiety is a pervasive tendency to attend to and experience fears and worries to a disproportionate degree, across various situations. This study sought to determine if participants who undergo emotional working memory training will have significantly lower scores on the trait anxiety scales post-intervention. The study also sought to determine if emotional regulation mediated the relationship between working memory training and trait anxiety. Forty-nine participants underwent 20 days of computerized emotional working memory training called Emotional Dual n-back, which involves viewing a continuous stream of emotional content on a grid, and then remembering the location and color of items presented on the grid. Participants of the treatment group had significantly lower trait anxiety compared to controls post-intervention. Mediation analysis determined that working memory training had no significant relationship to anxiety as measured by the Beck’s Anxiety Inventory-Trait (BAIT), but was significantly related to anxiety as measured by form Y2 of the Spielberger State-Trait Anxiety Inventory (STAI-Y2). Emotion regulation, as measured by the Emotional Regulation Questionnaire (ERQ), was found not to mediate between working memory training and trait anxiety reduction. Results suggest that working memory training may be useful in reducing psychoemotional symptoms rather than somatic symptoms of trait anxiety. Moreover, it proposes for future research to further look into the mediating role of emotion regulation via neuroimaging and the development of more comprehensive measures of emotion regulation.

Keywords: anxiety, emotion regulation, working-memory, working-memory training

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Authors: Sahil Kumar, Surinder Pal, Rahul Kapoor

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This paper is focused on to define the basic difference between hot and cold chamber high pressure die casting process which is not fully defined in a research before paper which we have studied. The pressure die casting is basically defined into two types (1) Hot chamber Die Casting (2) Cold chamber Die Casting. Cold chamber die casting is used for casting alloys that require high pressure and have a high melting temperature, such as brass, aluminum, magnesium, copper based alloys and other high melting point nonferrous alloys. Hot chamber die casting is suitable for casting zinc, tin, lead, and low melting point alloys. In hot chamber die casting machine, the molten metal is an integral pan of the machine. It mainly consists of hot chamber and gooseneck type metal container made of cast iron. This machine is mainly used for low melting alloys and alloys of metals like zinc, lead etc. Metals and alloys having a high melting point and those which are having an affinity for iron cannot be cast by this machine, which could otherwise attack the shot sleeve and damage the machine.

Keywords: hot chamber die casting, cold chamber die casting, metals and alloys, casting technology

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Authors: Yessica Nataliani, Miin-Shen Yang

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Cell formation (CF) is an important step in group technology. It is used in designing cellular manufacturing systems using similarities between parts in relation to machines so that it can identify part families and machine groups. There are many CF methods in the literature, but there is less spectral clustering used in CF. In this paper, we propose a spectral clustering algorithm for machine-part CF. Some experimental examples are used to illustrate its efficiency. Overall, the spectral clustering algorithm can be used in CF with a wide variety of machine/part matrices.

Keywords: group technology, cell formation, spectral clustering, grouping efficiency

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Authors: Jazmi Adlan Bohari, I. Dewa Ketut Kerta Widana

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Education on disaster management has been made as a mainstream focus of many countries. In Indonesia, this has been emphasized with the direct order of the President of Indonesia to implement disaster education at all levels in both formal and informal education. Indonesia Defense University (IDU) executes this order through Three Pillars of Higher Education, which consists of research, education, and community service. One of them is a five-day disaster management training for 105 participants divided into three batches that consist of faculty members and graduate students. This training uses the 2018 Basic Disaster Management Training Modul issued by the Indonesia National Disaster Management Agency (BNPB). This research aims to analyze the impact of this short training on the trainee’s knowledge and understanding of basic disaster management. This study is a qualitative research with case study approach. The research shows that after five days of training, there as a significant increase in knowledge and understanding of basic disaster management experienced by the trainees with a 61,73% overall increase. The post-training data shows that 61% of the trainees have a very good understanding, 24% with good understanding, 13% with adequate understanding, and 2% with poor understanding. The result suggests that a short-time education with a structured curriculum can successfully increase the knowledge and understanding of disaster management on a basic level and can hypothetically contribute to the effort to reduce disaster risks.

Keywords: disaster education, basic disaster management training, three Pillars of Higher Education, disaster risk reduction

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Authors: Sofia Hartati

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This research is aimed at describing training in early childhood education program empirically, describing teachers ability to plan lessons empirically, and acquiring empirical data as well as analyzing the influence of guided and independent training toward teachers competence in planning early childhood learning program. The method used is an experiment. It collected data with a population of 76 early childhood educators in Tunjung Teja Sub District area through random sampling technique and grouped into two namely 38 people in an experiment class and 38 people in a controlled class. The technique used for data collections is a test. The result of the research shows that there is a significant influence between training for guided educators toward Teachers Ability toward Planning Early Childhood Learning Program. Guided training has been proven to improve the ability to comprehend planning a learning program. The ability to comprehend planning a learning program owned by teachers of early childhood program comprises of 1) determining the characteristics and competence of students prior to learning; 2) formulating the objective of the learning; 3) selecting materials and its sequences; 4) selecting teaching methods; 5) determining the means or learning media; 6) selecting evaluation strategy as a part of teachers pedagogic competence. The result of this research describes a difference in the competence level of teachers who have joined guided training which is relatively higher than the teachers who joined the independent training. Guided training is one of an effective way to improve the knowledge and competence of early childhood educators.

Keywords: competence, planning, teachers, training

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Authors: A. Hassannia, S. Ramezani

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The technology of superconductivity has developed in many power system devices such as transmission cable, transformer, current limiter, motor and generator. Superconducting wires can carry high density current without loss, which is the capability that is used to design the compact, lightweight and more efficient electrical machines. Superconducting motors have found applications in marine and air propulsion systems as well as superconducting generators are considered in low power hydraulic and wind generators. This paper presents a rim-driven superconducting synchronous generator for hydraulic power plant. The rim-driven concept improves the performance of hydro turbine. Furthermore, high magnetic field that is produced by superconducting windings allows replacing the rotor core. As a consequent, the volume and weight of the machine is decreased significantly. In this paper, a 1 MW coreless rim-driven superconducting synchronous generator is designed. Main performance characteristics of the proposed machine are then evaluated using finite elements method and compared to an ordinary similar size synchronous generator.

Keywords: coreless machine, electrical machine design, hydraulic generator, rim-driven machine, superconducting generator

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Authors: Igbakura I. Luga, Alex A. Adikwu

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A comparison of resistance to quinolones was carried out on isolates of Shiga toxin-producing Escherichia coliO157:H7 from cattle and mecA and nuc genes harbouring Staphylococcus aureus from pigs. The isolates were separately tested in the first and current decades of the 21^st century. The objective was to demonstrate the dissemination of resistance to this frontline class of antibiotic by bacteria from food animals and bring to the limelight the spread of antibiotic resistance in Nigeria. A total of 10 isolates of the E. coli O157:H7 and 9 of mecA and nuc genes harbouring S. aureus were obtained following isolation, biochemical testing, and serological identification using the Remel Wellcolex E. coli O157:H7 test. Shiga toxin-production screening in the E. coli O157:H7 using the verotoxin E. coli reverse passive latex agglutination (VTEC-RPLA) test; and molecular identification of the mecA and nuc genes in S. aureus. Detection of the mecA and nuc genes were carried out using the protocol by the Danish Technical University (DTU) using the following primers mecA-1:5'-GGGATCATAGCGTCATTATTC-3', mecA-2: 5'-AACGATTGTGACACGATAGCC-3', nuc-1: 5'-TCAGCAAATGCATCACAAACAG-3', nuc-2: 5'-CGTAAATGCACTTGCTTCAGG-3' for the mecA and nuc genes, respectively. The nuc genes confirm the S. aureus isolates and the mecA genes as being methicillin-resistant and so pathogenic to man. The fluoroquinolones used in the antibiotic resistance testing were norfloxacin (10 µg) and ciprofloxacin (5 µg) in the E. coli O157:H7 isolates and ciprofloxacin (5 µg) in the S. aureus isolates. Susceptibility was tested using the disk diffusion method on Muller-Hinton agar. Fluoroquinolone resistance was not detected from isolates of E. coli O157:H7 from cattle. However, 44% (4/9) of the S. aureus were resistant to ciprofloxacin. Resistance of up to 44% in isolates of mecA and nuc genes harbouring S. aureus is a compelling evidence for the rapid spread of antibiotic resistance from bacteria in food animals from Nigeria. Ciprofloxacin is the drug of choice for the treatment of Typhoid fever, therefore widespread resistance to it in pathogenic bacteria is of great public health significance. The study concludes that antibiotic resistance in bacteria from food animals is on the increase in Nigeria. The National Food and Drug Administration and Control (NAFDAC) agency in Nigeria should implement the World Health Organization (WHO) global action plan on antimicrobial resistance. A good starting point can be coordinating the WHO, Office of International Epizootics (OIE), Food and Agricultural Organization (FAO) tripartite draft antimicrobial resistance monitoring and evaluation (M&E) framework in Nigeria.

Keywords: Fluoroquinolone, Nigeria, resistance, Staphylococcus aureus

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Authors: Mahtab Assadian, Mohd Hasbullah Idris, Mostafa Rezazadeh Shirdar, Mohammad Mahdi Taheri, ‎S. Izman

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Corrosion behaviour and surface roughness of magnesium substrate were investigated after NaOH pretreatment in different concentrations (1, 5, and 10 molar) and duration of (10 min, 30 min, 1 h, 3 h, 6 h and 24 h). Creation of Mg(OH)2 barrier layer after pretreatment enhanced corrostion resistance as well as wettability of substrate surface. Characterization including Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) was conducted to detect the existence of this barrier layer. Surface roughness and wettability of substrate was evaluated using atomic force microscopy (AFM) and contact angle measurement respectively. It is found that magnesium treated by 1M NaOH for 30 min reveals higher corrosion resistance and lower water contact angle of substrate surface. In addition, this investigation indicates that pH value of SBF solution is strongly influenced by different time and concentration of alkaline pretreatment.

Keywords: magnesium, NaOH pretreatment, corrosion resistance, wettability

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Authors: Rabia Faridi, Rizwana Maqbool, Umara Sahar Rana, Zaheer Ahmad

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Climate change impacts agriculture, notably in Germany, where spring faba beans predominate. However, improved winter hardiness aligns with milder winters, enabling autumn-sown varieties. Genetic resistance to Ascochyta blight is vital for crop integration. Traditional breeding faces challenges due to complex inheritance. This study assessed 224 homozygous faba bean lines for Ascochyta resistance traits. To achieve h²>70%, 12 replicates were required (realized h²=87%). Genetic variation and strong trait correlations were observed. Five lines outperformed 29H, while three were highly susceptible. A genome-wide association study (GWAS) with 188 inbred lines and 2058 markers, including 17 guide SNP markers, identified 12 markers associated with resistance traits, potentially indicating new resistance genes. One guide marker (Vf-Mt1g014230-001) on chromosome III validated a known QTL. The guided marker approach complemented GWAS, facilitating marker-assisted selection for Ascochyta resistance. The Göttingen Winter Bean Population offers promise for resistance breeding.

Keywords: genome wide association studies, marker assisted breeding, faba bean, ascochyta blight

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Authors: Saba Gachpaz, Hamid Reza Heidari

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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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Authors: J. Kazior, A. Szewczyk-Nykiel, T. Pieczonka, M. Laska

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Aluminium alloys are an important class of engineering materials for structural applications. This is due to the fact that these alloys have many interesting properties, namely, low density, high ratio of strength to density, good thermal and electrical conductivity, good corrosion resistance as well as extensive capabilities for shaping processes. In case of classical PM technology a particular attention should be paid to the selection of appropriate parameters of compacting and sintering processes and to keeping them. The latter need arises from the high sensitivity of aluminium based alloy powders on any fluctuation of technological parameters, in particular those related to the temperature-time profile and gas flow. Only then the desired sintered compacts with residual porosity may be produced. Except high mechanical properties, the other profitable properties of almost fully dense sintered components could be expected. Among them is corrosion resistance, rarely investigated on PM aluminium alloys. Thus, in the current study the Alumix 431/D commercial, press-ready grade powder was used for this purpose. Sintered compacts made of it in different conditions (isothermal sintering temperature, gas flow rate) were subjected to corrosion experiments in 0,1 M and 0,5 M NaCl solutions. The potentiodynamic curves were used to establish parameters characterising the corrosion resistance of sintered Alumix 431/D powder, namely, the corrosion potential, the corrosion current density, the polarization resistance, the breakdown potential. The highest value of polarization resistance, the lowest value of corrosion current density and the most positive corrosion potential was obtained for Alumix431/D powder sintered at 600°C and for highest protective gas flow rate.

Keywords: aluminium alloys, sintering, corrosion resistance, industry

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Authors: Emel Bayraktar, Gulengun Turk

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Introduction and Objective: Safe administration of medicines is one of the main responsibilities of nurses. Intramuscular drug administration is among the most common methods used by nurses among all drug applications. This study was carried out in order to determine determine the effect of education given on injection in ventrogluteal area on the level of knowledge of nurses on this subject. Methods: The sample of the study consisted of 20 nurses who agreed to participate in the study between 01 October and 31 December 2019. The research is a pretest-posttest comparative, quasi-experimental type pilot study. The nurses were given a 4-hour training prepared on injection into the ventrogluteal area. The training consisted of two hours of theoretical and two hours of laboratory practice. Before the training and 4 weeks after the training, a questionnaire form containing questions about their knowledge and practices regarding the injection of the ventrogluteal region was applied to the nurses. Results: The average age of the nurses is 26.55 ± 7.60, 35% (n = 7) of them are undergraduate and 30% (n = 6) of them work in intensive care units. Before the training, 35% (n = 7) of the nurses stated that the most frequently used intramuscular injection site was the ventrogluteal area, and 75% (n = 15) stated that the safest area was the rectus femoris muscle. After the training, 55% (n = 11) of the nurses stated that they most frequently used the ventrogluteal area and 100% (n = 20) of them stated that the ventrogluteal area was the safest area. The average score the nurses got from the premises before the training is 14.15 ± 6.63 (min = 0, max = 20), the total score is 184. The average score obtained after the training was determined as 18.69 ± 2.35 (min = 12, max = 20), and the total score was 243. Conclusion: As a result of the research, it was determined that the training given on the injection of ventrogluteal area increased the knowledge level of the nurses. It is recommended to organize in-service trainings for all nurses on the injection of ventrogluteal area.

Keywords: safe injection, knowledge level, nurse, intramuscular injection, ventrogluteal area

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Authors: Kalimi Trinadh, Corinne Nouveau, A. S. Khanna, Karanveer S. Aneja, K. Ram Mohan Rao

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This study concerns improving the corrosion resistance of low alloy steel after plasma nitriding performed at variable time and temperature. Nitriding carried out in the temperature range of 450-550ᵒC for a various time period of 1-8 hrs. at 500Pa in a glow discharge plasma of H₂ and N₂ (80:20). The substrate was kept biased negatively at 250V. Following nitriding the X-ray diffraction studies shown that the phases formed were mainly γ′ (Fe₄N) and ε (Fe₂₋₃N). The ε (Fe₂₋₃N) phase found to be the dominating phase. Cross sections of the samples under scanning electron microscope point analyses revealed the presence of nitrogen in the surface region. For the assessment of corrosion resistance property, potentiodynamic polarization tests were performed in 3.5% NaCl solution. It has been shown that the plasma nitriding significantly improved the corrosion resistance when compared to the as-received steel. Furthermore, it has also been found that nitriding for 6h has more corrosion resistance than nitriding for the 8h duration. The hardness of the nitrided samples was measured by Vicker’s microhardness tester. The hardness of the nitrided steel was found to be improved much above the hardness of the steel in the as-received condition. It was found to be around two-fold of the initial hardness.

Keywords: corrosion, steel, plasma nitriding, X-ray diffraction

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Authors: Chalakorn Chitsaart, Suchada Rianmora, Mann Rattana-Areeyagon, Wutichai Namjaiprasert

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G-code is the main factor in computer numerical control (CNC) machine for controlling the tool-paths and generating the profile of the object’s features. For obtaining high surface accuracy of the surface finish, non-stop operation is required for CNC machine. Recently, to design a new product, the strategy that concerns about a change that has low impact on business and does not consume lot of resources has been introduced. Cost and time for designing minor changes can be reduced since the traditional geometric details of the existing models are applied. In order to support this strategy as the alternative channel for machining operation, this research proposes the automatic generating codes for CNC milling operation. Using this technique can assist the manufacturer to easily change the size and the geometric shape of the product during the operation where the time spent for setting up or processing the machine are reduced. The algorithm implemented on MATLAB platform is developed by analyzing and evaluating the geometric information of the part. Codes are created rapidly to control the operations of the machine. Comparing to the codes obtained from CAM, this developed algorithm can shortly generate and simulate the cutting profile of the part.

Keywords: geometric shapes, milling operation, minor changes, CNC Machine, G-code, cutting parameters

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Authors: Ghada A. Alfattni

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Analysing unbalanced datasets is one of the challenges that practitioners in machine learning field face. However, many researches have been carried out to determine the effectiveness of the use of the synthetic minority over-sampling technique (SMOTE) to address this issue. The aim of this study was therefore to compare the effectiveness of the SMOTE over different models on unbalanced datasets. Three classification models (Logistic Regression, Support Vector Machine and Nearest Neighbour) were tested with multiple datasets, then the same datasets were oversampled by using SMOTE and applied again to the three models to compare the differences in the performances. Results of experiments show that the highest number of nearest neighbours gives lower values of error rates. 

Keywords: imbalanced datasets, SMOTE, machine learning, logistic regression, support vector machine, nearest neighbour

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Authors: Alireza Barari, Maryam Firoozi, Maryam Ebrahimzadeh, Romina Roohan Ardeshiri, Maryam Kamarloeei

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Background: The The purpose of this study was to evaluate the effect of six-week aerobic training and taxol consumption on interleukin 8 and Plasminogen Activator Inhibitor-1 (PAI-1) in mice with cervical cancer. Material and method: In this experimental study, 40 female C57 mice, eight weeks old, were randomly divided into 4 groups: cancer, cancer-taxol complement, cancer-training and cancer-training - taxol complement with 10 mice in each group. The implantation of cancerous tumors was performed under the skin of the upper pelvis. The training group completed the endurance training protocol, which included 3 sessions per week, 50 minutes per session, at a speed of 14-18 m/s for six weeks. A dose of 60 mg/ kg/day, a pure extract of Taxol was injected peritoneal Data were analyzed by t-test, One-way ANOVA and post hoc Bonferron's at the significant level P<0. 05. Results: The results showed that there was a significant difference between mean values of interleukin-8 (P < 0.05, F = 12.25) and the plasminogen activator inhibitor-1 (P < 0.05, P=0.10737) in four groups. A significance level of less than 0.05 in Tukey test for both variables also showed a significant difference between the "control" group and the complementary "exercise" group. Namely, six weeks of aerobic training, along with taxol, have a significant effect on the level of plasminogen activator inhibitor-1 and interleukin-8 mice with cervical cancer. Conclusion: Considering the effect of training on these variables, this type of exercise can be used as a complementary therapeutic approach along with other therapies for cervical cancer.

Keywords: cervical cancer, taxol, endurance training, interleukin 8, plasminogen activator inhibitor-1

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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Authors: Jon-Chao Hong, Tsai-Ru Fan, Shih-Min Hsu

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Virtual reality (VR) can generate mirror neurons that facilitate learners to transfer virtual skills to a real environment in skill training, and most studies approved the positive effect of applying in many domains. However, rare studies have focused on the experiential values of participants from a gender perspective. To address this issue, the present study used a VR program named kitchen assistant training, focusing on cutting vegetables and invited 400 students to practice for 20 minutes. Useful data from 367 were subjected to statistical analysis. The results indicated that male participants. From the comparison of average, it seems that females perceived higher than males in learning effectiveness. Expectedly, the VR-Cutting vegetables can be used for pre-training of real vegetable cutting.

Keywords: exponential value, facilitate learning, gender difference, virtual reality

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Authors: Fuad M. Alkoot

Abstract:

The main component of a machine learning system is the classifier. Classifiers are mathematical models that can perform classification tasks for a specific application area. Additionally, many classifiers are combined using any of the available methods to reduce the classifier error rate. The benefits gained from the combination of multiple classifier designs has motivated the development of diverse approaches to multiple classifiers. We aim to investigate using fractal geometry to develop an improved classifier combiner. Initially we experiment with measuring the fractal dimension of data and use the results in the development of a combiner strategy.

Keywords: fractal geometry, machine learning, classifier, fractal dimension

Procedia PDF Downloads 206