Search results for: security features

Authors: Peter M. Maurer Maurer

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DGL is a context free grammar-based tool for generating random data. Many types of simulator input data require some computation to be placed in the proper format. For example, it might be necessary to generate ordered triples in which the third element is the sum of the first two elements, or it might be necessary to generate random numbers in some sorted order. Although DGL is universal in computational power, generating these types of data is extremely difficult. To overcome this problem, we have enhanced DGL to include features that permit direct computation within the structure of a context free grammar. The features have been implemented as special types of productions, preserving the context free flavor of DGL specifications.

Keywords: DGL, Enhanced Context Free Grammars, Programming Constructs, Random Data Generation

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Authors: Meysam Jamali, Ebrahim Moghimi, Zean Alabden Jafarpour

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Karst term is the determiner of a variety of areas or landforms and unique perspectives that have been formed in result of the ingredients dissolution of rocks constituter by natural waters. Shiraz area with an area of 5322km2 is located in the simple folded belt in the southern part of Zagros Mountain of Fars, and is surrounded with Limestone Mountains (Asmari formation). Shiraz area is located in Calcareous areas. The Infrastructure of this city is lime and absorbing wells that the city has, can influence on the Limestone dissolution and those accelerate its rate and increases the cavitation below the surface. Dasht-e Arjan is a graben, which has been created as the result of activity of two normal faults in its east and west sides. It is a complete sample of Karst plains (Polje) which has been created with the help of tectonic forces (fault) and dissolution process of water in Asmari limestone formation. It is located 60km. off south west of Shiraz (on Kazeroon-Shiraz road). In 1971, UNESCO has recognized this plain as a reserve of biosphere. It is considered as one of the world’s most beautiful geological phenomena, so that most of the world’s geologists are interested in visiting this place. The purpose of this paper is to identify and introduce landscapes of Karst features shiraz city and Dasht-e Arjan including Karst dissolution features (Lapiez, Karst springs, dolines, caves, underground caves, ponors, and Karst valleys), anticlines and synclines, and Arjan Lake, which are studied in this paper.

Keywords: Dasht-eArjan, fault, Karst features, polje, Shiraz city, Zagros

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Authors: Mariam Mtunguja, Henry Laswai, Yasinta Muzanilla, Joseph Ndunguru

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Starchy tuberous roots of cassava provide food for people but also find application in various industries. Recently there has been the focus of concentrated research efforts to fully exploit its potential as a sustainable multipurpose crop. High starch yield is the important trait for commercial cassava production for the starch industries. Furthermore, cyanide present in cassava root poses a health challenge in the use of cassava for food. Farming communities where cassava is a staple food, prefer bitter (high cyanogenic) varieties as protection from predators and thieves. As a result, food insecure farmers prefer growing bitter cassava. This has led to cyanide intoxication to this farming communities. Cassava farmers can benefit from marketing cassava to starch producers thereby improving their income and food security. This will decrease dependency on cassava as staple food as a result of increased income and be able to afford other food sources. To achieve this, adequate information is required on the right cassava cultivars and appropriate harvesting period so as to maximize cassava production and profitability. This study aimed at identifying suitable cassava cultivars and optimum time of harvest to maximize starch production. Six commonly grown cultivars were identified and planted in a complete random block design and further analysis was done to assess variation in physicochemical characteristics, starch yield and cyanogenic potentials across three environments. The analysis showed that there is a difference in physicochemical characteristics between landraces (p ≤ 0.05), and can be targeted to different industrial applications. Among landraces, dry matter (30-39%), amylose (11-19%), starch (74-80%) and reducing sugars content (1-3%) varied when expressed on a dry weight basis (p ≤ 0.05); however, only one of the six genotypes differed in crystallinity and mean starch granule particle size, while glucan chain distribution and granule morphology were the same. In contrast, the starch functionality features measured: swelling power, solubility, syneresis, and digestibility differed (p ≤ 0.05). This was supported by Partial least square discriminant analysis (PLS-DA), which highlighted the divergence among the cassavas based on starch functionality, permitting suggestions for the targeted uses of these starches in diverse industries. The study also illustrated genotypic difference in starch yield and cyanogenic potential. Among landraces, Kiroba showed potential for maximum starch yield (12.8 t ha-1) followed by Msenene (12.3 t ha-1) and third was Kilusungu (10.2 t ha-1). The cyanide content of cassava landraces was between 15 and 800 ppm across all trial sites. GGE biplot analysis further confirmed that Kiroba was a superior cultivar in terms of starch yield. Kilusungu had the highest cyanide content and average starch yield, therefore it can also be suitable for use in starch production.

Keywords: cyanogen, cassava starch, food security, starch yield

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Authors: Jessica Kate Simonds

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The last successful hijacking perpetrated by Somali pirates in 2012 represented a critical turning point for the identity and brand of Indian Ocean (IO) insecurity, coined in this paper as the era of the post-piratical. This paper explores the broadening of the PMSC business model to account and contribute to the design of a new IO security environment that prioritises foreign and insurgency drone activity and Houthi rebel operations as the main threat to merchant shipping in the post-2012 era. This study is situated within a longer history of analysing maritime insecurity and also contributes a bespoke conceptual framework that understands the sea as a space that is produced and reproduced relative to existing and emerging threats to merchant shipping based on bespoke models of information sharing and intelligence acquisition. This paper also makes a prominent empirical contribution by drawing on a post-positivist methodology, data drawn from original semi-structured interviews with senior maritime insurers and active merchant seafarers that is triangulated with industry-produced guidance such as the BMP series as primary data sources. Each set is analysed through qualitative discourse and content analysis and supported by the quantitative data sets provided by the IMB Piracy Reporting center and intelligence networks. This analysis reveals that mechanisms such as the IGP&I Maritime Security Committee and intelligence divisions of PMSC’s have driven the exchanges of knowledge between land and sea and thus the reproduction of the maritime security environment through new regulations and guidance to account dones, rebels and bombs as the key challenges in the IO, beyond piracy. A contribution of this paper is the argument that experts who may not be in the highest-profile jobs are the architects of maritime insecurity based on their detailed knowledge and connections to vessels in transit. This paper shares the original insights of those who have served in critical decision making spaces to demonstrate that the development and refinement of industry produced deterrence guidance that has been accredited to the mitigation of piracy, have shaped new editions such as BMP 5 that now serve to frame a new security environment that prioritises the mitigation of risks from drones and WBEID’s from both state and insurgency risk groups. By highlighting the experiences and perspectives of key players on both land and at sea, the key finding of this paper is outlining that as pirates experienced a financial boom by profiteering from their bespoke business model during the peak of successful hijackings, the private security market encountered a similar level of financial success and guaranteed risk environment in which to prospect business. Thus, the reproduction of the Indian Ocean as a maritime security environment reflects a new found purpose for PMSC’s as part of the broader conglomerate of maritime insurers, regulators, shipowners and managers who continue to redirect the security consciousness and IO brand of insecurity.

Keywords: maritime security, private security, risk intelligence, political geography, international relations, political economy, maritime law, security studies

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Authors: Bo Liu, Chi-Man Pun

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A novel technique for digital forgery detection by signal noise inconsistency is proposed in this paper. The forged area spliced from the other picture contains some features which may be inconsistent with the rest part of the image. Noise pattern and the level is a possible factor to reveal such inconsistency. To detect such noise discrepancies, the test picture is initially segmented into small pieces. The noise pattern and level of each segment are then estimated by using various filters. The noise features constructed in this step are utilized in energy-based graph cut to expose forged area in the final step. Experimental results show that our method provides a good illustration of regions with noise inconsistency in various scenarios.

Keywords: forgery detection, splicing forgery, noise estimation, noise

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Authors: Yuntao Liu, Lei Wang, Haoran Xia

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Machine learning has shown extensive applications in the development of classification models for autism spectrum disorder (ASD) using neural image data. This paper proposes a fusion multi-modal classification network based on a graph neural network. First, the brain is segmented into 116 regions of interest using a medical segmentation template (AAL, Anatomical Automatic Labeling). The image features of sMRI and the signal features of fMRI are extracted, which build the node and edge embedding representations of the brain map. Then, we construct a dynamically updated brain map neural network and propose a method based on a dynamic brain map adjacency matrix update mechanism and learnable graph to further improve the accuracy of autism diagnosis and recognition results. Based on the Autism Brain Imaging Data Exchange I dataset(ABIDE I), we reached a prediction accuracy of 74% between ASD and TD subjects. Besides, to study the biomarkers that can help doctors analyze diseases and interpretability, we used the features by extracting the top five maximum and minimum ROI weights. This work provides a meaningful way for brain disorder identification.

Keywords: autism spectrum disorder, brain map, supervised machine learning, graph network, multimodal data, model interpretability

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Authors: Mohamed Alimoussa, Alice Porebski, Nicolas Vandenbroucke, Rachid Oulad Haj Thami, Sana El Fkihi

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Color and texture are highly discriminant visual cues that provide an essential information in many types of images. Color texture representation and classification is therefore one of the most challenging problems in computer vision and image processing applications. Color textures can be represented in different color spaces by using multiple image descriptors which generate a high dimensional set of texture features. In order to reduce the dimensionality of the feature set, feature selection techniques can be used. The goal of feature selection is to find a relevant subset from an original feature space that can improve the accuracy and efficiency of a classification algorithm. Traditionally, feature selection is focused on removing irrelevant features, neglecting the possible redundancy between relevant ones. This is why some feature selection approaches prefer to use feature clustering analysis to aid and guide the search. These techniques can be divided into two categories. i) Feature clustering-based ranking algorithm uses feature clustering as an analysis that comes before feature ranking. Indeed, after dividing the feature set into groups, these approaches perform a feature ranking in order to select the most discriminant feature of each group. ii) Feature clustering-based subset search algorithms can use feature clustering following one of three strategies; as an initial step that comes before the search, binded and combined with the search or as the search alternative and replacement. In this paper, we propose a new feature clustering-based sequential selection approach for the purpose of color texture representation and classification. Our approach is a three step algorithm. First, irrelevant features are removed from the feature set thanks to a class-correlation measure. Then, introducing a new automatic feature clustering algorithm, the feature set is divided into several feature clusters. Finally, a sequential search algorithm, based on a filter model and a separability measure, builds a relevant and non redundant feature subset: at each step, a feature is selected and features of the same cluster are removed and thus not considered thereafter. This allows to significantly speed up the selection process since large number of redundant features are eliminated at each step. The proposed algorithm uses the clustering algorithm binded and combined with the search. Experiments using a combination of two well known texture descriptors, namely Haralick features extracted from Reduced Size Chromatic Co-occurence Matrices (RSCCMs) and features extracted from Local Binary patterns (LBP) image histograms, on five color texture data sets, Outex, NewBarktex, Parquet, Stex and USPtex demonstrate the efficiency of our method compared to seven of the state of the art methods in terms of accuracy and computation time.

Keywords: feature selection, color texture classification, feature clustering, color LBP, chromatic cooccurrence matrix

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Authors: Nareshkumar Harale, B. B. Meshram

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The continued exponential growth of successful cyber intrusions against today’s businesses has made it abundantly clear that traditional perimeter security measures are no longer adequate and effective. We evolved the network trust architecture from trust-untrust to Zero-Trust, With Zero Trust, essential security capabilities are deployed in a way that provides policy enforcement and protection for all users, devices, applications, data resources, and the communications traffic between them, regardless of their location. Information exchange over the Internet, in spite of inclusion of advanced security controls, is always under innovative, inventive and prone to cyberattacks. TCP/IP protocol stack, the adapted standard for communication over network, suffers from inherent design vulnerabilities such as communication and session management protocols, routing protocols and security protocols are the major cause of major attacks. With the explosion of cyber security threats, such as viruses, worms, rootkits, malwares, Denial of Service attacks, accomplishing efficient and effective intrusion detection and prevention is become crucial and challenging too. In this paper, we propose a design and analysis model for next generation network intrusion detection and protection system as part of layered security strategy. The proposed system design provides intrusion detection for wide range of attacks with layered architecture and framework. The proposed network intrusion classification framework deals with cyberattacks on standard TCP/IP protocol, routing protocols and security protocols. It thereby forms the basis for detection of attack classes and applies signature based matching for known cyberattacks and data mining based machine learning approaches for unknown cyberattacks. Our proposed implemented software can effectively detect attacks even when malicious connections are hidden within normal events. The unsupervised learning algorithm applied to network audit data trails results in unknown intrusion detection. Association rule mining algorithms generate new rules from collected audit trail data resulting in increased intrusion prevention though integrated firewall systems. Intrusion response mechanisms can be initiated in real-time thereby minimizing the impact of network intrusions. Finally, we have shown that our approach can be validated and how the analysis results can be used for detecting and protection from the new network anomalies.

Keywords: network intrusion detection, network intrusion prevention, association rule mining, system analysis and design

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Authors: Obinna Emmanuel Nkomadu

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The sea attracts many criminal activities including drug trafficking. The illicit traffic in narcotic drugs and psychotropic substances by sea poses a serious threat to maritime security globally. The seizure of drugs, particularly, on the African continent is on the raise. In terms of Southern Africa, South Africa is a major transit point for Latin American drugs and South Africa is the largest market for illicit drugs entering the Southern African region. Nigeria and South Africa have taken a number of steps to address this scourge, but, despite those steps, drugs trafficking at sea continues. For that reason and to combat a number of other threats to maritime security around the continent, a substantial number of AU members in 2016 adopted the African Charter on Maritime Security and Safety and Development in Africa (“the Charter”). However, the Charter is yet to come into force due to the number of States required to accede or ratify the Charter. This paper set out the pre-existing international instruments on drugs, to ascertain the domestic laws of Nigeria and South Africa relating to drugs with the relevant provisions of the Lomé Charter in order to establish whether any legal steps are required to ensure that Nigeria and South Africa comply with its obligations under the Charter. Indeed, should Nigeria and South Africa decide to ratify it and should it come into force, both States must cooperate with other relevant States in establishing policies, as well as a regional and continental institutions, and ensure the implementation of such policies. The paper urged the States to urgently ratify the Charter as it is a step in the right direction in the prevention and repression of drugs trafficking on the African maritime domain.

Keywords: cooperation against drugs trafficking at sea, Lomé Charter, maritime security, Nigerian and South Africa legislation on drugs

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Authors: Anders Troedsson

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For us humans, risks are intimately linked to human vulnerabilities - where there is vulnerability, there is potentially insecurity, and risk. Reducing vulnerability through compensatory measures means increasing security and decreasing risk. The paper suggests that a meaningful way to approach the study of risks (including threats, assaults, crisis etc.), is to understand the vulnerabilities these external phenomena evoke in humans. As is argued, the basis of risk evaluation, as well as responses, is the more or less subjective perception by the individual person, or a group of persons, exposed to the external event or phenomena in question. This will be determined primarily by the vulnerability or vulnerabilities that the external factor are perceived to evoke. In this way, risk perception is primarily an inward dynamic, rather than an outward one. Therefore, a route towards an understanding of the perception of risks, is a closer scrutiny of the vulnerabilities which they can evoke, thereby approaching an understanding of what in the paper is called the essence of risk (including threat, assault etc.), or that which a certain perceived risk means to an individual or group of individuals. As a necessary basis for gauging the wide spectrum of potential risks and their meaning, the paper proposes a model of human vulnerabilities, drawing from i.a. a long tradition of needs theory. In order to account for the subjectivity factor, which mediates between the innate vulnerabilities on the one hand, and the event or phenomenon out there on the other hand, an ensuing ontological discussion about the timespace characteristics of risk/threat/assault as perceived by humans leads to the positing of two dimensions. These two dimensions are applied on the vulnerabilities, resulting in a modelling effort featuring four realms of vulnerabilities which are related to each other and together represent a dynamic whole. In approaching the problem of risk perception, the paper thus defines the relevant realms of vulnerabilities, depicting them as a dynamic whole. With reference to a substantial body of literature and a growing international policy trend since the 1990s, this model is put in the language of human security - a concept relevant not only for international security studies and policy, but also for other academic disciplines and spheres of human endeavor.

Keywords: human security, timespace, vulnerabilities, risk perception

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Authors: Debby Rizqie Amelia Gustin, Purnomo Yusgiantoro

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Hydrocarbon energy is still pivotal to today’s economy, but its existence is continually declining. Thus, preserving future energy supply has become the national interest of many countries, which they cater in various way, from importing to expansion and occupation. Underwater of Natuna islands in Indonesia deposits great amount of natural gas reserved, numbered to 46 TCF (trillion cubic feet), which is highly potential to meet Indonesia future energy demand. On the other hand, there could be a possibility that others also seek this natural resources. Natuna is located in the borderline of Indonesia, directly adjacent to the South China Sea, an area which is prolonged to conflict. It is a challenge for Indonesia government to preserve their energy deposit in Natuna islands and to response accordingly if the tension in South China Sea rises. This paper examines that nowadays defense and border security is not only a matter of guarding a country from foreign invasion, but also securing its resources accumulated on the borderline. Countries with great amount of energy deposits on their borderline need to build up their defense capacity continually, to ensure their territory along with their energy deposits is free from any interferences.

Keywords: border security, defense, energy, national interest, threat

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Authors: Shienna Marie Esteban

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The economic growth experience of the Philippines is one of the fastest in Asia. However, the said growth has not yet trickled down to every Filipino. This is evident to agricultural-dependent population. Moreover, the contribution of the agriculture sector to GDP has been dwindling while large number of labor force is still dependent on a relatively small share of GDP. As a result, poverty incidence worsened among rural poor causing hunger and malnutrition. Therefore, the existing agricultural policies in the Philippines are pushing to achieve greater food production and productivity to alleviate poverty and food insecurity. Through a review of related literature and collection and analysis of secondary data from DA, DBM, BAS - CountrySTAT, PSA, NSCB, PIDS, IRRI, UN-FAO, IFPRI, and World Bank among others, the study revealed that Philippines is still far from its goals of poverty reduction and food security. In addition, the agricultural sector is underperforming. The productivity growth of the sector comes out mediocre. The common observation is that weakness is attributed to the failures of policy and institutional environments of the agriculture sector. The policy environment failed to create a structure appropriate for the rapid growth of the sector due to institutional and governance weaknesses. A recommendation is to go through institutional and policy reforms through legislative or executive mandates should take form to improve the implementation and enforcement of existing policies.

Keywords: agriculture, food security, policy, poverty

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Authors: Uche Lucy Onyekwelu, Uche B. Ugwuanyi

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Suffice to say that socio-economic disruptions of any form is likely to affect the wellbeing of the citizenry. The upsurge of social disequilibrium caused by the incessant disruptive tendencies exhibited by youths and some others in Nigeria are not helping matters. In Nigeria the social unrest has caused different forms of draw backs in Socio Economic Development. This study has empirically evaluated the impact of insecurity and insurgency on the Economic Development of Nigeria. The paper noted that the different forms of insecurity in Nigeria are namely: Insurgency and Banditry as witnessed in Northern Nigeria; Militancy: Niger Delta area and self-determination groups pursuing various forms of agenda such as Sit –at- Home Syndrome in the South Eastern Nigeria and other secessionist movements. All these have in one way or the other hampered Economic development in Nigeria. Data for this study were collected through primary and secondary sources using questionnaire and some existing documentations. Cost of investment in different aspects of security outfits in Nigeria represents the independent variable while the differentials in the Gross Domestic Product(GDP) and Human Development Index(HDI) are the measures of the dependent variable. Descriptive statistics and Simple Linear Regression analytical tool were employed in the data analysis. The result revealed that Insurgency/Insecurity negatively affect the economic development of the different parts of Nigeria. Following the findings, a model to analyse the effect of insecurity and insurgency was developed, named INSECUREDEVNIG. It implies that the economic development of Nigeria will continue to deteriorate if insurgency and insecurity continue. The study therefore recommends that the government should do all it could to nurture its human capital, adequately fund the state security apparatus and employ individuals of high integrity to manage the various security outfits in Nigeria. The government should also as a matter of urgency train the security personnel in intelligence cum Information and Communications Technology to enable them ensure the effectiveness of implementation of security policies needed to sustain Gross Domestic Product and Human Capital Index of Nigeria.

Keywords: insecurity, insurgency, gross domestic product, human development index, Nigeria

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Authors: Muhammad Muhammad Suleiman

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Cloud Computing is a versatile concept that refers to a service that allows users to outsource their data without having to worry about local storage issues. However, the most pressing issues to be addressed are maintaining a secure and reliable data repository rather than relying on untrustworthy service providers. In this study, we look at how stenography approaches and collaboration with Digital Watermarking can greatly improve the system's effectiveness and data security when used for Cloud Computing. The main requirement of such frameworks, where data is transferred or exchanged between servers and users, is safe data management in cloud environments. Steganography is the cloud is among the most effective methods for safe communication. Steganography is a method of writing coded messages in such a way that only the sender and recipient can safely interpret and display the information hidden in the communication channel. This study presents a new text steganography method for hiding a loaded hidden English text file in a cover English text file to ensure data protection in cloud computing. Data protection, data hiding capability, and time were all improved using the proposed technique.

Keywords: cloud computing, steganography, information hiding, cloud storage, security

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Authors: Preeti Yadav, Dandeswar Bisoyi, Debkumar Chakrabati

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For many years organization have been exercising a creative technique of applying brand mascots, which results in making a visual ‘ambassador’ of a brand. The goal of mascot’s is just not confined to strengthening the brand identity, improving customer perception, but also acting as a vehicle of anthropomorphic translation towards the consumer. Such that it helps in embracing the power of recognition and processing the experiences happening in our daily lives. The study examines the relationship between the specific mascot features and brand attitude. It eliminates that mascot trust is an important mediator of the mascot features on brand attitude. Anthropomorphic characters turn out to be the key players despite the application of brand mascots in today’s marketing.

Keywords: advertising, mascot, branding, recall

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Authors: Ali Reza Sattarzadeh, Ronny J. Kutadinata, Pubudu N. Pathirana, Van Thanh Huynh

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Traffic congestion has become a severe worldwide problem, affecting everyday life, fuel consumption, time, and air pollution. The primary causes of these issues are inadequate transportation infrastructure, poor traffic signal management, and rising population. Traffic flow forecasting is one of the essential and effective methods in urban congestion and traffic management, which has attracted the attention of researchers. With the development of technology, undeniable progress has been achieved in existing methods. However, there is a possibility of improvement in the extraction of temporal and spatial features to determine the importance of traffic flow sequences and extraction features. In the proposed model, we implement the convolutional neural network (CNN) and long short-term memory (LSTM) deep learning models for mining nonlinear correlations and their effectiveness in increasing the accuracy of traffic flow prediction in the real dataset. According to the experiments, the results indicate that implementing Conv-LSTM networks increases the productivity and accuracy of deep learning models for traffic flow prediction.

Keywords: deep learning algorithms, intelligent transportation systems, spatiotemporal features, traffic flow prediction

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Authors: Yang Cao

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Analyzing the oral production of Chinese-speaking learners of English as a second language (L2), we can find a large variety of verb inflections – Why does it seem so hard for them to use consistent correct past morphologies in obligatory past contexts? Failed Functional Features Hypothesis (FFFH) attributes the rather non-target-like performance to the absence of [±past] feature in their L1 Chinese, arguing that for post puberty learners, new features in L2 are no more accessible. By contrast, Missing Surface Inflection Hypothesis (MSIH) tends to believe that all features are actually acquirable for late L2 learners, while due to the mapping difficulties from features to forms, it is hard for them to realize the consistent past morphologies on the surface. However, most of the studies are limited to the verb morphologies in finite clauses and few studies have ever attempted to figure out these learners’ performance in non-finite clauses. Additionally, it has been discussed that Chinese learners may be able to tell the finite/infinite distinction (i.e. the [±finite] feature might be selected in Chinese, even though the existence of [±past] is denied). Therefore, adopting a self-paced reading task (SPR), the current study aims to analyze the processing patterns of Chinese-speaking learners of L2 Russian, in order to find out if they are sensitive to misuse of tense morphologies in both finite and non-finite clauses and whether they are sensitive to the finite/infinite distinction presented in Russian. The study targets L2 Russian due to its systematic morphologies in both present and past tenses. A native Russian group, as well as a group of English-speaking learners of Russian, whose L1 has definitely selected both [±finite] and [±past] features, will also be involved. By comparing and contrasting performance of the three language groups, the study is going to further examine and discuss the two theories, FFFH and MSIH. Preliminary hypotheses are: a) Russian native speakers are expected to spend longer time reading the verb forms which violate the grammar; b) it is expected that Chinese participants are, at least, sensitive to the misuse of inflected verbs in non-finite clauses, although no sensitivity to the misuse of infinitives in finite clauses might be found. Therefore, an interaction of finite and grammaticality is expected to be found, which indicate that these learners are able to tell the finite/infinite distinction; and c) having selected [±finite] and [±past], English-speaking learners of Russian are expected to behave target-likely, supporting L1 transfer.

Keywords: features, finite clauses, morphosyntax, non-finite clauses, past morphologies, present morphologies, Second Language Acquisition, self-paced reading task, verb inflections

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Authors: Sungchul Ha, Hyunwoo Kim

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In mobile ad hoc networks, all nodes in a network only have limited resources and calculation ability. Therefore communication topology which have long lifetime is good for all nodes in mobile ad hoc networks. There are a variety of researches on security problems in wireless ad hoc networks. The existing many researches try to make efficient security schemes to reduce network power consumption and enhance network lifetime. Because a new node can join the network at any time, the wireless ad hoc networks are exposed to various threats and can be destroyed by attacks. Resource consumption is absolutely necessary to secure networks, but more resource consumption can be a critical problem to network lifetime. This paper focuses on efficient monitoring node distribution to enhance network lifetime in wireless ad hoc networks. Since the wireless ad hoc networks cannot use centralized infrastructure and security systems of wired networks, a new special IDS scheme is necessary. The scheme should not only cover all nodes in a network but also enhance the network lifetime. In this paper, we propose an efficient IDS node distribution scheme using minimum spanning tree (MST) method. The simulation results show that the proposed algorithm has superior performance in comparison with existing algorithms.

Keywords: MANETs, IDS, power control, minimum spanning tree

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Authors: J. Julius Adebayo

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The objective of this paper is to assess the agro-climatic condition of Ibadan in the rain forest ecological zone of Nigeria, using rainfall pattern and temperature between 1978-2018. Data on rainfall and temperature in Ibadan, Oyo State for a period of 40 years were obtained from Meteorological Section of Forestry Research Institute of Nigeria, Ibadan and Oyo State Meteorology Centre. Time series analysis was employed to analyze the data. The trend revealed that rainfall is decreasing slowly and temperature is averagely increasing year after year. The model for rainfall and temperature are Yₜ = 1454.11-8*t and Yₜ = 31.5995 + 2.54 E-02*t respectively, where t is the time. On this basis, a forecast of 20 years (2019-2038) was generated, and the results showed a further downward trend on rainfall and upward trend in temperature, this indicates persistence rainfall shortage and very hot weather for agricultural practices in the southwest rain forest ecological zone. Suggestions on possible solutions to avert climate change crisis and also promote climate-smart agriculture for sustainable food and nutrition security were also discussed.

Keywords: climate change, rainfall pattern, temperature, time series analysis, food and nutrition security

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Authors: Menuka Maharjan

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In the name of food security, agriculture intensification through conventional farming is being implemented in Nepal. Government focus on increasing agriculture production completely ignores soil as well human health. This leads to create serious soil degradation, i.e., reduction of soil fertility and microbial activity and health hazard in the country. On this note, organic farming is sustainable agriculture approach which can address challenge of sustaining food security while protecting the environment. This creates a win-win situation both for people and the environment. However, people have limited knowledge on significance of organic farming for environment conservation and food security especially developing countries like Nepal. Thus, the objective of the study was to assess the impacts of organic farming on soil fertility and microbial activity compared to conventional farming and forest in Chitwan, Nepal. Total soil organic carbon (C) was highest in organic farming (24 mg C g⁻¹ soil) followed by conventional farming (15 mg C g⁻¹ soil) and forest (9 mg C g⁻¹ soil) in the topsoil layer (0-10 cm depth). A similar trend was found for total nitrogen (N) content in all three land uses with organic farming soil possessing the highest total N content in both 0-10 cm and 10-20 cm depth. Microbial biomass C and N were also highest under organic farming, especially in the topsoil layer (350 and 46 mg g⁻¹ soil, respectively). Similarly, microbial biomass phosphorus (P) was higher (3.6 and 1.0 mg P kg⁻¹ at 0-10 and 10-20 cm depth, respectively) in organic farming compared to conventional farming and forest at both depths. However, conventional farming and forest soils had similar microbial biomass (C, N, and P) content. After conversion of forest, the P stock significantly increased by 373% and 170% in soil under organic farming at 0-10 and 10-20 cm depth, respectively. In conventional farming, the P stock increased by 64% and 36% at 0-10 cm and 10-20 cm depth, respectively, compared to forest. Overall, organic farming practices, i.e., crop rotation, residue input and farmyard manure application, significantly alters soil fertility and microbial activity. Organic farming system is emerging as a sustainable land use system which can address the issues of food security and environment conservation by increasing sustainable agriculture production and carbon sequestration, respectively, supporting to achieve goals of sustainable development.

Keywords: organic farming, soil fertility, micobial biomas, food security

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Authors: Wu You, Burra Venkata Durga Kumar

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This study examines the promising potential of integrating Blockchain and Artificial Intelligence (AI) technologies to scalability in Distributed Systems within the field of supply chain finance. The finance industry is continually confronted with scalability challenges in its Distributed Systems, particularly within the supply chain finance sector, impacting efficiency and security. Blockchain, with its inherent attributes of high scalability and secure distributed ledger system, coupled with AI's strengths in optimizing data processing and decision-making, holds the key to innovating the industry's approach to these issues. This study elucidates the synergistic interplay between Blockchain and AI, detailing how their fusion can drive a significant transformation in the supply chain finance sector's Distributed Systems. It offers specific use-cases within this field to illustrate the practical implications and potential benefits of this technological convergence. The study also discusses future possibilities and current challenges in implementing this groundbreaking approach within the context of supply chain finance. It concludes that the intersection of Blockchain and AI could ignite a new epoch of enhanced efficiency, security, and transparency in the Distributed Systems of supply chain finance within the financial industry.

Keywords: blockchain, artificial intelligence (AI), scaled distributed systems, supply chain finance, efficiency and security

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Authors: Wadea Ameen, Abdulrahman Al-Ahmari, Osama Abdulhameed

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Electron beam melting (EBM) is one of the modern additive manufacturing (AM) technologies. In EBM, the electron beam melts metal powder into a fully solid part layer by layer. Since EBM is a new technology, most designers are unaware of the capabilities and the limitations of EBM technology. Also, many engineers are facing many challenges to utilize the technology because of a lack of design rules for the technology. The aim of this study is to identify the capabilities and the limitations of EBM technology in fabrication of small features and overhang structures and develop a design rules that need to be considered by designers and engineers. In order to achieve this objective, a series of experiments are conducted. Several features having varying sizes were designed, fabricated, and evaluated to determine their manufacturability limits. In general, the results showed the capabilities and limitations of the EBM technology in fabrication of the small size features and the overhang structures. In the end, the results of these investigation experiments are used to develop design rules. Also, the results showed the importance of developing design rules for AM technologies in increasing the utilization of these technologies.

Keywords: additive manufacturing, design for additive manufacturing, electron beam melting, self-supporting overhang

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Authors: Kisik Song, Sungjoo Lee

Abstract:

With the growing importance of intangible assets recently, the impact of patent infringement on the business of a company has become more evident. Accordingly, it is essential for firms to estimate the risk of patent infringement risk before developing a technology and create new technology ideas to avoid the risk. Recognizing the needs, several attempts have been made to help develop new technology opportunities and most of them have focused on identifying emerging vacant technologies from patent analysis. In these studies, the IPC (International Patent Classification) system or keywords from text-mining application to patent documents was generally used to define vacant technologies. Unlike those studies, this study adopted F-term, which classifies patent documents according to the technical features of the inventions described in them. Since the technical features are analyzed by various perspectives by F-term, F-term provides more detailed information about technologies compared to IPC while more systematic information compared to keywords. Therefore, if well utilized, it can be a useful guideline to create a new technology idea. Recognizing the potential of F-term, this paper aims to suggest a novel approach to developing new technology ideas to avoid patent infringement based on F-term. For this purpose, we firstly collected data about F-term and then applied text-mining to the descriptions about classification criteria and attributes. From the text-mining results, we could identify other technologies with similar technical features of the existing one, the patented technology. Finally, we compare the technologies and extract the technical features that are commonly used in other technologies but have not been used in the existing one. These features are presented in terms of “purpose”, “function”, “structure”, “material”, “method”, “processing and operation procedure” and “control means” and so are useful for creating new technology ideas that help avoid infringing patent rights of other companies. Theoretically, this is one of the earliest attempts to adopt F-term to patent analysis; the proposed methodology can show how to best take advantage of F-term with the wealth of technical information. In practice, the proposed methodology can be valuable in the ideation process for successful product and service innovation without infringing the patents of other companies.

Keywords: patent infringement, new technology ideas, patent analysis, F-term

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Authors: Shunsuke Miyoshi, Yasuyuki Nogami, Takuya Kusaka, Nariyoshi Yamai

Abstract:

Elliptic curve discrete logarithm problem (ECDLP) is one of problems on which the security of pairing-based cryptography is based. This paper considers Pollard's rho method to evaluate the security of ECDLP on Barreto-Naehrig (BN) curve that is an efficient pairing-friendly curve. Some techniques are proposed to make the rho method efficient. Especially, the group structure on BN curve, distinguished point method, and Montgomery trick are well-known techniques. This paper applies these techniques and shows its optimization. According to the experimental results for which a large-scale parallel system with MySQL is applied, 94-bit ECDLP was solved about 28 hours by parallelizing 71 computers.

Keywords: Pollard's rho method, BN curve, Montgomery multiplication

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Authors: Mohammad Ashraf, Kawther Mohamed

Abstract:

This research tackles a new kind of additions (Nano Clay) and its effect on the features of concrete and both fresh and hardened cement mortar, as well as setting an optimal percentage of adding it to achieve the desired results and obtain on a strong concrete and mortar can be used for skyscrapers. The cementations additions are mineral materials in the form of a fine powder, added to concrete or cement mortar as partly cement substitutes, which means to be added instead of an equivalent amount of cement in order to improve and enhance some features of concrete or both the newly made and hardened cementations materials.

Keywords: nano clay in structure engineering, nanotechnology in construction industry, advanced additions in concrete, special concrete for skyscrapers

Procedia PDF Downloads 325

Authors: Krish Batra

Abstract:

The advent of open banking has revolutionized the financial services industry by fostering innovation, enhancing customer experience, and promoting competition. However, this paradigm shift towards more open and interconnected banking ecosystems has introduced complex cybersecurity challenges. This research paper delves into the multifaceted cybersecurity landscape of open banking, highlighting the vulnerabilities and threats inherent in sharing financial data across a network of banks and third-party providers. Through a detailed analysis of recent data breaches, phishing attacks, and other cyber incidents, the paper assesses the current state of cybersecurity within the open banking framework. It examines the effectiveness of existing security measures, such as encryption, API security protocols, and authentication mechanisms, in protecting sensitive financial information. Furthermore, the paper explores the regulatory response to these challenges, including the implementation of standards such as PSD2 in Europe and similar initiatives globally. By identifying gaps in current cybersecurity practices, the research aims to propose a set of robust, forward-looking strategies that can enhance the security and resilience of open banking systems. This includes recommendations for banks, third-party providers, regulators, and consumers on how to mitigate risks and ensure a secure open banking environment. The ultimate goal is to provide stakeholders with a comprehensive understanding of the cybersecurity implications of open banking and to outline actionable steps for safeguarding the financial ecosystem in an increasingly interconnected world.

Keywords: open banking, financial services industry, cybersecurity challenges, data breaches, phishing attacks, encryption, API security protocols, authentication mechanisms, regulatory response, PSD2, cybersecurity practices

Procedia PDF Downloads 49

Authors: Zuraidasahana Zulkarnain, Mohd Shafry Mohd Rahim, Nor Anita Fairos Ismail, Mohd Azhar M. Arsad

Abstract:

Handwritten signature is accepted widely as a biometric characteristic for personal authentication. The use of appropriate features plays an important role in determining accuracy of signature verification; therefore, this paper presents a feature based on the geometrical concept. To achieve the aim, triangle attributes are exploited to design a new feature since the triangle possesses orientation, angle and transformation that would improve accuracy. The proposed feature uses triangulation geometric set comprising of sides, angles and perimeter of a triangle which is derived from the center of gravity of a signature image. For classification purpose, Euclidean classifier along with Voting-based classifier is used to verify the tendency of forgery signature. This classification process is experimented using triangular geometric feature and selected global features. Based on an experiment that was validated using Grupo de Senales 960 (GPDS-960) signature database, the proposed triangular geometric feature achieves a lower Average Error Rates (AER) value with a percentage of 34% as compared to 43% of the selected global feature. As a conclusion, the proposed triangular geometric feature proves to be a more reliable feature for accurate signature verification.

Keywords: biometrics, euclidean classifier, features extraction, offline signature verification, voting-based classifier

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Authors: Attallah Bilal, Hendel Fatiha

Abstract:

This paper proposes the bimodal biometrics system for identity verification iris and fingerprint, at matching score level architecture using weighted sum of score technique. The features are extracted from the pre processed images of iris and fingerprint. These features of a query image are compared with those of a database image to obtain matching scores. The individual scores generated after matching are passed to the fusion module. This module consists of three major steps i.e., normalization, generation of similarity score and fusion of weighted scores. The final score is then used to declare the person as genuine or an impostor. The system is tested on CASIA database and gives an overall accuracy of 91.04% with FAR of 2.58% and FRR of 8.34%.

Keywords: iris, fingerprint, sum rule, fusion

Procedia PDF Downloads 361

Authors: Mona Almansoori, Ahmed Mustafa, Ahmad Elshamy

Abstract:

Wireless nodes in a sensor network gather and process critical information designed to process and communicate, information flooding through such network is critical for decision making and data processing, the integrity of such data is one of the most critical factors in wireless security without compromising the processing and transmission capability of the network. This paper presents mechanism to securely transmit data over a chain of sensor nodes without compromising the throughput of the network utilizing available battery resources available at the sensor node.

Keywords: hybrid protocol, data integrity, lightweight encryption, neighbor based key sharing, sensor node data processing, Z-MAC

Procedia PDF Downloads 139

Authors: Kenneth Fon Mbah, Arash Habibi Lashkari, Ali A. Ghorbani

Abstract:

Phishing e-mails are a security issue that not only annoys online users, but has also resulted in significant financial losses for businesses. Phishing advertisements and pornographic e-mails are difficult to detect as attackers have been becoming increasingly intelligent and professional. Attackers track users and adjust their attacks based on users’ attractions and hot topics that can be extracted from community news and journals. This research focuses on deceptive Phishing attacks and their variants such as attacks through advertisements and pornographic e-mails. We propose a framework called Phishing Alerting System (PHAS) to accurately classify e-mails as Phishing, advertisements or as pornographic. PHAS has the ability to detect and alert users for all types of deceptive e-mails to help users in decision making. A well-known email dataset has been used for these experiments and based on previously extracted features, 93.11% detection accuracy is obtainable by using J48 and KNN machine learning techniques. Our proposed framework achieved approximately the same accuracy as the benchmark while using this dataset.

Keywords: phishing e-mail, phishing detection, anti phishing, alarm system, machine learning

Procedia PDF Downloads 333