Search results for: work safety.

Authors: T. Abdulkadir

Abstract:

Most often, marking and assessment of multiple choice kinds of examinations have been opined by many as a cumbersome and herculean task to accomplished manually in Nigeria. Usually this may be in obvious nexus to the fact that mass numbers of candidates were known to take the same examination simultaneously. Eventually, marking such a mammoth number of booklets dared and dread even the fastest paid examiners who often undertake the job with the resulting consequences of stress and boredom. This paper explores the evolution, as well as the set aim to envision and transcend marking the Multiple Choice Objectives- type examination into a thing of creative recreation, or perhaps a more relaxing activity via the use of the mobile phone. A more “pragmatic” dimension method was employed to achieve this work, rather than the formal “in-depth research” based approach due to the “novelty” of the mobile-smartphone e-Marking Scheme discovery. Moreover, being an evolutionary scheme, no recent academic work shares a direct same topic concept with the ‘use of cell phone as an e-marking technique’ was found online; thus, the dearth of even miscellaneous citations in this work. Additional future advancements are what steered the anticipatory motive of this paper which laid the fundamental proposition. However, the paper introduces for the first time the concept of mobile-smart phone e-marking, the steps to achieve it, as well as the merits and demerits of the technique all spelt out in the subsequent pages.

Keywords: Cell phone, e-marking scheme, mobile phone, mobile-smart phone, multiple choice objectives, smartphone.

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Authors: W. C. Bracken

Abstract:

This paper discusses the forensic investigation of a fatality-involved catastrophic structure collapse and the special challenges faced when tasked with directing such an effort. While this paper discusses the investigation’s findings and the outcome of the event; this paper’s primary focus is on the challenges faced directing a forensic investigation that requires coordinating with governmental oversight while also having to accommodate multiple parties’ investigative teams. In particular the challenges discussed within this paper included maintaining on-site safety and operations while accommodating outside investigator’s interests. In addition this paper discusses unique challenges that one may face such as what to do about unethical conduct of interested party’s investigative teams, “off the record” sharing of information, and clandestinely transmitted evidence.

Keywords: Catastrophic structure collapse, collapse investigation, Jacksonville parking garage collapse, forensic investigation.

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Authors: Daniel Rivero, Julián Dorado, Juan R. Rabuñal, Alejandro Pazos, Javier Pereira

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The development of Artificial Neural Networks (ANNs) is usually a slow process in which the human expert has to test several architectures until he finds the one that achieves best results to solve a certain problem. This work presents a new technique that uses Genetic Programming (GP) for automatically generating ANNs. To do this, the GP algorithm had to be changed in order to work with graph structures, so ANNs can be developed. This technique also allows the obtaining of simplified networks that solve the problem with a small group of neurons. In order to measure the performance of the system and to compare the results with other ANN development methods by means of Evolutionary Computation (EC) techniques, several tests were performed with problems based on some of the most used test databases. The results of those comparisons show that the system achieves good results comparable with the already existing techniques and, in most of the cases, they worked better than those techniques.

Keywords: Artificial Neural Networks, Evolutionary Computation, Genetic Programming.

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Authors: D. Moser, D. Pinto, A. Cipriano

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A Disaster Management System (DMS) is very important for countries with multiple disasters, such as Chile. In the world (also in Chile)different disasters (earthquakes, tsunamis, volcanic eruption, fire or other natural or man-made disasters) happen and have an effect on the population. It is also possible that two or more disasters occur at the same time. This meansthata multi-risk situation must be mastered. To handle such a situation a Decision Support System (DSS) based on multiagents is a suitable architecture. The most known DMSs are concernedwith only a singledisaster (sometimes thecombination of earthquake and tsunami) and often with a particular disaster. Nevertheless, a DSS helps for a better real-time response. Analyze the existing systems in the literature and expand them for multi-risk disasters to construct a well-organized system is the proposal of our work. The here shown work is an approach of a multi-risk system, which needs an architecture and well defined aims. In this moment our study is a kind of case study to analyze the way we have to follow to create our proposed system in the future.

Keywords: Decision Support System, Disaster Management System, Multi-Risk, Multiagent System.

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Authors: Debajyoti Mishra, Urmila Bhanja

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In this paper, a novel fuzzy approach is developed while solving the Dynamic Routing and Wavelength Assignment (DRWA) problem in optical networks with Wavelength Division Multiplexing (WDM). In this work, the effect of nonlinear and linear impairments such as Four Wave Mixing (FWM) and amplifier spontaneous emission (ASE) noise are incorporated respectively. The novel algorithm incorporates fuzzy logic controller (FLC) to reduce the effect of FWM noise and ASE noise on a requested lightpath referred in this work as FWM aware fuzzy dynamic routing and wavelength assignment algorithm. The FWM crosstalk products and the static FWM noise power per link are pre computed in order to reduce the set up time of a requested lightpath, and stored in an offline database. These are retrieved during the setting up of a lightpath and evaluated online taking the dynamic parameters like cost of the links into consideration.

Keywords: Amplifier spontaneous emission (ASE), Dynamic routing and wavelength assignment, Four wave mixing (FWM), Fuzzy rule based system (FRBS).

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Authors: D. E. Gourgoulis, C. G. Yakinthos, M. G. Vassiliadou

Abstract:

With high speed vessels getting ever more sophisti-cated, travelling at higher and higher speeds and operating in With high speed vessels getting ever more sophisticated, travelling at higher and higher speeds and operating in areas of high maritime traffic density, training becomes of the highest priority to ensure that safety levels are maintained, and risks are adequately mitigated. Training onboard the actual craft on the actual route still remains the most effective way for crews to gain experience. However, operational experience and incidents during the last 10 years demonstrate the need for supplementary training whether in the area of simulation or man to man, man/ machine interaction. Training and familiarisation of the crew is the most important aspect in preventing incidents. The use of simulator, computer and web based training systems in conjunction with onboard training focusing on critical situations will improve the man machine interaction and thereby reduce the risk of accidents. Today, both ship simulator and bridge teamwork courses are now becoming the norm in order to improve further emergency response and crisis management skills. One of the main causes of accidents is the human factor. An efficient way to reduce human errors is to provide high-quality training to the personnel and to select the navigators carefully.areas of high maritime traffic density, training becomes of the highest priority to ensure that safety levels are maintained, and risks are adequately mitigated. Training onboard the actual craft on the actual route still remains the most effective way for crews to gain experience. How-ever, operational experience and incidents during the last 10 years demonstrate the need for supplementary training whether in the area of simulation or man to man, man/ machine interaction. Training and familiarisation of the crew is the most important aspect in preventing incidents. The use of simulator, computer and web based training systems in conjunction with onboard training focusing on critical situations will improve the man machine interaction and thereby reduce the risk of accidents. Today, both ship simulator and bridge teamwork courses are now becoming the norm in order to improve further emergency response and crisis management skills. One of the main causes of accidents is the human factor. An efficient way to reduce human errors is to provide high-quality training to the person-nel and to select the navigators carefully. KeywordsCBT - WBT systems, Human factors.

Keywords: CBT - WBT systems, Human factors.

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Authors: Hyun-Woo Cho

Abstract:

The early diagnostic decision making in industrial processes is absolutely necessary to produce high quality final products. It helps to provide early warning for a special event in a process, and finding its assignable cause can be obtained. This work presents a hybrid diagnostic schmes for batch processes. Nonlinear representation of raw process data is combined with classification tree techniques. The nonlinear kernel-based dimension reduction is executed for nonlinear classification decision boundaries for fault classes. In order to enhance diagnosis performance for batch processes, filtering of the data is performed to get rid of the irrelevant information of the process data. For the diagnosis performance of several representation, filtering, and future observation estimation methods, four diagnostic schemes are evaluated. In this work, the performance of the presented diagnosis schemes is demonstrated using batch process data.

Keywords: Diagnostics, batch process, nonlinear representation, data filtering, multivariate statistical approach

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Authors: Andreas Ahrens, Jelena Zascerinska

Abstract:

Emotions are crucial in online classes in adult education. Despite that, a little attention was devoted to the emotional experience of being an online teacher in the field of andragogy, and the online teacher’s emotional perspectives in ever changing environments have to be analysed. The paper aims at the analysis of teachers’ emotional experience in online classes in adult education in selected European countries. The research tends to propose implications for training of teachers who work in online classes in adult education. The survey was conducted in April 2022. In the selected European countries 78 respondents took part in the study. Among them, 30 respondents represented Germany, 28 respondents Greece, and 20 respondents were from Italy. The theoretical findings allow defining teacher emotional experience. The analysis of the elements of the respondents’ emotional experience allows concluding that teachers’ attitude to online classes has to be developed. The key content for teacher training is presented. Directions of further work are proposed.

Keywords: Adult education, online classes, teacher emotional experience, European countries.

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Authors: J. R. Wang, W.Y. Li, H.T. Lin, B.H. Lee, C. Shih, S.W. Chen

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In this research, the TRACE/PARCS model of  Lungmen ABWR has been developed for verification of ultimate  response guideline (URG) efficiency. This ultimate measure was  named as DIVing plan, abbreviated from system depressurization,  water injection and containment venting. The simulation initial  condition is 100% rated power/100% rated core flow. This research  focuses on the estimation of the time when the fuel might be damaged  with no water injection by using TRACE/PARCS first. Then, the  effect of the reactor core isolation system (RCIC), control  depressurization and ac-independent water addition system (ACIWA),  which can provide the injection with 950 gpm are also estimated for  the station blackout (SBO) transient.

 

Keywords: ABWR, TRACE, safety analysis, PARCS.

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Authors: Man Young Kim

Abstract:

The objective of this work is to investigate the turbulent reacting flow in a three dimensional combustor with emphasis on the effect of inlet swirl flow through a numerical simulation. Flow field is analyzed using the SIMPLE method which is known as stable as well as accurate in the combustion modeling, and the finite volume method is adopted in solving the radiative transfer equation. In this work, the thermal and flow characteristics in a three dimensional combustor by changing parameters such as equivalence ratio and inlet swirl angle have investigated. As the equivalence ratio increases, which means that more fuel is supplied due to a larger inlet fuel velocity, the flame temperature increases and the location of maximum temperature has moved towards downstream. In the mean while, the existence of inlet swirl velocity makes the fuel and combustion air more completely mixed and burnt in short distance. Therefore, the locations of the maximum reaction rate and temperature were shifted to forward direction compared with the case of no swirl.

Keywords: Gaseous Fuel, Inlet Swirl, Thermal Radiation, Turbulent Combustion

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Authors: Brenden M. Shutt, Lubjana Beshaj, Paul L. Goethals, Ambrose Kam

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Communication security is of particular interest to military data networks. A relatively novel approach to network security is blockchain, a cryptographically secured distribution ledger with a decentralized consensus mechanism for data transaction processing. Recent advances in blockchain technology have proposed new techniques for both data validation and trust management, as well as different frameworks for managing dataflow. The purpose of this work is to test the feasibility of different blockchain architectures as applied to military command and control networks. Various architectures are tested through discrete-event simulation and the feasibility is determined based upon a blockchain design’s ability to maintain long-term stable performance at industry standards of throughput, network latency, and security. This work proposes a consortium blockchain architecture with a computationally inexpensive consensus mechanism, one that leverages a Proof-of-Identity (PoI) concept and a reputation management mechanism.

Keywords: Blockchain, command & control network, discrete-event simulation, reputation management.

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Authors: Jae-Kyung LEE, Byung-Hak CHO, Kyung-Nam Jang, Sun-Chul Jung, Ki-Yong OH, Joon-Young PARK, Jong-Seog Kim

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The cables in a nuclear power plant are designed to be used for about 40 years in safe operation environment. However, the heat and radiation in the nuclear power plant causes the rapid performance deterioration of cables in nuclear vessels and heat exchangers, which requires cable lifetime estimation. The most accurate method of estimating the cable lifetime is to evaluate the cables in a laboratory. However, removing cables while the plant is operating is not allowed because of its safety and cost. In this paper, a robot system to estimate the cable lifetime in nuclear power plants is developed and tested. The developed robot system can calculate a modulus value to estimate the cable lifetime even when the nuclear power plant is in operation.

Keywords: Autonomous robot, Cable Inspection, Indenter, Nuclear Power Plant

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Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

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This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Keywords: Neural network, rule extraction, rule insertion, self-organizing map.

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Authors: Ioannis Andrianakis, Vasileios Gkatas, Nikos Eleftheriadis, Alexios Ellinidis, Ermioni Avramidou

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The paper discusses the main aspects involved in the development of a supply chain management system using the developed PredictionSCMS software as a basis for the discussion. The discussion is focused on three topics: the first is demand forecasting, where we present the predictive algorithms implemented and discuss related concepts such as the calculation of the safety stock, the effect of out-of-stock days etc. The second topic concerns the design of a supply chain, where the core parameters involved in the process are given, together with a methodology of incorporating these parameters in a meaningful order creation strategy. Finally, the paper discusses some critical events that can happen during the operation of a supply chain management system and how the developed software notifies the end user about their occurrence.

Keywords: Demand forecasting, machine learning, risk management, supply chain design.

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Authors: Benjamin Osei Tutu, Sharon Annison

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On 21^st November, 2016, an outbreak of foodborne illness occurred after a buffet lunch served during a stakeholders’ consultation meeting held in Accra. An investigation was conducted to characterise the affected people, determine the etiologic food, the source of contamination and the etiologic agent and to implement appropriate public health measures to prevent future occurrences. A retrospective cohort study was conducted via telephone interviews, using a structured questionnaire developed from the buffet menu. A case was defined as any person suffering from symptoms of foodborne illness e.g. diarrhoea and/or abdominal cramps after eating food served during the stakeholder consultation meeting in Accra on 21^st November, 2016. The exposure status of all the members of the cohort was assessed by taking the food history of each respondent during the telephone interview. The data obtained was analysed using Epi Info 7. An environmental risk assessment was conducted to ascertain the source of the food contamination. Risks of foodborne infection from the foods eaten were determined using attack rates and odds ratios. Data was obtained from 54 people who consumed food served during the stakeholders’ meeting. Out of this population, 44 people reported with symptoms of food poisoning representing 81.45% (overall attack rate). The peak incubation period was seven hours with a minimum and maximum incubation periods of four and 17 hours, respectively. The commonly reported symptoms were diarrhoea (97.73%, 43/44), vomiting (84.09%, 37/44) and abdominal cramps (75.00%, 33/44). From the incubation period, duration of illness and the symptoms, toxin-mediated food poisoning was suspected. The environmental risk assessment of the implicated catering facility indicated a lack of time/temperature control, inadequate knowledge on food safety among workers and sanitation issues. Limited number of food samples was received for microbiological analysis. Multivariate analysis indicated that illness was significantly associated with the consumption of the snacks served (OR 14.78, P < 0.001). No stool and blood or samples of etiologic food were available for organism isolation; however, the suspected etiologic agent was Staphylococcus aureus or Clostridium perfringens. The outbreak could probably be due to the consumption of unwholesome snack (tuna sandwich or chicken. The contamination and/or growth of the etiologic agent in the snack may be due to the breakdown in cleanliness, time/temperature control and good food handling practices. Training of food handlers in basic food hygiene and safety is recommended.

Keywords: Accra, buffet, C. perfringens, cohort study, food poisoning, gastroenteritis, office workers, Staphylococcus aureus.

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Authors: May Zin Lwin., Mya Mya Oo

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In the first part of the research work, an electrolyzer (10.16 cm dia and 24.13 cm height) to produce hydrogen and oxygen was constructed for single slice O2/H2 fuel cell using cation exchange membrane. The electrolyzer performance was tested with 23% NaOH, 30% NaOH, 30% KOH and 35% KOH electrolyte solution with current input 4 amp and 2.84 V from the rectifier. Rates of volume of hydrogen produced were 0.159 cm3/sec, 0.155 cm3/sec, 0.169 cm3/sec and 0.163 cm3/sec respectively from 23% NaOH, 30% NaOH, 30% KOH and 35% KOH solution. Rates of volume of oxygen produced were 0.212 cm3/sec, 0.201 cm3/sec, 0.227 cm3/sec and 0.219 cm3/sec respectively from 23% NaOH, 30% NaOH, 30% KOH and 35% KOH solution (1.5 L). In spite of being tested the increased concentration of electrolyte solution, the gas rate does not change significantly. Therefore, inexpensive 23% NaOH electrolyte solution was chosen to use as the electrolyte in the electrolyzer. In the second part of the research work, graphite serpentine flow plates, fiberglass end plates, stainless steel screen electrodes, silicone rubbers were made to assemble the single slice O2/H2 polymer electrolyte membrane fuel cell (PEMFC).

Keywords: electrolyzer, electrolyte solution, fuel cell, rectifier

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Authors: Adel Aloraini

Abstract:

Financial forecasting using machine learning techniques has received great efforts in the last decide . In this ongoing work, we show how machine learning of graphical models will be able to infer a visualized causal interactions between different banks in the Saudi equities market. One important discovery from such learned causal graphs is how companies influence each other and to what extend. In this work, a set of graphical models named Gaussian graphical models with developed ensemble penalized feature selection methods that combine ; filtering method, wrapper method and a regularizer will be shown. A comparison between these different developed ensemble combinations will also be shown. The best ensemble method will be used to infer the causal relationships between banks in Saudi equities market.

Keywords: Causal interactions , banks, feature selection, regularizere,

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Authors: Lydia Chan, Islam Shyha, Dale Dreyer, John Hamilton, Phil Hackney

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Nickel-based superalloys are generally known to be difficult to cut due to their strength, low thermal conductivity, and high work hardening tendency. Superalloy such as alloy 625 is often used in the oil and gas industry as a surfacing material to provide wear and corrosion resistance to components. The material is typically applied onto a metallic substrate through weld overlay cladding, an arc welding technique. Cladded surfaces are always rugged and carry a tough skin; this creates further difficulties to the machining process. The present work utilised design of experiment to optimise the internal cylindrical rough turning for weld overlay surfaces. An L27 orthogonal array was used to assess effects of the four selected key process variables: cutting insert, depth of cut, feed rate, and cutting speed. The optimal cutting conditions were determined based on productivity and the level of tool wear.

Keywords: Cylindrical turning, nickel superalloy, turning of overlay, weld overlay.

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Authors: Hani Shafeek, Mohammed Aman, Muhammad Marsudi

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Applied industrial engineering is concerned with imparting employable skills to improve the productivity for current situation of products and services. The purpose of this case study is to present the results of an initial research study conducted to identify the desired professional characteristics of an industrial engineer with an undergraduate degree and the emerging topic areas that should be incorporated into the curriculum to prepare industrial engineering (IE) graduates for the future workforce. Conclusions and recommendations for applied industrial engineering syllabus have been gathered and reported below. A two-pronged approach was taken which included a method of benchmarking by comparing the applied industrial engineering curricula of various universities and an industry survey to identify job market requirements. This methodology produced an analysis of the changing nature of industrial engineering from learning to practical education. A curriculum study for engineering is a relatively unexplored area of research in the Middle East, much less for applied industrial engineering. This work is an effort to bridge the gap between theoretical study in the classroom and the real world work applications in the industrial and service sectors.

Keywords: Applied industrial engineering, Faculty of Engineering, Industrial Engineering Curriculum, Syllabus.

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Authors: Yuwaraj M. Ghugal, Ajay G. Dahake

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A trigonometric shear deformation theory for flexure of thick beams, taking into account transverse shear deformation effects, is developed. The number of variables in the present theory is same as that in the first order shear deformation theory. The sinusoidal function is used in displacement field in terms of thickness coordinate to represent the shear deformation effects. The noteworthy feature of this theory is that the transverse shear stresses can be obtained directly from the use of constitutive relations with excellent accuracy, satisfying the shear stress free conditions on the top and bottom surfaces of the beam. Hence, the theory obviates the need of shear correction factor. Governing differential equations and boundary conditions are obtained by using the principle of virtual work. The thick simply supported isotropic beams are considered for the numerical studies to demonstrate the efficiency of the results obtained is discussed critically with those of other theories.

Keywords: Trigonometric shear deformation, thick beam, flexure, principle of virtual work, equilibrium equations, stress.

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Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L Duan

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The conditional density characterizes the distribution of a response variable y given other predictor x, and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts a motivating starting point. In this work, we extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zP , zN]. The zP component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zN component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach, coined Augmented Posterior CDE (AP-CDE), only requires a simple modification on the common normalizing flow framework, while significantly improving the interpretation of the latent component, since zP represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of x-related variations due to factors such as lighting condition and subject id, from the other random variations. Further, the experiments show that an unconditional NF neural network, based on an unsupervised model of z, such as Gaussian mixture, fails to generate interpretable results.

Keywords: Conditional density estimation, image generation, normalizing flow, supervised dimension reduction.

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Authors: Mohd. Israil, M. Salim Beg

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In order to accommodate various multimedia services, next generation wireless networks are characterized by very high transmission bit rates. Thus, in such systems and networks, the received signal is not only limited by noise but - especially with increasing symbols rate often more significantly by the intersymbol interference (ISI) caused by the time dispersive radio channels such as those are used in this work. This paper deals with the study of the performance of detector for high bit rate transmission on some worst case models of frequency selective fading channels for outdoor mobile radio environments. This paper deals with a number of different wireless channels with different power profiles and different number of resolvable paths. All the radio channels generated in this paper are for outdoor vehicular environments with Doppler spread of 100 Hz. A carrier frequency of 1800 MHz is used and all the channels used in this work are such that they are useful for next generation wireless systems. Schemes for mitigation of ISI with adaptive equalizers of different types have been investigated and their performances have been investigated in terms of BER measured as a function of SNR.

Keywords: Mobile channels, Rayleigh Fading, Equalization, NMLD.

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Authors: P. Saravanan, T. Arunkumar

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Vehicular Adhoc Network (VANET) is a new technology which aims to ensure intelligent inter-vehicle communications, seamless internet connectivity leading to improved road safety, essential alerts, and access to comfort and entertainment. VANET operations are hindered by mobile node’s (vehicles) uncertain mobility. Routing algorithms use metrics to evaluate which path is best for packets to travel. Metrics like path length (hop count), delay, reliability, bandwidth, and load determine optimal route. The proposed scheme exploits link quality, traffic density, and intersections as routing metrics to determine next hop. This study enhances Geographical Routing Protocol (GRP) using fuzzy controllers while rules are optimized with Bee Swarm Optimization (BSO). Simulations results are compared to conventional GRP.

Keywords: Bee Swarm Optimization (BSO), Geographical Routing Protocol (GRP), Vehicular Adhoc Network (VANET).

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Authors: Hae-Won Seo, Yong-Gu Lee

Abstract:

Recent progress in the next generation of automobile technology is geared towards incorporating information technology into cars. Collectively called smart cars are bringing intelligence to cars that provides comfort, convenience and safety. A branch of smart cars is connected-car system. The key concept in connected-cars is the sharing of driving information among cars through decentralized manner enabling collective intelligence. This paper proposes a foundation of the information model that is necessary to define the driving information for smart-cars. Road conditions are modeled through a unique data structure that unambiguously represent the time variant traffics in the streets. Additionally, the modeled data structure is exemplified in a navigational scenario and usage using UML. Optimal driving route searching is also discussed using the proposed data structure in a dynamically changing road conditions.

Keywords: Connected-car, data modeling, route planning, navigation system.

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Authors: Sangsuree Vasupongayya

Abstract:

Fair share objective has been included into the goaloriented parallel computer job scheduling policy recently. However, the previous work only presented the overall scheduling performance. Thus, the per-user performance of the policy is still lacking. In this work, the details of per-user fair share performance under the Tradeoff-fs(Tx:avgX) policy will be further evaluated. A basic fair share priority backfill policy namely RelShare(1d) is also studied. The performance of all policies is collected using an event-driven simulator with three real job traces as input. The experimental results show that the high demand users are usually benefited under most policies because their jobs are large or they have a lot of jobs. In the large job case, one job executed may result in over-share during that period. In the other case, the jobs may be backfilled for performances. However, the users with a mixture of jobs may suffer because if the smaller jobs are executing the priority of the remaining jobs from the same user will be lower. Further analysis does not show any significant impact of users with a lot of jobs or users with a large runtime approximation error.

Keywords: deviation, fair share, discrepancy search, priority scheduling.

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Authors: G. Lingam, N. Lingam, K. Raghuwaiya

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Thirty-eight rural school leaders in Solomon Islands responded to a questionnaire aimed at identifying their perceptions of work challenges. The data analysis points to an overwhelming percentage of school leaders feeling they face multifaceted problems in their work settings, including such challenges as untrained teachers, lack of funding, limited learning and teaching resources, and land disputes. The latter in particular is beyond the school leader’s jurisdiction; addressing it needs urgent attention from the principal stakeholder(s). Such challenges, seemingly tangential to the business of schooling, inadvertently affect the provision of good-quality education. The findings demonstrate that contextual challenges raise questions about what powers leadership at school level has to deal with some of them. The suggestion is advanced for the significant place-conscious leadership development to help address some community and cultural challenges. Implications of this paper are likely to be relevant to other similar contexts in the Pacific region and beyond.

Keywords: Rural school leaders, leadership, challenges, Solomon Islands, contextual factors.

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Authors: A. Mirrashid, M. Khoshbin, A. Atghaei, H. Shahbazi

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In various industries, smoke and fire are two of the most important threats in the workplace. One of the common methods for detecting smoke and fire is the use of infrared thermal and smoke sensors, which cannot be used in outdoor applications. Therefore, the use of vision-based methods seems necessary. The problem of smoke and fire detection is spatiotemporal and requires spatiotemporal solutions. This paper presents a method that uses spatial features along with temporal-based features to detect smoke and fire in the scene. It consists of three main parts; the task of each part is to reduce the error of the previous part so that the final model has a robust performance. This method also uses transformer modules to increase the accuracy of the model. The results of our model show the proper performance of the proposed approach in solving the problem of smoke and fire detection and can be used to increase workplace safety.

Keywords: Attention, fire detection, smoke detection, spatiotemporal.

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Authors: S. M. Gupta, Vanita Aggarwal, Som Nath Sachdeva

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The work reported through this paper is an experimental work conducted on High Performance Concrete (HPC) with super plasticizer with the aim to develop some models suitable for prediction of compressive strength of HPC mixes. In this study, the effect of varying proportions of fly ash (0% to 50% @ 10% increment) on compressive strength of high performance concrete has been evaluated. The mix designs studied were M30, M40 and M50 to compare the effect of fly ash addition on the properties of these concrete mixes. In all eighteen concrete mixes that have been designed, three were conventional concretes for three grades under discussion and fifteen were HPC with fly ash with varying percentages of fly ash. The concrete mix designing has been done in accordance with Indian standard recommended guidelines. All the concrete mixes have been studied in terms of compressive strength at 7 days, 28 days, 90 days, and 365 days. All the materials used have been kept same throughout the study to get a perfect comparison of values of results. The models for compressive strength prediction have been developed using Linear Regression method (LR), Artificial Neural Network (ANN) and Leave-One-Out Validation (LOOV) methods.

Keywords: ANN, concrete mixes, compressive strength, fly ash, high performance concrete, linear regression, strength prediction models.

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Authors: Murad A, Baker H, Mahmoud S, Gabr A

Abstract:

The groundwater is one of the main sources for sustainability in the United Arab Emirates (UAE). Intensive developments in Al-Ain area lead to increase water demand, which consequently reduced the overall groundwater quantity in major aquifers. However, in certain residential areas within Al-Ain, it has been noticed that the groundwater level is rising, for example in Sha-ab Al Askher area. The reasons for the groundwater rising phenomenon are yet to be investigated. In this work, twenty four seismic refraction profiles have been carried out along the study pilot area; as well as field measurement of the groundwater level in a number of available water wells in the area. The processed seismic data indicated the deepest and shallowest groundwater levels are 15m and 2.3 meters respectively. This result is greatly consistent with the proper field measurement of the groundwater level. The minimum detected value may be referred to perched subsurface water which may be associated to the infiltration from the surrounding water bodies such as lakes, and elevated farms. The maximum values indicate the accurate groundwater level within the study area. The findings of this work may be considered as a preliminary help to the decision makers.

Keywords: groundwater, shallow seismic method, United Arab Emirates

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Authors: Ji-il Park, Min Kyu Yu, Jong-woo Lee, Sam-hyeon Yoo

Abstract:

The purpose of this research is to analyze the gait strategy between the normal and loaded gait. To this end, five male participants satisfied two conditions: the normal and loaded gait (backpack load 25.2 kg). As expected, results showed that additional loads elicited not a proportional increase in vertical and shear ground reaction force (GRF) parameters but also increase of the impulse, momentum and mechanical work. However, in case of the loaded gait, the time duration of the double support phase was increased unexpectedly. It is because the double support phase which is more stable than the single support phase can reduce instability of the loaded gait. Also, the directions of the pre-collision and after-collision were moved upward and downward compared to the normal gait. As a result, regardless of the additional backpack load, the impulse-momentum diagram during the step-to-step transition was maintained such as the normal gait. It means that human walk efficiently to keep stability and minimize total net works in case of the loaded gait.

Keywords: Normal gait, loaded gait, impulse, collision, gait analysis, mechanical work, backpack load.

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