Search results for: robot programming

Authors: Suneel Kumar, Nanda Kumar J. Sreelal Sreedhar, Suchibrata Sen, V. Muralidharan,

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Fan technology is very critical and crucial for any aero engine technology. The fan disc forms a critical part of the fan module. It is an airworthiness requirement to have a metrological qualified quality disc. The current study uses a tactile probing and scanning on an articulated measuring machine (AMM), a bridge type coordinate measuring machine (CMM) and Metrology software for intermediate and final dimensional and geometrical verification during the prototype development of the disc manufactured through forging and machining process. The circumferential dovetails manufactured through the milling process are evaluated based on the evaluated and analysed metrological process. To perform metrological optimization a change of philosophy is needed making quality measurements available as fast as possible to improve process knowledge and accelerate the process but with accuracy, precise and traceable measurements. The offline CMM programming for inspection and optimisation of the CMM inspection plan are crucial portions of the study and discussed. The dimensional measurement plan as per the ASME B 89.7.2 standard to reach an optimised CMM measurement plan and strategy are an important requirement. The probing strategy, stylus configuration, and approximation strategy effects on the measurements of circumferential dovetail measurements of the developmental prototype disc are discussed. The results were discussed in the form of enhancement of the R &R (repeatability and reproducibility) values with uncertainty levels within the desired limits. The findings from the measurement strategy adopted for disc dovetail evaluation and inspection time optimisation are discussed with the help of various analyses and graphical outputs obtained from the verification process.

Keywords: coordinate measuring machine, CMM, aero engine, articulated measuring machine, fan disc

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Authors: Sylvie Michel, Emmanuelle Gagnou, Joanne Hamet

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New major ethical dilemmas are posed by artificial intelligence. This article identifies an existing gap between the ethical questions that AI/robotics researchers grapple with in their research practice and those identified by literature review. The objective is to understand which ethical dilemmas are identified or concern AI researchers in order to compare them with the existing literature. This will enable to conduct training and awareness initiatives for AI researchers, encouraging them to consider these questions during the development of AI. Qualitative analyses were conducted based on direct observation of an AI/Robotics research team focused on collaborative robotics over several months. Subsequently, semi-structured interviews were conducted with 16 members of the team. The entire process took place during the first semester of 2023. The observations were analyzed using an analytical framework, and the interviews were thematically analyzed using Nvivo software. While the literature identifies three primary ethical concerns regarding AI—transparency, bias, and responsibility—the results firstly demonstrate that AI researchers are primarily concerned with the publication and valorization of their work, with the initial ethical concerns revolving around this matter. Questions arise regarding the extent to which to "market" publications and the usefulness of some publications. Research ethics are a central consideration for these teams. Secondly, another result shows that the researchers studied adopt a consequentialist ethics (though not explicitly formulated as such). They ponder the consequences of their development in terms of safety (for humans in relation to Robots/AI), worker autonomy in relation to the robot, and the role of work in society (can robots take over jobs?). Lastly, results indicate that the ethical dilemmas highlighted in the literature (responsibility, transparency, bias) do not explicitly appear in AI/Robotics research. AI/robotics researchers raise specific and pragmatic ethical questions, primarily concerning publications initially and consequentialist considerations afterward. Results demonstrate that these concerns are distant from the existing literature. However, the dilemmas highlighted in the literature also deserve to be explicitly contemplated by researchers. This article proposes that the journals these researchers target should mandate ethical reflection for all presented works. Furthermore, results suggest offering awareness programs in the form of short educational sessions for researchers.

Keywords: ethics, artificial intelligence, research, robotics

Procedia PDF Downloads 80

Authors: Thais Cavalheri Santos, Pedro Jose Gabriel Ferreira, Alexandre Daliberto Frugoli, Lucio Leonardo, Pedro Americo Frugoli

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This paper presents a low cost education proposal to be used in engineering courses. The engineering education in universities of a developing country that is in need of an increasing number of engineers carried out with quality and affordably, pose a difficult problem to solve. In Brazil, the political and economic scenario requires academic managers able to reduce costs without compromising the quality of education. Within this context, the elaboration of a physics principles teaching method with the construction of an electronic balance is proposed. First, a method to develop and construct a load cell through which the students can understand the physical principle of strain gauges and bridge circuit will be proposed. The load cell structure was made with aluminum 6351T6, in dimensions of 80 mm x 13 mm x 13 mm and for its instrumentation, a complete Wheatstone Bridge was assembled with strain gauges of 350 ohms. Additionally, the process involves the use of a software tool to document the prototypes (design circuits), the conditioning of the signal, a microcontroller, C language programming as well as the development of the prototype. The project also intends to use an open-source I/O board (Arduino Microcontroller). To design the circuit, the Fritizing software will be used and, to program the controller, an open-source software named IDE®. A load cell was chosen because strain gauges have accuracy and their use has several applications in the industry. A prototype was developed for this study, and it confirmed the affordability of this educational idea. Furthermore, the goal of this proposal is to motivate the students to understand the several possible applications in high technology of the use of load cells and microcontroller.

Keywords: Arduino, load cell, low-cost education, strain gauge

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Authors: Cláudia Patrocínio, Beatriz Fernandes, Ana Filipa Pires

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Background: Mirror therapy (MT) is used to improve motor function after stroke. During MT, a mirror is placed between the two upper limbs (UL), thus reflecting movements of the non- affected side as if it were the affected side. Objectives: The aim of this review is to analyze the evidence on the effec.tiveness of MT in the recovery of UL function in population with post chronic stroke. Methods: The literature search was carried out in PubMed, ISI Web of Science, and PEDro database. Inclusion criteria: a) studies that include individuals diagnosed with stroke for at least 6 months; b) intervention with MT in UL or comparing it with other interventions; c) articles published until 2023; d) articles published in English or Portuguese; e) randomized controlled studies. Exclusion criteria: a) animal studies; b) studies that do not provide a detailed description of the intervention; c) Studies using central electrical stimulation. The methodological quality of the included studies was assessed using the Physiotherapy Evidence Database (PEDro) scale. Studies with < 4 on PEDro scale were excluded. Eighteen studies met all the inclusion criteria. Main results and conclusions: The quality of the studies varies between 5 and 8. One article compared muscular strength training (MST) with MT vs without MT and four articles compared the use of MT vs conventional therapy (CT), one study compared extracorporeal shock therapy (EST) with and without MT and another study compared functional electrical stimulation (FES), MT and biofeedback, three studies compared MT with Mesh Glove (MG) or Sham Therapy, five articles compared performing bimanual exercises with and without MT and three studies compared MT with virtual reality (VR) or robot training (RT). The assessment of changes in function and structure (International Classification of Functioning, Disability and Health parameter) was carried out, in each article, mainly using the Fugl Meyer Assessment-Upper Limb scale, activity and participation (International Classification of Functioning, Disability and Health parameter) were evaluated using different scales, in each study. The positive results were seen in these parameters, globally. Results suggest that MT is more effective than other therapies in motor recovery and function of the affected UL, than these techniques alone, although the results have been modest in most of the included studies. There is also a more significant improvement in the distal movements of the affected hand than in the rest of the UL.

Keywords: physical therapy, mirror therapy, chronic stroke, upper limb, hemiplegia

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Authors: Suehyun Cho, Darrell Harrington, Florent Cros, Olin Palmer, John Caputo, Michael Kardosh, Eran Oren, William Loudon, Alex Kiselyov, Michael Shpigelmacher

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The Dandy-Walker malformation (DWM) represents a clinical syndrome manifesting as a combination of posterior fossa cyst, hypoplasia of the cerebellar vermis, and obstructive hydrocephalus. Anatomic hallmarks include hypoplasia of the cerebellar vermis, enlargement of the posterior fossa, and cystic dilatation of the fourth ventricle. Current treatments of DWM, including shunting of the cerebral spinal fluid ventricular system and endoscopic third ventriculostomy (ETV), are frequently clinically insufficient, require additional surgical interventions, and carry risks of infections and neurological deficits. Bionaut Labs develops an alternative way to treat Dandy-Walker Malformation (DWM) associated with non-communicating hydrocephalus. We utilize our discreet microsurgical Bionaut™ particles that are controlled externally and remotely to perform safe, accurate, effective fenestration of the Dandy-Walker cyst, specifically in the posterior fossa of the brain, to directly normalize intracranial pressure. Bionaut™ allows for complex non-linear trajectories not feasible by any conventional surgical techniques. The microsurgical particle safely reaches targets in the lower occipital section of the brain. Bionaut™ offers a minimally invasive surgical alternative to highly involved posterior craniotomy or shunts via direct fenestration of the fourth ventricular cyst at the locus defined by the individual anatomy. Our approach offers significant advantages over the current standards of care in patients exhibiting anatomical challenge(s) as a manifestation of DWM, and therefore, is intended to replace conventional therapeutic strategies. Current progress, including platform optimization, Bionaut™ control, and real-time imaging and in vivo safety studies of the Bionauts™ in large animals, specifically the spine and the brain of ovine models, will be discussed.

Keywords: Bionaut™, cerebral spinal fluid, CSF, cyst, Dandy-Walker, fenestration, hydrocephalus, micro-robot

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Authors: Victor Prevost, Solene Landerneau, Michel Duhamel, Joel Sternheimer, Olivier Gallet, Pedro Ferrandiz, Marwa Mokni

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The search for homologous proteins is one of the ongoing challenges in biology and bioinformatics. Traditionally, a pair of proteins is thought to be homologous when they originate from the same ancestral protein. In such a case, their sequences share similarities, and advanced scientific research effort is spent to investigate this question. On this basis, we propose the Protein-Wave Alignment Tool (”P-WAT”) developed within the framework of the France Relance 2030 plan. Our work takes into consideration the mass-related wave aspect of protein biosynthesis, by associating specific frequencies to each amino acid according to its mass. Amino acids are then regrouped within their mass category. This way, our algorithm produces specific alignments in addition to those obtained with a common amino acid coding system. For this purpose, we develop the ”P-WAT” original algorithm, able to address large protein databases, with different attributes such as species, protein names, etc. that allow us to align user’s requests with a set of specific protein sequences. The primary intent of this algorithm is to achieve efficient alignments, in this specific conceptual frame, by minimizing execution costs and information loss. Our algorithm identifies sequence similarities by searching for matches of sub-sequences of different sizes, referred to as primers. Our algorithm relies on Boolean operations upon a dot plot matrix to identify primer amino acids common to both proteins which are likely to be part of a significant alignment of peptides. From those primers, dynamic programming-like traceback operations generate alignments and alignment scores based on an adjusted PAM250 matrix.

Keywords: protein, alignment, homologous, Genodic

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Authors: Amrit Vasdev, Edwin Rho, Gurinder Vasdev

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Robotic surgery has enabled a new spectrum of minimally invasive breast reconstruction by improving visualization, surgeon posturing, and improved patient outcomes.1 The DaVinci robot system can be utilized in nipple sparing mastectomies and reconstructions. The process involves the insufflation of the subglandular space and a dissection of the mammary gland with a combination of cautery and blunt dissection. This case outlines a 35-year-old woman who has a long-standing family history of breast cancer and a diagnosis of a deleterious BRCA2 genetic mutation. She has decided to proceed with bilateral nipple sparing mastectomies with implants. Her perioperative mammogram and MRI were negative for masses, however, her left internal mammary lymph node was enlarged. She has taken oral contraceptive pills for 3-5 years and denies DES exposure, radiation therapy, human replacement therapy, or prior breast surgery. She does not smoke and rarely consumes alcohol. During the procedure, the patient received a standardized anesthetic for out-patient surgery of propofol infusion, succinylcholine, sevoflurane, and fentanyl. Aprepitant was given as an antiemetic and preoperative Tylenol and gabapentin for pain management. Concerns for the patient during the procedure included CO2 insufflation into the subcutaneous space. With CO2 insufflation, there is a potential for rapid uptake leading to severe acidosis, embolism, and subcutaneous emphysema.2To mitigate this, it is important to hyperventilate the patient and reduce both the insufflation pressure and the CO2 flow rate to the minimal acceptable by the surgeon. For intraoperative monitoring during this 6-9 hour long procedure, it has been suggested to utilize an Arterial-Line for end-tidal CO2 monitoring. However, in this case, it was not necessary as the patient had excellent cardiovascular reserve, and end-tidal CO2 was within normal limits for the duration of the procedure. A BIS monitor was also utilized to reduce anesthesia burden and to facilitate a prompt discharge from the PACU. Minimal Invasive Robotic Surgery will continue to evolve, and anesthesiologists need to be prepared for the new challenges ahead. Based on our limit number of patients, robotic mastectomy appears to be a safe alternative to open surgery with the promise of clearer tissue demarcation and better cosmetic results.

Keywords: anesthesia, mastectomies, robotic, hypercarbia

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Authors: M. Mohan, J. P. Roise, G. P. Catts

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Despite living in an era where conservation zones are de-facto the central element in any sustainable wildlife management strategy, we still find ourselves grappling with several pareto-optimal situations regarding resource allocation and area distribution for the same. In this paper, a multi-objective decision making (MODM) model is presented to answer the question of whether or not we can establish mutual relationships between these contradicting objectives. For our study, we considered a Red-cockaded woodpecker (Picoides borealis) habitat conservation scenario in the coastal plain of North Carolina, USA. Red-cockaded woodpecker (RCW) is a non-migratory territorial bird that excavates cavities in living pine trees for roosting and nesting. The RCW groups nest in an aggregation of cavity trees called ‘cluster’ and for our model we use the number of clusters to be established as a measure of evaluating the size of conservation zone required. The case study is formulated as a linear programming problem and the objective function optimises the Red-cockaded woodpecker clusters, carbon retention rate, biofuel, public safety and Net Present Value (NPV) of the forest. We studied the variation of individual objectives with respect to the amount of area available and plotted a two dimensional dynamic graph after establishing interrelations between the objectives. We further explore the concept of interdependency by integrating the MODM model with GIS, and derive a raster file representing carbon distribution from the existing forest dataset. Model results demonstrate the applicability of interdependency from both linear and spatial perspectives, and suggest that this approach holds immense potential for enhancing environmental investment decision making in future.

Keywords: conservation, interdependency, multi-objective decision making, red-cockaded woodpecker

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Authors: Saleh Alotaibi, Mohammed Quddus, Craig Morton, Jobair Bin Alam

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This paper explores the role of large-scale investment in transport sectors and the impact of increased railway accessibility on the efficiency of the regional economic productivity in the Kingdom of Saudi Arabia (KSA). There are considerable differences among the KSA regions in terms of their levels of investment and productivity due to their geographical scale and location, which in turn greatly affect their relative efficiency. The study used a non-parametric linear programming technique - Data Envelopment Analysis (DEA) - to measure the regional efficiency change over time and determine the drivers of inefficiency and their scope of improvement. In addition, Window DEA analysis is carried out to compare the efficiency performance change for various time periods. Malmquist index (MI) is also analyzed to identify the sources of productivity change between two subsequent years. The analysis involves spatial and temporal panel data collected from 1999 to 2018 for the 13 regions of the country. Outcomes reveal that transport investment and improved railway accessibility, in general, have significantly contributed to regional economic development. Moreover, the endowment of the new railway stations has spill-over effects. The DEA Window analysis confirmed the dynamic improvement in the average regional efficiency over the study periods. MI showed that the technical efficiency change was the main source of regional productivity improvement. However, there is evidence of investment allocation discrepancy among regions which could limit the achievement of development goals in the long term. These relevant findings will assist the Saudi government in developing better strategic decisions for future transport investments and their allocation at the regional level.

Keywords: data envelopment analysis, transport investment, railway accessibility, efficiency

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Authors: Musse Mohamud Ahmed, Tina Linda Achilles, Mohammad Kamrul Hasan

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Deterioration of the mother nature is evident these day with clear danger of human catastrophe emanating from greenhouses (GHG) with increasing CO2 emissions to the environment. PV technology can help to reduce the dependency on fossil fuel, decreasing air pollution and slowing down the rate of global warming. The objective of this paper is to propose, develop and design the production of clean water supply to rural communities using an appropriate technology such as Internet of Things (IOT) that does not create any CO2 emissions. Additionally, maximization of solar energy power output and reciprocally minimizing the natural characteristics of solar sources intermittences during less presence of the sun itself is another goal to achieve in this work. The paper presents the development of critical automated control system for solar energy power output optimization using several new techniques. water pumping system is developed to supply clean water with the application of IOT-renewable energy. This system is effective to provide clean water supply to remote and off-grid areas using Photovoltaics (PV) technology that collects energy generated from the sunlight. The focus of this work is to design and develop a submersible solar water pumping system that applies an IOT implementation. Thus, this system has been executed and programmed using Arduino Software (IDE), proteus, Maltab and C++ programming language. The mechanism of this system is that it pumps water from water reservoir that is powered up by solar energy and clean water production was also incorporated using filtration system through the submersible solar water pumping system. The filtering system is an additional application platform which is intended to provide a clean water supply to any households in Sarawak State, Malaysia.

Keywords: IOT, automated production and control system, water filtration, automated submersible water pump, solar energy

Procedia PDF Downloads 88

Authors: Minjeong Kim, Seungchul Lee, Iman Janghorban Esfahani, Jeong Tai Kim, ChangKyoo Yoo

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A trajectory of set-point of ventilation control systems plays an important role for efficient ventilation inside subway stations since it affects the level of indoor air pollutants and ventilation energy consumption. To maintain indoor air quality (IAQ) at a comfortable range with lower ventilation energy consumption, the optimal trajectory of the ventilation control system needs to be determined. The concentration of air pollutants inside the station shows a diurnal variation in accordance with the variations in the number of passengers and subway frequency. To consider the diurnal variation of IAQ, an iterative dynamic programming (IDP) that searches for a piecewise control policy by separating whole duration into several stages is used. When outdoor air is contaminated by pollutants, it enters the subway station through the ventilation system, which results in the deteriorated IAQ and adverse effects on passenger health. In this study, to consider the influence of outdoor air quality (OAQ), a new performance index of the IDP with the passenger health risk and OAQ is proposed. This study was carried out for an underground subway station at Seoul Metro, Korea. The optimal set-points of the ventilation control system are determined every 3 hours, then, the ventilation controller adjusts the ventilation fan speed according to the optimal set-point changes. Compared to manual ventilation system which is operated irrespective of the OAQ, the IDP-based ventilation control system saves 3.7% of the energy consumption. Compared to the fixed set-point controller which is operated irrespective of the IAQ diurnal variation, the IDP-based controller shows better performance with a 2% decrease in energy consumption, maintaining the comfortable IAQ range inside the station.

Keywords: indoor air quality, iterative dynamic algorithm, outdoor air information, ventilation control system

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Authors: Ł. Morawiński, C. Jasiński, M. Jurkiewicz, S. Bou Habib, M. Bondyra

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With the development of optics, electronics, and computers, vision systems are increasingly used in various areas of life, science, and industry. Vision systems have a huge number of applications. They can be used in quality control, object detection, data reading, e.g., QR-code, etc. A large part of them is used for measurement purposes. Some of them make it possible to obtain a 3D reconstruction of the tested objects or measurement areas. 3D reconstruction algorithms are mostly based on creating depth maps from data that can be acquired from active or passive methods. Due to the specific appliance in airfield technology, only passive methods are applicable because of other existing systems working on the site, which can be blinded on most spectral levels. Furthermore, reconstruction is required to work long distances ranging from hundreds of meters to tens of kilometers with low loss of accuracy even with harsh conditions such as fog, rain, or snow. In response to those requirements, HRESS (Heliport REmote Safeguard System) was developed; which main part is a rotational head with a two-camera stereovision rig gathering images around the head in 360 degrees along with stereovision 3D reconstruction and point cloud combination. The sub-pixel analysis introduced in the HRESS system makes it possible to obtain an increased distance measurement resolution and accuracy of about 3% for distances over one kilometer. Ultimately, this leads to more accurate and reliable measurement data in the form of a point cloud. Moreover, the program algorithm introduces operations enabling the filtering of erroneously collected data in the point cloud. All activities from the programming, mechanical and optical side are aimed at obtaining the most accurate 3D reconstruction of the environment in the measurement area.

Keywords: airfield monitoring, artificial intelligence, stereovision, 3D reconstruction

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Authors: Wei Zhang, Chye Kiang Heng, John Chye Fung

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Background: The world’s demographics is currently undergoing the largest wave of both rapid ageing and dramatic urbanisation in human history. As one of the most rapidly ageing countries, Singapore will see about one in four residents aged 65 years and above by 2030 in its high-rise and high-density urban environment. Research questions: To support urban seniors ageing in place and interdependence among senior residents and their informal caregivers, this study argues a community-based care model with bottom-up mutual help networks and asks how neighbourhood built-environment influences the formulation and facilitation of bottom-up mutual help networks in Singapore. Methods: Two public housing communities with different physical environment and rich age-friendly neighbourhood initiatives were chosen as the case studies. The categories, participants and places of bottom-up mutual help activities will be obtained via field observation, non-structural interviews of participants, service providers and managers of care facilities, and documents. Mapping and content analysis will be used to explore the influences of neighbourhood built-environment on the formulation and facilitation of bottom-up mutual help networks. Results and conclusions: The results showed that neighbourhood design, place programming, and place governance have a confluence on the bottom-up mutual help networks for senior residents. Significance: The outcomes of this study will provide fresh evidence for paradigm shifts of community-based care for the elderly and neighbourhood planning. In addition, the research findings will shed light on meaningful implications of urban planners and policy makers as they tackle with the issues arising from the ageing society.

Keywords: Built environment, Mutual help, Neighbourhood, Senior residents, Singapore

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Levy flight, distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: Nkechinyere Joy Olawuyi, Babajide Samuel Afolabi, Bola Ibitoye

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This study collected a preprocessed dataset of chest radiographs and formulated a deep neural network model for detecting abnormalities. It also evaluated the performance of the formulated model and implemented a prototype of the formulated model. This was with the view to developing a deep neural network model to automatically classify abnormalities in chest radiographs. In order to achieve the overall purpose of this research, a large set of chest x-ray images were sourced for and collected from the CheXpert dataset, which is an online repository of annotated chest radiographs compiled by the Machine Learning Research Group, Stanford University. The chest radiographs were preprocessed into a format that can be fed into a deep neural network. The preprocessing techniques used were standardization and normalization. The classification problem was formulated as a multi-label binary classification model, which used convolutional neural network architecture to make a decision on whether an abnormality was present or not in the chest radiographs. The classification model was evaluated using specificity, sensitivity, and Area Under Curve (AUC) score as the parameter. A prototype of the classification model was implemented using Keras Open source deep learning framework in Python Programming Language. The AUC ROC curve of the model was able to classify Atelestasis, Support devices, Pleural effusion, Pneumonia, A normal CXR (no finding), Pneumothorax, and Consolidation. However, Lung opacity and Cardiomegaly had a probability of less than 0.5 and thus were classified as absent. Precision, recall, and F1 score values were 0.78; this implies that the number of False Positive and False Negative is the same, revealing some measure of label imbalance in the dataset. The study concluded that the developed model is sufficient to classify abnormalities present in chest radiographs into present or absent.

Keywords: transfer learning, convolutional neural network, radiograph, classification, multi-label

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Authors: G. C. Joshi, M. Paul, B. K. Kalita, V. Ranga, J. S. Rawat, P. S. Rawat

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Being a habitat of the global village, every place has established connection through the strength and power of social media piercing through the political boundaries. Social media is a digital platform, where people across the world can interact as it has advantages of being universal, anonymous, easily accessible, indirect interaction, gathering and sharing information. The power of social media lies in the intensity of sharing extreme opinions or feelings, in contrast to the personal interactions which can be easily mapped in the form of Sentiment Mapping. The easy access to social networking sites such as Facebook, Twitter and blogs made unprecedented opportunities for citizens to voice their opinions loaded with dynamics of emotions. These further influence human thoughts where social media plays a very active role. A recent incident of public importance was selected as a case study to map the sentiments of people through Twitter. Understanding those dynamics through the eye of an ordinary people can be challenging. With the help of R-programming language and by the aid of GIS techniques sentiment maps has been produced. The emotions flowing worldwide in the form of tweets were extracted and analyzed. The number of tweets had diminished by 91 % from 25/08/2017 to 31/08/2017. A boom of sentiments emerged near the origin of the case, i.e., Delhi, Haryana and Punjab and the capital showed maximum influence resulting in spillover effect near Delhi. The trend of sentiments was prevailing more as neutral (45.37%), negative (28.6%) and positive (21.6%) after calculating the sentiment scores of the tweets. The result can be used to know the spatial distribution of digital penetration in India, where highest concentration lies in Mumbai and lowest in North East India and Jammu and Kashmir.

Keywords: sentiment mapping, digital literacy, GIS, R statistical language, spatio-temporal

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Authors: Rohit Dey, Sailendra Karra

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This paper aims at solving the problem of multi-target searching in a Global Positioning System (GPS) denied environment using swarm robots with limited sensing and communication abilities. Typically, existing swarm-based search algorithms rely on the presence of a global coordinate system (vis-à-vis, GPS) that is shared by the entire swarm which, in turn, limits its application in a real-world scenario. This can be attributed to the fact that robots in a swarm need to share information among themselves regarding their location and signal from targets to decide their future course of action but this information is only meaningful when they all share the same coordinate frame. The paper addresses this very issue by eliminating any dependency of a search algorithm on the need of a predetermined global coordinate frame by the unification of the relative coordinate of individual robots when within the communication range, therefore, making the system more robust in real scenarios. Our algorithm assumes that all the robots in the swarm are equipped with range and bearing sensors and have limited sensing range and communication abilities. Initially, every robot maintains their relative coordinate frame and follow Levy walk random exploration until they come in range with other robots. When two or more robots are within communication range, they share sensor information and their location w.r.t. their coordinate frames based on which we unify their coordinate frames. Now they can share information about the areas that were already explored, information about the surroundings, and target signal from their location to make decisions about their future movement based on the search algorithm. During the process of exploration, there can be several small groups of robots having their own coordinate systems but eventually, it is expected for all the robots to be under one global coordinate frame where they can communicate information on the exploration area following swarm search techniques. Using the proposed method, swarm-based search algorithms can work in a real-world scenario without GPS and any initial information about the size and shape of the environment. Initial simulation results show that running our modified-Particle Swarm Optimization (PSO) without global information we can still achieve the desired results that are comparable to basic PSO working with GPS. In the full paper, we plan on doing the comparison study between different strategies to unify the coordinate system and to implement them on other bio-inspired algorithms, to work in GPS denied environment.

Keywords: bio-inspired search algorithms, decentralized control, GPS denied environment, swarm robotics, target searching, unifying coordinate systems

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Authors: Nigina Toktasynova, Sholpan Sagyndykova, Zhanat Kenzhebayeva, Maksat Kalimoldayev, Mariya Ishimova, Irbulat Utepbergenov

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Any business needs a stable operation and continuous improvement, therefore it is necessary to constantly interact with the environment, to analyze the work of the enterprise in terms of employees, executives and consumers, as well as to correct any inconsistencies of certain types of processes and their aggregate. In the case of heat supply organizations, in addition to suppliers, local legislation must be considered which often is the main regulator of pricing of services. In this case, the process approach used to build a functional organizational structure in these types of businesses in Kazakhstan is a challenge not only in the implementation, but also in ways of analyzing the employee's salary. To solve these problems, we investigated the management system of heating enterprise, including strategic planning based on the balanced scorecard (BSC), quality management in accordance with the standards of the Quality Management System (QMS) ISO 9001 and analysis of the system based on expert judgment using fuzzy inference. To carry out our work we used the theory of fuzzy sets, the QMS in accordance with ISO 9001, BSC according to the method of Kaplan and Norton, method of construction of business processes according to the notation IDEF0, theory of modeling using Matlab software simulation tools and graphical programming LabVIEW. The results of the work are as follows: We determined possibilities of improving the management of heat-supply plant-based on QMS; after the justification and adaptation of software tool it has been used to automate a series of functions for the management and reduction of resources and for the maintenance of the system up to date; an application for the analysis of the QMS based on fuzzy inference has been created with novel organization of communication software with the application enabling the analysis of relevant data of enterprise management system.

Keywords: balanced scorecard, heat supply, quality management system, the theory of fuzzy sets

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Authors: Iara Rezende, Djalma Silva, Alcino Costa Neto

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Considering the transformations of the contemporary world linked to globalization and climate changes caused by global warming, the environmental and energy issues have been increasingly present in the decisions of the world scenario. Thus, the aim of reducing the impacts caused by human activities there are the energy efficiency measures, which are also applicable in the scope of Civil Engineering. Considering that a large part of the energy demand from buildings is related to the need to adapt the internal environment to the users comfort and productivity, measures capable of reducing this need can minimize the climate changes impacts and also the energy consumption of the building. However, these important measures are currently little used by civil engineers, either because of the interdisciplinarity of the subject, the time required to apply certain methods or the difficult interpretation of the results obtained by computational programs that often have a complex and little applied approach. Thus, it was proposed the development of a Java application with a simpler and applied approach to evaluate the thermal performance of a building in order to obtain results capable of assisting the civil engineers in the decision making related to the users thermal comfort. The program was built in Java programming language and the method used for the evaluation was the Center Scientifique et Technique du Batiment (CSTB) method. The program was used to evaluate the thermal performance of a university classroom. The analysis was carried out from simulations considering the worst climatic situation of the building occupation. Thus, at the end of the process, the favorable result was obtained regarding the classroom comfort zone and the feasibility of using the program, thus achieving the proposed objectives.

Keywords: building occupation, CSTB method, energy efficiency measures, Java application, thermal comfort

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Authors: Antonio Horta, Renato Marinho, Raimir Holanda

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Considered as an evolution of the Blockchain, the Ethereum platform, besides allowing transactions of its cryptocurrency named Ether, it allows the programming of decentralised applications (DApps) and smart contracts. However, this functionality into blockchains has raised other types of threats, and the exploitation of smart contracts vulnerabilities has taken companies to experience big losses. This research intends to figure out the number of contracts that are under risk of being drained. Through a deep investigation, more than two hundred thousand smart contracts currently available in the Ethereum platform were scanned and estimated how much money is at risk. The experiment was based in a query run on Google Big Query in July 2022 and returned 50,707,133 contracts published on the Ethereum platform. After applying the filtering criteria, the experimentgot 430,584 smart contracts to download and analyse. The filtering criteria consisted of filtering out: ERC20 and ERC721 contracts, contracts without transactions, and contracts without balance. From this amount of 430,584 smart contracts selected, only 268,103 had source codes published on Etherscan, however, we discovered, using a hashing process, that there were contracts duplication. Removing the duplicated contracts, the process ended up with 20,417 source codes, which were analysed using the open source SAST tool smartbugswith oyente and securify algorithms. In the end, there was nearly $100,000 at risk of being drained from the potentially vulnerable smart contracts. It is important to note that the tools used in this study may generate false positives, which may interfere with the number of vulnerable contracts. To address this point, our next step in this research is to develop an application to test the contract in a parallel environment to verify the vulnerability. Finally, this study aims to alert users and companies about the risk on not properly creating and analysing their smart contracts before publishing them into the platform. As any other application, smart contracts are at risk of having vulnerabilities which, in this case, may result in direct financial losses.

Keywords: blockchain, reentrancy, static application security testing, smart contracts

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Authors: Antonio Pizzarello, Oris Friesen

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Networks, such as the electric power grid, must demonstrate exemplary performance and integrity. Integrity depends on the quality of both the system design model and the deployed software. Integrity of the deployed software is key, for both the original versions and the many that occur throughout numerous maintenance activity. Current software engineering technology and practice do not produce adequate integrity. Distributed systems utilize networks where each node is an independent computer system. The connections between them is realized via a network that is normally redundantly connected to guarantee the presence of a path between two nodes in the case of failure of some branch. Furthermore, at each node, there is software which may fail. Self-stabilizing protocols are usually present that recognize failure in the network and perform a repair action that will bring the node back to a correct state. These protocols first introduced by E. W. Dijkstra are currently present in almost all Ethernets. Super stabilization protocols capable of reacting to a change in the network topology due to the removal or addition of a branch in the network are less common but are theoretically defined and available. This paper describes how to use the Software Integrity Assessment (SIA) methodology to analyze self-stabilizing software. SIA is based on the UNITY formalism for parallel and distributed programming, which allows the analysis of code for verifying the progress property p leads-to q that describes the progress of all computations starting in a state satisfying p to a state satisfying q via the execution of one or more system modules. As opposed to demonstrably inadequate test and evaluation methods SIA allows the analysis and verification of any network self-stabilizing software as well as any other software that is designed to recover from failure without external intervention of maintenance personnel. The model to be analyzed is obtained by automatic translation of the system code to a transition system that is based on the use of the weakest precondition.

Keywords: network, power grid, self-stabilization, software integrity assessment, UNITY, weakest precondition

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Authors: Agodo Mugenyi Herbert

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Background: A high prevalence of both HIV infection and mental disorders exists in Sub-Saharan Africa, however there is little integration of care for mental health disorders among HIV-infected individuals. The study aimed at determining the management of common mental disorders among HIV/AIDS clients attending Antiretroviral clinic in Hoima regional referral hospital. Significancy of the study: The information generated by this study would help mental health advocates, ministry of health, Civil society organizations in HIV programming to advocate for enhanced mental health care for PLWHA. The result will be used in policy development and lobbying for integration of mental health care in HIV/AIDS care. Methods: This study applied a cross sectional design. It involved data collection from clients with HIV/AIDS attending ART clinic in Hoima regional referral hospital at one specific point in time. It aimed at providing data on the entire population under study. Data was collected from Hoima Regional Referral Hospital at the ART clinic. Data analysis was performed using SPSS version 24. Results: 66 HIV/AIDS clients and 10 health workers in the ART clinic who participated fully completed the study. The overall prevalence of at least one form of mental disorder was 83%. Majority of the health care practitioner do not use pharmacological, psychological, and social interventions to manage such disorders. Conclusion: These results are suggestive of a significant proportion of the HIV-infected patients experiencing psychological difficulty for which they do not receive treatment Recommendations: Current care practices applied to patients with HIV/AIDS should be integrated more generally to include treatment services to identify and manage common mental disorders.

Keywords: common mental disorders, mental health, mental illness, and severe mental illness

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Authors: Erva Akin

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– The use of copyrighted material for machine learning purposes is a challenging issue in the field of artificial intelligence (AI). While machine learning algorithms require large amounts of data to train and improve their accuracy and creativity, the use of copyrighted material without permission from the authors may infringe on their intellectual property rights. In order to overcome copyright legal hurdle against the data sharing, access and re-use of data, the use of copyrighted material for machine learning purposes may be considered permissible under certain circumstances. For example, if the copyright holder has given permission to use the data through a licensing agreement, then the use for machine learning purposes may be lawful. It is also argued that copying for non-expressive purposes that do not involve conveying expressive elements to the public, such as automated data extraction, should not be seen as infringing. The focus of such ‘copy-reliant technologies’ is on understanding language rules, styles, and syntax and no creative ideas are being used. However, the non-expressive use defense is within the framework of the fair use doctrine, which allows the use of copyrighted material for research or educational purposes. The questions arise because the fair use doctrine is not available in EU law, instead, the InfoSoc Directive provides for a rigid system of exclusive rights with a list of exceptions and limitations. One could only argue that non-expressive uses of copyrighted material for machine learning purposes do not constitute a ‘reproduction’ in the first place. Nevertheless, the use of machine learning with copyrighted material is difficult because EU copyright law applies to the mere use of the works. Two solutions can be proposed to address the problem of copyright clearance for AI training data. The first is to introduce a broad exception for text and data mining, either mandatorily or for commercial and scientific purposes, or to permit the reproduction of works for non-expressive purposes. The second is that copyright laws should permit the reproduction of works for non-expressive purposes, which opens the door to discussions regarding the transposition of the fair use principle from the US into EU law. Both solutions aim to provide more space for AI developers to operate and encourage greater freedom, which could lead to more rapid innovation in the field. The Data Governance Act presents a significant opportunity to advance these debates. Finally, issues concerning the balance of general public interests and legitimate private interests in machine learning training data must be addressed. In my opinion, it is crucial that robot-creation output should fall into the public domain. Machines depend on human creativity, innovation, and expression. To encourage technological advancement and innovation, freedom of expression and business operation must be prioritised.

Keywords: artificial intelligence, copyright, data governance, machine learning

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Authors: Reza Miresmaeili, Asghar Heydari Astaraee, Fereshteh Dolati

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In the present study, an analytical model based on dislocation density model was developed to simulate grain refinement in surface mechanical attrition treatment (SMAT). The correlation between SMAT time and development in plastic strain on one hand, and dislocation density evolution, on the other hand, was established to simulate the grain refinement in SMAT. A dislocation density-based constitutive material law was implemented using VUHARD subroutine. A random sequence of shots is taken into consideration for multiple impacts model using Python programming language by utilizing a random function. The simulation technique was to model each impact in a separate run and then transferring the results of each run as initial conditions for the next run (impact). The developed Finite Element (FE) model of multiple impacts describes the coverage evolution in SMAT. Simulations were run to coverage levels as high as 4500%. It is shown that the coverage implemented in the FE model is equal to the experimental coverage. It is depicted that numerical SMAT coverage parameter is adequately conforming to the well-known Avrami model. Comparison between numerical results and experimental measurements for residual stresses and depth of deformation layers confirms the performance of the established FE model for surface engineering evaluations in SMA treatment. X-ray diffraction (XRD) studies of grain refinement, including resultant grain size and dislocation density, were conducted to validate the established model. The full width at half-maximum in XRD profiles can be used to measure the grain size. Numerical results and experimental measurements of grain refinement illustrate good agreement and show the capability of established FE model to predict the gradient microstructure in SMA treatment.

Keywords: dislocation density, grain refinement, severe plastic deformation, simulation, surface mechanical attrition treatment

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Authors: Shanti Faridah Salleh, Azzahrah Anuar, Hamimah Ujir, Rohana Sapawi, Wan Hashim Wan Ibrahim, Noraziah Abdul Wahab, Majina Sulaiman, Raudhah Ahmadi, Al-Khalid Othman, Johari Abdullah

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Integrated Cumulative Grade Point Average or iCGPA is an evaluation and reporting system that represents a comprehensive development of students’ achievement in their academic programs. Universiti Malaysia Sarawak, UNIMAS has started its implementation of iCGPA in 2016. iCGPA is driven by the Outcome-Based Education (OBE) system that has been long integrated into the higher education in Malaysia. iCGPA is not only a tool to enhance the OBE concept through constructive alignment but it is also an integrated mechanism to assist various stakeholders in making decisions or planning for program improvement. The outcome of this integrated system is the reporting of students’ academic performance in terms of cognitive (knowledge), psychomotor (skills), and affective (attitude) of which the students acquire throughout the duration of their study. The iCGPA reporting illustrates the attainment of student’s attribute in the eight domains of learning outcomes listed in the Malaysian Qualifications Framework (MQF). This paper discusses on the implementation of iCGPA in UNIMAS on the policy and strategy to direct the whole university to implement the iCGPA. The steps and challenges in integrating the exsting Outcome-Based Education and utilising iCGPA as a tool to quantify the students’ achievement are also highlighted in this paper. Finally, the ACADEMIA system, which is a dedicated centralised program ensure the implementation of iCGPA is a success has been developed. This paper discusses the structure and the analysis of ACADEMIA program and concludes the analysis made on the improvement made on the implementation of constructive alignment in all 40 programs involves in iCGPA implementation.

Keywords: constructive alignment, holistic graduates, mapping of assessment, programme outcome

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Authors: Khanyisile Mnguni, Muthukrishnavellaisamy Kumarasamy, Jeff C. Smithers

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Umgeni Water is a water board that supplies most parts of KwaZulu Natal with bulk portable water. Currently, Umgeni Water is running its distribution system based on required reservoir levels and demands and does not consider the energy cost at different times of the day, number of pump switches, and background leakages. Including these constraints can reduce operational cost, energy usage, leakages, and increase performance. Optimising pump schedules can reduce energy usage and costs while adhering to hydraulic and operational constraints. Umgeni Water has installed an online hydraulic software, WaterNet Advisor, that allows running different operational scenarios prior to implementation in order to optimise the distribution system. This study will investigate operation scenarios using optimisation techniques and WaterNet Advisor for a local water distribution system. Based on studies reported in the literature, introducing pump scheduling optimisation can reduce energy usage by approximately 30% without any change in infrastructure. Including tariff structures in an optimisation problem can reduce pumping costs by 15%, while including leakages decreases cost by 10%, and pressure drop in the system can be up to 12 m. Genetical optimisation algorithms are widely used due to their ability to solve nonlinear, non-convex, and mixed-integer problems. Other methods such as branch and bound linear programming have also been successfully used. A suitable optimisation method will be chosen based on its efficiency. The objective of the study is to reduce energy usage, operational cost, and leakages, and the feasibility of optimal solution will be checked using the Waternet Advisor. This study will provide an overview of the optimisation of hydraulic networks and progress made to date in multi-objective optimisation for a selected sub-system operated by Umgeni Water.

Keywords: energy usage, pump scheduling, WaterNet Advisor, leakages

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Authors: Sakshi Gupta, Anupam Agrawal, Ekta Singla

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An exoskeleton design for rehabilitation purpose encounters many challenges, including ergonomically acceptable wearing technology, architectural design human-motion compatibility, actuation type, human-robot interaction, etc. In this paper, a passive architecture for upper limb exoskeleton is proposed for assisting in rehabilitation tasks. Kinematic modelling is detailed for task-based kinematic synthesis of the wearable exoskeleton for self-feeding tasks. The exoskeleton architecture possesses expansion and torsional springs which are able to store and redistribute energy over the human arm joints. The elastic characteristics of the springs have been optimized to minimize the mechanical work of the human arm joints. The concept of hybrid combination of a 4-bar parallelogram linkage and a serial linkage were chosen, where the 4-bar parallelogram linkage with expansion spring acts as a rigid structure which is used to provide the rotational degree-of-freedom (DOF) required for lowering and raising of the arm. The single linkage with torsional spring allows for the rotational DOF required for elbow movement. The focus of the paper is kinematic modelling, analysis and task-based synthesis framework for the proposed architecture, keeping in considerations the essential tasks of self-feeding and self-exercising during rehabilitation of partially healthy person. Rehabilitation of primary functional movements (activities of daily life, i.e., ADL) is routine activities that people tend to every day such as cleaning, dressing, feeding. We are focusing on the feeding process to make people independent in respect of the feeding tasks. The tasks are focused to post-surgery patients under rehabilitation with less than 40% weakness. The challenges addressed in work are ensuring to emulate the natural movement of the human arm. Human motion data is extracted through motion-sensors for targeted tasks of feeding and specific exercises. Task-based synthesis procedure framework will be discussed for the proposed architecture. The results include the simulation of the architectural concept for tracking the human-arm movements while displaying the kinematic and static study parameters for standard human weight. D-H parameters are used for kinematic modelling of the hybrid-mechanism, and the model is used while performing task-based optimal synthesis utilizing evolutionary algorithm.

Keywords: passive mechanism, task-based synthesis, emulating human-motion, exoskeleton

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Authors: Portia Muehlbauer

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This paper examines the evolving landscape of preventing and countering violent extremism (PCVE) by delving into the growing importance of integrating human rights principles into violence prevention strategies on the local, community level. This study sheds light on the underlying theoretical frameworks of violent extremism and the influence of gender while investigating the intersection between human rights preservation and violent extremism prevention. To gain practical insight, the research focuses on two prominent international non-governmental organizations, Women without Borders (WwB) and Hedayah, and their distinct PCVE initiatives. WwB adopts a gender-sensitive approach, implementing parental education programs that empower mothers in at-risk communities to prevent the spread of violent extremism. In contrast, Hedayah takes an indirect route, employing capacity building programs that enhance the capabilities of educators, social workers, and psychologists in early intervention, rehabilitation and reintegration efforts. Qualitative data for this comparative analysis was collected through an extensive four-month internship at WwB during the fall of 2020, a three-month internship at Hedayah in the spring of 2021, a thought-provoking semi-structured interview with the executive director of WwB, personal field notes, and a comprehensive discourse analysis of the prevailing literature on human rights considerations in PCVE practices. This study examines the merits and challenges of integrating human rights into PCVE programming through the lens of both organizations, WwB and Hedayah. The findings of this study will inform policymakers, practitioners, and researchers on the intricate relationship between human rights protection and effective PCVE strategies.

Keywords: preventing and countering violent extremism, human rights, counterterrorism, peacebuilding, capacity building programs, gender studies

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Authors: Ashimolowo Olubunmi

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Contraception use helps prevent pregnancy as well as health-related challenges, most especially among youths and girls. Our communities are bedeviled with many problems, including rape, defilement, neglect by the spouse, and intimate partner violence. Current interventions target only adults, with most facilities having youth and unfriendly adolescent services. To further support the need for this research, especially with our target beneficiaries, the partnership embarked on qualitative evidence-finding research through focus group discussions and in-depth-interview in Abeokuta and Ibadan (the capital cities of Ogun). The Focus Group Discussion (FGD) sessions were held in the state with adolescents (10-18 years) and young women (18-30 years). The result revealed that teenagers and youths who receive formal and sexual education on abstinence, and birth control methods, are likely to have healthier sexual behaviours through the promotion of abstinence and the use of condoms and other forms of contraceptives at their first intercourse, thereby protecting themselves against HIV/AIDs (Human Immunodeficiency Virus/Acquired immunodeficiency syndrome. The result further revealed that parents do not discuss issues around Adolescent and Sexual Reproductive Health (ASRH) with their adolescent girls, leading to gaps in knowledge of ASRH. Stakeholders’ involvement and trust are low. Respondents noted that there were few outreaches on ASRH and that youth-friendly adolescent centres are not common in the community. Respondents noted that there were few outreaches on ASRH organised within the community. Also, youth-friendly services were not common. There is a need to work with all stakeholders to promote those foundational life skills on pubertal changes, menstruation, and sexual life to prepare youths and girls for challenges ahead through sex education; we should work to institutionalize youth and adolescent-friendly Sexual and Reproductive Health (SRH) in our communities.

Keywords: contraception, family planning, focus group discussion, adolescents

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Authors: Soumyajit Koley, Kuladeep Rajamudili, Supriyo Ganguly

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In recent years, iron-based shape-memory alloys have been emerging as an inexpensive alternative to costly Ni-Ti alloy and thus considered suitable for many different applications in civil structures. Fe-17Mn-10Cr-5Si-4Ni-0.5V-0.5C alloy contains 37 wt.% of total solute elements. Such complex multi-component metallurgical system often leads to severe solute segregation and solidification cracking. Wire-arc additive manufacturing (WAAM) of Fe-17Mn-10Cr-5Si-4Ni-0.5V-0.5C alloy was attempted using a cold-wire fed plasma arc torch attached to a 6-axis robot. Self-standing walls were manufactured. However, multiple vertical cracks were observed after deposition of around 15 layers. Microstructural characterization revealed open surfaces of dendrites inside the crack, confirming these cracks as solidification cracks. Machine hammer peening (MHP) process was adopted on each layer to cold work the newly deposited alloy. Effect of MHP traverse speed were varied systematically to attain a window of operation where cracking was completely stopped. Microstructural and textural analysis were carried out further to correlate the peening process to microstructure.MHP helped in many ways. Firstly, a compressive residual stress was induced on each layer which countered the tensile residual stress evolved from solidification process; thus, reducing net tensile stress on the wall along its length. Secondly, significant local plastic deformation from MHP followed by the thermal cycle induced by deposition of next layer resulted into a recovered and recrystallized equiaxed microstructure instead of long columnar grains along the vertical direction. This microstructural change increased the total crack propagation length and thus, the overall toughness. Thirdly, the inter-layer peening significantly reduced the strong cubic {001} crystallographic texture formed along the build direction. Cubic {001} texture promotes easy separation of planes and easy crack propagation. Thus reduction of cubic texture alleviates the chance of cracking.

Keywords: Iron-based shape-memory alloy, wire-arc additive manufacturing, solidification cracking, inter-layer cold working, machine hammer peening

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