Search results for: disaster relief networks

Authors: Rafael Castilho Carvalho, Edjair de Souza Mota

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As the largest contributor to the biogeochemical functioning of the Earth system, the Amazon Rainforest has the greatest biodiversity on the planet, harboring about 15% of all the world's flora. Recognition and preservation are the focus of research that seeks to mitigate drastic changes, especially anthropic ones, which irreversibly affect this biome. Functional and low-cost monitoring alternatives to reduce these impacts are a priority, such as those using technologies such as Low Power Wide Area Networks (LPWAN). Promising, reliable, secure and with low energy consumption, LPWAN can connect thousands of IoT devices, and in particular, LoRa is considered one of the most successful solutions to facilitate forest monitoring applications. Despite this, the forest environment, in particular the Amazon Rainforest, is a challenge for these technologies, requiring work to identify and validate the use of technology in a real environment. To investigate the feasibility of deploying LPWAN in remote water quality monitoring of rivers in the Amazon Region, a LoRa-based test bed consisting of a Lora transmitter and a LoRa receiver was set up, both parts were implemented with Arduino and the LoRa chip SX1276. The experiment was carried out at the Federal University of Amazonas, which contains one of the largest urban forests in Brazil. There are several springs inside the forest, and the main goal is to collect water quality parameters and transmit the data through the forest in real time to the gateway at the uni. In all, there are nine water quality parameters of interest. Even with a high collection frequency, the amount of information that must be sent to the gateway is small. However, for this application, the battery of the transmitter device is a concern since, in the real application, the device must run without maintenance for long periods of time. With these constraints in mind, parameters such as Spreading Factor (SF) and Coding Rate (CR), different antenna heights, and distances were tuned to better the connectivity quality, measured with RSSI and loss rate. A handheld spectrum analyzer RF Explorer was used to get the RSSI values. Distances exceeding 200 m have soon proven difficult to establish communication due to the dense foliage and high humidity. The optimal combinations of SF-CR values were 8-5 and 9-5, showing the lowest packet loss rates, 5% and 17%, respectively, with a signal strength of approximately -120 dBm, these being the best settings for this study so far. The rains and climate changes imposed limitations on the equipment, and more tests are already being conducted. Subsequently, the range of the LoRa configuration must be extended using a mesh topology, especially because at least three different collection points in the same water body are required.

Keywords: IoT, LPWAN, LoRa, coverage, loss rate, forest

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Authors: M. G. Talasbayen, N. N. Dyussenbayev, Y. D. Kali, R. A. Zholbarysov, Y. N. Duissenbayev, I. Z. Mammadinova, S. M. Nuradilov

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Background. Hemorrhagic stroke is an acute cerebrovascular accident resulting from rupture of a cerebral vessel or increased permeability of the wall and imbibition of blood into the brain parenchyma. Arterial hypertension is a common cause of hemorrhagic stroke. Male gender and age over 55 years is a risk factor for intracerebral hemorrhage. Treatment of intracerebral hemorrhage is aimed at the primary pathophysiological link: the relief of coagulopathy and the control of arterial hypertension. Early surgical treatment can limit cerebral compression; prevent toxic effects of blood to the brain parenchyma. Despite progress in the development of neuroimaging data, the use of minimally invasive techniques, and navigation system, mortality from intracerebral hemorrhage remains high. Materials and methods. The study included 78 patients (62.82% male and 37.18% female) with a verified diagnosis of hemorrhagic stroke in the period from 2019 to 2021. The age of patients ranged from 25 to 80 years, the average age was 54.66±11.9 years. Demographic, brain CT data (localization, volume of hematomas), methods of treatment, and disease outcome were analyzed. Results. The retrospective analyze demonstrate that 78.2% of all patients underwent surgical treatment: decompressive craniectomy in 37.7%, craniotomy with hematoma evacuation in 29.5%, and hematoma draining in 24.59% cases. The study of the proportion of deaths, depending on the volume of intracerebral hemorrhage, shows that the number of deaths was higher in the group with a hematoma volume of more than 60 ml. Evaluation of the relationship between the time before surgery and mortality demonstrates that the most favorable outcome is observed during surgical treatment in the interval from 3 to 24 hours. Mortality depending on age did not reveal a significant difference between age groups. An analysis of the impact of the surgery type on mortality reveals that decompressive craniectomy with or without hematoma evacuation led to an unfavorable outcome in 73.9% of cases, while craniotomy with hematoma evacuation and drainage led to mortality only in 28.82% cases. Conclusion. Even though the multimodal approaches, the development of surgical techniques and equipment, and the selection of optimal conservative therapy, the question of determining the tactics of managing and treating hemorrhagic strokes is still controversial. Nevertheless, our experience shows that surgical intervention within 24 hours from the moment of admission and craniotomy with hematoma evacuation improves the prognosis of treatment outcomes.

Keywords: hemorragic stroke, Intracerebral hemorrhage, surgical treatment, stroke mortality

Procedia PDF Downloads 90

Authors: I. Agboola Julius, Christopher A. Kumolu-Johnson, O. Kolade Rafiu, A. Saba Abdulwakil

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This work elucidates on mangrove diversity, trends of change, factors responsible for loss over the years and implications for sustainable livelihoods of locals in four villages (Ajido (L1), Tarkwa bay (L2), University of Lagos (L3), and Ikosi (L4)) along the coast of Lagos, Nigeria. Primary data were collected through field survey, questionnaires, interviews, and review of existing literature. Field observation and data analysis reveals mangrove diversity as low and varied on a spatial scale, where Margalef’s Diversity Index (D) was 0.368, 0.269, 0.326, and 0.333, respectively for L1, L2, L3, and L4. Shannon Weiner’s Index (H) was estimated to be 1.003, 1.460, 1.160, 1.046, and Specie Richness (E) 0.913, 0.907, 0.858, and 0.015, respectively, for the four villages. Also, The Simpson’s index of diversity was analyzed to be 0.632, 0. 731, 0.647, 0.667, and Simpson’s reciprocal index 2.717, 3.717, 3.060, and 3.003, respectively, for the four villages. Chi-square test was used to analyze the impact of mangrove loss on the sustainable livelihood of coastal communities. Calculated Chi-square (X2) value (5) was higher than tabulated value (4.30), suggesting that loss of mangrove wetlands impacted on local communities’ livelihood at the four villages. Analyses of causes and trends of mangrove wetland loss over the years suggest that urbanization, fuel wood and agricultural activities are major causes. Current degradation observed in mangrove wetlands on the Lagos coast suggest a reduction in mangroves biodiversity and associated fauna with potential cascading effects on higher trophic levels such as fisheries. Low yield in fish catch, reduction in income and increasing cases of natural disaster has culminated in threats to sustainable livelihoods of local communities along the coast of Lagos.

Keywords: Mangroves, lagos coast, fisheries, management

Procedia PDF Downloads 623

Authors: Shuo Liu

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In Chinese text classification tasks, redundant words and phrases can interfere with the formation of extracted and analyzed text information, leading to a decrease in the accuracy of the classification model. To reduce irrelevant elements, extract and utilize text content information more efficiently and improve the accuracy of text classification models. In this paper, the text in the corpus is first extracted using the TextRank algorithm for abstraction, the words in the abstract are used as nodes to construct a text graph, and then the graph attention network (GAT) is used to complete the task of classifying the text. Testing on a Chinese dataset from the network, the classification accuracy was improved over the direct method of generating graph structures using text.

Keywords: Chinese natural language processing, text classification, abstract extraction, graph attention network

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Authors: Firas Gerges, Frank Y. Shih

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Malignant melanoma, known simply as melanoma, is a type of skin cancer that appears as a mole on the skin. It is critical to detect this cancer at an early stage because it can spread across the body and may lead to the patient's death. When detected early, melanoma is curable. In this paper, we propose a deep learning model (convolutional neural networks) in order to automatically classify skin lesion images as malignant or benign. Images underwent certain pre-processing steps to diminish the effect of the normal skin region on the model. The result of the proposed model showed a significant improvement over previous work, achieving an accuracy of 97%.

Keywords: deep learning, skin cancer, image processing, melanoma

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Authors: Qiaoyun Yang

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Organizational scholars have paid enormous attention on how local governments manage their knowledge during the past two decades. Government knowledge management (KM) research recognizes that the management of knowledge flows and networks is critical to reforms on government service efficiency and the effect of administration. When dealing with complex affairs, all the limitations resulting from a lack of KM concept, processes and technologies among all the involved organizations begin to be exposed and further compound the processing difficulty of the affair. As a result, the challenges for individual or group knowledge sharing, knowledge digging and organizations’ collaboration in government's activities are diverse and immense. This analysis presents recent situation of government KM in China drawing from a total of more than 300 questionnaires and highlights important challenges that remain. The causes of the lapses in KM processes within and across the government agencies are discussed.

Keywords: KM processes, KM technologies, government, KM situation

Procedia PDF Downloads 338

Authors: Gunasekaran Raja, Rajakumar Arul, Kottilingam Kottursamy, Ramkumar Jayaraman, Sathya Pavithra, Swaminathan Venkatraman

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Wireless Interoperability for Microwave Access (WiMAX) utilizes the IEEE 802.1X mechanism for authentication. However, this mechanism incurs considerable delay during handoffs. This delay during handoffs results in service disruption which becomes a severe bottleneck. To overcome this delay, our article proposes a key caching mechanism based on user path prediction. If the user mobility follows that path, the user bypasses the normal IEEE 802.1X mechanism and establishes the necessary authentication keys directly. Through analytical and simulation modeling, we have proved that our mechanism effectively decreases the handoff delay thereby achieving fast authentication.

Keywords: authentication, authorization, and accounting (AAA), handoff, mobile, user path prediction (UPP) and user pattern

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Authors: Sadiq J. Abou-Loukh

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The present work deals with implementation of Petri nets, which own the perfect ability of modeling, are used to establish a fault diagnosis model. Fault diagnosis of a control system received considerable attention in the last decades. The formalism of representing neural networks based on Petri nets has been presented. Neural Petri Net (NPN) reasoning model is investigated and developed for the fault diagnosis process of electric control system. The proposed NPN has the characteristics of easy establishment and high efficiency, and fault status within the system can be described clearly when compared with traditional testing methods. The proposed system is tested and the simulation results are given. The implementation explains the advantages of using NPN method and can be used as a guide for different online applications.

Keywords: petri net, neural petri net, electric control system, fault diagnosis

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Authors: Nuwan Kuruwitaarachchi, M. K. M. Peiris, C. N. Madawala, K. M. A. R. Perera, V. U. N Perera

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Dealing with businesses with the foreign market always took a special place in a country’s economy. Political and social factors came into play making currency rate changes fluctuate rapidly. Currency rate prediction has become an important factor for larger international businesses since large amounts of money exchanged between countries. This research focuses on comparing the accuracy of mainly three models; Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Networks(ANN) and Support Vector Machines(SVM). series of data import, export, USD currency exchange rate respect to LKR has been selected for training using above mentioned algorithms. After training the data set and comparing each algorithm, it was able to see that prediction in SVM performed better than other models. It was improved more by combining SVM and SVR models together.

Keywords: ARIMA, ANN, FFNN, RMSE, SVM, SVR

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Authors: Johannes Van Der Sandt

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This quantitative study investigates different approaches of community singing, in building social capital in South Tyrol, Italy, and South Africa. The impact of the various approaches of community singing is examined by investigating the main components of social capital, namely, social norms and obligations, social networks and associations and trust, and how these components are manifested in two different societies. The research is based on the premise that community singing is an important agent for the development of social capital. It seeks to establish in what form community singing can best enhance the social capital of communities in South Tyrol that are undergoing significant changes in the ways in which social capital is generally being generated on account of demographic, economic, technological and cultural changes. South Tyrol and South Africa share some similarities in the management of their multi-cultural composition. By comparing the different approaches to community singing in two multi-cultural societies, it is hoped to gain insight, and an understanding of the connections between culture, social cohesion, identity and therefore to be able to add to the understanding of the building of social capital through community singing. Participation in music contributes to the growth of social capital in communities, this is amongst others the finding of an ever increasing amount of research. In sociological discourses on social capital generation, the dimension of community music making is recognized as an important factor. Trust and mutual cooperation are products when people listen to each other, when they work or play together, and when they care about each other. This is how social capital develops as an important shared resource. Scholars of Community Music still do not agree on a short and concise definition for Community Music. For the purpose of this research, the author concurs with the definition of Community Music of the Community Music Activity commission of the International Society of Music Education as having the following characteristics: decentralization, accessibility, equal opportunity, and active participation in music-making. These principles are social and political ones, and there can be no doubt that community music activity is more than a purely musical one. Trust, shared norms and values civic and community involvement, networks, knowledge resources, contact with families and friends, and fellowship are key components in fostering group cohesion and social capital development in a community. The research will show that there is no better place for these factors to flourish than in a community singing group. Through this comparative study, it is the aim to identify, analyze and explain similarities and differences in approaches to community across societies that find themselves in a rapid transition from traditional cultural to global cultural habits characterized by a plurality of orientation points, with the aim to gain a better understanding of the various directions South Tyrolean singing culture can take.

Keywords: community music, multicultural, singing, social capital

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Authors: Azimollah Aleshzadeh, Enver Vural Yavuz

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The main goal of this study is to produce landslide susceptibility maps using different data-driven bivariate statistical approaches; namely, entropy weight method (EWM), evidence belief function (EBF), and information content model (ICM), at Uzundere county, Erzurum province, in the north-eastern part of Turkey. Past landslide occurrences were identified and mapped from an interpretation of high-resolution satellite images, and earlier reports as well as by carrying out field surveys. In total, 42 landslide incidence polygons were mapped using ArcGIS 10.4.1 software and randomly split into a construction dataset 70 % (30 landslide incidences) for building the EWM, EBF, and ICM models and the remaining 30 % (12 landslides incidences) were used for verification purposes. Twelve layers of landslide-predisposing parameters were prepared, including total surface radiation, maximum relief, soil groups, standard curvature, distance to stream/river sites, distance to the road network, surface roughness, land use pattern, engineering geological rock group, topographical elevation, the orientation of slope, and terrain slope gradient. The relationships between the landslide-predisposing parameters and the landslide inventory map were determined using different statistical models (EWM, EBF, and ICM). The model results were validated with landslide incidences, which were not used during the model construction. In addition, receiver operating characteristic curves were applied, and the area under the curve (AUC) was determined for the different susceptibility maps using the success (construction data) and prediction (verification data) rate curves. The results revealed that the AUC for success rates are 0.7055, 0.7221, and 0.7368, while the prediction rates are 0.6811, 0.6997, and 0.7105 for EWM, EBF, and ICM models, respectively. Consequently, landslide susceptibility maps were classified into five susceptibility classes, including very low, low, moderate, high, and very high. Additionally, the portion of construction and verification landslides incidences in high and very high landslide susceptibility classes in each map was determined. The results showed that the EWM, EBF, and ICM models produced satisfactory accuracy. The obtained landslide susceptibility maps may be useful for future natural hazard mitigation studies and planning purposes for environmental protection.

Keywords: entropy weight method, evidence belief function, information content model, landslide susceptibility mapping

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Authors: M. Khouil, N. Saber, M. Mestari

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This study aimed to propose, a different architecture of a Path Planning using the NECMOP. where several nonlinear objective functions must be optimized in a conflicting situation. The ability to detect and avoid collision is very important for mobile intelligent machines. However, many artificial vision systems are not yet able to quickly and cheaply extract the wealth information. This network, which has been particularly reviewed, has enabled us to solve with a new approach the problem of collision detection between two convex polyhedra in a fixed time (O (1) time). We used two types of neurons linear and threshold logic, which simplified the actual implementation of all the networks proposed. This article represents a comprehensive algorithm that determine through the AMAXNET network a measure (a mini-maximum point) in a fixed time, which allows us to detect the presence of a potential collision.

Keywords: path planning, collision detection, convex polyhedron, neural network

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Authors: Neetesh Saxena, Narendra S. Chaudhari

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Nowadays, SMS is a very popular mobile service and even the poor, illiterate people and those living in rural areas use SMS service very efficiently. Although many mobile operators have already started 3G and 4G services, 2G services are still being used by the people in many countries. In 2G (GSM), only encryption provided is between the MS and the BTS, there is no end-to-end encryption available. Sometimes we all need to send some confidential message to other person containing bank account number, some password, financial details, etc. Normally, a message is sent in plain text only to the recipient and it is not an acceptable standard for transmitting such important and confidential information. Authors propose an end-to-end encryption approach by proposing a terminal for sending/receiving a secure message. An asymmetric key exchange algorithm is used in order to transmit secret shared key securely to the recipient. The proposed approach with terminal device provides authentication, confidentiality, integrity and non-repudiation.

Keywords: AES, DES, Diffie-Hellman, ECDH, A5, SMS

Procedia PDF Downloads 389

Authors: Odey Moses Ogah, Felix Terhemba Ikyereve

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The study was carried out to analyzed risks in financing agriculture by agricultural cooperatives in Benue State, Nigeria. The study made use of research questionnaires for data collection. A multistage sampling technique was used to select a sample of 210 respondents from 21 agricultural cooperatives. Both descriptive and inferential statistics were employed in data analysis. Loan defaulting (66.7%) and reduction in savings by members (51.4%) were the major causes of risks faced by agricultural cooperatives in financing agriculture in the study area. Other causes include adverse changes in commodity prices (48.6%), disaster (45.7%), among others. It was found that risks adversely influence the profitability and competition of agricultural cooperatives (82.9%). Multiple regression analysis results showed that the coefficient of multiple determinations was 0.67, implying that the explanatory variables included in the model accounted for 67% of the variation in the level of profitability of agricultural cooperatives. The number of loans, average amount of loan and the interest rate were significant and important determinants of profitability of the cooperatives. The majority of the respondents (88.6%) made use of loan guarantors as a strategy of managing loan default/no repayment. It was found that the majority (70%) of the respondents were faced with the challenge of lack of insurance cover. The study recommends that agricultural cooperative officials should be encouraged to undergo formal training and education to easily acquire administrative skills in the management of agricultural loans; Farmer's loan size should be increased and released on time to enable them to use it effectively. Policies that enhance insuring farm activities should be put in place to discourage farmers from risk aversion.

Keywords: agriculture, analysis, cooperative, finance, risks

Procedia PDF Downloads 98

Authors: Joe Collins, Matthias Rother

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Background: Oral non-steroidal anti-inflammatory drugs (NSAIDs) are widely used for the relief of joint pain during and post-exercise. However, oral NSAIDs increase the risk of systemic side effects, even in healthy individuals, and retard recovery from muscle soreness. TDT 064 (Flexiseq®), a topical formulation containing ultra-deformable drug-free Sequessome™ vesicles, has demonstrated equivalent efficacy to oral celecoxib in reducing osteoarthritis-associated joint pain and stiffness. TDT 064 does not cause NSAID-related adverse effects. We describe clinical study data and a case report on the effectiveness of TDT 064 in reducing joint pain after exercise. Methods: Participants with a pain score ≥3 (10-point scale) 12–16 hours post-exercise were randomized to receive TDT 064 plus oral placebo, TDT 064 plus oral ketoprofen, or ketoprofen in ultra-deformable phospholipid vesicles plus oral placebo. Results: In the 168 study participants, pain scores were significantly higher with oral ketoprofen plus TDT 064 than with TDT 064 plus placebo in the 7 days post-exercise (P = 0.0240) and recovery from muscle soreness was significantly longer (P = 0.0262). There was a low incidence of adverse events. These data are supported by clinical experience. A 24-year-old male professional rugby player suffered a traumatic lisfranc fracture in March 2014 and underwent operative reconstruction. He had no relevant medical history and was not receiving concomitant medications. He had undergone anterior cruciate ligament reconstruction in 2008. The patient reported restricted training due to pain (score 7/10), stiffness (score 9/10) and poor function, as well as pain when changing direction and running on consecutive days. In July 2014 he started using TDT 064 twice daily at the recommended dose. In November 2014 he noted reduced pain on running (score 2-3/10), decreased morning stiffness (score 4/10) and improved joint mobility and was able to return to competitive rugby without restrictions. No side effects of TDT 064 were reported. Conclusions: TDT 064 shows efficacy against exercise- and injury-induced joint pain, as well as that associated with osteoarthritis. It does not retard muscle soreness recovery after exercise compared with an oral NSAID, making it an alternative approach for the treatment of joint pain during and post-exercise.

Keywords: exercise, joint pain, TDT 064, phospholipid vesicles

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Authors: Moh Hanif Mubarok, Muhammad Rivai

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The public's response to quality rice is very high. So it is necessary to set minimum standards in checking the quality of rice. Most rice quality measurements still use manual methods, which are prone to errors due to limited human vision and the subjectivity of testers. So, a gas detection system can be a solution that has high effectiveness and subjectivity for solving current problems. The use of gas sensors in testing rice quality must pay attention to several parameters. The parameters measured in this research are the percentage of rice water content, gas concentration, output voltage, and measurement time. Therefore, this research was carried out to identify carbon dioxide (CO₂), nitrous oxide (N₂O) and methane (CH₄) gases in rice quality using a series of gas sensors using the Neural Network method.

Keywords: carbon dioxide, dinitrogen oxide, methane, semiconductor gas sensor, neural network

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Authors: Yoshimoto Kurihara, Tad Gonsalves

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Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.

Keywords: 6D posture estimation, image recognition, deep learning, AlexNet

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Authors: Noxolo Mafu

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This study presents an overview of strategic planning in South African higher education institutions by tracing its trends and mystique in order to identify its impact. Over the democratic decades, strategic planning has become integral to institutional survival. It has been used as a potent tool by several institutions to catch up and surpass counterparts. While planning has always been part of higher education, strategic planning should be considered different. Strategic planning is primarily about development and maintenance of a strategic fitting between an institution and its dynamic opportunities. This presupposes existence of sets of stages that institutions pursue of which, can be regarded for assessment of the impact of strategic planning in an institution. The network theory serves guides the study in demystifying apparent organisational networks in strategic planning processes.

Keywords: network theory, strategy, planning, strategic planning, assessment, impact

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Authors: Saahith M. S., Sivakami R.

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In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

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Authors: Okike Benjamin, E. J. D. Garba

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The protection of sensitive information against unauthorized access or fraudulent changes has been of prime concern throughout the centuries. Modern communication techniques, using computers connected through networks, make all data even more vulnerable to these threats. The researchers in this work propose a new encryption technique to be known as Merged Irregular Transposition Cipher. In this proposed encryption technique, a message to be encrypted will first of all be split into multiple parts depending on the length of the message. After the split, different keywords are chosen to encrypt different parts of the message. After encrypting all parts of the message, the positions of the encrypted message could be swapped to other position thereby making it very difficult to decrypt by any unauthorized user.

Keywords: information security, message splitting, pattern, sequence

Procedia PDF Downloads 263

Authors: Dina Dahood Dabash

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Refugee camps are habitually defined as receptive sites, transient spaces of exile and nondescript depoliticized places of exception. However, such arguments form partial sides of reality, especially in countries that are geopolitically challenged and rely immensely on international aid. In Jordan, the dynamics brought with the floating population of refugees (Palestinian amongst others) have resulted in spatial after-effects that cannot be easily overlooked. For instance, Palestine refugee camps have turned by time into socioeconomic centers of gravity and cores of spatial evolution. Yet, such a position is not instantaneous. Amongst various reasons, it can be related, according to this paper, to a distinctive institutional climate that has been co-produced by the refugees, host community and the state. This paper aims to investigate the evolution of urban and spatial regulations in Jordan between 1948 and 1995, more specifically, state regulations, community regulations and refugee-self-regulation that all dynamically interacted that period. The paper aims to unpack the relations between refugee camps and their environs to further explore the agency of such floating populations in establishing rooted networks that extended the time and place boundaries. The paper’s argument stems from the fact that the spatial configuration of urban systems is not only an outcome of a historical evolutionary process but is also a result of interactions between the actors. The research operationalizes Marka camp in Jordan as a case study. Marka Camp is one of the six "emergency" camps erected in 1968 to shelter 15,000 Palestine refugees and displaced persons who left the West Bank and Gaza Strip. Nowadays, camp shelters more than 50,000 refugees in the same area of land. The camp is located in Russeifa, a city in Zarqa Governorate in Jordan. Together with Amman and Zarqa, Russeifa is part of a larger metropolitan area that acts as a home to more than half of Jordan’s businesses. The paper aspires to further understand the post-conflict strategies which were historically applied in Jordan and can be employed to handle more recent geopolitical challenges such as the Syrian refugee crisis. Methodological framework: The paper traces the evolution of the refugee-camp regulating norms in Jordan, parallel with the horizontal and vertical evolution of the Marka camp and its surroundings. Consequently, the main methods employed are historical and mental tracing, Interviews, in addition to using available Aerial and archival photos of the Marka camp and its surrounding.

Keywords: forced migration, Palestine refugee camps, spatial agency, urban regulations

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Authors: Firas M. Tuaimah

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This paper presents an Artificial Neural Network based approach for short-term load forecasting and exactly for two days ahead. Two seasons have been discussed for Iraqi power system, namely summer and winter; the hourly load demand is the most important input variables for ANN based load forecasting. The recorded daily load profile with a lead time of 1-48 hours for July and December of the year 2012 was obtained from the operation and control center that belongs to the Ministry of Iraqi electricity. The results of the comparison show that the neural network gives a good prediction for the load forecasting and for two days ahead.

Keywords: short-term load forecasting, artificial neural networks, back propagation learning, hourly load demand

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Authors: Umar Mujahid, Greatzel Unabia, Hongsik Choi, Binh Tran

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Radio Frequency Identification (RFID) is one of the most commonly used technologies in IoTs and Wireless Sensor Networks which makes the devices identification and tracking extremely easy to manage. Since RFID uses wireless channel for communication, which is open for all types of adversaries, researchers have proposed many Ultralightweight Mutual Authentication Protocols (UMAPs) to ensure security and privacy in a cost-effective manner. These UMAPs involve simple bitwise logical operators such as XOR, AND, OR & Rot, etc., to design the protocol messages. However, most of these UMAPs were later reported to be vulnerable against many malicious attacks. In this paper, we have presented a detailed overview of some eminent UMAPs and also discussed the many security attacks on them. Finally, some recommendations and suggestions have been discussed, which can improve the design of the UMAPs.

Keywords: RFID, Ultralightweight, UMAP, SASI

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Authors: Carolina Senabre, Sergio Valero, Miguel Lopez, Antonio Gabaldon

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This paper presents a comprehensive survey of the short-term load forecasting (STLF). Since the behavior of consumers and producers continue changing as new technologies, it is an ongoing process, and moreover, new policies become available. The results of a research study for the Spanish Transport System Operator (REE) is presented in this paper. It is presented the improvement of the forecasting accuracy in the Balearic Islands considering the introduction of meteorological variables, such as temperature to reduce forecasting error. Variables analyzed for the forecasting in terms of overall accuracy are cloudiness, solar radiation, and wind velocity. It has also been analyzed the type of days to be considered in the research.

Keywords: short-term load forecasting, power demand, neural networks, load forecasting

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Authors: Kazi Enamul Hoque

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Initiatives on sustainable development are currently aggressively pursued throughout the world. The Malaysian government has developed key policies and strategies for over 30 years to achieve the nation’s policy objectives which are designed to mitigate the issues of security, energy efficiency and environmental impact to meet the rising energy demand. Malaysia’s current focus is on developing effective policies on renewable energy (RE) in order to reduce dependency on fossil fuel and contribute towards mitigating the effects of climate change. In this light mass awareness should be considered as the highest priority to protect the environment and to escape disaster due to climate change. Schools can be the reliable and effective foundation to prepare students to get familiar with environmental issues such as renewable and non-renewable energy sources. Teachers can play a vital role to create awareness among students about the advantages and disadvantages of using different renewable and nonrenewable energy resources. Thus, this study aims to investigate teachers’ knowledge, perceptions and attitudes towards renewable energy through a survey aiming a sustainable energy future. Five hundred sets of questionnaires were distributed to the school teachers in Malaysia. Total 420 questionnaires were returned of which 410 were complete to analyze. Finding shows that teachers are very familiar with the renewable energy like solar, wind and also geothermal. Most teachers were not sure about the Photovoltaics and biodiesel. Furthermore, teachers are also aware that primary energy in Malaysia is imported fossil fuels. Most teachers heard about the renewable energy in Malaysia and only few claims that they did not hear of such things and the others said that they never heard of it. The outcomes of the study will assist the energy policy makers to use teachers to create mass awareness of energy usages for future planning.

Keywords: Malaysia, non-renewable energy, renewable energy, school teacher

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Authors: Ibrahim M Hassan, Lorna Que, Michael Rutland

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Type I SOD is usually diagnosed by anatomical imaging such as ultrasound, CT and MRCP. However, the types II and III SOD yield negative results despite the presence of significant symptoms. In particular, the type III is difficult to diagnose due to the absence of significant biochemical or anatomical abnormalities. Nuclear Medicine can aid in this diagnostic dilemma by demonstrating functional changes in the bile flow. Low dose Morphine (0.04mg/Kg) stimulates the tone of the sphincter of Oddi (SO) and its usefulness has been shown in diagnosing SOD by causing a delay in bile flow when compared to a non morphine provoked - baseline scan. This work expands on that process by using sublingual GTN at 60 minutes post tracer and morphine injection to relax the SO and induce an improvement in bile outflow, and in some cases show immediate relief of morphine induced abdominal pain. The criteria for positive SOD are as follows: if during the first hour of the morphine provocation showed (1) delayed intrahepatic biliary ducts tracer accumulation; plus (2) delayed appearance but persistent retention of activity in the common bile duct, and (3) delayed bile flow into the duodenum. In addition, patients who required GTN within the first hour to relieve abdominal pain were regarded as highly supportive of the diagnosis. Retrospective analysis of 85 patients (pts) (78F and 6M) referred for suspected SOD (type III) who had been intensively investigated because of recurrent right upper quadrant or abdominal pain post cholecystectomy. 99mTc-HIDA scan with morphine-provocation is performed followed by GTN at 60 minutes post tracer injection and a further thirty minutes of dynamic imaging are acquired. 30 pts were negative. 55 pts were regarded as positive for SOD and 38/55 (60%) of these patients with an abnormal result were further evaluated with a baseline 99mTc-HIDA. As expected, all 38 pts showed better bile flow characteristics than during the morphine provocation. 20/55 (36%) patients were treated by ERCP sphincterotomy and the rest were managed conservatively by medical therapy. In all cases regarded as positive for SOD, the sublingual GTN at 60 minutes showed immediate improvement in bile flow. 11/55(20%) who developed severe post-morphine abdominal pain were relieved by GTN almost instantaneously. We propose that GTN is a useful agent in the diagnosis of SOD when performing 99mTc-HIDA scan and that the satisfactory response to the sublingual GTN could offer additional information in patients who have severe pain at the time the procedure or when presenting to the emergency unit because of biliary pain. And also in determining whether a trial of medical therapy may be used before considering surgery.

Keywords: GTN, HIDA, MORPHINE, SOD

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Authors: Joanna Grzybowska, Magdalena Igras, Mariusz Ziółko

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Association rule learning is an approach for discovering interesting relationships in large databases. The analysis of relations, invisible at first glance, is a source of new knowledge which can be subsequently used for prediction. We used this data mining technique (which is an automatic and objective method) to learn about interesting affects associations in a corpus of emergency phone calls. We also made an attempt to match revealed rules with their possible situational context. The corpus was collected and subjectively annotated by two researchers. Each of 3306 recordings contains information on emotion: (1) type (sadness, weariness, anxiety, surprise, stress, anger, frustration, calm, relief, compassion, contentment, amusement, joy) (2) valence (negative, neutral, or positive) (3) intensity (low, typical, alternating, high). Also, additional information, that is a clue to speaker’s emotional state, was annotated: speech rate (slow, normal, fast), characteristic vocabulary (filled pauses, repeated words) and conversation style (normal, chaotic). Exponentially many rules can be extracted from a set of items (an item is a previously annotated single information). To generate the rules in the form of an implication X → Y (where X and Y are frequent k-itemsets) the Apriori algorithm was used - it avoids performing needless computations. Then, two basic measures (Support and Confidence) and several additional symmetric and asymmetric objective measures (e.g. Laplace, Conviction, Interest Factor, Cosine, correlation coefficient) were calculated for each rule. Each applied interestingness measure revealed different rules - we selected some top rules for each measure. Owing to the specificity of the corpus (emergency situations), most of the strong rules contain only negative emotions. There are though strong rules including neutral or even positive emotions. Three examples of the strongest rules are: {sadness} → {anxiety}; {sadness, weariness, stress, frustration} → {anger}; {compassion} → {sadness}. Association rule learning revealed the strongest configurations of affects (as well as configurations of affects with affect-related information) in our emergency phone calls corpus. The acquired knowledge can be used for prediction to fulfill the emotional profile of a new caller. Furthermore, a rule-related possible context analysis may be a clue to the situation a caller is in.

Keywords: data mining, emergency phone calls, emotional profiles, rules

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Authors: Can Huang, Xiaoliang Wang, Qingquan Liu

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Soil‒water coupling is an important process in landslide-generated impulse waves (LGIW) problems, accompanied by large deformation of soil, strong interface coupling and three-dimensional effect. A meshless particle method, smooth particle hydrodynamics (SPH) has great advantages in dealing with complex interface and multiphase coupling problems. This study presents an improved soil‒water coupled model to simulate LGIW problems based on an open source code DualSPHysics (v4.0). Aiming to solve the low efficiency problem in modeling real large-scale LGIW problems, graphics processing unit (GPU) acceleration technology is implemented into this code. An experimental example, subaerial landslide-generated water waves, is simulated to demonstrate the accuracy of this model. Then, the Huangtian LGIW, a real large-scale LGIW problem is modeled to reproduce the entire disaster chain, including landslide dynamics, fluid‒solid interaction, and surge wave generation. The convergence analysis shows that a particle distance of 5.0 m can provide a converged landslide deposit and surge wave for this example. Numerical simulation results are in good agreement with the limited field survey data. The application example of the Huangtian LGIW provides a typical reference for large-scale LGIW assessments, which can provide reliable information on landslide dynamics, interface coupling behavior, and surge wave characteristics.

Keywords: soil‒water coupling, landslide-generated impulse wave, large-scale, SPH

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Authors: Aravind Mohan Krishnan

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This paper identifies a research gap in the literature on tourism entrepreneurship in Malawi, Africa, and investigates how entrepreneurs from the Malawian tourism sector discover and exploit business opportunities. In particular, the importance of prior experience and business networks in the opportunity development process is debated. Another area of empirical research examined here is the opportunity recognition-venture creation sequence. While Malawi presents fruitful business opportunities, exploiting these opportunities into fully realized business ideas is a real challenge due to the country’s difficult business environment and poor promotional and marketing efforts. The study concludes by calling for further research in Sub-Saharan Africa in order to develop our understanding of entrepreneurship in this (African) context.

Keywords: entrepreneurship, Malawi, opportunities, tourism

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Authors: Victor Rocha Carvalho

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The Bonner Sphere Spectrometry was used to obtain the average energy, the fluence rate, and radioprotection quantities such as the personal and ambient dose equivalent of the ²⁴¹AmLi and ²⁴¹AmF isotopic neutron sources used in the Neutron Metrology Laboratory - LN. The counts of the sources were performed with six different spherical moderators around the detector. Through this, the neutron spectrum was obtained by means of the software named NeuraLN, developed by the LN, that uses the neural networks technique. The 241AmLi achieved a result close to the literature, and 241AmF, which contains few published references, acquired a result with a slight variation from the literature. Therefore, besides fulfilling its objective, the work raises questions about a possible standard of the ²⁴¹AmLi and about the lack of work with the ²⁴¹AmF.

Keywords: nuclear physics, neutron metrology, neutron spectrometry, bonner sphere spectrometers

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