Search results for: restricted Boltzmann machine

Authors: Hussain M. Al-foudari, Weizhong Chen, James M. Bishop

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Correlations between oceanographic variables and monthly catch rates of total shrimp and those of each of the major species (Penaeus semisulcatus, Metapenaeus affinis and Parapenaeopsis stylifera) showed significant differences for particular conditions. Catches of P. semisulcatus were basically positively correlated with temperature, i.e., the higher the temperature, the higher the catch rate, while those of M. affinis and P. stylifera were negatively correlated with temperature, i.e., high catch rates occurred in the low temperature waters. Thus, during the months January and April, P. semisulcatus preferred waters with high temperature, usually the offshore and southern areas, while M. affinis and P. stylifera preferred waters with low temperature, usually inshore and northern areas. The relationships between the catch rate of P. semisulcatus and salinity were not so clear. Results indicated that although salinity was one of the factors affecting the distribution of P. semisulcatus, it was not the principal factor, and impacts from other variables, such as temperature, might overshadow the correlation between the catch rates of P. semisulcatus and salinity. The relationship between shrimp catch rates and dissolved oxygen (DO) also showed mixed results. The catch rates of M. affinis increased with a decrease of surface DO in November 2013, but decreased with lower bottom DO in December. These results indicated that DO might be a factor affecting distributions of the shrimp; however; the true correlation between catch rate and DO might be easily overshadowed by other environmental variables. Catch rates of P. semisulcatus did not show any relationship with depth. P. semisulcatus is a migratory species and widely distributed in Kuwait's waters.During the shrimp season from July through December, P. semisulcatus occurs in almost all areas in Kuwait's waters irrespective of water depth. The catch rates of M. affinis and P. stylifera, however, showed clear relationships with depth. Both species had significantly higher catch rates in shallower waters, indicative of their restricted distribution.

Keywords: Kuwait, Penaeus semisulcatus, Metapenaeus affinis, Parapenaeopsis stylifera, Arabian gulf

Procedia PDF Downloads 489

Authors: Amit Kaushik

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Equus kiang kiang is an indigenous large-bodied herbivore species, and in India, it is restricted to limited geographies of Ladakh. One of such areas is the Tsokar Basin. With the rise in global pashmina demand, the livestock numbers have grown significantly. Previous studies have reported conflict between a nomadic pastoral community, the Changpas, and kiang. Absentee pastoralism (in lieu of pure pastoralism) and tourism are two major economic activities among the local people. However, the social, economic, political, and ecological changes are inevitable in such a contemporary system. The study examines several factors influencing the local pastoral economy and focuses on the presence of two non-human cohabitants, kiang, and the wolf. This study used semi-structured interviews and vehicle count method in four different seasons. The results show that people perceived kiang as a threat but also reveal a level of tolerance towards them. The locals predicted high kiang numbers ranging from 200-3000 in the basin and contrastingly ranked them behind wolves, which are very few in numbers. Due to a lack of scientific pieces of evidence, the kiang population status remains obscure, and local peoples’ concerns remain unaddressed. But how this competitive dysfunctionality does take place? On one side, the rural development or the animal husbandry department aims at developing the area by providing stall-feed and tourism, whereas, on another side, the wildlife department emphasizes wildlife conservation. Therefore, the managers and planners may need to be cautious about the local socio-ecological complexities and may require inter-departmental communications. The study concludes that an interdisciplinary inquiry may be an important tool in understanding such a precarious situation and may be used in the policy-making processes.

Keywords: coexistence, human-livestock-wildlife interactions, interdisciplinary approach, kiang, policymaking, tsokar.

Procedia PDF Downloads 138

Authors: Sarekha Woranuch, Rangrong Yoksan

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Chitosan is a derivative of chitin, which is a second most naturally abundant polysaccharide found in crab shells, shrimp shells, and squid pens. The applications of chitosan in pharmaceutical, cosmetics, food and packaging industries have been reported owing to its general recognition as safe, excellent biodegradability and biocompatibility, as well as ability to form films, membranes, gels, beads, fibers and particles. Nevertheless, chitosan is an amino polysaccharide consisting of strong inter- and intramolecular hydrogen bonds which limit its solubility in neutral pH water resulting in restricted utilization. Chemical modification is an alternative way to impede hydrogen bond formation. The objective of the present research is to improve water solubility and antioxidant activity of chitosan by grafting with ferulic acid. Ferulic acid was grafted onto chitosan at the C-2 position via a carbodiimide-mediated coupling reaction. Different mole ratios of chitosan to ferulic acid (i.e. 1.0:0.0, 1.0:0.5, 1.0:1.0, 1.0:1.5, 1.0:2.0, and 1.0:2.5) and various reaction temperatures (i.e. 40, 60, and 80 °C) were used. The reaction was performed at different times (i.e. 1.5, 3.0, 4.5, and 6.0 h). The obtained ferulic acid-grafted chitosan was characterized by FTIR and 1H NMR technique. The influences of ferulic acid on crystallinity, solubility and radical scavenging activity of chitosan were also investigated. Ferulic acid grafted chitosan was successfully synthesized as confirmed from (i) the appearance of FTIR absorption band at 1517 cm-1 belonging to C=C aromatic ring of ferulic acid and the increased C–H stretching band intensity and (ii) the appearance of proton signals at δ = 6.31-7.67 ppm ascribing to methine protons of ferulic acid. The condition in which the reaction temperature of 60°C, reaction time of 3 h and the mole ratio of chitosan to ferulic acid of 1:1 gave the highest ferulic acid substitution degree, i.e. 0.37. The resulting ferulic acid grafted chitosan was soluble in water (1.3 mg/mL) due to its reduced crystallinity as compared with chitosan and also exhibited 90% greater radical scavenging activity than chitosan. The result suggested the utilization of ferulic acid grafted chitosan as an antioxidant material.

Keywords: antioxidant property, chitosan, ferulic acid, grafting

Procedia PDF Downloads 458

Authors: Chloé Kernaléguen, Laura Kundun, Tessie Lery, Ryan Laleg, Zhangyun Tan

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This study explores global disparities in respiratory syncytial virus (RSV) bronchiolitis incidence among children aged 0-2 years, focusing on the human development index (HDI) as a key determinant. RSV bronchiolitis poses a significant health risk to young children, influenced by factors, including socio-economic conditions captured by the HDI. Through a comprehensive systematic review and dataset selection (Switzerland, Brazil, United States of America), we formulated an HDI-SEIRS numerical model within the SEIRS framework. Results show variations in RSV bronchiolitis dynamics across countries, emphasizing the influence of HDI. Modelling reveals a correlation between higher HDI and increased bronchiolitis spread, notably in the USA and Switzerland. The ratios HDIcountry over HDImax strengthen this association, while climate disparities contribute to variations, especially in colder climates like the USA and Switzerland. The study raises the hypothesis of an indirect link between higher HDI and more frequent bronchiolitis, underlining the need for nuanced understanding. Factors like improved healthcare access, population density, mobility, and social behaviors in higher HDI countries might contribute to unexpected trends. Limitations include dataset quality and restricted RSV bronchiolitis data. Future research should encompass diverse HDI datasets to refine HDI's role in bronchiolitis dynamics. In conclusion, HDI-SEIRS models offer insights into factors influencing RSV bronchiolitis spread. While HDI is a significant indicator, its impact is indirect, necessitating a holistic approach to effective public health policies. This analysis sets the stage for further investigations into multifaceted interactions shaping bronchiolitis dynamics in diverse socio-economic contexts.

Keywords: bronchiolitis propagation, HDI influence, respiratory syncytial virus, SEIRS model

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Authors: Enes Gunaltili, Burak Dam

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The airplane history started with the Wright brothers' aircraft and improved day by day. With the help of this advancements, big aircrafts replace with small and unmanned air vehicles, so in this study we design this type of air vehicles. First of all, aircrafts mainly divided into two main parts in our day as a rotary and fixed wing aircrafts. The fixed wing aircraft generally use for transport, cargo, military and etc. The rotary wing aircrafts use for same area but there are some superiorities from each other. The rotary wing aircraft can take off vertically from the ground, and it can use restricted area. On the other hand, rotary wing aircrafts generally can fly lower range than fixed wing aircraft. There are one kind of aircraft consist of this two types specifications. It is named as VTOL (vertical take-off and landing) type aircraft. VTOLs are able to takeoff and land vertically and fly horizontally. The VTOL aircrafts generally can fly higher range from the rotary wings but can fly lower range from the fixed wing aircraft but it gives beneficial range between them. There are many other advantages of VTOL aircraft from the rotary and fixed wing aircraft. Because of that, VTOLs began to use for generally military, cargo, search, rescue and mapping areas. Within this framework, this study answers the question that how can we design VTOL as a small unmanned aircraft systems for search and rescue application for benefiting the advantages of fixed wing and rotary wing aircrafts by eliminating the disadvantages of them. To answer that question and design VTOL aircraft, multidisciplinary design optimizations (MDO), some theoretical terminologies, formulations, simulations and modelling systems based on CFD (Computational Fluid Dynamics) is used in same time as design methodology to determine design parameters and steps. As a conclusion, based on tests and simulations depend on design steps, suggestions on how the VTOL aircraft designed and advantages, disadvantages, and observations for design parameters are listed, then VTOL is designed and presented with the design parameters, advantages, and usage areas.

Keywords: airplane, rotary, fixed, VTOL, CFD

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Authors: Aouaouche Elmaouhab, Hassina Beggar

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Solving multi-objective discrete optimization applications has always been limited by the resources of one machine: By computing power or by memory, most often both. To speed up the calculations, the grid computing represents a primary solution for the treatment of these applications through the parallelization of these resolution methods. In this work, we are interested in the study of some methods for solving multiple objective integer linear programming problem based on Branch-and-Bound and the study of grid computing technology. This study allowed us to propose an implementation of the method of Abbas and Al on the grid by reducing the execution time. To enhance our contribution, the main results are presented.

Keywords: multi-objective optimization, integer linear programming, grid computing, parallel computing

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Authors: Cathy SW. Chow, Kristina Shin, Faming Wang, B. C. L. So

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During some dynamic giant puppet performances, an ergonomically designed load carrier system is necessary for the puppeteers to carry a giant puppet body’s heavy load with minimum muscle stress. A load carrier (i.e. prototype) was designed with two small wheels on the foot; and a hybrid spring device on the knee in order to assist the sliding and knee bending movements respectively. Thus, the purpose of this study was to evaluate the effect of three load carriers including two other commercially available load mounting systems, Tepex and SuitX, and the prototype. Ten male participants were recruited for the experiment. Surface electromyography (sEMG) was used to collect the participants’ muscle activities during forward moving and bouncing and with and without load of 11.1 kg that was 60 cm above the shoulder. Five bilateral muscles including the lumbar erector spinae (LES), rectus femoris (RF), bicep femoris (BF), tibialis anterior (TA), and gastrocnemius (GM) were selected for data collection. During forward moving task, the sEMG data showed smallest muscle activities by Tepex harness which exhibited consistently the lowest, compared with the prototype and SuitX which were significantly higher on left LES 68.99% and 64.99%, right LES 26.57% and 82.45%; left RF 87.71% and 47.61%, right RF 143.57% and 24.28%; left BF 80.21% and 22.23%, right BF 96.02% and 21.83%; right TA 6.32% and 4.47%; left GM 5.89% and 12.35% respectively. The result above reflected mobility was highly restricted by tested exoskeleton devices. On the other hand, the sEMG data from bouncing task showed the smallest muscle activities by prototype which exhibited consistently the lowest, compared with the Tepex harness and SuitX which were significantly lower on lLES 6.65% and 104.93, rLES 23.56% and 92.19%; lBF 33.21% and 93.26% and rBF 24.70% and 81.16%; lTA 46.51% and 191.02%; rTA 12.75% and 125.76%; IGM 31.54% and 68.36%; rGM 95.95% and 96.43% respectively.

Keywords: exoskeleton, giant puppet performers, load carriage system, surface electromyography

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Authors: Hushyar Azari

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Aim and background: Deep brain stimulation (DBS) is regarded as an important therapeutic choice for Parkinson's disease (PD). The two most common targets for DBS are the subthalamic nucleus (STN) and globus pallidus (GPi). This review was conducted to compare the clinical effectiveness of these two targets. Methods: A systematic literature search in electronic databases: Embase, Cochrane Library and PubMed were restricted to English language publications 2010 to 2021. Specified MeSH terms were searched in all databases. Studies which evaluated the Unified Parkinson's Disease Rating Scale (UPDRS) III were selected by meeting the following criteria: (1) compared both GPi and STN DBS; (2) had at least three months follow-up period; (3)at least five participants in each group; (4)conducted after 2010. Study quality assessment was performed using the Modified Jadad Scale. Results: 3577 potentially relevant articles were identified, of these, 3569 were excluded based on title and abstract, duplicate and unsuitable article removal. Eight articles satisfied the inclusion criteria and were scrutinized (458 PD patients). According to Modified Jadad Scale, the majority of included studies had low evidence quality which was a limitation of this review. 5 studies reported no statistically significant between-group difference for improvements in UPDRS ш scores. At the same time, there were some results in terms of pain, action tremor, rigidity, and urinary symptoms, which indicated that STN DBS might be a better choice. Regarding the adverse effects, GPi was superior. Conclusion: It is clear that other larger randomized clinical trials with longer follow-up periods and control groups are needed to decide which target is more efficient for deep brain stimulation in Parkinson’s disease and imposes fewer adverse effects on the patients. Meanwhile, STN seems more reasonable according to the results of this systematic review.

Keywords: brain stimulation, globus pallidus, Parkinson's disease, subthalamic nucleus

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Authors: S. Vivekananda Pandian

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A major challenging task in this current scenario is protecting your computer and other electronic gadgets against Cyber-attacks. In this current era Cyber warfare becomes a major threat to the entire world which targets a particular organization or a country spreading the Malwares, Breaching the securities, causing major loss to the organization. Several sectors both public and private are computerized such as Energy sectors, Oil refinery sectors, Defense sectors and Aviation sectors are prone to attacks. Several attacks are unknown while accessing the internet. To study the characteristics and Intention of the Attacker Kippo Honeypots are used. Honeypots are the trap set by us which enables them to monitor the malicious activities and detailed study about attackers which leads to strengthening of the security.

Keywords: attackers, security, Kippo Honeypots, virtual machine

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Authors: Zsolt János Viharos, Krisztián Balázs Kis, Imre Paniti, Gábor Belső, Péter Németh, János Farkas

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The paper presents the results and industrial applications in the production setup period estimation based on industrial data inherited from the field of polymer cutting. The literature of polymer cutting is very limited considering the number of publications. The first polymer cutting machine is known since the second half of the 20th century; however, the production of polymer parts with this kind of technology is still a challenging research topic. The products of the applying industrial partner must met high technical requirements, as they are used in medical, measurement instrumentation and painting industry branches. Typically, 20% of these parts are new work, which means every five years almost the entire product portfolio is replaced in their low series manufacturing environment. Consequently, it requires a flexible production system, where the estimation of the frequent setup periods' lengths is one of the key success factors. In the investigation, several (input) parameters have been studied and grouped to create an adequate training information set for an artificial neural network as a base for the estimation of the individual setup periods. In the first group, product information is collected such as the product name and number of items. The second group contains material data like material type and colour. In the third group, surface quality and tolerance information are collected including the finest surface and tightest (or narrowest) tolerance. The fourth group contains the setup data like machine type and work shift. One source of these parameters is the Manufacturing Execution System (MES) but some data were also collected from Computer Aided Design (CAD) drawings. The number of the applied tools is one of the key factors on which the industrial partners’ estimations were based previously. The artificial neural network model was trained on several thousands of real industrial data. The mean estimation accuracy of the setup periods' lengths was improved by 30%, and in the same time the deviation of the prognosis was also improved by 50%. Furthermore, an investigation on the mentioned parameter groups considering the manufacturing order was also researched. The paper also highlights the manufacturing introduction experiences and further improvements of the proposed methods, both on the shop floor and on the quotation preparation fields. Every week more than 100 real industrial setup events are given and the related data are collected.

Keywords: artificial neural network, low series manufacturing, polymer cutting, setup period estimation

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Authors: Zheng Yuxun

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This review critically assesses the advancements and prospective developments in defect detection methodologies within the semiconductor industry, an essential domain that significantly affects the operational efficiency and reliability of electronic components. As semiconductor devices continue to decrease in size and increase in complexity, the precision and efficacy of defect detection strategies become increasingly critical. Tracing the evolution from traditional manual inspections to the adoption of advanced technologies employing automated vision systems, artificial intelligence (AI), and machine learning (ML), the paper highlights the significance of precise defect detection in semiconductor manufacturing by discussing various defect types, such as crystallographic errors, surface anomalies, and chemical impurities, which profoundly influence the functionality and durability of semiconductor devices, underscoring the necessity for their precise identification. The narrative transitions to the technological evolution in defect detection, depicting a shift from rudimentary methods like optical microscopy and basic electronic tests to more sophisticated techniques including electron microscopy, X-ray imaging, and infrared spectroscopy. The incorporation of AI and ML marks a pivotal advancement towards more adaptive, accurate, and expedited defect detection mechanisms. The paper addresses current challenges, particularly the constraints imposed by the diminutive scale of contemporary semiconductor devices, the elevated costs associated with advanced imaging technologies, and the demand for rapid processing that aligns with mass production standards. A critical gap is identified between the capabilities of existing technologies and the industry's requirements, especially concerning scalability and processing velocities. Future research directions are proposed to bridge these gaps, suggesting enhancements in the computational efficiency of AI algorithms, the development of novel materials to improve imaging contrast in defect detection, and the seamless integration of these systems into semiconductor production lines. By offering a synthesis of existing technologies and forecasting upcoming trends, this review aims to foster the dialogue and development of more effective defect detection methods, thereby facilitating the production of more dependable and robust semiconductor devices. This thorough analysis not only elucidates the current technological landscape but also paves the way for forthcoming innovations in semiconductor defect detection.

Keywords: semiconductor defect detection, artificial intelligence in semiconductor manufacturing, machine learning applications, technological evolution in defect analysis

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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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Authors: Pradeep Joshi, Prashant Dhiman, Shiv Dayal Dhakad

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Inconel 718 is a family if Nickel-Chromium based Superalloy; it has very high oxidation and corrosion resistance. Inconel 718 is widely being used in aerospace, engine, turbine etc. due to its high mechanical strength and creep resistance. Being widely used, its machining should be easy but in real its machining is very difficult, especially by using traditional machining methods. It becomes easy to machine only by using non Traditional machining such as EDM. During EDM machining there is wear of both tool and workpiece, the tool wear is undesired because it changes tool shape, geometry. To reduce the tool wear rate (TWR) cryogenic treatment is performed on tool before the machining operation. The machining performances of the process are to be evaluated in terms of MRR, TWR which are functions of Discharge current, Pulse on-time, Pulse Off-time.

Keywords: EDM, cyrogenic, TWR, MRR

Procedia PDF Downloads 453

Authors: Mackenzie Leake, Liyu Xia, Kamil Rocki, Wayne Imaino

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In the Hierarchical Temporal Memory (HTM) paradigm the effect of overlap between inputs on the activation of columns in the spatial pooler is studied. Numerical results suggest that similar inputs are represented by similar sets of columns and dissimilar inputs are represented by dissimilar sets of columns. It is shown that the spatial pooler produces these results under certain conditions for the connectivity and proximal thresholds. Following the discussion of the initialization of parameters for the thresholds, corresponding qualitative arguments about the learning dynamics of the spatial pooler are discussed.

Keywords: hierarchical temporal memory, HTM, learning algorithms, machine learning, spatial pooler

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Authors: Josef Brychta, Jiri Kratochvil, Marek Pagac

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The group of progressive cutting materials can include non-traditional, emerging and less-used materials that can be an efficient use of cutting their lead to a quantum leap in the field of machining. This is essentially a “superhard” materials (STM) based on polycrystalline diamond (PCD) and polycrystalline cubic boron nitride (PCBN) cutting performance ceramics and development is constantly "perfecting" fine coated cemented carbides. The latter cutting materials are broken down by two parameters, toughness and hardness. A variation of alloying elements is always possible to improve only one of each parameter. Reducing the size of the core on the other hand doing achieves "contradictory" properties, namely to increase both hardness and toughness.

Keywords: grained cutting materials difficult to machine materials, optimum utilization, mechanic, manufacturing

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Authors: Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun

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Current state-of-the-art classification and detection algorithms rely on supervised training. In this work we study unsupervised feature learning in the context of temporally coherent video data. We focus on feature learning from unlabeled video data, using the assumption that adjacent video frames contain semantically similar information. This assumption is exploited to train a convolutional pooling auto-encoder regularized by slowness and sparsity. We establish a connection between slow feature learning to metric learning and show that the trained encoder can be used to define a more temporally and semantically coherent metric.

Keywords: machine learning, pattern clustering, pooling, classification

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Authors: Sheng-Tse Wu, Wu-Sung Yao

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In this paper, a drift assist control system is proposed for remote control (RC) cars to get the perfect drift angle. A steering servo control scheme is given powerfully to assist the drift driving. A gyroscope sensor is included to detect the machine's tail sliding and to achieve a better automatic counter-steering to prevent RC car from spinning. To analysis tire traction and vehicle dynamics is used to obtain the dynamic track of RC cars. It comes with a control gain to adjust counter-steering amount according to the sensor condition. An illustrated example of 1:10 RC drift car is given and the real-time control algorithm is realized by Arduino Uno.

Keywords: drift assist control system, remote control cars, gyroscope, vehicle dynamics

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Authors: Dilip K. Prasad, C. Krishna Prasath, Deepu Rajan, Lily Rachmawati, Eshan Rajabally, Chai Quek

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This paper discusses the technical challenges in maritime image processing and machine vision problems for video streams generated by cameras. Even well documented problems of horizon detection and registration of frames in a video are very challenging in maritime scenarios. More advanced problems of background subtraction and object detection in video streams are very challenging. Challenges arising from the dynamic nature of the background, unavailability of static cues, presence of small objects at distant backgrounds, illumination effects, all contribute to the challenges as discussed here.

Keywords: autonomous maritime vehicle, object detection, situation awareness, tracking

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Authors: Afroze Ibrahim Baqapuri, Ilya Trofimov

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Sponsored search is a multi-billion dollar industry and makes up a major source of revenue for search engines (SE). Click-through-rate (CTR) estimation plays a crucial role for ads selection, and greatly affects the SE revenue, advertiser traffic and user experience. We propose a novel architecture of solving CTR prediction problem by combining artificial neural networks (ANN) with decision trees. First, we compare ANN with respect to other popular machine learning models being used for this task. Then we go on to combine ANN with MatrixNet (proprietary implementation of boosted trees) and evaluate the performance of the system as a whole. The results show that our approach provides a significant improvement over existing models.

Keywords: neural networks, sponsored search, web advertisement, click prediction, click-through rate

Procedia PDF Downloads 572

Authors: Omar Imhemed Alramli

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As Transmission Control Protocol (TCP), User Datagram Protocol (UDP) is transfer protocol in the transportation layer in Open Systems Interconnection model (OSI model) or in TCP/IP model of networks. The UDP aspects evaluation were not recognized by using the pcattcp tool on the windows operating system platform like TCP. The study has been carried out to find a tool which supports UDP aspects evolution. After the information collection about different tools, iperf tool was chosen and implemented on Cygwin tool which is installed on both Windows XP platform and also on Windows XP on virtual box machine on one computer only. Iperf is used to make experimental evaluation of UDP and to see what will happen during the sending the packets between the Host and Guest in wired and wireless networks. Many test scenarios have been done and the major UDP aspects such as jitter, packet losses, and throughput are evaluated.

Keywords: TCP, UDP, IPERF, wireless LAN

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Authors: Stephanie Lehmann, Esther Ruf, Sabina Misoch

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Background: Due to demographic change and shortage of skilled nursing staff, assistive robots are built to support older adults at home and nursing staff in care institutions. When assistive robots facilitate tasks that are usually performed by humans, user acceptance is essential. Even though they are an important aspect of acceptance, emotions towards different assistive robots and different situations of robot-use have so far not been examined in detail. The appearance of assistive robots can trigger emotions that affect their acceptance. Acceptance of robots is assumed to be greater when they look more human-like; however, too much human similarity can be counterproductive. Regarding different groups, it is assumed that older adults have a more negative attitude towards robots than younger adults. Within the framework of a simulated robot study, the aim was to investigate emotions of older adults compared to students towards robots with different appearances and in different situations and so contribute to a deeper view of the emotions influencing acceptance. Methods: In a questionnaire study, vignettes were used to assess emotions toward robots in different situations and of different appearance. The vignettes were composed of two situations (service and care) shown by video and four pictures of robots varying in human similarity (machine-like to android). The combination of the vignettes was randomly distributed to the participants. One hundred forty-two older adults and 35 bachelor students of nursing participated. They filled out a questionnaire that surveyed 30 positive and 30 negative emotions. For each group, older adults and students, a sum score of “positive emotions” and a sum score of “negative emotions” was calculated. Mean value, standard deviation, or n for sample size and % for frequencies, according to the scale level, were calculated. For differences in the scores of positive and negative emotions for different situations, t-tests were calculated. Results: Overall, older adults reported significantly more positive emotions than students towards robots in general. Students reported significantly more negative emotions than older adults. Regarding the two different situations, the results were similar for the care situation, with older adults reporting more positive emotions than students and less negative emotions than students. In the service situation, older adults reported significantly more positive emotions; negative emotions did not differ significantly from the students. Regarding the appearance of the robot, there were no significant differences in emotions reported towards the machine-like, the mechanical-human-like and the human-like appearance. Regarding the android robot, students reported significantly more negative emotions than older adults. Conclusion: There were differences in the emotions reported by older adults compared to students. Older adults reported more positive emotions, and students reported more negative emotions towards robots in different situations and with different appearances. It can be assumed that older adults have a different attitude towards the use of robots than younger people, especially young adults in the health sector. Therefore, the use of robots in the service or care sector should not be rejected rashly based on the attitudes of younger persons, without considering the attitudes of older adults equally.

Keywords: emotions, robots, seniors, young adults

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Authors: Benchalak Muangmeesri

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The purpose of this paper is to discuss how to test the best control performance of a ceramics. Hydraulic press machine (HPM) is the most common shaping of advanced ceramic with products, dimensions, and ceramic products mainly from synthetic powders. A microcontroller can be achieved to control process and has set high standards in the shaping of raw materials in powder form. HPM was proposed to develop a position control system that linked to the embedded controller PIC16F877 via Proportional and Derivative (PD) controller. The model is performed using MATLAB/SIMULINK and the best control performance of an HPM. Finally, PD controller results, showing the best performance as it had the smallest overshoot and highest quality using a microcontroller control.

Keywords: ceramics, hydraulic press, microcontroller, PD controller

Procedia PDF Downloads 354

Authors: Senthuran Manoharan, Rathesan Sivagananalingam

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One of the main issues in system security is Authentication. Authentication can be defined as the process of recognizing the user's identity and it is the most important step in the access control process to safeguard data/resources from being accessed by unauthorized users. The static method of authentication cannot ensure the genuineness of the user. Due to this reason, more innovative authentication mechanisms came into play. At first two factor authentication was introduced and later, multi-factor authentication was introduced to enhance the security of the system. It also had some issues and later, adaptive authentication was introduced. In this research paper, the design of an adaptive authentication engine was put forward. The user risk profile was calculated based on the user parameters and then the user was challenged with a suitable authentication method.

Keywords: authentication, adaptive authentication, machine learning, security

Procedia PDF Downloads 246

Authors: Ruzanna Muradyan

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Medical data mining is a crucial field in contemporary healthcare that offers cutting-edge tactics with enormous potential to transform patient care. This abstract examines how sophisticated data mining techniques could transform the healthcare industry, with a special focus on how they might improve patient outcomes. Healthcare data repositories have dynamically evolved, producing a rich tapestry of different, multi-dimensional information that includes genetic profiles, lifestyle markers, electronic health records, and more. By utilizing data mining techniques inside this vast library, a variety of prospects for precision medicine, predictive analytics, and insight production become visible. Predictive modeling for illness prediction, risk stratification, and therapy efficacy evaluations are important points of focus. Healthcare providers may use this abundance of data to tailor treatment plans, identify high-risk patient populations, and forecast disease trajectories by applying machine learning algorithms and predictive analytics. Better patient outcomes, more efficient use of resources, and early treatments are made possible by this proactive strategy. Furthermore, data mining techniques act as catalysts to reveal complex relationships between apparently unrelated data pieces, providing enhanced insights into the cause of disease, genetic susceptibilities, and environmental factors. Healthcare practitioners can get practical insights that guide disease prevention, customized patient counseling, and focused therapies by analyzing these associations. The abstract explores the problems and ethical issues that come with using data mining techniques in the healthcare industry. In order to properly use these approaches, it is essential to find a balance between data privacy, security issues, and the interpretability of complex models. Finally, this abstract demonstrates the revolutionary power of modern data mining methodologies in transforming the healthcare sector. Healthcare practitioners and researchers can uncover unique insights, enhance clinical decision-making, and ultimately elevate patient care to unprecedented levels of precision and efficacy by employing cutting-edge methodologies.

Keywords: data mining, healthcare, patient care, predictive analytics, precision medicine, electronic health records, machine learning, predictive modeling, disease prognosis, risk stratification, treatment efficacy, genetic profiles, precision health

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Authors: I Lamri, L Arabet, M. Hidjeb

Abstract:

The direct shear test was used to determine the shear strength parameters C and Ø of a series of samples with different cement content. Samples stabilized with a certain percentage of cement showed a substantial gain in compressive strength and a significant increase in shear strength parameters. C and Ø. The laboratory equipment used in UCS tests consisted of a conventional 102mm diameter sample triaxial loading machine. Beyond 4% cement content a very important increase in shear strength was observed. It can be deduced from a comparative study of shear strength of soil samples with 4%, 7%, and 10% cement with sample containing 2 %, that the sample with a 4% cement content showed 90% increase in shear strength while those with 7% and 10% showed an increase of around 13 and 21 fold.

Keywords: cement, compression strength, shear stress, cohesion, angle of internal friction

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Authors: Emre Kara, Metehan Demir, Şura Karakuzu, Kadir Koç, Ahmet F. Geylan, Halil Aykul

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While the polymeric foam cored sandwiches have been realized for many years, recently there is a growing and outstanding interest on the use of sandwiches consisting of aluminum foam core because of their some of the distinct mechanical properties such as high bending stiffness, high load carrying and energy absorption capacities. These properties make them very useful in the transportation industry (automotive, aerospace, shipbuilding industry), where the "lightweight design" philosophy and the safety of vehicles are very important aspects. Therefore, in this study, the sandwich panels with aluminum alloy foam core and various types and thicknesses of glass fiber reinforced polymer (GFRP) skins produced via Vacuum Assisted Resin Transfer Molding (VARTM) technique were obtained by using a commercial toughened epoxy based adhesive with two components. The aim of this contribution was the analysis of the bending response of sandwiches with various glass fiber reinforced polymer skins. The three point bending tests were performed on sandwich panels at different values of support span distance using a universal static testing machine in order to clarify the effects of the type and thickness of the GFRP skins in terms of peak load, energy efficiency and absorbed energy values. The GFRP skins were easily bonded to the aluminum alloy foam core under press machine with a very low pressure. The main results of the bending tests are: force-displacement curves, peak force values, absorbed energy, collapse mechanisms and the influence of the support span length and GFRP skins. The obtained results of the experimental investigation presented that the sandwich with the skin made of thicker S-Glass fabric failed at the highest load and absorbed the highest amount of energy compared to the other sandwich specimens. The increment of the support span distance made the decrease of the peak force and absorbed energy values for each type of panels. The common collapse mechanism of the panels was obtained as core shear failure which was not affected by the skin materials and the support span distance.

Keywords: aluminum foam, collapse mechanisms, light-weight structures, transport application

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Authors: Sara Cumming, Julianne DiSanto, Leah Burton

Abstract:

Homelessness in Canada is a persistent problem. It has been widely argued that the best tactic for eradicating homelessness is to approach social issues from a Housing First perspective—an approach that centers on quickly moving people into permanent and independent housing and then providing them additional support and services as needed. It is recognized that life skills training is both necessary and an effective way to reduce cyclical homelessness; however, there is a scarcity of research on effective ways to teach life skills; this problem was exacerbated in a pandemic context, where in-person delivery was severely restricted or no longer possible. Very little attention has been paid to the diverse cultural needs of clients in a multicultural context and the need to foster cultural knowledge/awareness in individuals to successfully contribute to the cultural safety of communities. This research attempts to fill these gaps in the literature and in practice by employing a community-engaged research (CER) approach. Academic, government, funders, front-line staff, and clients at 15 not-for-profits from across the Greater Toronto Area in Ontario, Canada, collaborated to co-create a virtual, client-centric, equity, diversity, and inclusion (EDI) informed life skill learning management system. We employed a triangulation methodology for this research. An environmental scan was conducted for best practices. Two separate Creative Problem Solving Sessions were held with over 100 front-line workers, managers, and executive directors who work with homeless populations. Quantitative and open-ended surveys were completed by over 200 individuals with experience with homelessness. All sections of this research aimed to discover the areas of skills that individuals need to maintain housing and to ascertain what a more client-driven EDI approach to life skills training should include. This research will showcase which life skills are deemed essential for homeless and precariously housed individuals.

Keywords: homelessness, Housing First, life skills, community engaged research

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Authors: S. Tehsin, S. Kausar

Abstract:

The ultimate aim of machine intelligence is to explore and materialize the human capabilities, one of which is the ability to detect various text objects within one or more images displayed on any canvas including prints, videos or electronic displays. Multimedia data has increased rapidly in past years. Textual information present in multimedia contains important information about the image/video content. However, it needs to technologically testify the commonly used human intelligence of detecting and differentiating the text within an image, for computers. Hence in this paper feature set based on anatomical study of human text detection system is proposed. Subsequent examination bears testimony to the fact that the features extracted proved instrumental to text detection.

Keywords: biologically inspired vision, content based retrieval, document analysis, text extraction

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Authors: Kemal Polat

Abstract:

In this study, it has been estimated whether there is skin by using RBG values obtained from the camera and k-nearest neighbor (k-NN) classifier. The dataset used in this study has an unbalanced distribution and a linearly non-separable structure. This problem can also be called a big data problem. The Skin dataset was taken from UCI machine learning repository. As the classifier, we have used the k-NN method to handle this big data problem. For k value of k-NN classifier, we have used as 1. To train and test the k-NN classifier, 50-50% training-testing partition has been used. As the performance metrics, TP rate, FP Rate, Precision, recall, f-measure and AUC values have been used to evaluate the performance of k-NN classifier. These obtained results are as follows: 0.999, 0.001, 0.999, 0.999, 0.999, and 1,00. As can be seen from the obtained results, this proposed method could be used to predict whether the image is skin or not.

Keywords: k-NN classifier, skin or non-skin classification, RGB values, classification

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Authors: Rym Saidi, Pape Alioune Ndiaye, Ibnyasser Ammar, Zineb Rchiad, Khalid Daoui, Issam Kadmiri Meftahi, Adnane Bargaz

Abstract:

Chickpea (Cicer arietinum L.) is an important leguminous crop grown worldwide and plays a significant role in humans’ dietary consumption. Alongside nitrogen (N), low phosphorus (P) availability within agricultural soils is one of the major factors limiting chickpea growth and productivity. The combined application of beneficial bacterial inoculants and Rock P-fertilizer could boost chickpea performance and productivity, increasing P-utilization efficiency and minimizing nutrient losses under P-deficiency conditions. A greenhouse experiment was conducted to evaluate the response of chickpeas to two P-fertilizer forms (RP and TSP) under N2-fixer and P-solubilizer consortium inoculation to improve biological N fixation and P nutrition under P-deficient conditions. Under inoculation, chickpea chlorophyll content and chlorophyll fluorescence (RP+I and TSP+I) were increased compared to uninoculated treatments. The RP+I treatment increased both shoot and root dry weights by 48,80% and 72,68%, respectively, compared to the uninoculated RP fertilized control. Indeed, the bacterial consortium contributed to enhancing root morphological traits (e.g., root volume, surface area, and diameter) of all inoculated treatments versus the uninoculated treatments. Furthermore, soil available P and root inorganic P were significantly improved in RP+I by 162,84% and 73,24%, respectively, compared to uninoculated RP control. Our research outcomes suggest that the co-inoculation of chickpeas with N2-fixing, and P-solubilizing bacteria improves biomass yield and nutrient uptake. Eventually, enhancing chickpea agrophysiological performance, especially in restricted P-availability conditions.

Keywords: chickpea, consortium, beneficial bacterial inoculants, phosphorus deficiency, rock p-fertilizer, nutrient uptake

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