Search results for: inventory classification

Authors: Monireh Ahmadi Bani, Adel Khorramrouz, Lalenoor Morvarid, Bagheri Mahtab

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Background:- Foot disorders are common in musculoskeletal problems. Plantar pressure distribution measurement is one the most important part of foot disorders diagnosis for quantitative analysis. However, the association of plantar pressure and foot disorders is not clear. With the growth of dataset and machine learning methods, the relationship between foot disorders and plantar pressures can be detected. Significance of the study:- The purpose of this study was to predict the probability of common foot disorders based on peak plantar pressure distribution and center of pressure during walking. Methodologies:- 2323 participants were assessed in a foot therapy clinic between 2015 and 2021. Foot disorders were diagnosed by an experienced physician and then they were asked to walk on a force plate scanner. After the data preprocessing, due to the difference in walking time and foot size, we normalized the samples based on time and foot size. Some of force plate variables were selected as input to a deep neural network (DNN), and the probability of any each foot disorder was measured. In next step, we used support vector machine (SVM) and run dataset for each foot disorder (classification of yes or no). We compared DNN and SVM for foot disorders prediction based on plantar pressure distributions and center of pressure. Findings:- The results demonstrated that the accuracy of deep learning architecture is sufficient for most clinical and research applications in the study population. In addition, the SVM approach has more accuracy for predictions, enabling applications for foot disorders diagnosis. The detection accuracy was 71% by the deep learning algorithm and 78% by the SVM algorithm. Moreover, when we worked with peak plantar pressure distribution, it was more accurate than center of pressure dataset. Conclusion:- Both algorithms- deep learning and SVM will help therapist and patients to improve the data pool and enhance foot disorders prediction with less expense and error after removing some restrictions properly.

Keywords: deep neural network, foot disorder, plantar pressure, support vector machine

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Authors: Allioua Meryem

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Similar to much of the developing world, Algeria is currently undergoing an epidemiological transition. While mal- and under-nutrition and infectious diseases used to be the main causes of poor health, today there is a higher proportion of chronic, non-communicable diseases (NCDs), including cardiovascular disease, diabetes mellitus, cancer, etc. According to estimates for Algeria from the World Health Organization (WHO), NCDs accounted for 63% of all deaths in 2010. The objective of this study was the assessment of eating habits and anthropometric characteristics in a group of youth aged 15 to 19 years in Tlemcen. This study was conducted on a total effective of 806 youth enrolled in a descriptive cross-sectional study; the classification of nutritional status has been established by international standards IOTF, youth were defined as obese if they had a BMI ≥ 95th percentile, and youth with 85th ≤ BMI ≤ 95th percentile were defined as overweight. Wc is classified by the criteria HD, Wc with moderate risk ≥ 90th percentile and Wc with high risk ≥ 95th percentile. The dietary assessment was based on a 24-hour dietary recall assisted by food records. USDA’S nutrient database for Nutrinux® program was used to analyze dietary intake. Nutrients adequacy ratio was calculated by dividing daily individual intake to dietary recommended intake DRI for each nutrient. 9% of the population was overweight, 3% was obese, 7.5% had abdominal obesity, foods eaten in moderation are chips, cookies, chocolate 1-3 times/day and increased consumption of fried foods in the week, almost half of youth consume sugary drinks more than 3 times per week, we observe a decreased intake of energy, protein (P < 0.001, P = 0.003), SFA (P = 0.018), the NAR of phosphorus, iron, magnesium, vitamin B6, vitamin E, folate, niacin, and thiamin reflecting less consumption of fruit, vegetables, milk, and milk products. Youth surveyed have eating habits at risk of developing obesity and chronic disease.

Keywords: food intake, health, anthropometric characteristics, Algeria

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Authors: Venuka Kuruwita Arachchige Don, Mohamed Shaheen, Chris Goodier

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Aerated autoclaved concrete (AAC) is known for its lightweight, easy handling, high thermal insulation, and extremely porous structure. Investigation of pore behavior in AAC is crucial for characterizing the material, standardizing design and production techniques, enhancing the mechanical, durability, and thermal performance, studying the effectiveness of protective measures, and analyzing the effects of weather conditions. The significant details of pores are complicated to observe with acknowledged accuracy. The High-resolution Field Emission Scanning Electron Microscope (FESEM) image analysis is a promising technique for investigating the pore behavior and density of AAC, which is adopted in this study. Mercury intrusion porosimeter and gas pycnometer were employed to characterize porosity distribution and density parameters. The analysis considered three different densities of AAC blocks and three layers in the altitude direction within each block. A set of understandings was presented to extract and analyze the details of pore shape, pore size, pore connectivity, and pore percentages from FESEM images of AAC. Average pore behavior outcomes per unit area were presented. Comparison of porosity distribution and density parameters revealed significant variations. FESEM imaging offered unparalleled insights into porosity behavior, surpassing the capabilities of other techniques. The analysis conducted from a multi-staged approach provides porosity percentage occupied by various pore categories, total porosity, variation of pore distribution compared to AAC densities and layers, number of two-dimensional and three-dimensional pores, variation of apparent and matrix densities concerning pore behaviors, variation of pore behavior with respect to aluminum content, and relationship among shape, diameter, connectivity, and percentage in each pore classification.

Keywords: autoclaved aerated concrete, density, imaging technique, microstructure, porosity behavior

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Authors: Mariam Vardiashvili

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The economic value of the asset impairment process is quite large. Impairment reflects the reduction of future economic benefits or service potentials itemized in the asset. The assets owned by public sector entities bring economic benefits or are used for delivery of the free-of-charge services. Consequently, they are classified as cash-generating and non-cash-generating assets. IPSAS 21 - Impairment of non-cash-generating assets, and IPSAS 26 - Impairment of cash-generating assets, have been designed considering this specificity.  When measuring impairment of assets, it is important to select the relevant methods. For measurement of the impaired Non-Cash-Generating Assets, IPSAS 21 recommends three methods: Depreciated Replacement Cost Approach, Restoration Cost Approach, and  Service Units Approach. Impairment of Value in Use of Cash-Generating Assets (according to IPSAS 26) is measured by discounted value of the money sources to be received in future. Value in use of the cash-generating asserts (as per IPSAS 26) is measured by the discounted value of the money sources to be received in the future. The article provides classification of the assets in the public sector  as non-cash-generating assets and cash-generating assets and, deals also with the factors which should be considered when evaluating  impairment of assets. An essence of impairment of the non-financial assets and the methods of measurement thereof evaluation are formulated according to IPSAS 21 and IPSAS 26. The main emphasis is put on different methods of measurement of the value in use of the impaired Cash-Generating Assets and Non-Cash-Generation Assets and the methods of their selection. The traditional and the expected cash flow approaches for calculation of the discounted value are reviewed. The article also discusses the issues of recognition of impairment loss and its reflection in the financial reporting. The article concludes that despite a functional purpose of the impaired asset, whichever method is used for measuring the asset, presentation of realistic information regarding the value of the assets should be ensured in the financial reporting. In the theoretical development of the issue, the methods of scientific abstraction, analysis and synthesis were used. The research was carried out with a systemic approach. The research process uses international standards of accounting, theoretical researches and publications of Georgian and foreign scientists.

Keywords: cash-generating assets, non-cash-generating assets, recoverable (usable restorative) value, value of use

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Authors: Folong Tchoffo Marlyse Fabiola, Anaba Onana Achille Basile

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Located in the western region of Cameroon, in the BAMBOUTOS department, the city of Mbouda belongs to the Pan-African basement. The water resources exploited in this region consist of surface water and groundwater from weathered and fractured aquifers within the same basement. To study the factors determining the productivity of aquifers in the Mbouda area, we adopted a methodology based on collecting data from boreholes drilled in the region, identifying different types of rocks, analyzing structures, and conducting geophysical surveys in the field. The results obtained allowed us to distinguish two main types of rocks: metamorphic rocks composed of amphibolites and migmatitic gneisses and igneous rocks, namely granodiorites and granites. Several types of structures were also observed, including planar structures (foliation and schistosity), folded structures (folds), and brittle structures (fractures and lineaments). A structural synthesis combines all these elements into three major phases of deformation. Phase D1 is characterized by foliation and schistosity, phase D2 is marked by shear planes and phase D3 is characterized by open and sealed fractures. The analysis of structures (fractures in outcrops, Landsat lineaments, subsurface structures) shows a predominance of ENE-WSW and WNW-ESE directions. Through electrical surveys and borehole data, we were able to identify the sequence of different geological formations. Four geo-electric layers were identified, each with a different electrical conductivity: conductive, semi-resistive, or resistive. The last conductive layer is considered a potentially aquiferous zone. The flow rates of the boreholes ranged from 2.6 to 12 m3/h, classified as moderate to high according to the CIEH classification. The boreholes were mainly located in basalts, which are mineralogically rich in ferromagnesian minerals. This mineral composition contributes to their high productivity as they are more likely to be weathered. The boreholes were positioned along linear structures or at their intersections.

Keywords: Mbouda, Pan-African basement, productivity, west-Cameroon

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Authors: Aswathaman Vijayan, Manish Jha, Ullas Theertha

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Climate change and Global warming have become an issue for both developed and developing countries and perhaps the biggest threat to the environment. We at ITC Limited believe that a company’s performance must be measured by its Triple Bottom Line contribution to building economic, social and environmental capital. This Triple Bottom Line strategy focuses on - Embedding sustainability in business practices, Investing in social development and Adopting a low carbon growth path with a cleaner environment approach. The Agri Business Division - ILTD operates in the tobacco crop growing regions of Andhra Pradesh and Karnataka province of India. The Agri value chain of the company comprises of two distinct phases: First phase is Agricultural operations undertaken by ITC trained farmers and the second phase is Industrial operations which include marketing and processing of the agricultural produce. This research work covers the Greenhouse Gas (GHG) management strategy of ITC in the Agricultural operations undertaken by the farmers. The agriculture sector adds considerably to global GHG emissions through the use of carbon-based energies, use of fertilizers and other farming operations such as ploughing. In order to minimize the impact of farming operations on the environment, ITC has a taken a big leap in implementing system and process in reducing the GHG impact in farm value chain by partnering with the farming community. The company has undertaken a unique three-pronged approach for GHG management at the farm value chain: 1) GHG inventory at farm value chain: Different sources of GHG emission in the farm value chain were identified and quantified for the baseline year, as per the IPCC guidelines for greenhouse gas inventories. The major sources of emission identified are - emission due to nitrogenous fertilizer application during seedling production and main-field; emission due to diesel usage for farm machinery; emission due to fuel consumption and due to burning of crop residues. 2) Identification and implementation of technologies to reduce GHG emission: Various methodologies and technologies were identified for each GHG emission source and implemented at farm level. The identified methodologies are – reducing the consumption of chemical fertilizer usage at the farm through site-specific nutrient recommendation; Usage of sharp shovel for land preparation to reduce diesel consumption; implementation of energy conservation technologies to reduce fuel requirement and avoiding burning of crop residue by incorporation in the main field. These identified methodologies were implemented at farm level, and the GHG emission was quantified to understand the reduction in GHG emission. 3) Social and farm forestry for CO2 sequestration: In addition, the company encouraged social and farm forestry in the waste lands to convert it into green cover. The plantations are carried out with fast growing trees viz., Eucalyptus, Casuarina, and Subabul at the rate of 10,000 Ha of land per year. The above approach minimized considerable amount of GHG emission at the farm value chain benefiting farmers, community, and environment at a whole. In addition, the CO₂ stock created by social and farm forestry program has made the farm value chain to become environment-friendly.

Keywords: CO₂ sequestration, farm value chain, greenhouse gas, ITC limited

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Authors: Rafay Ahmed, Condon Lau

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Bone healing is a complex and sequential process involving changes at the molecular level. Raman spectroscopy is a promising technique to study bone mineral and matrix environments simultaneously. In this study, subcritical calvarial defects are used to study bone composition during healing without discomposing the fracture. The model allowed to monitor the natural healing of bone avoiding mechanical harm to the callus. Calvarial defects were created using 1mm burr drill in the parietal bones of Sprague-Dawley rats (n=8) that served in vivo defects. After 7 days, their skulls were harvested after euthanizing. One additional defect per sample was created on the opposite parietal bone using same calvarial defect procedure to serve as control defect. Raman spectroscopy (785 nm) was established to investigate bone parameters of three different skull surfaces; in vivo defects, control defects and normal surface. Principal component analysis (PCA) was utilized for the data analysis and interpretation of Raman spectra and helped in the classification of groups. PCA was able to distinguish in vivo defects from normal surface and control defects. PC1 shows that the major variation at 958 cm⁻¹, which corresponds to ʋ1 phosphate mineral band. PC2 shows the major variation at 1448 cm⁻¹ which is the characteristic band of CH2 deformation and corresponds to collagens. Raman parameters, namely, mineral to matrix ratio and crystallinity was found significantly decreased in the in vivo defects compared to surface and controls. Scanning electron microscope and optical microscope images show the formation of newly generated matrix by means of bony bridges of collagens. Optical profiler shows that surface roughness increased by 30% from controls to in vivo defects after 7 days. These results agree with Raman assessment parameters and confirm the new collagen formation during healing.

Keywords: Raman spectroscopy, principal component analysis, calvarial defects, tissue characterization

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Authors: Dana Zelicha

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A 6-week mindfulness programme was launched to improve the well being and performance of 20 managers (including the supervisor) of an international corporation in London. A unique assessment methodology was customised to the organisation’s needs, measuring four parameters: prioritising skills, listening skills, mindfulness levels and happiness levels. All parameters showed significant improvements (p < 0.01) post intervention, with a remarkable increase in listening skills and mindfulness levels. Although corporate mindfulness programmes have proven to be effective, the challenge remains the low engagement levels at home and the implementation of these tools beyond the scope of the intervention. This study has offered an innovative approach to enforce home engagement levels, which yielded promising results. The programme launched with a 2-day introduction intervention, which was followed by a 6-week training course (1 day a week; 2 hours each). Participants learned all basic principles of mindfulness such as mindfulness meditations, Mindfulness Based Stress Reduction (MBSR) techniques and Mindfulness Based Cognitive Therapy (MBCT) practices to incorporate into their professional and personal lives. The programme contained experiential mindfulness meditations and innovative mindfulness tools (OWBA-MT) created by OWBA - The Well Being Agency. Exercises included Mindful Meetings, Unitasking and Mindful Feedback. All sessions concluded with guided discussions and group reflections. One fundamental element of this programme was engagement level outside of the workshop. In the office, participants connected with a mindfulness buddy - a team member in the group with whom they could find support throughout the programme. At home, participants completed online daily mindfulness forms that varied according to weekly themes. These customised forms gave participants the opportunity to reflect on whether they made time for daily mindfulness practice, and to facilitate a sense of continuity and responsibility. At the end of the programme, the most engaged team member was crowned the ‘mindful maven’ and received a special gift. The four parameters were measured using online self-reported questionnaires, including the Listening Skills Inventory (LSI), Mindfulness Attention Awareness Scale (MAAS), Time Management Behaviour Scale (TMBS) and a modified version of the Oxford Happiness Questionnaire (OHQ). Pre-intervention questionnaires were collected at the start of the programme, and post-intervention data was collected 4-weeks following completion. Quantitative analysis using paired T-tests of means showed significant improvements, with a 23% increase in listening skills, a 22% improvement in mindfulness levels, a 12% increase in prioritising skills, and an 11% improvement in happiness levels. Participant testimonials exhibited high levels of satisfaction and the overall results indicate that the mindfulness programme substantially impacted the team. These results suggest that 6-week mindfulness programmes can improve employees’ capacities to listen and work well with others, to effectively manage time and to experience enhanced satisfaction both at work and in life. Limitations noteworthy to consider include the afterglow effect and lack of generalisability, as this study was conducted on a small and fairly homogenous sample.

Keywords: corporate mindfulness, listening skills, organisational well being, prioritising skills, mindful leadership

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Authors: Ayat Ayman Abdelaziz Ibrahim Amayem, Hassan Abdel-Salam, Zeyad El-Sayad

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Nowadays, ICTs have spread extensively in everyday life in an unprecedented way. A great attention is paid to the ICTs while ignoring the social aspect. With the immersive invasion of internet as well as smart phones’ applications and digital social networking, people become more socially connected through virtual spaces instead of meeting in physical public spaces. Thus, this paper aims to find the ways of implementing ICTs in public spaces to regain their status as attractive places for people, incite meetings in real life and create sustainable lively city centers. One selected example of urban space in the city center of Alexandria is selected for the study. Alexandria represents a large metropolitan city subjected to rapid transformation. Improving the quality of its public spaces will have great effects on the whole well-being of the city. The major roles that ICTs can play in the public space are: culture and art, education, planning and design, games and entertainment, and information and communication. Based on this classification various examples and proposals of ICTs interventions in public spaces are presented and analyzed to encourage good old fashioned social interaction by creating the New Social Public Place of this Digital Era. The paper will adopt methods such as questionnaire for evaluating the people’s willingness to accept the idea of using ICTs in public spaces, their needs and their proposals for an attractive place; the technique of observation to understand the people behavior and their movement through the space and finally will present an experimental design proposal for the selected urban space. Accordingly, this study will help to find design principles that can be adopted in the design of future public spaces to meet the needs of the digital era’s users with the new concepts of social life respecting the rules of place-making.

Keywords: Alexandria sustainable city center, digital place-making, ICTs, social interaction, social networking, urban places

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Authors: Kemal Efe Eseller, Göktuğ Yazici

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Laser-induced breakdown spectroscopy (LIBS) is a rapid optical atomic emission spectroscopy which is used for material identification and analysis with the advantages of in-situ analysis, elimination of intensive sample preparation, and micro-destructive properties for the material to be tested. LIBS delivers short pulses of laser beams onto the material in order to create plasma by excitation of the material to a certain threshold. The plasma characteristics, which consist of wavelength value and intensity amplitude, depends on the material and the experiment’s environment. In the present work, medicine samples’ spectrum profiles were obtained via LIBS. Medicine samples’ datasets include two different concentrations for both paracetamol based medicines, namely Aferin and Parafon. The spectrum data of the samples were preprocessed via filling outliers based on quartiles, smoothing spectra to eliminate noise and normalizing both wavelength and intensity axis. Statistical information was obtained and principal component analysis (PCA) was incorporated to both the preprocessed and raw datasets. The machine learning models were set based on two different train-test splits, which were 70% training – 30% test and 80% training – 20% test. Cross-validation was preferred to protect the models against overfitting; thus the sample amount is small. The machine learning results of preprocessed and raw datasets were subjected to comparison for both splits. This is the first time that all supervised machine learning classification algorithms; consisting of Decision Trees, Discriminant, naïve Bayes, Support Vector Machines (SVM), k-NN(k-Nearest Neighbor) Ensemble Learning and Neural Network algorithms; were incorporated to LIBS data of paracetamol based pharmaceutical samples, and their different concentrations on preprocessed and raw dataset in order to observe the effect of preprocessing.

Keywords: machine learning, laser-induced breakdown spectroscopy, medicines, principal component analysis, preprocessing

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Authors: D. Castillo T., Luis F. Jimenez

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The compressed earth blocks (CEBs) constitute an alternative as a constructive element for building homes in regions with high levels of poverty and marginalization. Such is the case of Southeastern Mexico, where the population, predominantly indigene, build their houses with feeble materials like wood and palm, vulnerable to extreme weather in the area, because they do not have the financial resources to acquire concrete blocks. There are several advantages that can provide BTCs compared to traditional vibro-compressed concrete blocks, such as the availability of materials, low manufacturing cost and reduced CO2 emissions to the atmosphere for not be subjected to a burning process. However, to improve its mechanical properties and resistance to adverse weather conditions in terms of humidity and temperature of the sub-humid climate zones, it requires the use of a chemical stabilizer; in this case we chose Ca(OH)2. The stabilization method Eades-Grim was employed, according to ASTM C977-03. This method measures the optimum amount of lime required to stabilize the soil, increasing the pH to 12.4 or higher. The minimum amount of lime required in this experiment was 1% and the maximum was 10%. The employed material was clay unconsolidated low to medium plasticity (CL type according to the Unified Soil Classification System). Based on these results, the CEBs manufacturing process was determined. The obtained blocks were from 10x15x30 cm using a mixture of soil, water and lime in different proportions. Later these blocks were put to dry outdoors and subjected to several physical and mechanical tests, such as compressive strength, absorption and drying shrinkage. The results were compared with the limits established by the Mexican Standard NMX-C-404-ONNCCE-2005 for the construction of housing walls. In this manner an alternative and sustainable material was obtained for the construction of rural households in the region, with better security conditions, comfort and cost.

Keywords: calcium hydroxide, chemical stabilization, compressed earth blocks, sub-humid warm weather

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Authors: Sarita Magu, Deepak Singh

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Study Design: This prospective study was conducted at the department of Radio Diagnosis, at Pt B.D. Sharma PGIMS, Rohtak in 57 patients of spine injury on radiographs or radiographically normal patients with neurological deficits presenting within 72 hours of injury. Aims: Evaluation of the role of Magnetic Resonance Imaging (MRI) in Spinal Trauma Patients and to compare MRI findings with clinical profile and neurological status of the patient and to correlate the MRI findings with neurological recovery of the patient and predict the outcome. Material and Methods: Neurological status of patients was assessed at the time of admission and discharge in all the patients and at long term interval of six months to one year in 27 patients as per American spine injury association classification (ASIA). On MRI cord injury was categorized into cord hemorrhage, cord contusion, cord edema only, and normal cord. Quantitative assessment of injury on MRI was done using mean canal compromise (MCC), mean spinal cord compression (MSCC) and lesion length. Neurological status at admission and neurological recovery at discharge and long term follow up was compared with various qualitative cord findings and quantitative parameters on MRI. Results: Cord edema and normal cord was associated with favorable neurological outcome. Cord contusion show lesser neurological recovery as compared to cord edema. Cord hemorrhage was associated with worst neurological status at admission and poor neurological recovery. Mean MCC, MSCC, and lesion length values were higher in patients presenting with ASIA A grade injury and showed decreasing trends towards ASIA E grade injury. Patients showing neurological recovery over the period of hospital stay and long term follow up had lower mean MCC, MSCC, and lesion length as compared to patients showing no neurological recovery. The data was statistically significant with p value <.05. Conclusion: Cord hemorrhage and higher MCC, MSCC and lesion length has poor prognostic value in spine injury patients.

Keywords: spine injury, cord hemorrhage, cord contusion, MCC, MSCC, lesion length, ASIA grading

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Authors: N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae

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Hand gesture recognition is a technique used to locate, detect, and recognize a hand gesture. Detection and recognition are concepts of Artificial Intelligence (AI). AI concepts are applicable in Human Computer Interaction (HCI), Expert systems (ES), etc. Hand gesture recognition can be used in sign language interpretation. Sign language is a visual communication tool. This tool is used mostly by deaf societies and those with speech disorder. Communication barriers exist when societies with speech disorder interact with others. This research aims to build a hand recognition system for Lesotho’s Sesotho and English language interpretation. The system will help to bridge the communication problems encountered by the mentioned societies. The system has various processing modules. The modules consist of a hand detection engine, image processing engine, feature extraction, and sign recognition. Detection is a process of identifying an object. The proposed system uses Canny pruning Haar and Haarcascade detection algorithms. Canny pruning implements the Canny edge detection. This is an optimal image processing algorithm. It is used to detect edges of an object. The system employs a skin detection algorithm. The skin detection performs background subtraction, computes the convex hull, and the centroid to assist in the detection process. Recognition is a process of gesture classification. Template matching classifies each hand gesture in real-time. The system was tested using various experiments. The results obtained show that time, distance, and light are factors that affect the rate of detection and ultimately recognition. Detection rate is directly proportional to the distance of the hand from the camera. Different lighting conditions were considered. The more the light intensity, the faster the detection rate. Based on the results obtained from this research, the applied methodologies are efficient and provide a plausible solution towards a light-weight, inexpensive system which can be used for sign language interpretation.

Keywords: canny pruning, hand recognition, machine learning, skin tracking

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Authors: P. Behera, K. K. Singh, D. K. Saini, M. De

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Implementation of 2D materials in the detection of bio analytes is highly advantageous in the field of sensing because of its high surface to volume ratio. We have designed our sensor array with different cationic two-dimensional MoS₂, where surface modification was achieved by cationic thiol ligands with different functionality. Green fluorescent protein (GFP) was chosen as signal transducers for its biocompatibility and anionic nature, which can bind to the cationic MoS₂ surface easily, followed by fluorescence quenching. The addition of bio-analyte to the sensor can decomplex the cationic MoS₂ and GFP conjugates, followed by the regeneration of GFP fluorescence. The fluorescence response pattern belongs to various analytes collected and transformed to linear discriminant analysis (LDA) for classification. At first, 15 different proteins having wide range of molecular weight and isoelectric points were successfully discriminated at 50 nM with detection limit of 1 nM. The sensor system was also executed in biofluids such as serum, where 10 different proteins at 2.5 μM were well separated. After successful discrimination of protein analytes, the sensor array was implemented for bacteria sensing. Six different bacteria were successfully classified at OD = 0.05 with a detection limit corresponding to OD = 0.005. The optimized sensor array was able to classify uropathogens from non-uropathogens in urine medium. Further, the technique was applied for discrimination of bacteria possessing resistance to different types and amounts of drugs. We found out the mechanism of sensing through optical and electrodynamic studies, which indicates the interaction between bacteria with the sensor system was mainly due to electrostatic force of interactions, but the separation of native bacteria from their drug resistant variant was due to Van der Waals forces. There are two ways bacteria can be detected, i.e., through bacterial cells and lysates. The bacterial lysates contain intracellular information and also safe to analysis as it does not contain live cells. Lysates of different drug resistant bacteria were patterned effectively from the native strain. From unknown sample analysis, we found that discrimination of bacterial cells is more sensitive than that of lysates. But the analyst can prefer bacterial lysates over live cells for safer analysis.

Keywords: array-based sensing, drug resistant bacteria, linear discriminant analysis, two-dimensional MoS₂

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Authors: Alena Nesterenko, Svetlana Petrikova

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Research evaluation is one of the most important elements of self-regulation and development of researchers as it is impartial and independent process of assessment. The method of expert evaluations as a scientific instrument solving complicated non-formalized problems is firstly a scientifically sound way to conduct the assessment which maximum effectiveness of work at every step and secondly the usage of quantitative methods for evaluation, assessment of expert opinion and collective processing of the results. These two features distinguish the method of expert evaluations from long-known expertise widespread in many areas of knowledge. Different typical problems require different types of expert evaluations methods. Several issues which arise with these methods are experts’ selection, management of assessment procedure, proceeding of the results and remuneration for the experts. To address these issues an on-line system was created with the primary purpose of development of a versatile application for many workgroups with matching approaches to scientific work management. Online documentation assessment and statistics system allows: - To realize within one platform independent activities of different workgroups (e.g. expert officers, managers). - To establish different workspaces for corresponding workgroups where custom users database can be created according to particular needs. - To form for each workgroup required output documents. - To configure information gathering for each workgroup (forms of assessment, tests, inventories). - To create and operate personal databases of remote users. - To set up automatic notification through e-mail. The next stage is development of quantitative and qualitative criteria to form a database of experts. The inventory was made so that the experts may not only submit their personal data, place of work and scientific degree but also keywords according to their expertise, academic interests, ORCID, Researcher ID, SPIN-code RSCI, Scopus AuthorID, knowledge of languages, primary scientific publications. For each project, competition assessments are processed in accordance to ordering party demands in forms of apprised inventories, commentaries (50-250 characters) and overall review (1500 characters) in which expert states the absence of conflict of interest. Evaluation is conducted as follows: as applications are added to database expert officer selects experts, generally, two persons per application. Experts are selected according to the keywords; this method proved to be good unlike the OECD classifier. The last stage: the choice of the experts is approved by the supervisor, the e-mails are sent to the experts with invitation to assess the project. An expert supervisor is controlling experts writing reports for all formalities to be in place (time-frame, propriety, correspondence). If the difference in assessment exceeds four points, the third evaluation is appointed. As the expert finishes work on his expert opinion, system shows contract marked ‘new’, managers commence with the contract and the expert gets e-mail that the contract is formed and ready to be signed. All formalities are concluded and the expert gets remuneration for his work. The specificity of interaction of the examination officer with other experts will be presented in the report.

Keywords: expertise, management of research evaluation, method of expert evaluations, research evaluation

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Authors: Hamza Ikhlaq, Stephen Franks

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Background: Polycystic ovarian syndrome (PCOS) is one of the most common endocrine disorders affecting women of reproductive age. The aetiology behind PCOS is poorly understood but influencing ethnic, environmental, and genetic factors have been recognised. However, literature examining the impact of ethnicity is scarce. We hypothesised Body Mass Index (BMI) and ethnicity influence the clinical, metabolic, and biochemical presentations of PCOS, with an interaction between these factors. Methods: A database of 1081 women with PCOS and a control group of 72 women were analysed. BMIs were grouped using the World Health Organisation classification into normal weight, overweight and obese groups. Ethnicities were classified into European, South Asian, and Afro-Caribbean groups. Biochemical and clinical presentations were compared amongst these groups, and statistical analyses were performed to assess significance. Results: This study revealed ethnicity significantly influences biochemical and clinical presentations of PCOS. A greater proportion of South Asian women are impacted by menstrual cycle disturbances and hirsutism than European and Afro-Caribbean women. South Asian and Afro-Caribbean women show greater measures of insulin resistance and weight gain when compared to their European peers. Women with increased BMI are shown to have an increased prevalence of PCOS phenotypes alongside increased levels of insulin resistance and testosterone. Furthermore, significantly different relationships between the waist-hip ratio and measures of insulin and glucose control for Afro-Caribbean women were identified compared to other ethnic groups. Conclusions: The findings of this study show ethnicity significantly influence the phenotypic and biochemical presentations of PCOS, with an interaction between body habitus and ethnicity found. Furthermore, we provide further data on the influences of BMI on the manifestations of PCOS. Therefore, we highlight the need to consider these factors when reviewing diagnostic criteria and delivering clinical care for these groups.

Keywords: PCOS, ethnicity, BMI, clinical

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Authors: Man Ying Kang, Joshua Kin Man Nan

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The prolonged pandemic has posed alarming public health challenges to various parts of the world, and face-to-face mental health treatment is largely discounted for the control of virus transmission, online psychological services and self-help mental health kits have become essential. Online self-help mindfulness-based interventions have proved their effects on fostering mental health for different populations over the globe. This paper was to test the effectiveness of an online short-term audio-based mindfulness (SAM) program in enhancing wellbeing, dispositional mindfulness, and reducing stress and negative affect in community settings in China, and to explore possible mechanisms of how dispositional mindfulness, stress, and negative affect influenced the intervention effects on wellbeing. Community-dwelling adults were recruited via online social networking sites (e.g., QQ, WeChat, and Weibo). Participants (n=100) were randomized into the mindfulness group (n=50) and a waitlist control group (n=50). In the mindfulness group, participants were advised to spend 10–20 minutes listening to the audio content, including mindful-form practices (e.g., eating, sitting, walking, or breathing). Then practice daily mindfulness exercises for 3 weeks (a total of 21 sessions), whereas those in the control group received the same intervention after data collection in the mindfulness group. Participants in the mindfulness group needed to fill in the World Health Organization Five Well-Being Index (WHO), Positive and Negative Affect Schedule (PANAS), Perceived Stress Scale (PSS), and Freiburg Mindfulness Inventory (FMI) four times: at baseline (T0) and at 1 (T1), 2 (T2), and 3 (T3) weeks while those in the waitlist control group only needed to fill in the same scales at pre- and post-interventions. Repeated-measure analysis of variance, paired sample t-test, and independent sample t-test was used to analyze the variable outcomes of the two groups. The parallel process latent growth curve modeling analysis was used to explore the longitudinal moderated mediation effects. The dependent variable was WHO slope from T0 to T3, the independent variable was Group (1=SAM, 2=Control), the mediator was FMI slope from T0 to T3, and the moderator was T0NA and T0PSS separately. The different levels of moderator effects on WHO slope was explored, including low T0NA or T0PSS (Mean-SD), medium T0NA or T0PSS (Mean), and high T0NA or T0PSS (Mean+SD). The results found that SAM significantly improved and predicted higher levels of WHO slope and FMI slope, as well as significantly reduced NA and PSS. FMI slope positively predict WHO slope. FMI slope partially mediated the relationship between SAM and WHO slope. Baseline NA and PSS as the moderators were found to be significant between SAM and WHO slope and between SAM and FMI slope, respectively. The conclusion was that SAM was effective in promoting levels of mental wellbeing, positive affect, and dispositional mindfulness as well as reducing negative affect and stress in community settings in China. SAM improved wellbeing faster through the faster enhancement of dispositional mindfulness. Participants with medium-to-high negative affect and stress buffered the therapy effects of SAM on wellbeing improvement speed.

Keywords: mindfulness, negative affect, stress, wellbeing, randomized control trial

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Authors: Antonio Marques, Graça Guedes

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The Portuguese footwear industry had in the last five years a remarkable performance in the exportation values, the trade balance and others economic indicators. After a long period of difficulties and with a strong reduction of companies and employees since 1994 until 2009, the Portuguese footwear industry changed the strategy and is now a success case between the international players of footwear. Only the Italian industry sells footwear with a higher value than the Portuguese and the distance between them is decreasing year by year. This paper analyses how the Portuguese footwear companies innovate and make innovation, according the classification proposed by the Oslo Manual. Also analyses the strategy follow in the innovation process, as suggested by Freeman and Soete, and shows the linkage between the type of innovation and the strategy of innovation. The research methodology was qualitative and the strategy for data collection was the case study. The qualitative data will be analyzed with the MAXQDA software. The economic results of the footwear companies studied shows differences between all of them and these differences are related with the innovation strategy adopted. The companies focused in product and marketing innovation, oriented to their target market, have higher ratios “turnover per worker” than the companies focused in process innovation. However, all the footwear companies in this “low-tech” industry create value and contribute to a positive foreign trade of 1.310 million euros in 2013. The growth strategies implemented has the participation of the sectorial organizations in several innovative projects. And it’s obvious that cooperation between all of them is a critical element to the performance achieved by the companies and the innovation observed. Can conclude that the Portuguese footwear sector has in the last years an excellent performance (economic results, exportation values, trade balance, brands and international image) and his performance is strongly related with the strategy in innovation followed, the type of innovation and the networks in the cluster. A simplified model, called “Ace of Diamonds”, is proposed by the authors and explains the way how this performance was reached by the seven companies that participate in the study (two of them are the leaders in the setor), and if this model can be used in others traditional and “low-tech” industries.

Keywords: footwear, innovation, “low-tech” industry, Oslo manual

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Authors: Hoorieh Darvishi, Rezaei

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Introduction: This study investigates the efficacy of computer-based interventions for children with Autism Spectrum Disorder , specifically targeting communication deficits and repetitive behaviors. The research evaluates novel software applications designed to enhance narrative capabilities and sensory integration through structured, progressive intervention protocols Method: The study evaluated two intervention software programs designed for children with autism, focusing on narrative speech and sensory integration. Twelve children aged 5-11 participated in the two-month intervention, attending three 45-minute weekly sessions, with pre- and post-tests measuring speech, communication, and behavioral outcomes. The narrative speech software incorporated 14 stories using the Cohen model. It progressively reduced software assistance as children improved their storytelling abilities, ultimately enabling independent narration. The process involved story comprehension questions and guided story completion exercises. The sensory integration software featured approximately 100 exercises progressing from basic classification to complex cognitive tasks. The program included attention exercises, auditory memory training (advancing from single to four-syllable words), problem-solving, decision-making, reasoning, working memory, and emotion recognition activities. Each module was accompanied by frequency and pitch-adjusted music that child enjoys it to enhance learning through multiple sensory channels (visual, auditory, and tactile). Conclusion: The results indicated that the use of these software programs significantly improved communication and narrative speech scores in children, while also reducing scores related to repetitive behaviors. Findings: These findings highlight the positive impact of computer-based interventions on enhancing communication skills and reducing repetitive behaviors in children with autism.

Keywords: autism, communication_skills, repetitive_behaviors, sensory_integration

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Authors: Mostafa Elbaba

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Because childhood renal diseases are grossly different compared to adult diseases, pediatric nephrology was founded as a specialty in 1965. Renal pathology specialty was introduced at the London Ciba Symposium in 1961. The history of renal pathology can be divided into two eras: one starting in the 1650s with the invention of the microscope, the second in the 1950s with the implementation of renal biopsy, and the presence of electron microscopy and immunofluorescence study. Prior to the 1950s, the study of diseased human kidneys was restricted to postmortem examination by gross pathology. In 1827, Richard Bright first described his triad of kidney disease, which was confirmed by morbid kidney changes at autopsy. In 1905 Friedrich Mueller coined the term “nephrosis” describing the inflammatory form of “degenerative” diseases, and later F. Munk added the term “lipoid nephrosis”. The most profound influence on renal diseases’ classification came from the publication of Volhard and Fahr in 1914. In 1899, Carl Max Wilhelm Wilms described Wilms' tumor of the kidneys in children. Chronic pyelonephritis was a popular renal diagnosis and the most common cause of uremia until the 1960s. Although kidney biopsy had been used early in the 1930s for renal tumors, the earliest reports of its use in the diagnosis of medical kidney disease were by Iversen and Brun in 1951, followed by Alwall in 1952, then by Pardo in 1953. The earliest intentional renal biopsies were done in 1944 by Nils Alwall, while the procedure was abandoned after the death of one of his 13 patients who biopsied. In 1950, Antonino Perez-Ara attempted renal biopsies, but his results were missed because of an unpopular journal publication. In the year 1951, Claus Brun and Poul Iverson developed the biopsy procedure using an aspiration technique. Popularizing renal biopsy practice is accredited to Robert Kark, who published his distinct work in 1954. He perfected the technique of renal biopsy in the prone position using the Vim-Silverman needle and used intravenous pyelography to improve the localization of the kidney.

Keywords: history, medicine, nephrology, pediatrics, pathology

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Authors: Hoorieh Darvishi, Rezaei

Abstract:

Introduction: This study investigates the efficacy of computer-based interventions for children with Autism Spectrum Disorder , specifically targeting communication deficits and repetitive behaviors. The research evaluates novel software applications designed to enhance narrative capabilities and sensory integration through structured, progressive intervention protocols Method: The study evaluated two intervention software programs designed for children with autism, focusing on narrative speech and sensory integration. Twelve children aged 5-11 participated in the two-month intervention, attending three 45-minute weekly sessions, with pre- and post-tests measuring speech, communication, and behavioral outcomes. The narrative speech software incorporated 14 stories using the Cohen model. It progressively reduced software assistance as children improved their storytelling abilities, ultimately enabling independent narration. The process involved story comprehension questions and guided story completion exercises. The sensory integration software featured approximately 100 exercises progressing from basic classification to complex cognitive tasks. The program included attention exercises, auditory memory training (advancing from single to four-syllable words), problem-solving, decision-making, reasoning, working memory, and emotion recognition activities. Each module was accompanied by frequency and pitch-adjusted music that child enjoys it to enhance learning through multiple sensory channels (visual, auditory, and tactile). Conclusion: The results indicated that the use of these software programs significantly improved communication and narrative speech scores in children, while also reducing scores related to repetitive behaviors. Findings: These findings highlight the positive impact of computer-based interventions on enhancing communication skills and reducing repetitive behaviors in children with autism.

Keywords: autism, narrative speech, persian, SI, repetitive behaviors, communication

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Authors: Messaoudi Mohammed Amin

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The reduction of available land resources and the increased cout associated with the use of hight quality materials have led to the need for local soils to be used in geotecgnical construction however, poor engineering properties of these soils pose difficulties for constructions project and need to be stabilized to improve their properties in oyher works unsuitable soils with low bearing capacity, high plasticity coupled with high insatbility are frequently encountered hense, there is a need to improve the physical and mechanical charateristics of these soils to make theme more suitable for construction this can be done by using different mechanical and chemical methods clayey soil stabilization has been practiced for quite sometime bu mixing additives, such us cement, lime and fly ash to the soil to increase its strength. The aim of this project is to study the effect of using lime, natural pozzolana or combination of both on the geotecgnical cherateristics of clayey soil. Test specimen were subjected to atterberg limits test, compaction test, box shear test and uncomfined compression test Lime or natural pozzolana was added to clayey soil at rangs of 0-8% and 0-20% respectively. In addition combinations of lime –natural pozzolana were added to clayey soil at the same ranges specimen were cured for 1-7, and 28 days after which they were tested for uncofined compression tests. Based on the experimental results, it was concluded that an important decrease of plasticity index was observed for thr samples stabilized with the combinition lime-natural pozzolana in addition, the use of the combination lime-natural pozzolana modifies the clayey soil classification according to casagrand plasiticity chart. Moreover, based on the favourable results of shear and compression strength obtained, it can be concluded that clayey soil can be successfuly stabilized by combined action of lime and natural pozzolana also this combination showed an appreciable improvement of the shear parameters. Finally, since natural pozzolana is much cheaper than lime ,the addition of natural pozzolana in lime soil mix may particulary become attractive and can result in cost reduction of construction.

Keywords: clay, soil stabilization, natural pozzolana, atterberg limits, compaction, compressive strength shear strength, curing

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Authors: Basit Aftab, Zhichao Wang, Feng Zhongke

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Land Use and Land Cover Change (LULCC) is a critical environmental issue that has significant effects on biodiversity, ecosystem services, and climate change. This study examines the spatiotemporal dynamics of land use and land cover (LULC) across a three-decade period (1992–2022) in a district area. The goal is to support sustainable land management and urban planning by utilizing the combination of remote sensing, GIS data, and observations from Landsat satellites 5 and 8 to provide precise predictions of the trajectory of urban sprawl. In order to forecast the LULCC patterns, this study suggests a hybrid strategy that combines the Random Forest method with Multilayer Perceptron (MLP) and Markov Chain analysis. To predict the dynamics of LULC change for the year 2035, a hybrid technique based on multilayer Perceptron and Markov Chain Model Analysis (MLP-MCA) was employed. The area of developed land has increased significantly, while the amount of bare land, vegetation, and forest cover have all decreased. This is because the principal land types have changed due to population growth and economic expansion. The study also discovered that between 1998 and 2023, the built-up area increased by 468 km² as a result of the replacement of natural resources. It is estimated that 25.04% of the study area's urbanization will be increased by 2035. The performance of the model was confirmed with an overall accuracy of 90% and a kappa coefficient of around 0.89. It is important to use advanced predictive models to guide sustainable urban development strategies. It provides valuable insights for policymakers, land managers, and researchers to support sustainable land use planning, conservation efforts, and climate change mitigation strategies.

Keywords: land use land cover, Markov chain model, multi-layer perceptron, random forest, sustainable land, remote sensing.

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Authors: Prabhdip Brar

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Since the ancient times recycling, reusing and upcycling has been strongly practiced in India. However, previously reprocess was common due to lack of resources and availability of free time, especially with women who were homemakers. The upward strategy of design philosophy and drift of sustainability is sustainable fashion which is also termed eco fashion, the aspiration of which is to craft a classification which can be supported ad infinitum in terms of environmentalism and social responsibility. The viable approach of sustaining fashion is part of the larger trend of justifiable design where a product is generated and produced while considering its social impact to the environment. The purpose of this qualitative research paper is to find out if the apparel design boutiques in Chandigarh, (an educated fashion-conscious city) are contributing towards making conscious efforts with the re-use of environmentally responsive materials to rethink about eco-conscious traditional techniques and socially responsible approaches of the invention. Observation method and case studies of ten renowned boutiques of Chandigarh were conducted to find out about the creativity of their waste management and social contribution. Owners were interviewed with open-ended questions to find out their understanding of sustainability. This paper concludes that there are many sustainable ideas existing within India from olden times that can be incorporated into modern manufacturing techniques. The results showed all the designers are aware of sustainability as a concept. In all practical purposes, a patch of fabric is being used for bindings or one over the other as surface ornamentation techniques. Plain Fabrics and traditional prints and fabrics are valued more by the owners for using on other garments. Few of them sort their leftover pieces according to basic colors. Few boutique owners preferred donating it to Non-Government organizations. Still, they have enough waste which is not utilized because of lack of time and labor. This paper discusses how the Indian traditional techniques still derive influences though design and techniques, making India one of the contributing countries to the sustainability of fashion and textiles.

Keywords: eco-fashion textile, sustainable textiles, sustainability in india, waste management

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Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

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Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should properly evaluate their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, Neural Networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable to offer an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

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Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

Abstract:

Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should evaluate properly their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, neural networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable of offering an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

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Authors: Sunil Arora, Anitya Kumar Jena, S. A. Ravi

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India is at the cusp of major reforms in the hydrocarbon sector. Oil and gas sector is highly liberalised to attract private investment and to increase domestic production. Major hydrocarbon Exploration & Production (E&P) activity here have been undertaken by Government owned companies but with easing up and reworking of hydro carbon exploration licensing policies private players have also joined the fray towards achieving energy security for India. Government of India has come up with policy and administrative reforms including Hydrocarbon Exploration and Licensing Policy (HELP), Sagarmala (port-led development with coastal connectivity), and Development of Small Discovered Fields, etc. with the intention to make industry friendly conditions for investment, ease of doing business and reduce gestation period. To harness the potential resources of Deep water and Ultra deep water, High Pressure – High Temperature (HP-HT) regions, Coal Bed Methane (CBM), Shale Hydrocarbons besides Gas Hydrates, participation shall be required from both domestic and international players. Companies engaged in E&P activities in India have traditionally been managing through their captive supply base, but with crude prices under hammer, the need is being felt to outsource non-core activities. This necessitates establishment of a robust support services to cater to E&P Industry, which is currently non-existent to meet the bourgeon challenges. This paper outlines an agenda for creating an Integrated Services Hub (ISH) under Special Economic Zone (SEZ) to facilitate complete gamut of non-core support activities of E&P industry. This responsive and proficient multi-usage facility becomes viable with better resource utilization, economies of scale to offer cost effective services. The concept envisages companies to bring-in their core technical expertise leaving complete hardware peripherals outsourced to this ISH. The Integrated Services Hub, complying with the best in class global standards, shall typically provide following Services under Single Window Solution, but not limited to: a) Logistics including supply base operations, transport of manpower and material, helicopters, offshore supply vessels, warehousing, inventory management, sourcing and procurement activities, international freight forwarding, domestic trucking, customs clearance service etc. b) Trained/Experienced pool of competent Manpower (Technical, Security etc.) will be available for engagement by companies on either short or long term basis depending upon the requirements with provisions of meeting any training requirements. c) Specialized Services through tie-up with global best companies for Crisis Management, Mud/Cement, Fishing, Floating Dry-dock besides provision of Workshop, Repair and Testing facilities, etc. d) Tools and Tackles including drill strings, etc. A pre-established Integrated Services Hub shall facilitate an early start-up of activities with substantial savings in time lines. This model can be replicated at other parts of the world to expedite E&P activities.

Keywords: integrated service hub, India, oil gas, offshore supply base

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Authors: Yude Wu

Abstract:

Mongolia, grappling with significant socio-economic challenges, faces pressing issues of inequality and poverty, as evidenced by a high Gini coefficient and the highest poverty rate among the top 20 largest Asian countries. Despite government efforts, Mongolia's poverty rate experienced only a slight reduction from 29.6 percent in 2016 to 27.8 percent in 2020. PEER countries, such as South Africa, Botswana, Kazakhstan, and Peru, share characteristics with Mongolia, including reliance on the mining industry and classification as lower middle-income countries. Successful transitions of these countries to upper middle-income status between 1994 and the 2010s provide valuable insights. Drawing on secondary analyses of existing research and PEER country profiles, the study evaluates past policies, identifies gaps in current approaches, and proposes recommendations to combat poverty sustainably. The hypothesis includes a reliance on the mining industry and a transition from lower to upper middle-income status. Policies from these countries, such as the GEAR policy in South Africa and economic diversification in Botswana, offer insights into Mongolia's development. This essay aims to illuminate the multidimensional nature of underdevelopment in Mongolia through a secondary analysis of existing research and PEER country profiles, evaluating past policies, identifying gaps in current approaches, and providing recommendations for sustainable progress. Drawing inspiration from PEER countries, Mongolia can implement policies such as economic diversification to reduce vulnerability and create stable job opportunities. Emphasis on infrastructure, human capital, and strategic partnerships for Foreign Direct Investment (FDI) aligns with successful strategies implemented by PEER countries, providing a roadmap for Mongolia's development objectives.

Keywords: inequality, PEER countries, comparative analysis, nomadic animal husbandry, sustainable growth

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Authors: Irene Yi

Abstract:

Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Computational linguistics is a growing field dealing with such issues of data collection for technological development. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Computational analysis on such linguistic data is used to find patterns of misogyny. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: computational analysis, gendered grammar, misogynistic language, neural networks

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Authors: Forouzan Salehi Fergeni

Abstract:

Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

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