Search results for: healthcare data security

Authors: Jacob Msughter Gwa, Rhys Williams

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It is widely known that food security is a major concern in Sub-Saharan Africa. In many regions, including Nigeria, this is due to an agriculture-old problem of soil erosion beyond replacement levels. It seems that the use of fertilizer would be an immediate solution as it can boost agricultural productivity, and low agricultural productivity is attributed to the low use of fertilizers in Nigeria. The Government of Nigeria has been addressing the challenges of food shortage but with limited success. The utilisation of a practical and efficient subsidy programme in addressing this issue seems to be needed. However, the problem of procurement and distribution changes from one stage of subsidy to another. This paper looks at the difference between the ideal and the actual implementation of agricultural fertilizer policies in Nigeria, as it currently runs the risk of meeting required standards on paper but missing the desired real outcomes, and recognises the need to close the gap between the paper work and the realities on the ground.

Keywords: agricultural productivity, fertilizer distribution, fertilizer procurement, Nigeria

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Authors: Hongliang Ding, Ziqu Ouyang

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Under the basic national conditions that the energy structure is dominated by coal, it is of great significance to realize deep and flexible peak shaving of boilers in pulverized coal power plants, and maximize the consumption of renewable energy in the power grid, to ensure China's energy security and scientifically achieve the goals of carbon peak and carbon neutrality. With the promising self-preheating combustion technology, which had the potential of broad-load regulation and rapid response to load changes, this study mainly investigated the different load operation and rapid load-change characteristics of pulverized coal combustion. Four effective load-stabilization bases were proposed according to preheating temperature, coal gas composition (calorific value), combustion temperature (spatial mean temperature and mean square temperature fluctuation coefficient), and flue gas emissions (CO and NOx concentrations), on the basis of which the load-change rates were calculated to assess the load response characteristics. Due to the improvement of the physicochemical properties of pulverized coal after preheating, stable ignition and combustion conditions could be obtained even at a low load of 25%, with a combustion efficiency of over 97.5%, and NOx emission reached the lowest at 50% load, with the concentration of 50.97 mg/Nm3 (@6%O2). Additionally, the load ramp-up stage displayed higher load-change rates than the load ramp-down stage, with maximum rates of 3.30 %/min and 3.01 %/min, respectively. Furthermore, the driving force formed by high step load was conducive to the increase of load-change rate. The rates based on the preheating indicator attained the highest value of 3.30 %/min, while the rates based on the combustion indicator peaked at 2.71 %/min. In comparison, the combustion indicator accurately described the system’s combustion state and load changes, whereas the preheating indicator was easier to acquire, with a higher load-change rate, hence the appropriate evaluation strategy should depend on the actual situation. This study verified a feasible method for deep and flexible peak shaving of coal-fired power units, further providing basic data and technical supports for future engineering applications.

Keywords: clean coal combustion, load-change rate, peak shaving, self-preheating

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Authors: Wesam Hamed

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This paper contributes to the existing literature by investigating the impact of political risks on the capital adequacy ratio in the banking sector of Gulf Cooperation Council (GCC) countries, which is the first attempt for this nexus to the best of our knowledge. The dynamic panel data model (System‐GMM) showed that political risks significantly decrease the capital adequacy ratio in the banking sector. For this purpose, we used political risks, bank-specific, profitability, and macroeconomic variables that are utilized from the data stream database for the period 2005-2017. The results also actively support the “too big to fail” hypothesis. Finally, the robustness results confirm the conclusions derived from the baseline System‐GMM model.

Keywords: capital adequacy ratio, system GMM, GCC, political risks

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Authors: Abdolghader Pourali, Mohammad V. Malakooti, Muhammad Hussein Yektaie

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A mobile payment system in mobile e-commerce generally have high security so that the user can trust it for doing business deals, sales, paying financial transactions, etc. in the mobile payment system. Since an architecture or payment model in e-commerce only shows the way of interaction and collaboration among users and mortgagers and does not present any evaluation of effectiveness and confidence about financial transactions to stakeholders. In this paper, we try to present a detailed assessment of the reliability of a mobile payment model in the mobile e-commerce using formal models and colored Petri nets. Finally, we demonstrate that the reliability of this system has high value (case study: a secure payment model in mobile commerce.

Keywords: reliability, colored Petri net, assessment, payment models, m-commerce

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Authors: W. S. Hsu, S. W. Chen, Y. T. Ku, Y. Chiang, J. R. Wang , J. H. Yang, C. Shih

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ALOHA code was used to calculate the concentration under the CO₂ storage burst condition for Maanshan nuclear power plant (NPP) in this study. Five main data are input into ALOHA code including location, building, chemical, atmospheric, and source data. The data from Final Safety Analysis Report (FSAR) and some reports were used in this study. The ALOHA results are compared with the failure criteria of R.G. 1.78 to confirm the habitability of control room. The result of comparison presents that the ALOHA result is below the R.G. 1.78 criteria. This implies that the habitability of control room can be maintained in this case. The sensitivity study for atmospheric parameters was performed in this study. The results show that the wind speed has the larger effect in the concentration calculation.

Keywords: PWR, ALOHA, habitability, Maanshan

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Authors: Mayuri Gandhi, Nayan Agrawal, Harshita Bhatia

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In the present work, cerium fluoride (CeF3) was selected as the host material because of its high density, fast response and high radiation resistance, efficient absorption and energy transfer by host (to activator). For the synthesis of CeF3 nanoparticles doped with Sm3+ ion, co-precipitation route was employed. Thus for optimum results, concentration dependent studies of the fluorescence of Sm3+ was carried out. The photoluminescence gave emissions in both visible as well as the NIR region and therefore it can have its application in solar cells, where it can absorb a large spectrum of energy. CeF3:Sm3+ nanoparticles were carefully incorporated in a suitable polymer matrix in order to demonstrate a variety of applications to improve the performance of the polymer materials and use it to develop high grade optoelectronic devices such as LEDs, security labelling, lasers, displays, biological imaging, etc.

Keywords: bioimaging, cerium fluoride, NIR emission, samarium

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Authors: Yogita Mishra, Arijit Roy, Dhruval Bhavsar

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The study estimates the nitrogen concentration in selected vegetation community’s i.e. chir pine (pinusroxburghii) by using hyperspectral satellite data and also identified the appropriate spectral bands and nitrogen indices. The Short Wave InfraRed reflectance spectrum at 1790 nm and 1680 nm shows the maximum possible absorption by nitrogen in selected species. Among the nitrogen indices, log normalized nitrogen index performed positively and negatively too. The strong positive correlation is taken out from 1510 nm and 760 nm for the pinusroxburghii for leaf nitrogen concentration and leaf nitrogen mass while using NDNI. The regression value of R² developed by using linear equation achieved maximum at 0.7525 for the analysis of satellite image data and R² is maximum at 0.547 for ground truth data for pinusroxburghii respectively.

Keywords: hyperspectral, NDNI, nitrogen concentration, regression value

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Authors: K. Hołda, D. Śliwa, K. Daniec, A. Nawrat

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This article was created as part of the developed master's thesis. It attempts to present a newly developed device, which will support the work of specialists dealing with broadly understood cybersecurity terms. The device is contrived to automate security tests. In addition, it simulates potential cyberattacks in the most realistic way possible, without causing permanent damage to the network, in order to maximize the quality of the subsequent corrections to the tested network systems. The proposed solution is a fully operational prototype created from commonly available electronic components and a single board computer. The focus of the following article is not only put on the hardware part of the device but also on the theoretical and applicatory way in which implemented cybersecurity tests operate and examples of their results.

Keywords: Raspberry Pi, ethernet, automated cybersecurity tests, ARP, DNS, backdoor, TCP, password sniffing

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Authors: Laurent Thiry, Michel Hassenforder

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This paper presents a general approach to implement efficient queries’ interpreters in a functional programming language. Indeed, most of the standard tools actually available use an imperative and/or object-oriented language for the implementation (e.g. Java for Jena-Fuseki) but other paradigms are possible with, maybe, better performances. To proceed, the paper first explains how to model data structures and queries in a functional point of view. Then, it proposes a general methodology to get performances (i.e. number of computation steps to answer a query) then it explains how to integrate some optimization techniques (short-cut fusion and, more important, data transformations). It then compares the functional server proposed to a standard tool (Fuseki) demonstrating that the first one can be twice to ten times faster to answer queries.

Keywords: data transformation, functional programming, information server, optimization

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Authors: Yogita M. Ahire, Nedal M. Mohammed, Ahmed A. Hamoud

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Scientific computation outsourcing is gaining popularity because it allows customers with limited computing resources and storage devices to outsource complex computation workloads to more powerful service providers. However, it raises some security and privacy concerns and challenges, such as customer input and output privacy, as well as cloud cheating behaviors. This study was motivated by these concerns and focused on privacy-preserving Two-Point Boundary Value Problems (BVP) as a common and realistic instance for verifiable safe multiparty computing. We'll look at the safe and verifiable schema with correctness guarantees by utilizing standard multiparty approaches to compute the result of a computation and then solely using verifiable ways to check that the result was right.

Keywords: verifiable computing, cloud computing, secure and privacy BVP, secure computation outsourcing

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Authors: Jianqin Qu

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This paper proposes a rigid point set matching algorithm in arbitrary dimensions based on the idea of symmetric covariant function. A group of functions of the points in the set are formulated using rigid invariants. Each of these functions computes a pair of correspondence from the given point set. Then the computed correspondences are used to recover the unknown rigid transform parameters. Each computed point can be geometrically interpreted as the weighted mean center of the point set. The algorithm is compact, fast, and dimension free without any optimization process. It either computes the desired transform for noiseless data in linear time, or fails quickly in exceptional cases. Experimental results for synthetic data and 2D/3D real data are provided, which demonstrate potential applications of the algorithm to a wide range of problems.

Keywords: covariant point, point matching, dimension free, rigid registration

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Authors: Mehtap Öztürk, Adem Öğüt, Emine Öğüt

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Leader member exchange is considered as relationship-based approach to leadership. The focal point of this theory is that effective leadership processes occur when leaders and followers are able to develop mature leadership relationships and thus gain access to a variety of benefits these relationships bring. In this context, it can be claimed that the quality of leader member exchange appears to have a strong affect on perceived organizational support and reduce turnover intention. The purpose of this study is to determine the relationship between the levels of leader member exchange, perceived organizational support and turnover intention on the employees of a health institution operating in the province of Konya. A field study based on survey method on 134 physicians who are employees of a health institution operating in the mentioned sample. In accordance with this purpose, it has been observed that there is a negative and statistically significant relationship between leader member exchange and turnover intention. Furthermore, it has been also realized that there is a negative and statistically significant relationship between perceived organizational support and turnover intention.

Keywords: leader member exchange, perceived organizational support, social exchange theory, turnover intention

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Authors: Anila Syed, Manzoor Ahmad

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The relationship between United States and India has transformed from estrangement to wider engagement since 2004. With the convergence of interests and shared values both the US and India came close towards each other and evolved strategic partnership through civil nuclear cooperation. This paper analyze the cost and benefit of strategic partnership with India for US, the impact of India’s emergence as regional power on South Asian balance of power and its impact on Pak-US relationship. It also focuses on security structure of the region and challenges for the US to maintain strategic partnership with two rival states (India and Pakistan). The work also gives some recommendations for balancing power in the region in order to ensure durable peace not only between India and Pakistan but also in south Asia.

Keywords: US-India strategic partnership, civil-nuclear cooperation, balance of power, impacts on Pak-US relationship

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Authors: Hossein Jafari, Xiangfang Li, Lijun Qian, Alexander Aved, Timothy Kroecker

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Traditionally in sensor networks and recently in the Internet of Things, numerous heterogeneous sensors are deployed in distributed manner to monitor a phenomenon that often can be model by an underlying stochastic process. The big time-series data collected by the sensors must be analyzed to detect change in the stochastic process as quickly as possible with tolerable false alarm rate. However, sensors may have different accuracy and sensitivity range, and they decay along time. As a result, the big time-series data collected by the sensors will contain uncertainties and sometimes they are conflicting. In this study, we present a framework to take advantage of Evidence Theory (a.k.a. Dempster-Shafer and Dezert-Smarandache Theories) capabilities of representing and managing uncertainty and conflict to fast change detection and effectively deal with complementary hypotheses. Specifically, Kullback-Leibler divergence is used as the similarity metric to calculate the distances between the estimated current distribution with the pre- and post-change distributions. Then mass functions are calculated and related combination rules are applied to combine the mass values among all sensors. Furthermore, we applied the method to estimate the minimum number of sensors needed to combine, so computational efficiency could be improved. Cumulative sum test is then applied on the ratio of pignistic probability to detect and declare the change for decision making purpose. Simulation results using both synthetic data and real data from experimental setup demonstrate the effectiveness of the presented schemes.

Keywords: CUSUM, evidence theory, kl divergence, quickest change detection, time series data

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Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

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The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

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Authors: Andrew J. Zacharias

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The forest garden approach (FGA) was established by Trees for the Future (TREES) over the organization’s 30 years of agroforestry projects in Sub-Saharan Africa. This method transforms traditional agricultural systems into highly managed gardens that produce food and marketable products year-round. The effects of the FGA on food security, dietary diversity, and economic resilience have been measured closely, and TREES has begun to closely monitor the environmental impacts through the use of sensors mounted on unmanned aerial vehicles, commonly known as 'drones'. These drones collect thousands of pictures to create 3-D models in both the visible and the near-infrared wavelengths. Analysis of these models provides TREES with quantitative and qualitative evidence of improvements to the annual above-ground biomass and leaf area indices, as measured in-situ using NDVI calculations.

Keywords: agroforestry, biomass, drones, NDVI

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Authors: Tabinda Sadiq, Tehmina Ashfaq Qazi, Hoor Shumail

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Recently, the advent of emerging technology has created an emerging generation of restaurant marketing. It explores the aspects that influence customers’ decision-making process in selecting a restaurant after reading food bloggers' reviews online. The motivation behind this research is to investigate the correlation between the credibility of the source and their attitude toward restaurant visits. The researcher collected the data by distributing a survey questionnaire through google forms by employing the Source credibility theory. Non- probability purposive sampling technique was used to collect data. The questionnaire used a predeveloped and validated scale by Ohanian to measure the relationship. Also, the researcher collected data from 250 respondents in order to investigate the influence of food bloggers on Gen Z's decision-making process. SPSS statistical version 26 was used for statistical testing and analyzing the data. The findings of the survey revealed that there is a moderate positive correlation between the variables. So, it can be analyzed that food bloggers do have an impact on Generation Z's decision making process.

Keywords: credibility, decision making, food bloggers, generation z, e-wom

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Authors: Pornpimol Chaiwuttisak

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The study aims to compare the performance of the logistics for Thailand’s wholesale and retail trade industries (except motor vehicles, motorcycle, and stalls) by using data (data envelopment analysis). Thailand Standard Industrial Classification in 2009 (TSIC - 2009) categories that industries into sub-group no. 45: wholesale and retail trade (except for the repair of motor vehicles and motorcycles), sub-group no. 46: wholesale trade (except motor vehicles and motorcycles), and sub-group no. 47: retail trade (except motor vehicles and motorcycles. Data used in the study is collected by the National Statistical Office, Thailand. The study consisted of four input factors include the number of companies, the number of personnel in logistics, the training cost in logistics, and outsourcing logistics management. Output factor includes the percentage of enterprises having inventory management. The results showed that the average relative efficiency of small-sized enterprises equals to 27.87 percent and 49.68 percent for the medium-sized enterprises.

Keywords: DEA, wholesales and retails, logistics, Thailand

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Authors: Folajinmi Oluwasina, Towolawi Adetayo, Kate Ssamula, Penninah Iutung, Daniel Reijer

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Objective: Routine HIV screening has been promoted as an essential component of efforts to reduce incidence, morbidity, and mortality. The objectives of this study were to identify the optimal annual volume needed to realize the public health goals of HIV screening in the AIDS Healthcare Foundation supported hospitals and establish an implementation process to realize that optimal annual volume. Methods: Starting in 2011 a program was established to routinize HIV screening within communities and government hospitals. In 2016 Five-years of HIV screening data were reviewed to identify the optimal annual proportions of age-eligible patients screened to realize the public health goals of reducing new diagnoses and ending late-stage diagnosis (tracked as concurrent HIV/AIDS diagnosis). Analysis demonstrated that rates of new diagnoses level off when 42% of age-eligible patients were screened, providing a baseline for routine screening efforts; and concurrent HIV/AIDS diagnoses reached statistical zero at screening rates of 70%. Annual facility based targets were re-structured to meet these new target volumes. Restructuring efforts focused on right-sizing HIV screening programs to align and transition programs to integrated HIV screening within standard medical care and treatment. Results: Over one million patients were screened for HIV during the five years; 16, 033 new HIV diagnoses and access to care and treatment made successfully for 82 % (13,206), and concurrent diagnosis rates went from 32.26% to 25.27%. While screening rates increased by 104.7% over the 5-years, volume analysis demonstrated that rates need to further increase by 62.52% to reach desired 20% baseline and more than double to reach optimal annual screening volume. In 2011 facility targets for HIV screening were increased to reflect volume analysis, and in that third year, 12 of the 19 facilities reached or exceeded new baseline targets. Conclusions and Recommendation: Quantifying targets against routine HIV screening goals identified optimal annual screening volume and allowed facilities to scale their program size and allocate resources accordingly. The program transitioned from utilizing non-evidence based annual volume increases to establishing annual targets based on optimal volume analysis. This has allowed efforts to be evaluated on the ability to realize quantified goals related to the public health value of HIV screening. Optimal volume analysis helps to determine the size of an HIV screening program. It is a public health tool, not a tool to determine if an individual patient should receive screening.

Keywords: HIV screening, optimal volume, HIV diagnosis, routine

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Authors: Yiqi Zhu, Jean Francois Trani, Rameez Ulhassan

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Extreme weather phenomena increased by 46% between 2007 and 2017 and have become more intense with the rise in global average temperatures. This increased intensity of climate variations often induces humanitarian crises and particularly affects vulnerable populations in low- and middle-income countries (LMICs). Expectant and lactating mothers are among the most vulnerable groups. Pakistan ranks 10th among the most affected countries by climate disasters. In 2022, monsoon floods submerged a third of the country, causing the loss of 1,500 lives. Approximately 650,000 expectant and lactating mothers faced systematic stress from climatic disasters. Our study used participatory methods to investigate the systematic impact of climatic disasters on maternal health. In March 2023, we conducted six Group Model Building (GMB) workshops with healthcare workers, fathers, and mothers separately in two of the most affected areas in Pakistan. This study was approved by the Islamic Relief Research Review Board. GMB workshops consist of three sessions. In the first session, participants discussed the factors that impact maternal health. After identifying the factors, they discussed the connections among them and explored the system structures that collectively impact maternal health. Based on the discussion, a causal loop diagram (CLD) was created. Finally, participants discussed action ideas that could improve the system to enhance maternal health. Based on our discussions and the causal loop diagram, we identified interconnected factors at the family, community, and policy levels. Mothers and children are directly impacted by three interrelated factors: food insecurity, unstable housing, and lack of income. These factors create a reinforcing cycle that negatively affects both mothers and newborns. After the flood, many mothers were unable to produce sufficient breastmilk due to their health status. Without breastmilk and sufficient food for complementary feeding, babies tend to get sick in damp and unhygienic environments resulting from temporary or unstable housing. When parents take care of sick children, they miss out on income-generating opportunities. At the community level, the lack of access to clean water and sanitation (WASH) and maternal healthcare further worsens the situation. Structural failures such as a lack of safety nets and programs associated with flood preparedness make families increasingly vulnerable with each disaster. Several families reported that they had not fully recovered from a flood that occurred ten years ago, and this latest disaster destroyed their lives again. Although over twenty non-profit organizations are working in these villages, few of them provide sustainable support. Therefore, participants called for systemic changes in response to the increasing frequency of climate disasters. The study reveals the systematic vulnerabilities of mothers and children after climatic disasters. The most vulnerable populations are often affected the most by climate change. Collaborative efforts are required to improve water and forest management, strengthen public infrastructure, increase access to WASH, and gradually build climate-resilient communities. Governments, non-governmental organizations, and the community should work together to develop and implement effective strategies to prevent, mitigate, and adapt to climate change and its impacts.

Keywords: climatic disasters, maternal health, Pakistan, systematic impact, flood, disaster relief.

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Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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Authors: S. K. Gupta, Richa Bansal

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In a deregulated power system structure, power producers, and customers share a common transmission network for wheeling power from the point of generation to the point of consumption. All parties in this open access environment may try to purchase the energy from the cheaper source for greater profit margins, which may lead to overloading and congestion of certain corridors of the transmission network. This may result in violation of line flow, voltage and stability limits and thereby undermine the system security. Utilities therefore need to determine adequately their Available Transfer Capability (ATC) to ensure that system reliability is maintained while serving a wide range of bilateral and multilateral transactions. This paper presents power transfer distribution factor based on AC load flow for the determination and enhancement of ATC. The study has been carried out for IEEE 24 bus Reliability Test System.

Keywords: available transfer capability, FACTS devices, power transfer distribution factors, electric

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Authors: Ezrah Kipkirui Tonui, George Otieno Orwa

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A survey of 138 farmers was conducted in Rift valley, Kenya, in November and December 2013 in three counties (Uasin-gishu, Elgeyo-marakwet, and Tranzoia) to determine public knowledge and attitude towards genetically modified (GM) maize. Above two third (70%) of the respondents had knowledge of GM maize, mostly those educated and male. Female was found to be having low knowledge on GM maize. Public acknowledged the technology’s potential positive impacts, with more than 90% willing to adopt and more than 98% willing to buy GM seedlings at any given price. A small percentage less than 3% were of a negative opinion about willing to buy and adopt GM seeds. We conclude that GM technology has a role to play in food security in Kenya. However, the public needs more information about the technology, which can be provided through established sources of information and training. Finally, public knowledge and attitude on GM maize should be studied on a regular basis, and the survey population broadened to 47 counties.

Keywords: public, knowledge, attitudes, GM maize, Kenya

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Authors: Parvin Ghafarian, Mohammadreza Mohammadpur Panchah, Mehri Fallahi

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Synoptic patterns from surface up to tropopause are very important for forecasting the weather and atmospheric conditions. There are many tools to prepare and analyze these maps. Reanalysis data and the outputs of numerical weather prediction models, satellite images, meteorological radar, and weather station data are used in world forecasting centers to predict the weather. The forecasting extreme precipitating on the southern coast of the Caspian Sea (CS) is the main issue due to complex topography. Also, there are different types of climate in these areas. In this research, we used two reanalysis data such as ECMWF Reanalysis 5th Generation Description (ERA5) and National Centers for Environmental Prediction /National Center for Atmospheric Research (NCEP/NCAR) for verification of the numerical model. ERA5 is the latest version of ECMWF. The temporal resolution of ERA5 is hourly, and the NCEP/NCAR is every six hours. Some atmospheric parameters such as mean sea level pressure, geopotential height, relative humidity, wind speed and direction, sea surface temperature, etc. were selected and analyzed. Some different type of precipitation (rain and snow) was selected. The results showed that the NCEP/NCAR has more ability to demonstrate the intensity of the atmospheric system. The ERA5 is suitable for extract the value of parameters for specific point. Also, ERA5 is appropriate to analyze the snowfall events over CS (snow cover and snow depth). Sea surface temperature has the main role to generate instability over CS, especially when the cold air pass from the CS. Sea surface temperature of NCEP/NCAR product has low resolution near coast. However, both data were able to detect meteorological synoptic patterns that led to heavy rainfall over CS. However, due to the time lag, they are not suitable for forecast centers. The application of these two data is for research and verification of meteorological models. Finally, ERA5 has a better resolution, respect to NCEP/NCAR reanalysis data, but NCEP/NCAR data is available from 1948 and appropriate for long term research.

Keywords: synoptic patterns, heavy precipitation, reanalysis data, snow

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Authors: Argaw T. Gurmu, Muhammad N. Mahmood

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The objective of this research is to identify the architecture and construction management students’ learning challenges of the building measurement. This research used the survey data obtained collected from the students who completed the building measurement unit. NVivo qualitative data analysis software was used to identify relevant themes. The analysis of the qualitative data revealed the major learning difficulties such as inadequacy of practice questions for the examination, inability to work as a team, lack of detailed understanding of the prerequisite units, insufficiency of the time allocated for tutorials and incompatibility of lecture and tutorial schedules. The output of this research can be used as a basis for improving the teaching and learning activities in construction measurement units.

Keywords: building measurement, construction management, learning challenges, evaluate survey

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Authors: Ing-Jen Hung, Tzu-Chien Wang

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Nowadays, customers can interact with firms through miscellaneous online ads on different channels easily. In other words, customer now has innumerable options and limitless time to accomplish their commercial activities with firms, individualizing their own online customer journey. This kind of convenience emphasizes the importance of online advertisement allocation on different channels. Therefore, profound understanding of customer behavior can make considerable benefit from optimizing fund allocation on diverse ad channels. To achieve this objective, multiple firms utilize numerical methodology to create data-driven advertisement policy. In our research, we aim to exploit online customer click data to discover the correlations between each channel and their sequential relations. We use LSTM to deal with sequential property of our data and compare its accuracy with other non-sequential methods, such as CART decision tree, logistic regression, etc. Besides, we also classify our customers into several groups by their behavioral characteristics to perceive the differences between all groups as customer portrait. As a result, we discover distinct customer journey under each customer portrait. Our article provides some insights into marketing research and can help firm to formulate online advertising criteria.

Keywords: LSTM, customer journey, marketing, channel ads

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Authors: Safoin Aktaou, Aya Al Masri, Kamel Guerchouche, Malorie Martin, Fouad Maaloul

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Introduction: In the ‘Magnetic Resonance Imaging (MRI)’ department, all workers involved in preparing the patient, setting it up, tunnel cleaning, etc. are likely to be exposed to ‘ElectroMagnetic fields (EMF)’ emitted by the MRI device. Exposure to EMF can cause adverse radio-biological effects to workers. The purpose of this study is to propose an organizational process to manage and control EMF risks. Materials and methods: The study was conducted at seven MRI departments using machines with 1.5 and 3 Tesla magnetic fields. We assessed the exposure of each one by measuring the two electromagnetic fields (static and dynamic) at different distances from the MRI machine both inside and around the examination room. Measurement values were compared with British and American references (those of the UK's ‘Medicines and Healthcare Regulatory Agency (MHRA)’ and the ‘American Radiology Society (ACR)’). Results: Following the results of EMF measurements and their comparison with the recommendations of learned societies, a zoning system that adapts to needs of different MRI services across the country has been proposed. In effect, three risk areas have been identified within the MRI services. This has led to the development of a good practice guide related to the magnetic protection of MRI workers. Conclusion: The guide established by our study is a standard that allows MRI workers to protect themselves against the risk of electromagnetic fields.

Keywords: comparison with international references, measurement of electromagnetic fields, magnetic protection of workers, magnetic resonance imaging

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Authors: Jawad Taheri

Abstract:

This paper investigates the impact of foreign aid-funded development projects on corruption perception in Afghanistan, utilizing instrumental variable (IV) approaches in regression analysis setting. Seven sub-categories of development projects are examined in order to have a glance over comparative usefulness of each project. The study incorporates natural disaster indicators as exogenous variables to mitigate endogeneity concerns and control variables. The findings reveal significant associations between certain types of projects and corruption perception. Road and bridge construction, irrigation, and agriculture projects are found to decrease corruption perception, fostering optimism and trust within affected communities. Mosque construction and healthcare initiatives aligned with religious beliefs also contribute to reduced corruption perception. However, drinking water projects are associated with increased corruption perception, highlighting potential challenges in their implementation. The study emphasizes the importance of well-implemented projects, cultural contexts, and effective governance in mitigating corruption and fostering trust within communities. These findings contribute to a refined understanding of the relationship between development projects and corruption perception in Afghanistan.

Keywords: foreign aid, development projects, corruption perception, Afghanistan, instrumental variable analysis, survey of Afghan people (SAP), natural disasters, exogenous variation

Procedia PDF Downloads 68

Authors: M. Barsa

Abstract:

This paper argues that current liberal trade regimes have had the unfortunate effect of concentrating food production by area and by crop. While such hyper-specialization and standardization might be efficient under ordinary climate conditions, the increasing severity of climate shocks makes such a food production system especially vulnerable. Examining domestic US crop production, and the fact that similar patterns are evident worldwide, this paper explores the vulnerabilities of several major crops and suggests that the academic arguments surrounding increasing liberalization of trade are ill-suited to the climate challenges to come. Indeed, a case can be made that protectionist measures—especially by developing countries whose agricultural sectors are vulnerable to the cheap US and European exports—are increasingly necessary to scatter food production geographically and to retain a resilient diversity of crop varieties.

Keywords: climate change, crop resilience, diversity, international trade

Procedia PDF Downloads 126

Authors: Yalda Zarnegarnia, Shari Messinger

Abstract:

Receiver operating characteristic (ROC) curves have been widely used in medical research to illustrate the performance of the biomarker in correctly distinguishing the diseased and non-diseased groups. Correlated biomarker data arises in study designs that include subjects that contain same genetic or environmental factors. The information about correlation might help to identify family members at increased risk of disease development, and may lead to initiating treatment to slow or stop the progression to disease. Approaches appropriate to a case-control design matched by family identification, must be able to accommodate both the correlation inherent in the design in correctly estimating the biomarker’s ability to differentiate between cases and controls, as well as to handle estimation from a matched case control design. This talk will review some developed methods for ROC curve estimation in settings with correlated data from case control design and will discuss the limitations of current methods for analyzing correlated familial paired data. An alternative approach using Conditional ROC curves will be demonstrated, to provide appropriate ROC curves for correlated paired data. The proposed approach will use the information about the correlation among biomarker values, producing conditional ROC curves that evaluate the ability of a biomarker to discriminate between diseased and non-diseased subjects in a familial paired design.

Keywords: biomarker, correlation, familial paired design, ROC curve

Procedia PDF Downloads 234