Search results for: carbon nanotubes network

Authors: Dina Mohamed Ayman, Rafieu Akin

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In an attempt to increase the female total entrepreneurial activities (TEA) within Egypt and Nigeria, this paper aims to investigate the challenges facing female entrepreneurs operating in Egypt, in relative to Nigeria. In this regard, both researchers undertook a qualitative approach due to the scarcity of the literature reviewed on the topic; in those particular countries, and as an in-depth comparative mode. Therefore, ten Egyptian entrepreneurs in relative to ten Nigerian entrepreneurs were in-depth investigated. The research findings prove that female entrepreneurs face complex problems for being both gender and country-specific. Regarding the gender-specific obstacles, the work/life imbalance due to the scarcity of child-care nurseries and the prevalence of the gender-role division while performing the house chores rather than the concept of co-operation, acted as a main source of cultural challenge because women are considered mostly as 'housewives'. However, interestingly, this specific gender-discrimination challenge is proven to have no grounded effect in terms of the business-establishment and daily dealings neither in Egypt nor Nigeria, as one of the sample exclaimed 'as long as you pay, then no gender difference is set on the table'. Other country-specific challenges facing female entrepreneurs, lied in, the aggregate weak entrepreneurial framework governing both countries, also, women faced the difficulty of access to financial institutions with collateral requirements that are usually "hardly to be met", besides, the absence of the "micro-credit-Grameen-banks" concept. As well, the scarcity of incubators and business training centers providing network, consultancy and well-trained workforce to female entrepreneurs constitute a major hurdle for women entrepreneurs operating in both countries. Finally, this paper will conclude the research by offering a set of public-policy recommendations to pave the way for females to choose self-employment as a career path.

Keywords: entrepreneurship, female entrepreneurship, obstacles, framework conditions, culture, micro-credit

Procedia PDF Downloads 372

Authors: Zhihao Peng, Qiong Zhang, Xiyao Li, Yongzhen Peng

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Nowadays, conventional nitrogen removal process (nitrification and denitrification) was adopted in most wastewater treatment plants, but many problems have occurred, such as: high aeration energy consumption, extra carbon sources dosage and high sludge treatment costs. The emergence of anammox has bring about the great revolution to the nitrogen removal technology, and only the ammonia and nitrite were required to remove nitrogen autotrophically, no demand for aeration and sludge treatment. However, there existed many challenges in anammox applications: difficulty of biomass retention, insufficiency of nitrite substrate, damage from complex organic etc. Much effort was put into the research in overcoming the above challenges, and the payment was rewarded. It was also imperative to establish an innovative process that can settle the above problems synchronously, after all any obstacle above mentioned can cause the collapse of anammox system. Therefore, in this study, a two-stage process was established that the sequencing batch reactor (SBR) and upflow anaerobic sludge blanket (UASB) were used in the pre-stage and post-stage, respectively. The domestic wastewater entered into the SBR first and went through anaerobic/aerobic/anoxic (An/O/A) mode, and the draining at the aerobic end of SBR was mixed with domestic wastewater, the mixture then entering to the UASB. In the long term, organic and nitrogen removal performance was evaluated. All along the operation, most COD was removed in pre-stage (COD removal efficiency > 64.1%), including some macromolecular organic matter, like: tryptophan, tyrosinase and fulvic acid, which could weaken the damage of organic matter to anammox. And the An/O/A operating mode of SBR was beneficial to the achievement and maintenance of partial nitrification (PN). Hence, sufficient and steady nitrite supply was another favorable condition to anammox enhancement. Besides, the flexible mixing ratio helped to gain a substrate ratio appropriate to anammox (1.32-1.46), which further enhance the anammox. Further, the UASB was used and gas recirculation strategy was adopted in the post-stage, aiming to achieve granulation by the selection pressure. As expected, the granules formed rapidly during 38 days, which increased from 153.3 to 354.3 μm. Based on bioactivity and gene measurement, the anammox metabolism and abundance level rose evidently, by 2.35 mgN/gVss·h and 5.3 x109. The anammox bacteria mainly distributed in the large granules (>1000 μm), while the biomass in the flocs (<200 μm) and microgranules (200-500 μm) barely displayed anammox bioactivity. Enhanced anammox promoted the advanced autotrophic nitrogen removal, which increased from 71.9% to 93.4%, even when the temperature was only 12.9 ℃. Therefore, it was feasible to enhance anammox in the multiple favorable conditions created, and the strategy extended the application of anammox to the full-scale mainstream, enhanced the understanding of anammox in the aspects of culturing conditions.

Keywords: anammox, granules, nitrite accumulation, nitrogen removal efficiency

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Authors: Ana Hol

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We live in a constantly changing environment where technology has become an integral component of our day to day life. We rely heavily on mobile devices, we search for data via web, we utilise smart home sensors to create the most suited ambiences and we utilise applications to shop, research, communicate and share data. Heavy reliance on technology therefore is creating new connections between STEM (Science, Technology, Engineering and Mathematics) fields which in turn rises a question of what the STEM education of the future should be like? This study was based on the reviews of the six Australian Information Systems students who undertook an international study tour to India where they were given an opportunity to network, communicate and meet local students, staff and business representatives and from them learn about the local business implementations, local customs and regulations. Research identifies that if we are to continue to implement and utilise electronic devices on the global scale, such as for example implement smart cars that can smoothly cross borders, we will need the workforce that will have the knowledge about the cars themselves, their parts, roads and transport networks, road rules, road sensors, road monitoring technologies, graphical user interfaces, movement detection systems as well as day to day operations, legal rules and regulations of each region and country, insurance policies, policing and processes so that the wide array of sensors can be controlled across country’s borders. In conclusion, it can be noted that allowing students to learn about the local conditions, roads, operations, business processes, customs and values in different countries is giving students a cutting edge advantage as such knowledge cannot be transferred via electronic sources alone. However once understanding of each problem or project is established, multidisciplinary innovative STEM projects can be smoothly conducted.

Keywords: STEM, curiosity, innovation, advancements

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Authors: Trevor Malambo Simbayi, Diane Hildebrandt, Tonderayi Matambo

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The rapid growth of population in recent decades has resulted in an increased need for energy to meet human activities. As energy demands increase, the need for other sources of energy other than fossil fuels, increases in turn. Furthermore, environmental concerns such as global warming due to the use of fossil fuels, depleting fossil fuel reserves and the rising cost of oil have contributed to an increased interest in renewables sources of energy. Biogas is a renewable source of energy produced through the process of anaerobic digestion (AD) and it offers a two-fold solution; it provides an environmentally friendly source of energy and its production helps to reduce the amount of organic waste taken to landfills. This research seeks to address the waste management problem caused by an aquatic weed called water hyacinth (Eichhornia crassipes) at the Hartbeespoort (Harties) Dam in the North West Province of South Africa, through biogas production of the weed. Water hyacinth is a category 1 invasive species and it is deemed to be the most problematic aquatic weed. This weed is said to double its size in the space of five days. Eutrophication in the Hartbeespoort Dam has manifested itself through the excessive algae bloom and water hyacinth infestation. A large amount of biomass from water hyacinth and algae are generated per annum from the two hundred hectare surface area of the dam exposed to the sun. This biomass creates a waste management problem. Water hyacinth when in full bloom can cover nearly half of the surface of Hartbeespoort Dam. The presence of water hyacinth in the dam has caused economic and environmental problems. Economic activities such as fishing, boating, and recreation, are hampered by the water hyacinth’s prolific growth. This research proposes the use of water hyacinth as a feedstock or substrate for biogas production in order to find an economic and environmentally friendly means of waste management for the communities living around the Hartbeespoort Dam. In order to achieve this objective, water hyacinth will be collected from the dam and it will be mechanically pretreated before anaerobic digestion. Pretreatment is required for lignocellulosic materials like water hyacinth because such materials are called recalcitrant solid materials. Cow manure will be employed as a source of microorganisms needed for biogas production to occur. Once the water hyacinth and the cow dung are mixed, they will be placed in laboratory anaerobic reactors. Biogas production will be monitored daily through the downward displacement of water. Characterization of the substrates (cow manure and water hyacinth) to determine the nitrogen, sulfur, carbon and hydrogen, total solids (TS) and volatile solids (VS). Liquid samples from the anaerobic digesters will be collected and analyzed for volatile fatty acids (VFAs) composition by means of a liquid gas chromatography machine.

Keywords: anaerobic digestion, biogas, waste management, water hyacinth

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Authors: N. Nalini, Bhanu Prakash Gopularam

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The term data security refers to the degree of resistance or protection given to information from unintended or unauthorized access. The core principles of information security are the confidentiality, integrity and availability, also referred as CIA triad. Cloud computing services are classified as SaaS, IaaS and PaaS services. With cloud adoption the confidential enterprise data are moved from organization premises to untrusted public network and due to this the attack surface has increased manifold. Several cloud computing platforms like OpenStack, Eucalyptus, Amazon EC2 offer users to build and configure public, hybrid and private clouds. While the traditional encryption based on PKI infrastructure still works in cloud scenario, the management of public-private keys and trust certificates is difficult. The Identity based Public Key Cryptography (also referred as ID-PKC) overcomes this problem by using publicly identifiable information for generating the keys and works well with decentralized systems. The users can exchange information securely without having to manage any trust information. Another advantage is that access control (role based access control policy) information can be embedded into data unlike in PKI where it is handled by separate component or system. In OpenStack cloud platform the keystone service acts as identity service for authentication and authorization and has support for public key infrastructure for auto services. In this paper, we explain OpenStack security architecture and evaluate the PKI infrastructure piece for data confidentiality. We provide method to integrate ID-PKC schemes for securing data while in transit and stored and explain the key measures for safe guarding data against security attacks. The proposed approach uses JPBC crypto library for key-pair generation based on IEEE P1636.3 standard and secure communication to other cloud services.

Keywords: data confidentiality, identity based cryptography, secure communication, open stack key stone, token scoping

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Authors: Obed Asamoah

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Forests are very vital for human survival and our well-being. During the past years, the world has taken an increasingly significant role in the modification of the global environment. The high rate of deforestation in Ghana is of primary national concern as the forests provide many ecosystem services and functions that support the country’s predominantly agrarian economy and foreign earnings. Ghana forest is currently major source of carbon sink that helps to mitigate climate change. Ghana forests, both the reserves and off-reserves, are under pressure of deforestation. The causes of deforestation are varied but can broadly be categorized into anthropogenic and natural factors. For the anthropogenic factors, increased wood fuel collection, clearing of forests for agriculture, illegal and poorly regulated timber extraction, social and environmental conflicts, increasing urbanization and industrialization are the primary known causes for the loss of forests and woodlands. Mineral exploitation in the forest areas is considered as one of the major causes of deforestation in Ghana. Mining activities especially mining of gold by both the licensed mining companies and illegal mining groups who are locally known as "gallantly mining" also cause damage to the nation's forest reserves. Several works have been conducted regarding the causes of the high rate of deforestation in Ghana, major attention has been placed on illegal logging and using forest lands for illegal farming and mining activities. Less emphasis has been placed on the timber production companies on their harvesting methods in the forests in Ghana and other activities that are carried out in the forest. The main objective of the work is to find out the harvesting methods and the activities of the timber production companies and their effects on the forests in Ghana. Both qualitative and quantitative research methods were engaged in the research work. The study population comprised of 20 Timber industries (Sawmills) forest areas of Ghana. These companies were selected randomly. The cluster sampling technique was engaged in selecting the respondents. Both primary and secondary data were employed. In the study, it was observed that most of the timber production companies do not know the age, the weight, the distance covered from the harvesting to the loading site in the forest. It was also observed that old and heavy machines are used by timber production companies in their operations in the forest, which makes the soil compact prevents regeneration and enhances soil erosion. It was observed that timber production companies do not abide by the rules and regulations governing their operations in the forest. The high rate of corruption on the side of the officials of the Ghana forestry commission makes the officials relax and do not embark on proper monitoring on the operations of the timber production companies which makes the timber companies to cause more harm to the forest. In other to curb this situation the Ghana forestry commission with the ministry of lands and natural resources should monitor the activities of the timber production companies and sanction all the companies that make foul play in their activities in the forest. The commission should also pay more attention to the policy “fell one plant 10” to enhance regeneration in both reserves and off-reserves forest.

Keywords: companies, deforestation, forest, Ghana, timber

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Authors: Vedat Uyak

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Seasonal variations of trihalomethanes (THMs) and haloacetic acids (HAAs) concentrations were investigated within three distribution systems of a coastal city of Istanbul, Turkey. Moreover, total trihalomethanes and other organics concentration were also analyzed. The investigation was based on an intensive 16 month (2009-2010) sampling program, undertaken during the spring, summer, fall and winter seasons. Four THM (chloroform, dichlorobromomethane, chlorodibromomethane, bromoform), and nine HAA (the most commonly occurring one being dichloroacetic acid (DCAA) and trichloroacetic acid (TCAA); other compounds are monochloroacetic acid (MCAA), monobromoacetic acid (MBAA), dibromoacetic acid (DBAA), tribromoacetic acid (TBAA), bromochloroacetic acid (BCAA), bromodichloroacetic acid (BDCAA) and chlorodibromoacetic acid (CDBAA)) species and other water quality and operational parameters were monitored at points along the distribution system between the treatment plant and the system’s extremity. The effects of coastal water sources, seasonal variation and spatial variation were examined. The results showed that THMs and HAAs concentrations vary significantly between treated waters and water at the distribution networks. When water temperature exceeds 26°C in summer, the THMs and HAAs levels are 0.8 – 1.1, and 0.4 – 0.9 times higher than treated water, respectively. While when water temperature is below 12°C in the winter, the measured THMs and HAAs concentrations at the system’s extremity were very rarely higher than 100 μg/L, and 60 μg/L, respectively. The highest THM concentrations occurred in the Buyukcekmece distribution system, with an average total HAA concentration of 92 μg/L. Moreover, the lowest THM levels were observed in the Omerli distribution network, with a mean concentration of 7 μg/L. For HAA levels, the maximum concentrations again were observed in the Buyukcekmece distribution system, with an average total HAA concentration of 57 μg/l. High spatial and seasonal variation of disinfection by-products in the drinking water of Istanbul was attributed of illegal wastewater discharges to water supplies of Istanbul city.

Keywords: disinfection byproducts, drinking water, trihalomethanes, haloacetic acids, seasonal variation

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Authors: Daniel Monsalve, Takafumi Noguchi

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Mycelium-based composites (MBC) are made by growing living mycelium on lignocellulosic fibres to create a porous composite material which can be lightweight, and biodegradable, making them suitable as a sustainable thermal insulation. Thus, they can help to reduce material extraction while improving the energy efficiency of buildings, especially when agricultural by-products are used. However, as MBC are hygroscopic materials, moisture can reduce their thermal insulation efficiency. It is known that surface growth, or “mycelium skin”, can form a natural coating due to the hydrophobic properties in the mycelium cell wall. Therefore, this research aims to biofabricate a homogeneous mycelium skin and measure its influence on the final composite material by testing material properties such as thermal conductivity, vapour permeability and water absorption by partial immersion over 24 hours. In addition, porosity, surface morphology and chemical composition were also analyzed. The white-rot fungi species Pleurotus ostreatus, Ganoderma lucidum, and Trametes versicolor were grown on 10 mm hemp fibres (Cannabis sativa), and three different biofabrication protocols were used during incubation, varying the time and surface treatment, including the addition of pre-colonised sawdust. The results indicate that density can be reduced by colonisation time, which will favourably impact thermal conductivity but will negatively affect vapour and liquid water control. Additionally, different fungi can exhibit different resistance to prolonged water absorption, and due to osmotic sensitivity, mycelium skin may also diminish moisture control. Finally, a collapse in the mycelium network after water immersion was observed through SEM, indicating how the microstructure is affected, which is also dependent on fungi species and the type of skin achieved. These results help to comprehend the differences and limitations of three of the most common species used for MBC fabrication and how precise engineering is needed to effectively control the material output.

Keywords: mycelium, thermal conductivity, vapor permeability, water absorption

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Authors: Soumyadeep Bhaduri, Rahul Ghosh, Rahul Shukla, Manaswini Behera

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The textile industry consumes a substantial amount of water throughout the processing and production of textile fabrics. The water eventually turns into wastewater, where it acts as an immense damaging nuisance due to its dye content. Wastewater streams contain a percentage ranging from 2.0% to 50.0% of the total weight of dye used, depending on the dye class. The management of dye effluent in textile industries presents a formidable challenge to global sustainability. The current focus is on implementing wastewater treatment technology that enable the recycling of wastewater, reduce energy usage and offset carbon emissions. Microbial fuel cell (MFC) is a device that utilizes microorganisms as a bio-catalyst to effectively treat wastewater while also producing electricity. The MFC harnesses the chemical energy present in wastewater by oxidizing organic compounds in the anodic chamber and reducing an electron acceptor in the cathodic chamber, thereby generating electricity. This research investigates the potential of MFCs to tackle this challenge of azo dye removal with simultaneously generating electricity. Although MFCs are well-established for wastewater treatment, their application in dye decolorization with concurrent electricity generation remains relatively unexplored. This study aims to address this gap by assessing the effectiveness of MFCs as a sustainable solution for treating wastewater containing azo dyes. By harnessing microorganisms as biocatalysts, MFCs offer a promising avenue for environmentally friendly dye effluent management. The performance of MFCs in treating azo dyes and generating electricity was evaluated by optimizing the Chemical Oxygen Demand (COD) and Hydraulic Retention Time (HRT) of influent. COD and HRT values ranged from 1600 mg/L to 2400 mg/L and 5 to 9 days, respectively. Results showed that the maximum open circuit voltage (OCV) reached 648 mV at a COD of 2400 mg/L and HRT of 5 days. Additionally, maximum COD removal of 98% and maximum color removal of 98.91% were achieved at a COD of 1600 mg/L and HRT of 9 days. Furthermore, the study observed a maximum power density of 19.95 W/m3 at a COD of 2400 mg/L and HRT of 5 days. Electrochemical analysis, including linear sweep voltammetry (LSV), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were done to find out the response current and internal resistance of the system. To optimize pH and dye concentration, pH values were varied from 4 to 10, and dye concentrations ranged from 25 mg/L to 175 mg/L. The highest voltage output of 704 mV was recorded at pH 7, while a dye concentration of 100 mg/L yielded the maximum output of 672 mV. This study demonstrates that MFCs offer an efficient and sustainable solution for treating azo dyes in textile industry wastewater, while concurrently generating electricity. These findings suggest the potential of MFCs to contribute to environmental remediation and sustainable development efforts on a global scale.

Keywords: textile wastewater treatment, microbial fuel cell, renewable energy, sustainable wastewater treatment

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Authors: Said Benaissa, David Plets, Emmeric Tanghe, Jens Trogh, Luc Martens, Leen Vandaele, Annelies Van Nuffel, Frank A. M. Tuyttens, Bart Sonck, Wout Joseph

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The herd monitoring and managing - in particular the detection of ‘attention animals’ that require care, treatment or assistance is crucial for effective reproduction status, health, and overall well-being of dairy cows. In large sized farms, traditional methods based on direct observation or analysis of video recordings become labour-intensive and time-consuming. Thus, automatic monitoring systems using sensors have become increasingly important to continuously and accurately track the health status of dairy cows. Wireless sensor networks (WSNs) and internet-of-things (IoT) can be effectively used in health tracking of dairy cows to facilitate herd management and enhance the cow welfare. Since on-cow measuring devices are energy-constrained, a proper characterization of the off-body wireless channel between the on-cow sensor nodes and the back-end base station is required for a power-optimized deployment of these networks in barns. The aim of this study was to characterize the off-body wireless channel in indoor (barns) environment at 868 MHz using LoRa nodes. LoRa is an emerging wireless technology mainly targeted at WSNs and IoT networks. Both large scale fading (i.e., path loss) and temporal fading were investigated. The obtained path loss values as a function of the transmitter-receiver separation were well fitted by a lognormal path loss model. The path loss showed an additional increase of 4 dB when the wireless node was actually worn by the cow. The temporal fading due to movement of other cows was well described by Rician distributions with a K-factor of 8.5 dB. Based on this characterization, network planning and energy consumption optimization of the on-body wireless nodes could be performed, which enables the deployment of reliable dairy cow monitoring systems.

Keywords: channel, channel modelling, cow monitoring, dairy cows, health monitoring, IoT, LoRa, off-body propagation, PLF, propagation

Procedia PDF Downloads 319

Authors: Zsolt Kotroczó, Katalin Juhos, Áron Béni, Gábor Várbíró, Tamás Kocsis, István Fekete

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Soil organic matter plays an extremely important role in the functioning and regulation processes of ecosystems. It follows that the C content of organic matter in soil is one of the most important indicators of soil fertility. Part of the carbon stored in them is returned to the atmosphere during soil respiration. Climate change and inappropriate land use can accelerate these processes. Our work aimed to determine how soil CO2 emissions change over ten years as a result of organic matter manipulation treatments. With the help of this, we were able to examine not only the effects of the different organic matter intake but also the effects of the different microclimates that occur as a result of the treatments. We carried out our investigations in the area of the Síkfőkút DIRT (Detritus Input and Removal Treatment) Project. The research area is located in the southern, hilly landscape of the Bükk Mountains, northeast of Eger (Hungary). GPS coordinates of the project: 47°55′34′′ N and 20°26′ 29′′ E, altitude 320-340 m. The soil of the area is Luvisols. The 27-hectare protected forest area is now under the supervision of the Bükki National Park. The experimental plots in Síkfőkút were established in 2000. We established six litter manipulation treatments each with three 7×7 m replicate plots established under complete canopy cover. There were two types of detritus addition treatments (Double Wood and Double Litter). In three treatments, detritus inputs were removed: No Litter No Roots plots, No Inputs, and the Controls. After the establishment of the plots, during the drier periods, the NR and NI treatments showed the highest CO2 emissions. In the first few years, the effect of this process was evident, because due to the lack of living vegetation, the amount of evapotranspiration on the NR and NI plots was much lower, and transpiration practically ceased on these plots. In the wetter periods, the NL and NI treatments showed the lowest soil respiration values, which were significantly lower compared to the Co, DW, and DL treatments. Due to the lower organic matter content and the lack of surface litter cover, the water storage capacity of these soils was significantly limited, therefore we measured the lowest average moisture content among the treatments after ten years. Soil respiration is significantly influenced by temperature values. Furthermore, the supply of nutrients to the soil microorganisms is also a determining factor, which in this case is influenced by the litter production dictated by the treatments. In the case of dry soils with a moisture content of less than 20% in the initial period, litter removal treatments showed a strong correlation with soil moisture (r=0.74). In very dry soils, a smaller increase in moisture does not cause a significant increase in soil respiration, while it does in a slightly higher moisture range. In wet soils, the temperature is the main regulating factor, above a certain moisture limit, water displaces soil air from the soil pores, which inhibits aerobic decomposition processes, and so heterotrophic soil respiration also declines.

Keywords: soil biology, organic matter, nutrition, DIRT, soil respiration

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Authors: Stephen Dankwa, Zheng Wenfeng, Xiaolu Li

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Climate change is recently gaining the attention of many countries across the world. Climate change, which is also known as global warming, referring to the increasing in average surface temperature has been a concern to the Environmental Protection Agency of Ghana. Recently, Ghana has become vulnerable to the effect of the climate change as a result of the dependence of the majority of the population on agriculture. The clearing down of trees to grow crops and burning of charcoal in the country has been a contributing factor to the rise in temperature nowadays in the country as a result of releasing of carbon dioxide and greenhouse gases into the air. Recently, petroleum stations across the cities have been on fire due to this climate changes and which have position Ghana in a way not able to withstand this climate event. As a result, the significant of this research paper is to project how the rise in the average surface temperature will be like at the end of the mid-21st century when agriculture and deforestation are allowed to continue for some time in the country. This study uses the Coupled Modeled Intercomparison Project phase 5 (CMIP5) experiment RCP 8.5 model output data to monitor the future climate changes from 2041-2050, at the end of the mid-21st century over the ten (10) major cities (Accra, Bolgatanga, Cape Coast, Koforidua, Kumasi, Sekondi-Takoradi, Sunyani, Ho, Tamale, Wa) in Ghana. In the models, Support Vector Machine and Random forest, where the cities as a function of heat wave metrics (minimum temperature, maximum temperature, mean temperature, heat wave duration and number of heat waves) assisted to provide more than 50% accuracy to predict and monitor the pattern of the surface air temperature. The findings identified were that the near-surface air temperature will rise between 1°C-2°C (degrees Celsius) over the coastal cities (Accra, Cape Coast, Sekondi-Takoradi). The temperature over Kumasi, Ho and Sunyani by the end of 2050 will rise by 1°C. In Koforidua, it will rise between 1°C-2°C. The temperature will rise in Bolgatanga, Tamale and Wa by 0.5°C by 2050. This indicates how the coastal and the southern part of the country are becoming hotter compared with the north, even though the northern part is the hottest. During heat waves from 2041-2050, Bolgatanga, Tamale, and Wa will experience the highest mean daily air temperature between 34°C-36°C. Kumasi, Koforidua, and Sunyani will experience about 34°C. The coastal cities (Accra, Cape Coast, Sekondi-Takoradi) will experience below 32°C. Even though, the coastal cities will experience the lowest mean temperature, they will have the highest number of heat waves about 62. Majority of the heat waves will last between 2 to 10 days with the maximum 30 days. The surface temperature will continue to rise by the end of the mid-21st century (2041-2050) over the major cities in Ghana and so needs to be addressed to the Environmental Protection Agency in Ghana in order to mitigate this problem.

Keywords: climate changes, CMIP5, Ghana, heat waves, random forest, SVM

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Authors: L. V. S. S. Phaneendra Bolem, S. Shankar

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Low Volume Rural Roads (LVRRs) constitute an integral component of the road system in all countries. These encompass all aspects of the social and economic development of rural communities. It is known that on a worldwide basis the number of low traffic roads far exceeds the length of high volume roads. Across India, 90% of the roads are LVRRs, and they often form the most important link in terms of providing access to educational, medical, recreational and commercial activities in local and regional areas. In the recent past, Government of India (GoI), with the initiation of the ambitious programme namely 'Pradhan Mantri Gram Sadak Yojana' (PMGSY) gave greater importance to LVRRs realizing their role in economic development of rural communities. The vast expansion of the road network has brought connectivity to the rural areas of the country. Further, it is noticed that due to increasing axle loads and lack of timely maintenance, is accelerated the process of deterioration of LVRRs. In addition to this due to limited budget for maintenance of these roads systematic and scientific approach in utilizing the available resources has been necessitated. This would enable better prioritization and ranking for the maintenance and make ‘all-weather roads’. Taking this into account the present study has adopted a multi-criteria approach. The multi-criteria approach includes parameters such as social, economic, environmental and pavement condition as the main criterion and some sub-criteria to find the best suitable parameters and their weight. For this purpose the expert’s opinion survey was carried out using Delphi Technique (DT) considering Likert scale, pairwise comparison and ranking methods and entire data was analyzed. Finally, this study developed the maintenance criterion considering the socio-economic, environmental and pavement condition parameters for effective maintenance of low volume roads based on the engineering judgment.

Keywords: Delphi technique, experts opinion survey, low volume rural road maintenance, multi criteria analysis

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Authors: Ben Khayut, Lina Fabri, Maya Avikhana

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The models of the modern Artificial Narrow Intelligence (ANI) cannot: a) independently and continuously function without of human intelligence, used for retraining and reprogramming the ANI’s models, and b) think, understand, be conscious, cognize, infer, and more in state of Uncertainty, and changes in situations, and environmental objects. To eliminate these shortcomings and build a new generation of Artificial Intelligence systems, the paper proposes a Conception, Model, and Method of Computational Psycholinguistic Cognitive Situational-Fuzzy Self-Controlled Brain and Mind System (CPCSFSCBMSUU) using a neural network as its computational memory, operating under uncertainty, and activating its functions by perception, identification of real objects, fuzzy situational control, forming images of these objects, modeling their psychological, linguistic, cognitive, and neural values of properties and features, the meanings of which are identified, interpreted, generated, and formed taking into account the identified subject area, using the data, information, knowledge, and images, accumulated in the Memory. The functioning of the CPCSFSCBMSUU is carried out by its subsystems of the: fuzzy situational control of all processes, computational perception, identifying of reactions and actions, Psycholinguistic Cognitive Fuzzy Logical Inference, Decision making, Reasoning, Systems Thinking, Planning, Awareness, Consciousness, Cognition, Intuition, Wisdom, analysis and processing of the psycholinguistic, subject, visual, signal, sound and other objects, accumulation and using the data, information and knowledge in the Memory, communication, and interaction with other computing systems, robots and humans in order of solving the joint tasks. To investigate the functional processes of the proposed system, the principles of Situational Control, Fuzzy Logic, Psycholinguistics, Informatics, and modern possibilities of Data Science were applied. The proposed self-controlled System of Brain and Mind is oriented on use as a plug-in in multilingual subject Applications.

Keywords: computational brain, mind, psycholinguistic, system, under uncertainty

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Authors: Nathenal Thomas

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In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

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Authors: Tonghua Li

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Under the neoliberal corporate food regime, biofuels are a double-edged sword that exacerbates tensions between national food security and trade in green agricultural products. Biofuels have the potential to help achieve green sustainable development goals, but they threaten food security by exacerbating competition for land and changing global food trade patterns. The U.S.-China trade war complicates this debate. Under the influence of different political and corporate coordination mechanisms in China and the US, trade disputes can have different impacts on sustainable agricultural practices. This paper develops an actor-centred ‘network governance framework’ focusing on trade in soybean and corn-based biofuels to explain how trade wars can change the actions of governmental and non-governmental actors in the context of oligopolistic competition and market concentration in agricultural trade. There is evidence that the US-China trade decoupling exacerbates the conflict between national security, free trade in agriculture, and the realities and needs of green and sustainable energy development. The US government's trade policies reflect concerns about China's relative gains, leading to a loss of trade profits, making it impossible for the parties involved to find a balance between the three objectives and, consequently, to get into a biofuels and soybean industry dilemma. Within the setting of prioritizing national security and strategic interests, the government has replaced the dominant position of large agribusiness in the neoliberal food system, and the goal of environmental sustainability has been marginalized by high politics. In contrast, China faces tensions in the trade war between food security self-sufficiency policy and liberal sustainable trade, but the state-capitalist model ensures policy coordination and coherence in trade diversion and supply chain adjustment. Despite ongoing raw material shortages and technological challenges, China remains committed to playing a role in global environmental governance and promoting green trade objectives.

Keywords: food security, green trade, biofuels, soybeans, US-China trade war

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Authors: K. S. Vedasingha, K. K. M. T. Perera, K. I. Hathurusinghe, H. W. I. Akalanka, Nelum Chathuranga Amarasena, Nalaka R. Dissanayake

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Railways provide the most convenient and economically beneficial mode of transportation, and it has been the most popular transportation method among all. According to the past analyzed data, it reveals a considerable number of accidents which occurred at railways and caused damages to not only precious lives but also to the economy of the countries. There are some major issues which need to be addressed in railways of South Asian countries since they fall under the developing category. The goal of this research is to minimize the influencing aspect of railway level crossing accidents by developing the “railway process automation system”, as there are high-risk areas that are prone to accidents, and safety at these places is of utmost significance. This paper describes the implementation methodology and the success of the study. The main purpose of the system is to ensure human safety by using the Internet of Things (IoT) and image processing techniques. The system can detect the current location of the train and close the railway gate automatically. And it is possible to do the above-mentioned process through a decision-making system by using past data. The specialty is both processes working parallel. As usual, if the system fails to close the railway gate due to technical or a network failure, the proposed system can identify the current location and close the railway gate through a decision-making system, which is a revolutionary feature. The proposed system introduces further two features to reduce the causes of railway accidents. Railway track crack detection and motion detection are those features which play a significant role in reducing the risk of railway accidents. Moreover, the system is capable of detecting rule violations at a level crossing by using sensors. The proposed system is implemented through a prototype, and it is tested with real-world scenarios to gain the above 90% of accuracy.

Keywords: crack detection, decision-making, image processing, Internet of Things, motion detection, prototype, sensors

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Authors: Ntachobazi bosco

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Tourism Development and Planning in Rwanda: Rwanda, a small landlocked country located in the heart of Africa, has experienced significant growth in its tourism industry in recent years. The country’s stunning natural beauty, rich cultural heritage, and warm hospitality have made it an attractive destination for travelers from around the world. However, to ensure sustainable tourism development and planning, the Rwandan government has implemented various strategies and policies to promote responsible tourism practices. Infrastructure Development: To support the growth of the tourism industry, the Rwandan government has invested heavily in infrastructure development. This includes the construction of new hotels, resorts, and lodges, as well as the upgrading of existing facilities. The government has also improved the country’s transportation network, including the construction of new airports and the upgrading of existing ones. Conservation Efforts: Rwanda is home to several national parks and reserves, including the famous Volcanoes National Park, which is known for its mountain gorilla populations. To protect these natural wonders, the Rwandan government has implemented conservation efforts, such as the establishment of protected areas and the development of sustainable tourism practices. Community-Based Tourism: Community-based tourism is a key component of Rwanda’s tourism development strategy. The government has established several community-based tourism programs, which aim to involve local communities in the tourism industry and provide them with economic benefits. These programs include homestays, village tours, and cultural performances. Sustainable Tourism Practices: To promote sustainable tourism practices, the Rwandan government has implemented several initiatives, such as the use of eco-friendly accommodations and the promotion of responsible wildlife viewing practices. The government has also established the Rwanda Tourism Board, which is responsible for promoting and regulating the tourism industry. Challenges and Opportunities: Despite the growth of the tourism industry in Rwanda, several challenges need to be addressed, such as the lack of skilled labor and the need for more infrastructure development. However, there are also several opportunities for the industry, such as the potential for ecotourism and the growth of the meetings, incentives, conventions, and exhibitions (MICE) market.

Keywords: tourism, in rwanda, developent, in africa

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Authors: Ritwik Saha, Anindita Chaudhuri

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The psychological dimension of work-based mobility of the contemporary time in the context of the ever-changing socio-economic process mounting the interest to address the consequential issues of quality of life and well-being of the migrant section of society. The negotiation with the fluidity of the job market and the changing psychosocial dimensions within and between psychosocial relations may disentangle the resilience as well as the mechanism of diligence toward migrant (marginal) life. The work-based mobility and its associated phenomena have highly impacted the migrant’s quality of life especially the marginalized (socioeconomically weak) ones along with their family members staying away from them. The subjective experiences of the journey of their migrant life and reconstruction of the psychosocial being in terms of existence and well-being at the host place are the minimal addressed issues in migrant literature. Hence this gap instigates to bring forth the issue with the present study exploring the phenomenal aspects of lived experiences, resilience, and sense-making of the well-being of migrant living by the marginalized migrant people engaging in unorganized space. In doing so qualitative research method was followed, and semi-structured interviews were used for data collection from the four selected migrant groups (Fuchkawala, Bhunjawala, Bhari - drinking water supplier, Construction worker) as they migrated to Kolkata and its metropolis area from different states of India, Five participants from each group (20 participants in total) age range between 20 to 45 were interviewed physically and participants’ observatory notes were taken to capture their lived experiences, audio recordings were transcribed and analyzed systematically following Charmaz’s three-layer coding of grounded theory. Being truthful to daily industry, the strong desire to build children’s future, the mastering mechanism to dual existence, use of traditional social network these four themes emerges after analysis of the data. However, incorporating fate as their usual way of life and making sense of well-being through their assertion is another evolving aspect of migrant life.

Keywords: lived experiences, marginal living, resilience, sense-making process, well-being

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Authors: Luis Alvarado, Victor Poblete, Isaac Gonzalez, Yetzabeth Gonzalez

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In MIREX 2016 (http://www.music-ir.org/mirex), the deep neural network (DNN)-Deep Chroma Extractor, proposed by Korzeniowski and Wiedmer, reached the highest score in an audio chord recognition task. In the present paper, this tool is assessed under acoustic reverberant environments and distinct source-microphone distances. The evaluation dataset comprises The Beatles and Queen datasets. These datasets are sequentially re-recorded with a single microphone in a real reverberant chamber at four reverberation times (0 -anechoic-, 1, 2, and 3 s, approximately), as well as four source-microphone distances (32, 64, 128, and 256 cm). It is expected that the performance of the trained DNN will dramatically decrease under these acoustic conditions with signals degraded by room reverberation and distance to the source. Recently, the effect of the bio-inspired Locally-Normalized Cepstral Coefficients (LNCC), has been assessed in a text independent speaker verification task using speech signals degraded by additive noise at different signal-to-noise ratios with variations of recording distance, and it has also been assessed under reverberant conditions with variations of recording distance. LNCC showed a performance so high as the state-of-the-art Mel Frequency Cepstral Coefficient filters. Based on these results, this paper proposes a variation of locally-normalized triangular filters called Locally-Normalized Quarter Tone (LNQT) filters. By using the LNQT spectrogram, robustness improvements of the trained Deep Chroma Extractor are expected, compared with classical triangular filters, and thus compensating the music signal degradation improving the accuracy of the chord recognition system.

Keywords: chord recognition, deep neural networks, feature extraction, music information retrieval

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Authors: Aisling De Paor

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Scientific and technological developments are driving genetics and genetic technologies into the public sphere. Scientists are making genetic discoveries as to the make up of the human body and the cause and effect of disease, diversity and disability amongst individuals. Technological innovation in the field of genetics is also advancing, with the development of genetic testing, and other emerging genetic technologies, including gene editing (which offers the potential for genetic modification). In addition to the benefits for medicine, health care and humanity, these genetic advances raise a range of ethical, legal and societal concerns. From an ethical perspective, such advances may, for example, change the concept of humans and what it means to be human. Science may take over in conceptualising human beings, which may push the boundaries of existing human rights. New genetic technologies, particularly gene editing techniques create the potential to stigmatise disability, by highlighting disability or genetic difference as something that should be eliminated or anticipated. From a disability perspective, use (and misuse) of genetic technologies raise concerns about discrimination and violations to the dignity and integrity of the individual. With an acknowledgement of the likely future orientation of genetic science, and in consideration of the intersection of genetics and disability, this paper highlights the main concerns raised as genetic science and technology advances (particularly with gene editing developments), and the consequences for disability and human rights. Through the use of traditional doctrinal legal methodologies, it investigates the use (and potential misuse) of gene editing as creating the potential for a unique form of discrimination and stigmatization to develop, as well as a potential gateway to a form of new, subtle eugenics. This article highlights the need to maintain caution as to the use, application and the consequences of genetic technologies. With a focus on the law and policy position in Europe, it examines the need to control and regulate these new technologies, particularly gene editing. In addition to considering the need for regulation, this paper highlights non-normative approaches to address this area, including awareness raising and education, public discussion and engagement with key stakeholders in the field and the development of a multifaceted genetics advisory network.

Keywords: disability, gene-editing, genetics, law, regulation

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Authors: Abayomi O. Adetuyi, Jamiu M. Jabar, Samuel O. Afolabi

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Vegetable fibres are classes of fibres of low density, biodegradable and non-abrasive that are largely abundant fibre materials with specific properties and mostly found/ obtained in plants on earth surface. They are classified into three categories, depending on the part of the plant from which they are gotten from namely: fruit, Blast and Leaf fibre. Ever since four/five millennium B.C, attention has been focussing on the commonest and highly utilized cotton fibre obtained from the fruit of cotton plants (Gossypium spp), for the production of cotton fabric used in every home today. The present study, therefore, focused on the ability of three underutilized vegetable (fruit) fibres namely: coir fiber (Eleas coniferus), palm kernel fiber and empty fruit bunch fiber (Elias guinensis) through chemical modifications for better composite value addition performance to polyurethane form and dye adsorption. These fibres were sourced from their parents’ plants, identified and cleansed with 2% hot detergent solution 1:100, rinsed in distilled water and oven-dried to constant weight, before been chemically modified through alkali bleaching, mercerization and acetylation. The alkali bleaching involves treating 0.5g of each fiber material with 100 mL of 2% H2O2 in 25 % NaOH solution with refluxing for 2 h. While that of mercerization and acetylation involves the use of 5% sodium hydroxide NaOH solution for 2 h and 10% acetic acid- acetic anhydride 1:1 (v/v) (CH3COOH) / (CH3CO)2O solution with conc. H2SO4 as catalyst for 1 h, respectively on the fibres. All were subsequently washed thoroughly with distilled water and oven dried at 105 0C for 1 h. These modified fibres were incorporated as composite into polyurethane form and used in dye adsorption study of indigo. The first two treatments led to fiber weight reduction, while the acidified acetic anhydride treatment gave the fibers weight increment. All the treated fibers were found to be of less hydrophilic nature, better mechanical properties, higher thermal stabilities as well as better adsorption surfaces/capacities than the untreated ones. These were confirmed by gravimetric analysis, Instron Universal Testing Machine, Thermogravimetric Analyser and the Scanning Electron Microscope (SEM) respectively. The fiber morphology of the modified fibers showed smoother surfaces than unmodified fibres.The empty fruit bunch fibre and the coconut coir fibre are better than the palm kernel fibres as reinforcers for composites or as adsorbents for waste-water treatment. Acetylation and alkaline bleaching treatment improve the potentials of the fibres more than mercerization treatment. Conclusively, vegetable fibres, especially empty fruit bunch fibre and the coconut coir fibre, which are cheap, abundant and underutilized, can replace the very costly powdered activated carbon in wastewater treatment and as reinforcer in foam.

Keywords: chemical modification, industrial application, value addition, vegetable fibre

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Authors: Katharina M. Rischer, Angelika Dierolf, Ana M. Gonzalez-Roldan, Pedro Montoya, Fernand Anton, Marian van der Meulen

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Even though age has been associated with increased and prolonged episodes of pain, little is known about potential age-related changes in the ˈtop-downˈ modulation of pain, such as cognitive distraction from pain. The analgesic effects of distraction result from competition for attentional resources in the prefrontal cortex (PFC), a region that is also involved in executive functions. Given that the PFC shows pronounced age-related atrophy, distraction may be less effective in reducing pain in older compared to younger adults. The aim of this study was to investigate the influence of aging on task-related analgesia and the underpinning neural mechanisms, with a focus on the role of executive functions in distraction from pain. In a first session, 64 participants (32 young adults: 26.69 ± 4.14 years; 32 older adults: 68.28 ± 7.00 years) completed a battery of neuropsychological tests. In a second session, participants underwent a pain distraction paradigm, while fMRI images were acquired. In this paradigm, participants completed a low (0-back) and a high (2-back) load condition of a working memory task while receiving either warm or painful thermal stimuli to their lower arm. To control for age-related differences in sensitivity to pain and perceived task difficulty, stimulus intensity, and task speed were individually calibrated. Results indicate that both age groups showed significantly reduced activity in a network of regions involved in pain processing when completing the high load distraction task; however, young adults showed a larger neural distraction effect in different parts of the insula and the thalamus. Moreover, better executive functions, in particular inhibitory control abilities, were associated with a larger behavioral and neural distraction effect. These findings clearly demonstrate that top-down control of pain is affected in older age, and could explain the higher vulnerability for older adults to develop chronic pain. Moreover, our findings suggest that the assessment of executive functions may be a useful tool for predicting the efficacy of cognitive pain modulation strategies in older adults.

Keywords: executive functions, cognitive pain modulation, fMRI, PFC

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Authors: Sophie Kroeling, Agnetha Schuchardt

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Striving for sustainability brings a lot of challenges for different fields of interest, e. g. security or health concerns. In Germany, civil protection is predominantly carried out by emergency responders who perform essential tasks of civil protection. Based on theoretical concepts of different psychological stress theories this contribution focuses on the question, how the resilience of emergency responders can be improved. The goal is to identify resources and successful coping strategies that help to prevent and reduce negative outcomes during or after stressful events. The paper will present results from a qualitative analysis of semi-structured qualitative interviews with 20 emergency responders. These results provide insights into the complexity of coping processes (e. g. controlling the situation, downplaying perceived personal threats through humor) and show the diversity of stressors (like complexity of the disastrous situation, intrusive press and media, or lack of social support within the organization). Self-efficacy expectation was a very important resource for coping with stressful situations. The results served as a starting point for a quantitative survey (that was conducted in March 2017), the development of education and training tools for emergency responders and the improvement of critical incident stress management processes. First results from the quantitative study with more than 700 participants show that, e. g., the emergency responders use social coping within their private social network and also within their aid organization and that both are correlated to resilience. Moreover, missing information, bureaucratic problems and social conflicts within the organization are events that the majority of the participants considered very onerous. Further results from regression analysis will be presented. The proposed paper will combine findings from the qualitative study with the quantitative results, illustrating figures and correlations with respective statements from the interviews. At the end, suggestions for the improvement of the emergency responder’s resilience are given and it is discussed how this can make a contribution to strive for civil security and furthermore a sustainable development.

Keywords: civil security, emergency responders, stress, resilience, resources

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Authors: Peiming Li

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This paper presents an innovative blockchain-based approach to enhance the reliability and efficiency of federated learning systems. By integrating a decentralized oracle consensus mechanism into the federated learning framework, we address key challenges of data and model integrity. Our approach utilizes a network of redundant oracles, functioning as independent validators within an epoch-based training system in the federated learning model. In federated learning, data is decentralized, residing on various participants' devices. This scenario often leads to concerns about data integrity and model quality. Our solution employs blockchain technology to establish a transparent and tamper-proof environment, ensuring secure data sharing and aggregation. The decentralized oracles, a concept borrowed from blockchain systems, act as unbiased validators. They assess the contributions of each participant using a Hidden Markov Model (HMM), which is crucial for evaluating the consistency of participant inputs and safeguarding against model poisoning and malicious activities. Our methodology's distinct feature is its epoch-based training. An epoch here refers to a specific training phase where data is updated and assessed for quality and relevance. The redundant oracles work in concert to validate data updates during these epochs, enhancing the system's resilience to security threats and data corruption. The effectiveness of this system was tested using the Mnist dataset, a standard in machine learning for benchmarking. Results demonstrate that our blockchain-oriented federated learning approach significantly boosts system resilience, addressing the common challenges of federated environments. This paper aims to make these advanced concepts accessible, even to those with a limited background in blockchain or federated learning. We provide a foundational understanding of how blockchain technology can revolutionize data integrity in decentralized systems and explain the role of oracles in maintaining model accuracy and reliability.

Keywords: federated learning system, block chain, decentralized oracles, hidden markov model

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Authors: Annika Stechemesser, Rachel Pounds, Emma Lucas, Chris Dawson, Julia Lipecki, Pavle Vrljicak, Jan Brosens, Sean Kehoe, Jason Yap, Lawrence Young, Sascha Ott

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Advances in technology make it now possible to retrieve the genetic information of thousands of single cancerous cells. One of the key challenges in single cell analysis of cancerous tissue is to determine the number of different cell types and their characteristic genes within the sample to better understand the tumors and their reaction to different treatments. For this analysis to be possible, it is crucial to filter out background noise as it can severely blur the downstream analysis and give misleading results. In-depth analysis of the state-of-the-art filtering methods for single cell data showed that they do, in some cases, not separate noisy and normal cells sufficiently. We introduced an algorithm that filters and clusters single cell data simultaneously without relying on certain genes or thresholds chosen by eye. It detects communities in a Shared Nearest Neighbor similarity network, which captures the similarities and dissimilarities of the cells by optimizing the modularity and then identifies and removes vertices with a weak clustering belonging. This strategy is based on the fact that noisy data instances are very likely to be similar to true cell types but do not match any of these wells. Once the clustering is complete, we apply a set of evaluation metrics on the cluster level and accept or reject clusters based on the outcome. The performance of our algorithm was tested on three datasets and led to convincing results. We were able to replicate the results on a Peripheral Blood Mononuclear Cells dataset. Furthermore, we applied the algorithm to two samples of ovarian cancer from the same patient before and after chemotherapy. Comparing the standard approach to our algorithm, we found a hidden cell type in the ovarian postchemotherapy data with interesting marker genes that are potentially relevant for medical research.

Keywords: cancer research, graph theory, machine learning, single cell analysis

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Authors: Dheyaa W. Abbood, Rafa H. AL-Suhaili, May S. Saleh

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A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs length sand their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy.The optimization carried out subjected to constraints that ensure a safe structure against the uplift pressure force and sufficient protection length at the downstream side of the structure to overcome an excessive exit gradient. The Geo-studios oft ware, was used to analyze 1200 different cases. For each case the length of protection and volume of structure required to satisfy the safety factors mentioned previously were estimated. An ANN model was developed and verified using these cases input-output sets as its data base. A MatLAB code was written to perform a genetic algorithm optimization modeling coupled with this ANN model using a formulated optimization model. A sensitivity analysis was done for selecting the cross-over probability, the mutation probability and level ,the number of population, the position of the crossover and the weights distribution for all the terms of the objective function. Results indicate that the most factor that affects the optimum solution is the number of population required. The minimum value that gives stable global optimum solution of this parameters is (30000) while other variables have little effect on the optimum solution.

Keywords: inclined cutoff, optimization, genetic algorithm, artificial neural networks, geo-studio, uplift pressure, exit gradient, factor of safety

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Authors: S. Somerset, D. J. Hoare, P. Leighton

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Limited participation in physical activity and sport has been linked to poorer mental and physical health in children. Studies have shown that children who participate in sports benefit from improved social skills, self-confidence, communication skills and a better quality of life. Children who participate in sport are also more likely to continue their participation into their adult life. Deaf or hard of hearing children should have the same opportunities to participate in sport and receive the benefits as their hearing peers. Anecdotal evidence suggests this isn’t always the case. This is concerning given there are 45,000 children in the UK with permanent hearing loss. The aim of this study was to understand what encourages or discourages deaf or hard of hearing children to take part in sports. Ethical approval for the study was obtained from the University of Nottingham School of Medicine ethics committee. We conducted eight focus groups with deaf or hard of hearing children aged 10 to 15 years. A total of 45 children (19 male, 26 female) recruited from local schools and sports clubs took part. Information was gathered on the children’s thoughts and feelings about participation in sport. This included whether they played sports and who with, whether they did or did not like sport, and why they got involved in sport. Focus groups were audio recorded and transcribed. Transcripts were analysed using thematic analysis. Several key themes were identified as being associated with levels of sports participation. These included friendships, family and communication. Deaf or hard of hearing children with active siblings had participated in more sports. Communication was a common theme throughout regardless of the type of hearing-assistive technology a child used. Children found communication easier during sport if they were allowed to use their technology and had particular difficulty during sports such as swimming. Children expressed a desire not to have to identify themselves at a club as having a hearing loss. This affected their confidence when participating in sport. Not surprisingly, children who are deaf or hard of hearing are more likely to participate in sport if they have a good support network of parents, coaches and friends. The key barriers to participation for these children are communication, lack of visual information, lack of opportunity and a lack of awareness. By addressing these issues more deaf and hard of hearing children will take part in sport and will continue their participation.

Keywords: barrier, children, deaf, participation, hard of hearing, sport

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Authors: Liana Melissa E. de la Rosa, Jayson P. Ada

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This exploratory study was conducted to determine the sociology of the Facebook. Specifically, it aimed to know the socio-demographic profile of the respondents in terms of age, sex, year level and monthly allowance; find out the common usage of Facebook to the respondents; identify the features of Facebook that are commonly used by the respondents; understand the benefits and risks of using the Facebook; determine how frequent the respondents use the Facebook; and find out if there is a significant relationship between socio-demographic profile of the respondents and their Facebook usage. This study used the exploratory research design and correlational design employing research survey questionnaire as its main data gathering instrument. Students of the University of Eastern Philippines were selected as the respondents of this study through quota sampling. Ten (10) students were randomly selected from each college of the university. Based on the findings of this study, the following conclusion were drawn: The majority of the respondents are aged 18 and 21 old, female, are third year students, and have monthly allowance of P 2,000 above. On the respondents’ usage of Facebook, the majority of use the Facebook on a daily basis for one to two (1-2) hours everyday. And most users used Facebook by renting a computer in an internet cafe. On the use of Facebook, most users have created their profiles mainly to connect with people and gain new friends. The most commonly used features of Facebook, are: photos application, like button, wall, notification, friend, chat, network, groups and “like” pages status updates, messages and inbox and events. While the other Facebook features that are seldom used by the respondents are games, news feed, user name, video sharing and notes. And the least used Facebook features are questions, poke feature, credits and the market place. The respondents stated that the major benefit that the Facebook has given to its users is its ability to keep in touch with family members or friends while the main risk identified is that the users can become addicted to the Internet. On the tests of relationships between the respondents’ use of Facebook and the four (4) socio-demographic profile variables: age, sex, year level, and month allowance, were found to be not significantly related to the respondents’ use of the Facebook. While the variable found to be significantly related was gender.

Keywords: Facebook, sociology, social networking, exploratory study

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Authors: Kemal Efe Eseller, Göktuğ Yazici

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

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

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