Search results for: smart and intelligent packaging

Authors: Abdul Basit Kiani

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Web development, the art of creating and maintaining websites, has witnessed remarkable advancements. The aim is to provide an overview of some of the cutting-edge developments in the field. Firstly, the rise of responsive web design has revolutionized user experiences across devices. With the increasing prevalence of smartphones and tablets, web developers have adapted to ensure seamless browsing experiences, regardless of screen size. This progress has greatly enhanced accessibility and usability, catering to the diverse needs of users worldwide. Additionally, the evolution of web frameworks and libraries has significantly streamlined the development process. Tools such as React, Angular, and Vue.js have empowered developers to build dynamic and interactive web applications with ease. These frameworks not only enhance efficiency but also bolster scalability, allowing for the creation of complex and feature-rich web solutions. Furthermore, the emergence of progressive web applications (PWAs) has bridged the gap between native mobile apps and web development. PWAs leverage modern web technologies to deliver app-like experiences, including offline functionality, push notifications, and seamless installation. This innovation has transformed the way users interact with websites, blurring the boundaries between traditional web and mobile applications. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) has opened new horizons in web development. Chatbots, intelligent recommendation systems, and personalization algorithms have become integral components of modern websites. These AI-powered features enhance user engagement, provide personalized experiences, and streamline customer support processes, revolutionizing the way businesses interact with their audiences. Lastly, the emphasis on web security and privacy has been a pivotal area of progress. With the increasing incidents of cyber threats, web developers have implemented robust security measures to safeguard user data and ensure secure transactions. Innovations such as HTTPS protocol, two-factor authentication, and advanced encryption techniques have bolstered the overall security of web applications, fostering trust and confidence among users. Hence, recent progress in web development has propelled the industry forward, enabling developers to craft innovative and immersive digital experiences. From responsive design to AI integration and enhanced security, the landscape of web development continues to evolve, promising a future filled with endless possibilities.

Keywords: progressive web applications (PWAs), web security, machine learning (ML), web frameworks, advancement responsive web design

Procedia PDF Downloads 39

Authors: Ursula D. C. Resende, Yan G. Santos, Lucas M. de O. Andrade

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The recent and fast development of the internet, wireless, telecommunication technologies and low-power electronic devices has led to an expressive amount of electromagnetic energy available in the environment and the smart applications technology expansion. These applications have been used in the Internet of Things devices, 4G and 5G solutions. The main feature of this technology is the use of the wireless sensor. Although these sensors are low-power loads, their use imposes huge challenges in terms of an efficient and reliable way for power supply in order to avoid the traditional battery. The radio frequency based energy harvesting technology is especially suitable to wireless power sensors by using a rectenna since it can be completely integrated into the distributed hosting sensors structure, reducing its cost, maintenance and environmental impact. The rectenna is an equipment composed of an antenna and a rectifier circuit. The antenna function is to collect as much radio frequency radiation as possible and transfer it to the rectifier, which is a nonlinear circuit, that converts the very low input radio frequency energy into direct current voltage. In this work, a set of rectennas, mounted on a paper substrate, which can be used for the inner coating of buildings and simultaneously harvest electromagnetic energy from the environment, is proposed. Each proposed individual rectenna is composed of a 2.45 GHz patch antenna and a voltage doubler rectifier circuit, built in the same paper substrate. The antenna contains a rectangular radiator element and a microstrip transmission line that was projected and optimized by using the Computer Simulation Software (CST) in order to obtain values of S11 parameter below -10 dB in 2.45 GHz. In order to increase the amount of harvested power, eight individual rectennas, incorporating metamaterial cells, were connected in parallel forming a system, denominated Electromagnetic Wall (EW). In order to evaluate the EW performance, it was positioned at a variable distance from the internet router, and a 27 kΩ resistive load was fed. The results obtained showed that if more than one rectenna is associated in parallel, enough power level can be achieved in order to feed very low consumption sensors. The 0.12 m2 EW proposed in this work was able to harvest 0.6 mW from the environment. It also observed that the use of metamaterial structures provide an expressive growth in the amount of electromagnetic energy harvested, which was increased from 0. 2mW to 0.6 mW.

Keywords: electromagnetic energy harvesting, metamaterial, rectenna, rectifier circuit

Procedia PDF Downloads 143

Authors: Jonathan Turner, Julie Doyle, Laura O’Philbin, Dympna O’Sullivan

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People living with dementia should be at the centre of decision-making regarding goals for daily living. These goals include basic activities (dressing, hygiene, and mobility), advanced activities (finances, transportation, and shopping), and meaningful activities that promote well-being (pastimes and intellectual pursuits). However, there is limited involvement of people living with dementia in the design of technology to support their goals. A project is described that is co-designing intelligent computer-based support for, and with, people affected by dementia and their carers. The technology will support self-management, empower participation in shared decision-making with carers and help people living with dementia remain healthy and independent in their homes for longer. It includes information from the patient’s care plan, which documents medications, contacts, and the patient's wishes on end-of-life care. Importantly for this work, the plan can outline activities that should be maintained or worked towards, such as exercise or social contact. The authors discuss how to integrate care goal information from such a care plan with data collected from passive sensors in the patient’s home in order to deliver individualized planning and interventions for persons with dementia. A number of scientific challenges are addressed: First, to co-design with dementia patients and their carers computerized support for shared decision-making about their care while allowing the patient to share the care plan. Second, to develop a new and open monitoring framework with which to configure sensor technologies to collect data about whether goals and actions specified for a person in their care plan are being achieved. This is developed top-down by associating care quality types and metrics elicited from the co-design activities with types of data that can be collected within the home, from passive and active sensors, and from the patient’s feedback collected through a simple co-designed interface. These activities and data will be mapped to appropriate sensors and technological infrastructure with which to collect the data. Third, the application of machine learning models to analyze data collected via the sensing devices in order to investigate whether and to what extent activities outlined via the care plan are being achieved. The models will capture longitudinal data to track disease progression over time; as the disease progresses and captured data show that activities outlined in the care plan are not being achieved, the care plan may recommend alternative activities. Disease progression may also require care changes, and a data-driven approach can capture changes in a condition more quickly and allow care plans to evolve and be updated.

Keywords: care goals, decision-making, dementia, self-care, sensors

Procedia PDF Downloads 149

Authors: Shengnan Chen, Shuhua Wang

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Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

Procedia PDF Downloads 267

Authors: Roseliza Mat Alipiah, David Raffaelli, J. C. R. Smart

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This research is a new approach as it integrates information from both environmental and social sciences to inform effective management of the wetlands. A three-stage research framework was developed for modelling the drivers and pressures imposed on the wetlands and their impacts to the ecosystem and the local communities. Firstly, a Bayesian Belief Network (BBN) was used to predict the probability of anthropogenic activities affecting the delivery of different key wetland ecosystem services under different management scenarios. Secondly, Choice Experiments (CEs) were used to quantify the relative preferences which key wetland stakeholder group (aquaculturists) held for delivery of different levels of these key ecosystem services. Thirdly, a Multi-Criteria Decision Analysis (MCDA) was applied to produce an ordinal ranking of the alternative management scenarios accounting for their impacts upon ecosystem service delivery as perceived through the preferences of the aquaculturists. This integrated ecosystem management approach was applied to a wetland ecosystem in Setiu, Terengganu, Malaysia which currently supports a significant level of aquaculture activities. This research has produced clear guidelines to inform policy makers considering alternative wetland management scenarios: Intensive Aquaculture, Conservation or Ecotourism, in addition to the Status Quo. The findings of this research are as follows: The BBN revealed that current aquaculture activity is likely to have significant impacts on water column nutrient enrichment, but trivial impacts on caged fish biomass, especially under the Intensive Aquaculture scenario. Secondly, the best fitting CE models identified several stakeholder sub-groups for aquaculturists, each with distinct sets of preferences for the delivery of key ecosystem services. Thirdly, the MCDA identified Conservation as the most desirable scenario overall based on ordinal ranking in the eyes of most of the stakeholder sub-groups. Ecotourism and Status Quo scenarios were the next most preferred and Intensive Aquaculture was the least desirable scenario. The methodologies developed through this research provide an opportunity for improving planning and decision making processes that aim to deliver sustainable management of wetland ecosystems in Malaysia.

Keywords: Bayesian belief network (BBN), choice experiments (CE), multi-criteria decision analysis (MCDA), aquaculture

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Authors: Carlos V. Gonzalez

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Background: Providers of in-home and community based services strive for the elimination of preventable harm to the people under their care as well as to the employees who support them. Traditional models of safety and protection from harm have assumed that the absence of incidents of harm is a good indicator of safe practices. However, this model creates an illusion of safety that is easily shaken by sudden and inadvertent harmful events. As an alternative, we have developed and implemented an evidence-based resilient model of safety known as C.O.P.E. (Caring, Observing, Predicting and Evaluating). Within this model, safety is not defined by the absence of harmful incidents, but by the presence of continuous monitoring, anticipation, learning, and rapid response to events that may lead to harm. Objective: The objective was to evaluate the effectiveness of the C.O.P.E. model for the reduction of harm to individuals with mental disabilities who receive home and community based services. Methods: Over the course of 2 years we counted the number of incidents of harm and near misses. We trained employees on strategies to eliminate incidents before they fully escalated. We trained employees to track different levels of patient status within a scale from 0 to 10. Additionally, we provided direct support professionals and supervisors with customized smart phone applications to track and notify the team of changes in that status every 30 minutes. Finally, the information that we collected was saved in a private computer network that analyzes and graphs the outcome of each incident. Result and conclusions: The use of the COPE model resulted in: A reduction in incidents of harm. A reduction the use of restraints and other physical interventions. An increase in Direct Support Professional’s ability to detect and respond to health problems. Improvement in employee alertness by decreasing sleeping on duty. Improvement in caring and positive interaction between Direct Support Professionals and the person who is supported. Developing a method to globally measure and assess the effectiveness of prevention from harm plans. Future applications of the COPE model for the reduction of harm to people who receive home and community based services are discussed.

Keywords: harm, patients, resilience, safety, mental illness, disability

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Authors: Ammar Y. Alqahtani

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In order to minimize the negative impact on the environment, it is essential to manage the waste that generated from the premature disposal of end-of-life (EOL) products properly. Consequently, government and international organizations introduced new policies and regulations to minimize the amount of waste being sent to landfills. Moreover, the consumers’ awareness regards environment has forced original equipment manufacturers to consider being more environmentally conscious. Therefore, manufacturers have thought of different ways to deal with waste generated from EOL products viz., remanufacturing, reusing, recycling, or disposing of EOL products. The rate of depletion of virgin natural resources and their dependency on the natural resources can be reduced by manufacturers when EOL products are treated as remanufactured, reused, or recycled, as well as this will cut on the amount of harmful waste sent to landfills. However, disposal of EOL products contributes to the problem and therefore is used as a last option. Number of EOL need to be estimated in order to fulfill the components demand. Then, disassembly process needs to be performed to extract individual components and subassemblies. Smart products, built with sensors embedded and network connectivity to enable the collection and exchange of data, utilize sensors that are implanted into products during production. These sensors are used for remanufacturers to predict an optimal warranty policy and time period that should be offered to customers who purchase remanufactured components and products. Sensor-provided data can help to evaluate the overall condition of a product, as well as the remaining lives of product components, prior to perform a disassembly process. In this paper, a multi-period disassembly-to-order (DTO) model is developed that takes into consideration the different system uncertainties. The DTO model is solved using Nonlinear Programming (NLP) in multiple periods. A DTO system is considered where a variety of EOL products are purchased for disassembly. The model’s main objective is to determine the best combination of EOL products to be purchased from every supplier in each period which maximized the total profit of the system while satisfying the demand. This paper also addressed the impact of sensor embedded products on the cost of warranties. Lastly, this paper presented and analyzed a case study involving various simulation conditions to illustrate the applicability of the model.

Keywords: closed-loop supply chains, environmentally conscious manufacturing, product recovery, reverse logistics

Procedia PDF Downloads 124

Authors: Valeria Tatano, Francesca Guidolin, Francesca Peltrera

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The preservation of historical Italian heritage, at the urban and architectural scale, has to consider restrictions and requirements connected with conservation issues and usability needs, which are often at odds with historical heritage preservation. Recent decades have been marked by the search for increased accessibility not only of public and private buildings, but to the whole historical city, also for people with disability. Moreover, in the last years the concepts of Smart City and Healthy City seek to improve accessibility both in terms of mobility (independent or assisted) and fruition of goods and services, also for historical cities. The principles of Inclusive Design have introduced new criteria for the improvement of public urban space, between current regulations and best practices. Moreover, they have contributed to transforming “special needs” into an opportunity of social innovation. These considerations find a field of research and analysis in the historical city of Venice, which is at the same time a site of UNESCO world heritage, a mass tourism destination bringing in visitors from all over the world and a city inhabited by an aging population. Due to its conformation, Venetian urban fabric is only partially accessible: about four thousand bridges divide thousands of islands, making it almost impossible to move independently. These urban characteristics and difficulties were the base, in the last 20 years, for several researches, experimentations and solutions with the aim of eliminating architectural barriers, in particular for the usability of bridges. The Venetian Municipality with the EBA Office and some external consultants realized several devices (e.g. the “stepped ramp” and the new accessible ramps for the Venice Marathon) that should determine an innovation for the city, passing from the use of mechanical replicable devices to specific architectural projects in order to guarantee autonomy in use. This paper intends to present the state-of-the-art in bridges accessibility, through an analysis based on Inclusive Design principles and on the current national and regional regulation. The purpose is to evaluate some possible strategies that could improve performances, between limits and possibilities of interventions. The aim of the research is to lay the foundations for the development of a strategic program for the City of Venice that could successfully bring together both conservation and improvement requirements.

Keywords: accessibility of historical cities, historical heritage preservation, inclusive design, technological and social innovation

Procedia PDF Downloads 260

Authors: Tamar Trop, Boris Portnov

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Public Space Lighting (PSL) of outdoor urban areas promotes comfort, defines spaces and neighborhood identities, enhances perceived safety and security, and contributes to residential satisfaction and wellbeing. However, if excessive or misdirected, PSL leads to unnecessary energy waste and increased greenhouse gas emissions, poses a non-negligible threat to the nocturnal environment, and may become a potential health hazard. At present, PSL is designed according to international, regional, and national standards, which consolidate best practice. Yet, knowledge regarding the optimal light characteristics needed for creating a perception of personal comfort and safety in densely populated residential areas, and the factors associated with this perception, is still scarce. The presented study suggests a paradigm shift in designing PSL towards a user-centered approach, which incorporates pedestrians' perspectives into the process. The study is an ongoing joint research project between China and Israel Ministries of Science and Technology. Its main objectives are to reveal inhabitants' perceptions of and preferences for PSL in different densely populated neighborhoods in China and Israel, and to develop a model that links instrumentally measured parameters of PSL (e.g., intensity, spectra and glare) with its perceived comfort and quality, while controlling for three groups of attributes: locational, temporal, and individual. To investigate measured and perceived PSL, the study employed various research methods and data collection tools, developed a location-based mobile application, and used multiple data sources, such as satellite multi-spectral night-time light imagery, census statistics, and detailed planning schemes. One of the study’s preliminary findings is that higher sense of safety in the investigated neighborhoods is not associated with higher levels of light intensity. This implies potential for energy saving in brightly illuminated residential areas. Study findings might contribute to the design of a smart and adaptive PSL strategy that enhances pedestrians’ perceived safety and comfort while reducing light pollution and energy consumption.

Keywords: energy efficiency, light pollution, public space lighting, PSL, safety perceptions

Procedia PDF Downloads 113

Authors: Charles Mazhazhate

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This study interrogates and analyses the intricate kin- and- kith network patterns of corruption and mismanagement of resources prevalent in public sector supply chains bedeviling the developing economies of Sub-Saharan Africa with particular reference to Zimbabwe. This is forcing governments to resort to harsh fiscal policies that see their citizens paying high taxes against a backdrop of incomes below the poverty datum line, and this negatively affects their quality of life. The corporate world is also affected by the various tax-regime instituted. Mismanagement of resources and corrupt practices are rampant in state-owned enterprises to the extent that institutional policies, procedures, and practices are often flouted for the benefit of a clique of individuals. This interwoven in kith and kin blood human relations in organizations where appointments to critical positions are based on ascribed status. People no longer place value in their systems to make them work thereby violating corporate governance principles. Greediness and ‘unholy friendship connections’ are instrumental in fueling the employment of people who know each other from their discrete backgrounds. Such employments or socio-metric unions are meant to protect those at the top by giving them intelligent information through spying on what other subordinates are doing inside and outside the organization. This practice has led to the underperforming of organizations as those employees with connections and their upper echelons favorites connive to abuse resources for their own benefit. Even if culprits are known, no draconian measures are employed as a deterrence measure. Public value along public sector supply chains is lost. The study used a descriptive case study research design on fifty organizations in Zimbabwe mainly state-owned enterprises. Both qualitative and quantitative instrumentations were used. Both Snowball and random sampling techniques were used. The study found out that in all the fifty SOEs, there were employees in key positions related to top management, with tentacles feeding into the law enforcement agents, judiciary, security systems, and the executive. Such employees in public seem not to know each other with but would be involved in dirty scams and then share the proceeds with top people behind the scenes. The study also established that the same employees do not have the necessary competencies, qualifications, abilities, and capabilities to be in those positions. This culture is now strong that it is difficult to bust. The study recommends recruitment of all employees through an independent employment bureau to ensure strategic fit.

Keywords: corruption, state owned enterprises, strategic fit, public sector supply chains, efficiency

Procedia PDF Downloads 143

Authors: Stefan Papastefanou

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Artificial intelligence (AI) is an interdisciplinary field of computer science with the aim of creating intelligent machine behavior. Early approaches to AI have been configured to operate in very constrained environments where the behavior of the AI system was previously determined by formal rules. Knowledge was presented as a set of rules that allowed the AI system to determine the results for specific problems; as a structure of if-else rules that could be traversed to find a solution to a particular problem or question. However, such rule-based systems typically have not been able to generalize beyond the knowledge provided. All over the world and especially in IT-heavy industries such as the United States, the European Union, Singapore, and China, machine learning has developed to be an immense asset, and its applications are becoming more and more significant. It has to be examined how such products of machine learning models can and should be protected by IP law and for the purpose of this paper patent law specifically, since it is the IP law regime closest to technical inventions and computing methods in technical applications. Genetic breeding models are currently less popular than recursive neural network method and deep learning, but this approach can be more easily described by referring to the evolution of natural organisms, and with increasing computational power; the genetic breeding method as a subset of the evolutionary algorithms models is expected to be regaining popularity. The research method focuses on patentability (according to the world’s most significant patent law regimes such as China, Singapore, the European Union, and the United States) of AI inventions and machine learning. Questions of the technical nature of the problem to be solved, the inventive step as such, and the question of the state of the art and the associated obviousness of the solution arise in the current patenting processes. Most importantly, and the key focus of this paper is the problem of patenting inventions that themselves are developed through machine learning. The inventor of a patent application must be a natural person or a group of persons according to the current legal situation in most patent law regimes. In order to be considered an 'inventor', a person must actually have developed part of the inventive concept. The mere application of machine learning or an AI algorithm to a particular problem should not be construed as the algorithm that contributes to a part of the inventive concept. However, when machine learning or the AI algorithm has contributed to a part of the inventive concept, there is currently a lack of clarity regarding the ownership of artificially created inventions. Since not only all European patent law regimes but also the Chinese and Singaporean patent law approaches include identical terms, this paper ultimately offers a comparative analysis of the most relevant patent law regimes.

Keywords: algorithms, inventor, genetic breeding models, machine learning, patentability

Procedia PDF Downloads 98

Authors: Bulcha Belay Etana, Benny Malengier, Debelo Oljira, Janarthanan Krishnamoorthy, Lieva Vanlangenhove

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Electromyography (EMG) is a technique used to measure the electrical activity of muscles. EMG can be used to assess muscle function in a variety of settings, including clinical, research, and sports medicine. The aim of this study was to develop a wearable textile sensor for EMG monitoring. The sensor was designed to be soft, stretchable, and washable, making it suitable for long-term use. The sensor was fabricated using a conductive thread material that was embroidered onto a fabric substrate. The sensor was then connected to a microcontroller unit (MCU) and a Wi-Fi-enabled module. The MCU was programmed to acquire the EMG signal and transmit it wirelessly to the Wi-Fi-enabled module. The Wi-Fi-enabled module then sent the signal to a server, where it could be accessed by a computer or smartphone. The sensor was able to successfully acquire and transmit EMG signals from a variety of muscles. The signal quality was comparable to that of commercial EMG sensors. The development of this sensor has the potential to improve the way EMG is used in a variety of settings. The sensor is soft, stretchable, and washable, making it suitable for long-term use. This makes it ideal for use in clinical settings, where patients may need to wear the sensor for extended periods of time. The sensor is also small and lightweight, making it ideal for use in sports medicine and research settings. The data for this study was collected from a group of healthy volunteers. The volunteers were asked to perform a series of muscle contractions while the EMG signal was recorded. The data was then analyzed to assess the performance of the sensor. The EMG signals were analyzed using a variety of methods, including time-domain analysis and frequency-domain analysis. The time-domain analysis was used to extract features such as the root mean square (RMS) and average rectified value (ARV). The frequency-domain analysis was used to extract features such as the power spectrum. The question addressed by this study was whether a wearable textile sensor could be developed that is soft, stretchable, and washable and that can successfully acquire and transmit EMG signals. The results of this study demonstrate that a wearable textile sensor can be developed that meets the requirements of being soft, stretchable, washable, and capable of acquiring and transmitting EMG signals. This sensor has the potential to improve the way EMG is used in a variety of settings.

Keywords: EMG, electrode position, smart wearable, textile sensor, IoT, IoT-integrated textile sensor

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Authors: Anusha Jain, Santosh Vishwanathan, Praveen K. Gupta, Shwetha S., Kavitha S. N.

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Agriculture has a major impact on the Indian economy, with the highest employment ratio than any sector of the country. Currently, most of the traditional agricultural practices and farming methods are manual, which results in farmers not realizing their maximum productivity often due to increasing in labour cost, inefficient use of water sources leading to wastage of water, inadequate soil moisture content, subsequently leading to food insecurity of the country. This research paper aims to solve this problem by developing a full-fledged web application-based platform that has the capacity to associate itself with a Microcontroller-based Automated Irrigation System which schedules the irrigation of crops based on real-time soil moisture content employing soil moisture sensors centric to the crop’s requirements using WSN (Wireless Sensor Networks) and M2M (Machine To Machine Communication) concepts, thus optimizing the use of the available limited water resource, thereby maximizing the crop yield. This robust automated irrigation system provides end-to-end automation of Irrigation of crops at any circumstances such as droughts, irregular rainfall patterns, extreme weather conditions, etc. This platform will also be capable of achieving a nationwide united farming community and ensuring the welfare of farmers. This platform is designed to equip farmers with prerequisite knowledge on tech and the latest farming practices in general. In order to achieve this, the MailChimp mailing service is used through which interested farmers/individuals' email id will be recorded and curated articles on innovations in the world of agriculture will be provided to the farmers via e-mail. In this proposed system, service is enabled on the platform where nearby crop vendors will be able to enter their pickup locations, accepted prices and other relevant information. This will enable farmers to choose their vendors wisely. Along with this, we have created a blogging service that will enable farmers and agricultural enthusiasts to share experiences, helpful knowledge, hardships, etc., with the entire farming community. These are some of the many features that the platform has to offer.

Keywords: WSN (wireless sensor networks), M2M (M/C to M/C communication), automation, irrigation system, sustainability, SAAS (software as a service), soil moisture sensor

Procedia PDF Downloads 109

Authors: Begum Koru, Isik Aybay, Demet Celik Ulusoy

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The discipline of law is quite complex and has its own terminology. Apart from written legal rules, there is also living law, which refers to legal practice. Basic legal rules aim at the happiness of individuals in social life and have different characteristics in different branches such as public or private law. On the other hand, law is a national phenomenon. The law of one nation and the legal system applied on the territory of another nation may be completely different. People who are experts in a particular field of law in one country may have insufficient expertise in the law of another country. Today, in addition to the local nature of law, international and even supranational law rules are applied in order to protect basic human values and ensure the protection of human rights around the world. Systems that offer algorithmic solutions to legal problems using artificial intelligence (AI) tools will perhaps serve to produce very meaningful results in terms of human rights. However, algorithms to be used should not be developed by only computer experts, but also need the contribution of people who are familiar with law, values, judicial decisions, and even the social and political culture of the society to which it will provide solutions. Otherwise, even if the algorithm works perfectly, it may not be compatible with the values of the society in which it is applied. The latest developments involving the use of AI techniques in legal systems indicate that artificial law will emerge as a new field in the discipline of law. More AI systems are already being applied in the field of law, with examples such as predicting judicial decisions, text summarization, decision support systems, and classification of documents. Algorithms for legal systems employing AI tools, especially in the field of prediction of judicial decisions and decision support systems, have the capacity to create automatic decisions instead of judges. When the judge is removed from this equation, artificial intelligence-made law created by an intelligent algorithm on its own emerges, whether the domain is national or international law. In this work, the aim is to make a general analysis of this new topic. Such an analysis needs both a literature survey and a perspective from computer experts' and lawyers' point of view. In some societies, the use of prediction or decision support systems may be useful to integrate international human rights safeguards. In this case, artificial law can serve to produce more comprehensive and human rights-protective results than written or living law. In non-democratic countries, it may even be thought that direct decisions and artificial intelligence-made law would be more protective instead of a decision "support" system. Since the values of law are directed towards "human happiness or well-being", it requires that the AI algorithms should always be capable of serving this purpose and based on the rule of law, the principle of justice and equality, and the protection of human rights.

Keywords: AI and law, artificial law, protection of human rights, AI tools for legal systems

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Authors: Waraporn Boonchieng, Ekkarat Boonchieng, Wilawan Senaratana, Jaras Singkaew

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Geographical information system (GIS) is a designated system widely used for collecting and analyzing geographical data. Since the introduction of ultra-mobile, 'smart' devices, investigators, clinicians, and even the general public have had powerful new tools for collecting, uploading and accessing information in the field. Epidemiology paired with GIS will increase the efficacy of preventive health care services. The objective of this study is to apply GPS location services that are available on the common mobile device with district health systems, storing data on our private cloud system. The mobile application has been developed for use on iOS, Android, and web-based platforms. The system consists of two parts of district health information, including recorded resident data forms and individual health recorded data forms, which were developed and approved by opinion sharing and public hearing. The application's graphical user interface was developed using HTML5 and PHP with MySQL as a database management system (DBMS). The reporting module of the developed software displays data in a variety of views, from traditional tables to various types of high-resolution, layered graphics, incorporating map location information with street views from Google Maps. Multi-extension exporting is also supported, utilizing standard platforms such as PDF, PNG, JPG, and XLS. The data were collected in the database beginning in March 2013, by district health volunteers and district youth volunteers who had completed the application training program. District health information consisted of patients’ household coordinates, individual health data, social and economic information. This was combined with Google Street View data, collected in March 2014. Studied groups consisted of 16,085 (67.87%) and 47,811 (59.87%) of the total 23,701 households and 79,855 people were collected by the system respectively, in Saraphi district, Chiang Mai Province. The report generated from the system has had a major benefit directly to the Saraphi District Hospital. Healthcare providers are able to use the basic health data to provide a specific home health care service and also to create health promotion activities according to medical needs of the people in the community.

Keywords: health, public health, GIS, geographic information system

Procedia PDF Downloads 312

Authors: Nasser S. Shebka

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Fuzzy logic is used in complex adaptive systems where classical tools of representing knowledge are unproductive. Nevertheless, the incorporation of fuzzy logic, as it’s the case with all artificial intelligence tools, raised some inconsistencies and limitations in dealing with increased complexity systems and rules that apply to real-life situations and hinders the ability of the inference process of such systems, but it also faces some inconsistencies between inferences generated fuzzy rules of complex or imprecise knowledge-based systems. The use of fuzzy logic enhanced the capability of knowledge representation in such applications that requires fuzzy representation of truth values or similar multi-value constant parameters derived from multi-valued logic, which set the basis for the three t-norms and their based connectives which are actually continuous functions and any other continuous t-norm can be described as an ordinal sum of these three basic ones. However, some of the attempts to solve this dilemma were an alteration to fuzzy logic by means of non-monotonic logic, which is used to deal with the defeasible inference of expert systems reasoning, for example, to allow for inference retraction upon additional data. However, even the introduction of non-monotonic fuzzy reasoning faces a major issue of conflict resolution for which many principles were introduced, such as; the specificity principle and the weakest link principle. The aim of our work is to improve the logical representation and functional modelling of AI systems by presenting a method of resolving existing and potential rule conflicts by representing temporal modalities within defeasible inference rule-based systems. Our paper investigates the possibility of resolving fuzzy rules conflict in a non-monotonic fuzzy reasoning-based system by introducing temporal modalities and Kripke's general weak modal logic operators in order to expand its knowledge representation capabilities by means of flexibility in classifying newly generated rules, and hence, resolving potential conflicts between these fuzzy rules. We were able to address the aforementioned problem of our investigation by restructuring the inference process of the fuzzy rule-based system. This is achieved by using time-branching temporal logic in combination with restricted first-order logic quantifiers, as well as propositional logic to represent classical temporal modality operators. The resulting findings not only enhance the flexibility of complex rule-base systems inference process but contributes to the fundamental methods of building rule bases in such a manner that will allow for a wider range of applicable real-life situations derived from a quantitative and qualitative knowledge representational perspective.

Keywords: fuzzy rule-based systems, fuzzy tense inference, intelligent systems, temporal modalities

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Authors: Scott Hollier, Ruchi Permvattana

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The purpose of this abstract is to share the findings of a recently completed disability-related Internet of Things (IoT) project undertaken at Curtin University in Australia. The project focused on identifying how IoT could support people with disabilities with their educational outcomes. To achieve this, the research consisted of an analysis of current literature and interviews conducted with students with vision, hearing, mobility and print disabilities. While the research acknowledged the ability to collect data with IoT is now a fairly common occurrence, its benefits and applicability still need to be grounded back into real-world applications. Furthermore, it is important to consider if there are sections of our society that may benefit from these developments and if those benefits are being fully realised in a rush by large companies to achieve IoT dominance for their particular product or digital ecosystem. In this context, it is important to consider a group which, to our knowledge, has had little specific mainstream focus in the IoT area –people with disabilities. For people with disabilities, the ability for every device to interact with us and with each other has the potential to yield significant benefits. In terms of engagement, the arrival of smart appliances is already offering benefits such as the ability for a person in a wheelchair to give verbal commands to an IoT-enabled washing machine if the buttons are out of reach, or for a blind person to receive a notification on a smartphone when dinner has finished cooking in an IoT-enabled microwave. With clear benefits of IoT being identified for people with disabilities, it is important to also identify what implications there are for education. With higher education being a critical pathway for many people with disabilities in finding employment, the question as to whether such technologies can support the educational outcomes of people with disabilities was what ultimately led to this research project. This research will discuss several significant findings that have emerged from the research in relation to how consumer-based IoT can be used in the classroom to support the learning needs of students with disabilities, how industrial-based IoT sensors and actuators can be used to monitor and improve the real-time learning outcomes for the delivery of lectures and student engagement, and a proposed method for students to gain more control over their learning environment. The findings shared in this presentation are likely to have significant implications for the use of IoT in the classroom through the implementation of affordable and accessible IoT solutions and will provide guidance as to how policies can be developed as the implications of both benefits and risks continue to be considered by educators.

Keywords: disability, higher education, internet of things, students

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Authors: Wenhao Li, Shijun Guo

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Carbon fibre reinforced composites are progressively replacing metal structures in modern civil aircraft. This is because composite materials have large potential of weight saving compared with metal. However, the achievement to date of weight saving in composite structure is far less than the theoretical potential due to many uncertainties in structural integrity and safety concern. Unlike the conventional metallic structure, composite components are bonded together along the joints where structural integrity is a major concern. To ensure the safety, metal fasteners are used to reinforce the composite bonded joints. One of the solutions for a significant weight saving of composite structure is to develop an effective technology of on-board Structural Health Monitoring (SHM) System. By monitoring the real-life stress status of composite structures during service, the safety margin set in the structure design can be reduced with confidence. It provides a means of safeguard to minimize the need for programmed inspections and allow for maintenance to be need-driven, rather than usage-driven. The aim of this paper is to develop smart composite joint. The key technology is a multifunctional thermoplastic composite fastener (MTCF). The MTCF will replace some of the existing metallic fasteners in the most concerned locations distributed over the aircraft composite structures to reinforce the joints and form an on-board SHM network system. Each of the MTCFs will work as a unit of the AU and AE technology. The proposed MTCF technology has been patented and developed by Prof. Guo in Cranfield University, UK in the past a few years. The manufactured MTCF has been successfully employed in the composite SLJ (Single-Lap Joint). In terms of the structure integrity, the hybrid SLJ reinforced by MTCF achieves 19.1% improvement in the ultimate failure strength in comparison to the bonded SLJ. By increasing the diameter or rearranging the lay-up sequence of MTCF, the hybrid SLJ reinforced by MTCF is able to achieve the equivalent ultimate strength as that reinforced by titanium fastener. The predicted ultimate strength in simulation is in good agreement with the test results. In terms of the structural health monitoring, a signal from the MTCF was measured well before the load of mechanical failure. This signal provides a warning of initial crack in the joint which could not be detected by the strain gauge until the final failure.

Keywords: composite single-lap joint, crack propagation, multifunctional composite fastener, structural health monitoring

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: Elizabeth Parrott, Harry Pointon, Frederic Bezombes, Heather Panter

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Unmanned aerial vehicles (UAV’s) are making a profound effect within policing, forensic and fire service procedures worldwide. These intelligent devices have already proven useful in photographing and recording large-scale outdoor and indoor sites using orthomosaic and three-dimensional (3D) modelling techniques, for the purpose of capturing and recording sites during and post-incident. UAV’s are becoming an established tool as they are extending the reach of the photographer and offering new perspectives without the expense and restrictions of deploying full-scale aircraft. 3D reconstruction quality is directly linked to the resolution of captured images; therefore, close proximity flights are required for more detailed models. As technology advances deployment of UAVs in confined spaces is becoming more common. With this in mind, this study investigates the effects of UAV operation within active crimes scenes with regard to the dispersal of particulate evidence. To date, there has been little consideration given to the potential effects of using UAV’s within active crime scenes aside from a legislation point of view. Although potentially the technology can reduce the likelihood of contamination by replacing some of the roles of investigating practitioners. There is the risk of evidence dispersal caused by the effect of the strong airflow beneath the UAV, from the downwash of the propellers. The initial results of this study are therefore presented to determine the height of least effect at which to fly, and the commercial propeller type to choose to generate the smallest amount of disturbance from the dataset tested. In this study, a range of commercially available 4-inch propellers were chosen as a starting point due to the common availability and their small size makes them well suited for operation within confined spaces. To perform the testing, a rig was configured to support a single motor and propeller powered with a standalone mains power supply and controlled via a microcontroller. This was to mimic a complete throttle cycle and control the device to ensure repeatability. By removing the variances of battery packs and complex UAV structures to allow for a more robust setup. Therefore, the only changing factors were the propeller and operating height. The results were calculated via computer vision analysis of the recorded dispersal of the sample particles placed below the arm-mounted propeller. The aim of this initial study is to give practitioners an insight into the technology to use when operating within confined spaces as well as recognizing some of the issues caused by UAV’s within active crime scenes.

Keywords: dispersal, evidence, propeller, UAV

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Authors: Ahmed Slami, Med El Amine Brixi Nigassa, Nassima Labdelli, Sofiane Soulimane, Arnaud Pothier

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Many people suffer from diabetes, a disease marked by abnormal levels of sugar in the blood; 285 million people have diabetes, 6.6% of the world adult population (in 2010), according to the International Diabetes Federation. Insulin medicament is invented to be injected into the body. Generally, the injection requires the patient to do it manually. However, in many cases he will be unable to inject the drug, saw that among the side effects of hyperglycemia is the weakness of the whole body. The researchers designed a medical device that injects insulin too autonomously by using micro-pumps. Many micro-pumps of concepts have been investigated during the last two decades for injecting molecules in blood or in the body. However, all these micro-pumps are intended for slow infusion of drug (injection of few microliters by minute). Now, the challenge is to develop micro-pumps for fast injections (1 microliter in 10 seconds) with accuracy of the order of microliter. Recently, studies have shown that only piezoelectric actuators can achieve this performance, knowing that few systems at the microscopic level were presented. These reasons lead us to design new smart microsystems injection drugs. Therefore, many technological advances are still to achieve the improvement of materials to their uses, while going through their characterization and modeling action mechanisms themselves. Moreover, it remains to study the integration of the piezoelectric micro-pump in the microfluidic platform features to explore and evaluate the performance of these new micro devices. In this work, we propose a new micro-pump model based on piezoelectric actuation with a new design. Here, we use a finite element model with Comsol software. Our device is composed of two pumping chambers, two diaphragms and two actuators (piezoelectric disks). The latter parts will apply a mechanical force on the membrane in a periodic manner. The membrane deformation allows the fluid pumping, the suction and discharge of the liquid. In this study, we present the modeling results as function as device geometry properties, films thickness, and materials properties. Here, we demonstrate that we can achieve fast injection. The results of these simulations will provide quantitative performance of our micro-pumps. Concern the spatial actuation, fluid rate and allows optimization of the fabrication process in terms of materials and integration steps.

Keywords: COMSOL software, piezoelectric, micro-pump, microfluidic

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Authors: Chia-Wen Wang, Patou Masika Musumari, Teeranee Techasrivichien, S. Pilar Suguimoto, Chang-Chuan Chan, Masako Ono-Kihara, Masahiro Kihara

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Background: In recent years, a particular form of bullying, referred to as 'cyberbullying' has emerged along with the rapid expansion of the Internet, social network services (SNSs) and smart phones. Many Asian countries, including Taiwan, are faced with both the cyberbullying and the traditional form of bullying. This study aims to explore Taiwanese adolescents’ experiences, perceptions and opinions regarding cyberbullying and traditional bullying through the perspective of victim, perpetrator, or witness. Method: This is a qualitative study using face-to-face in-depth interviews guided by a semi-structured questionnaire among high school students -aged 16 to 18 years- in Taipei, Taiwan. The participants were recruited through convenience sampling from five high schools between June and November 2016. Interviews were digitally recorded, transcribed, and analyzed using the thematic analysis approach. Results: Forty-eight participants were recruited, of which, 14 (29.2%) reported had ever experienced bullying. Specifically, 7 participants (14.6%) reported had ever been victims of cyberbullying, 1 (2%) had been victims of traditional bullying, and 6 (12.5%) had been victims of both cyber and traditional bullying. The majority (70.8%) reported had ever witnessed acts of bullying; however, none of the participants recognized had ever been a perpetrator of bullying. Cyberbullying mostly happens on social media (Facebook and Instagram) or LINE instant messaging application, and included upload and sharing of degrading pictures and videos of victims, as well as gossip and mean messages by the perpetrators. The anonymous and public nature of social media groups in schools made it easier to perpetrate bullying. The victim of traditional bullying reported being the target of verbal attack because of his physical appearance. Regardless of the type of bullying, victims reported feeling bad, angry, or depressed as a result of being bullied. Witnesses of both cyber- and traditional bullying cited physical appearance (e.g. having the big/flat bust or big butt, or overweight or obese) and disability as the most reasons of being a bullying victim. Conclusion: Both cyberbullying and traditional bullying had negative emotional and psychological impacts on victims. This study warrants further research to assess the extent of this phenomenon and understand the characteristics of perpetrators, victims, and witnesses to inform the design of tailored interventions using appropriate channels of dissemination.

Keywords: cyberbullying, traditional bullying, social media, adolescents

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Authors: Sven Borén, Lisiana Nurhadi, Henrik Ny

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From a theoretical perspective, electric buses can be more sustainable and can be cheaper than fossil fuelled buses in city traffic. The authors have not found other studies based on actual urban public transport in Swedish winter climate. Further on, noise measurements from buses for the European market were found old. The aims of this follow-up study was therefore to test and possibly verify in a real-life environment how energy efficient and silent electric buses are, and then conclude on if electric buses are preferable to use in public transport. The Ebusco 2.0 electric bus, fitted with a 311 kWh battery pack, was used and the tests were carried out during November 2014-April 2015 in eight municipalities in the south of Sweden. Six tests took place in urban traffic and two took place in more of a rural traffic setting. The energy use for propulsion was measured via logging of the internal system in the bus and via an external charging meter. The average energy use turned out to be 8% less (0,96 kWh/km) than assumed in the earlier theoretical study. This rate allows for a 320 km range in public urban traffic. The interior of the bus was kept warm by a diesel heater (biodiesel will probably be used in a future operational traffic situation), which used 0,67 kWh/km in January. This verified that electric buses can be up to 25% cheaper when used in public transport in cities for about eight years. The noise was found to be lower, primarily during acceleration, than for buses with combustion engines in urban bus traffic. According to our surveys, most passengers and drivers appreciated the silent and comfortable ride and preferred electric buses rather than combustion engine buses. Bus operators and passenger transport executives were also positive to start using electric buses for public transport. The operators did however point out that procurement processes need to account for eventual risks regarding this new technology, along with personnel education. The study revealed that it is possible to establish a charging infrastructure for almost all studied bus lines. However, design of a charging infrastructure for each municipality requires further investigations, including electric grid capacity analysis, smart location of charging points, and tailored schedules to allow fast charging. In conclusion, electric buses proved to be a preferable alternative for all stakeholders involved in public bus transport in the studied municipalities. However, in order to electric buses to be a prominent support for sustainable development, they need to be charged either by stand-alone units or via an expansion of the electric grid, and the electricity should be made from new renewable sources.

Keywords: sustainability, electric, bus, noise, greencharge

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Authors: Kedar J. Mahadeshwar

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Concept introduction: This paper talks about how an innovative cloud based analytics enabled solution that could address a major industry challenge that is approaching all of us globally faster than what one would think. The world of supply chain for drugs and devices is changing today at a rapid speed. In the US, the Drug Supply Chain Security Act (DSCSA) is a new law for Tracing, Verification and Serialization phasing in starting Jan 1, 2015 for manufacturers, repackagers, wholesalers and pharmacies / clinics. Similarly we are seeing pressures building up in Europe, China and many countries that would require an absolute traceability of every drug and device end to end. Companies (both manufacturers and distributors) can use this opportunity not only to be compliant but to differentiate themselves over competition. And moreover a country such as UAE can be the leader in coming up with a global solution that brings innovation in this industry. Problem definition and timing: The problem of counterfeit drug market, recognized by FDA, causes billions of dollars loss every year. Even in UAE, the concerns over prevalence of counterfeit drugs, which enter through ports such as Dubai remains a big concern, as per UAE pharma and healthcare report, Q1 2015. Distribution of drugs and devices involves multiple processes and systems that do not talk to each other. Consumer confidence is at risk due to this lack of traceability and any leading provider is at risk of losing its reputation. Globally there is an increasing pressure by government and regulatory bodies to trace serial numbers and lot numbers of every drug and medical devices throughout a supply chain. Though many of large corporations use some form of ERP (enterprise resource planning) software, it is far from having a capability to trace a lot and serial number beyond the enterprise and making this information easily available real time. Solution: The solution here talks about a service provider that allows all subscribers to take advantage of this service. The solution allows a service provider regardless of its physical location, to host this cloud based traceability and analytics solution of millions of distribution transactions that capture lots of each drug and device. The solution platform will capture a movement of every medical device and drug end to end from its manufacturer to a hospital or a doctor through a series of distributor or retail network. The platform also provides advanced analytics solution to do some intelligent reporting online. Why Dubai? Opportunity exists with huge investment done in Dubai healthcare city also with using technology and infrastructure to attract more FDI to provide such a service. UAE and countries similar will be facing this pressure from regulators globally in near future. But more interestingly, Dubai can attract such innovators/companies to run and host such a cloud based solution and become a hub of such traceability globally.

Keywords: cloud, pharmaceutical, supply chain, tracking

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Authors: Temitayo Tosin Alawiye

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Plant disease control is important in maintaining plant vigour, grain quantity, abundance of food, feed, and fibre produced by farmers all over the world. Farmers make use of different methods in controlling these diseases but one of the commonly used method is the use of chemicals. However, the continuous and excessive usages of these agrochemicals pose a danger to the environment, man and wildlife. The more the population growth the more the food security challenge which leads to more pressure on agronomic growth. Agricultural waste also known as green waste are the residues from the growing and processing of raw agricultural products such as fruits, vegetables, rice husk, corn cob, mushroom growth medium waste, coconut husk. They are widely used in land bioremediation, crop production and protection which include disease control. These agricultural wastes help the crop by improving the soil fertility, increase soil organic matter and reduce in many cases incidence and severity of disease. The objective was to review the agricultural waste that has worked effectively against certain soil-borne diseases such as Fusarium oxysporum, Pythiumspp, Rhizoctonia spp so as to help minimize the use of chemicals. Climate change is a major problem of agriculture and vice versa. Climate change and agriculture are interrelated. Change in climatic conditions is already affecting agriculture with effects unevenly distributed across the world. It will increase the risk of food insecurity for some vulnerable groups such as the poor in Sub Saharan Africa. The food security challenge will become more difficult as the world will need to produce more food estimated to feed billions of people in the near future with Africa likely to be the biggest hit. In order to surmount this hurdle, smallholder farmers in Africa must embrace climate-smart agricultural techniques and innovations which includes the use of green waste in agriculture, conservative agriculture, pasture and manure management, mulching, intercropping, etc. Training and retraining of smallholder farmers on the use of green energy to mitigate the effect of climate change should be encouraged. Policy makers, academia, researchers, donors, and farmers should pay more attention to the use of green energy as a way of reducing incidence and severity of soilborne plant diseases to solve looming food security challenges.

Keywords: agricultural waste, climate change, green energy, soil borne plant disease

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Authors: Hamed Ahari, Behrouz Akbari Adreghani, Vadood Razavilar, Amirali Anvar, Sima Moradi, Hourieh Shalchi

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Considering the ever increasing population and industrialization of the developmental trend of humankind's life, we are no longer able to detect the toxins produced in food products using the traditional techniques. This is due to the fact that the isolation time for food products is not cost-effective and even in most of the cases, the precision in the practical techniques like the bacterial cultivation and other techniques suffer from operator errors or the errors of the mixtures used. Hence with the advent of nanotechnology, the design of selective and smart sensors is one of the greatest industrial revelations of the quality control of food products that in few minutes time, and with a very high precision can identify the volume and toxicity of the bacteria. Methods and Materials: In this technique, based on the bacterial antibody connection to nanoparticle, a sensor was used. In this part of the research, as the basis for absorption for the recognition of bacterial toxin, medium sized silica nanoparticles of 10 nanometer in form of solid powder were utilized with Notrino brand. Then the suspension produced from agent-linked nanosilica which was connected to bacterial antibody was positioned near the samples of distilled water, which were contaminated with Staphylococcus aureus bacterial toxin with the density of 10-3, so that in case any toxin exists in the sample, a connection between toxin antigen and antibody would be formed. Finally, the light absorption related to the connection of antigen to the particle attached antibody was measured using spectrophotometry. The gene of 23S rRNA that is conserved in all Staphylococcus spp., also used as control. The accuracy of the test was monitored by using serial dilution (l0-6) of overnight cell culture of Staphylococcus spp., bacteria (OD600: 0.02 = 107 cell). It showed that the sensitivity of PCR is 10 bacteria per ml of cells within few hours. Result: The results indicate that the sensor detects up to 10-4 density. Additionally, the sensitivity of the sensors was examined after 60 days, the sensor by the 56 days had confirmatory results and started to decrease after those time periods. Conclusions: Comparing practical nano biosensory to conventional methods like that culture and biotechnology methods(such as polymerase chain reaction) is accuracy, sensitiveness and being unique. In the other way, they reduce the time from the hours to the 30 minutes.

Keywords: exotoxin, nanobiosensor, recognition, Staphylococcus aureus

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Authors: Boris Barbolyas, Kristina Buckova, Tomas Volensky, Cyril Belavy, Ladislav Dedik

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Background: Based on statokinezigram, the human balance control is often studied. Approach to human postural reaction analysis is based on a combination of stabilometry output signal with retroreflective marker data signal processing, analysis, and understanding, in this study. The study shows another original application of Method of Developed Statokinesigram Trajectory (MDST), too. Methods: In this study, the participants maintained quiet bipedal standing for 10 s on stabilometry platform. Consequently, bilateral vibration stimuli to Achilles tendons in 20 s interval was applied. Vibration stimuli caused that human postural system took the new pseudo-steady state. Vibration frequencies were 20, 60 and 80 Hz. Participant's body segments - head, shoulders, hips, knees, ankles and little fingers were marked by 12 retroreflective markers. Markers positions were scanned by six cameras system BTS SMART DX. Registration of their postural reaction lasted 60 s. Sampling frequency was 100 Hz. For measured data processing were used Method of Developed Statokinesigram Trajectory. Regression analysis of developed statokinesigram trajectory (DST) data and retroreflective marker developed trajectory (DMT) data were used to find out which marker trajectories most correlate with stabilometry platform output signals. Scaling coefficients (λ) between DST and DMT by linear regression analysis were evaluated, too. Results: Scaling coefficients for marker trajectories were identified for all body segments. Head markers trajectories reached maximal value and ankle markers trajectories had a minimal value of scaling coefficient. Hips, knees and ankles markers were approximately symmetrical in the meaning of scaling coefficient. Notable differences of scaling coefficient were detected in head and shoulders markers trajectories which were not symmetrical. The model of postural system behavior was identified by MDST. Conclusion: Value of scaling factor identifies which body segment is predisposed to postural instability. Hypothetically, if statokinesigram represents overall human postural system response to vibration stimuli, then markers data represented particular postural responses. It can be assumed that cumulative sum of particular marker postural responses is equal to statokinesigram.

Keywords: center of pressure (CoP), method of developed statokinesigram trajectory (MDST), model of postural system behavior, retroreflective marker data

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Authors: Elena Pucci, Margherita Tufarelli, Leonardo Giliberti

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As central for human and social development of the future, sustainability is becoming a recurring theme also in the fashion industry, where the need to explore new possible directions aimed at achieving sustainability goals and their communication is rising. Scholars have been devoted to the overall environmental impact of the textile and fashion industry, which, emerging as one of the world’s most polluting, today concretely assumes the need to take the path of sustainability in both products and production processes. Every day we witness the impact of our consumption, showing that the sustainability concept is as vast as complex: with a sometimes ambiguous definition, sustainability can concern projects, products, companies, sales, packagings, supply chains in relation to the actors proximity as well as traceability, raw materials procurement, and disposal. However, in its primary meaning, sustainability is the ability to maintain specific values and resources for future generations. The contribution aims to address sustainability in the fashion system as a layered problem that requires substantial changes at different levels: in the fashion product (materials, production processes, timing, distribution, and disposal), in the functioning of the system (life cycle, impact, needs, communication) and last but not least in the practice of fashion design which should conceive durable, low obsolescence and possibly demountable products. Moreover, consumers play a central role for the growing awareness, together with an increasingly strong sensitivity towards the environment and sustainable clothing. Since it is also a market demand, undertaking significant efforts to achieve total transparency and sustainability in all production and distribution processes is becoming fundamental for the fashion system. Sustainability is not to be understood as purely environmental but as the pursuit of collective well-being in relation to conscious production, human rights, and social dignity with the aim to achieve intelligent, resource, and environmentally friendly production and consumption patterns. Assuming sustainability as a layered problem makes the role of communication crucial to convey scientific or production specific content so that people can obtain and interpret information to make related decisions. Hence, if it is true that “what designers make becomes the future we inhabit'', design is facing great and challenging responsibility. The fashion industry needs a system of rules able to assess the sustainability of products, which is transparent and easily interpreted by consumers, identifying and enhancing virtuous practices. There are still complex and fragmented value chains that make it extremely difficult for brands and manufacturers to know the history of their products, to identify exactly where the risks lie, and to respond to the growing demand from consumers and civil society for responsible and sustainable production practices in the fashion industry.

Keywords: fashion design, fashion system, sustainability, communication, complexity

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Authors: Ohud Adnan Saffar

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This study aims to know the effect of using universal design for learning (UDL) to improve the quality of vocational programme with intellectual disabilities (SID) and the challenges facing this method from the teachers' point of view. The significance of the study: There are comparatively few published studies on UDL in emerging nations. Therefore, this study will encourage the researchers to consider a new approaches teaching. Development of this study will contribute significant information on the cognitively disabled community on a universal scope. In order to collect and evaluate the data and for the verification of the results, this study has been used the mixed research method, by using two groups comparison method. To answer the study questions, we were used the questionnaire, lists of observations, open questions, and pre and post-test. Thus, the study explored the advantages and drawbacks, and know about the impact of using the UDL method on integrating SID with students non-special education needs in the same classroom. Those aims were realized by developing a workshop to explain the three principles of the UDL and train (16) teachers in how to apply this method to teach (12) students non-special education needs and the (12) SID in the same classroom, then take their opinion by using the questionnaire and questions. Finally, this research will explore the effects of the UDL on the teaching of professional photography skills for the SID in Saudi Arabia. To achieve this goal, the research method was a comparison of the performance of the SID using the UDL method with that of female students with the same challenges applying other strategies by teachers in control and experiment groups, we used the observation lists, pre and post-test. Initial results: It is clear from the previous response to the participants that most of the answers confirmed that the use of UDL achieves the principle of inclusion between the SID and students non-special education needs by 93.8%. In addition, the results show that the majority of the sampled people see that the most important advantages of using UDL in teaching are creating an interactive environment with using new and various teaching methods, with a percentage of 56.2%. Following this result, the UDL is useful for integrating students with general education, with a percentage of 31.2%. Moreover, the finding indicates to improve understanding through using the new technology and exchanging the primitive ways of teaching with the new ones, with a percentage of 25%. The result shows the percentages of the sampled people's opinions about the financial obstacles, and it concluded that the majority see that the cost is high and there is no computer maintenance available, with 50%. There are no smart devices in schools to help in implementing and applying for the program, with a percentage of 43.8%.

Keywords: universal design for learning, intellectual disabilities, vocational programme, the challenges facing this method

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Authors: Ali H. Daraji, Jack M. Hale, Ye Jianqiao

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With the extensive use of high specific strength structures to optimise the loading capacity and material cost in aerospace and most engineering applications, much effort has been expended to develop intelligent structures for active vibration reduction and structural health monitoring. These structures are highly flexible, inherently low internal damping and associated with large vibration and long decay time. The modification of such structures by adding lightweight piezoelectric sensors and actuators at efficient locations integrated with an optimal control scheme is considered an effective solution for structural vibration monitoring and controlling. The size and location of sensor and actuator are important research topics to investigate their effects on the level of vibration detection and reduction and the amount of energy provided by a controller. Several methodologies have been presented to determine the optimal location of a limited number of sensors and actuators for small-scale structures. However, these studies have tackled this problem directly, measuring the fitness function based on eigenvalues and eigenvectors achieved with numerous combinations of sensor/actuator pair locations and converging on an optimal set using heuristic optimisation techniques such as the genetic algorithms. This is computationally expensive for small- and large-scale structures subject to optimise a number of s/a pairs to suppress multiple vibration modes. This paper proposes an efficient method to determine optimal locations for a limited number of sensor/actuator pairs for active vibration reduction of a flexible structure based on finite element method and Hamilton’s principle. The current work takes the simplified approach of modelling a structure with sensors at all locations, subjecting it to an external force to excite the various modes of interest and noting the locations of sensors giving the largest average percentage sensors effectiveness measured by dividing all sensor output voltage over the maximum for each mode. The methodology was implemented for a cantilever plate under external force excitation to find the optimal distribution of six sensor/actuator pairs to suppress the first six modes of vibration. It is shown that the results of the optimal sensor locations give good agreement with published optimal locations, but with very much reduced computational effort and higher effectiveness. Furthermore, it is shown that collocated sensor/actuator pairs placed in these locations give very effective active vibration reduction using optimal linear quadratic control scheme.

Keywords: optimisation, plate, sensor effectiveness, vibration control

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