Pub Date : 2020-07-01DOI: 10.4018/ijskd.2020070102
T. Iyamu
The concepts of e-government and e-health have usually been separately studied and sparsely implemented in many developing countries. In the few studies where both concepts are combined, the role of e-government is hardly examined in the implementation and practice of e-health. This article offers an exploratory analysis and provides insight on the factors that influence the complementarity of both concepts, with focus on the Africa continent. Existing literature in the areas of e-government and e-health were gathered and used as data, from a qualitative method viewpoint. Dimensions of change from the perspective of the structuration theory was employed as a lens to guide the data analysis, which was conducted by using the hermeneutic approach. From the analysis, the role of the e-government in the implementation and practice of e-health was found to manifest from six main factors, which are source, platforms, collaboration, transparency, heterogeneity, and privacy. Based on these factors, a model was developed, which is intended to guide professionals in their practices. Also, the study might be of interest to academics from theoretical standpoint.
{"title":"Examining E-Government Enabling of E-Health Service Through the Lens of Structuration Theory","authors":"T. Iyamu","doi":"10.4018/ijskd.2020070102","DOIUrl":"https://doi.org/10.4018/ijskd.2020070102","url":null,"abstract":"The concepts of e-government and e-health have usually been separately studied and sparsely implemented in many developing countries. In the few studies where both concepts are combined, the role of e-government is hardly examined in the implementation and practice of e-health. This article offers an exploratory analysis and provides insight on the factors that influence the complementarity of both concepts, with focus on the Africa continent. Existing literature in the areas of e-government and e-health were gathered and used as data, from a qualitative method viewpoint. Dimensions of change from the perspective of the structuration theory was employed as a lens to guide the data analysis, which was conducted by using the hermeneutic approach. From the analysis, the role of the e-government in the implementation and practice of e-health was found to manifest from six main factors, which are source, platforms, collaboration, transparency, heterogeneity, and privacy. Based on these factors, a model was developed, which is intended to guide professionals in their practices. Also, the study might be of interest to academics from theoretical standpoint.","PeriodicalId":13656,"journal":{"name":"Int. J. Sociotechnology Knowl. Dev.","volume":"62 1","pages":"26-40"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83946512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Deep Learning on Digital Image Splicing Detection Using CFA Artifacts","authors":"Nadheer Younus Hussien, R. Mahmoud, Hala H. Zayed","doi":"10.4018/ijskd.2020040102","DOIUrl":"https://doi.org/10.4018/ijskd.2020040102","url":null,"abstract":"Digitalimageforgeryisaseriousproblemofanincreasingattentionfromtheresearchsociety.Image splicingisawell-knowntypeofdigitalimageforgeryinwhichtheforgedimageissynthesizedfrom twoormoreimages.Splicingforgerydetectionismorechallengingwhencomparedwithotherforgery typesbecausetheforgedimagedoesnotcontainanyduplicatedregions.Inaddition,unavailabilityof sourceimagesintroducesnoevidenceabouttheforgeryprocess.Inthisstudy,anautomatedimage splicingforgerydetectionschemeispresented.Itdependsonextractingthefeatureofimagesbased ontheanalysisofcolorfilterarray(CFA).Afeaturereductionprocessisperformedusingprincipal componentanalysis (PCA) to reduce thedimensionalityof the resulting featurevectors.Adeep beliefnetwork-basedclassifierisbuiltandtrainedtoclassifythetestedimagesasauthenticorspliced images.TheproposedschemeisevaluatedthroughasetofexperimentsonColumbiaImageSplicing DetectionEvaluationDataset(CISDED)underdifferentscenariosincludingaddingpostprocessing onthesplicedimagessuchJPEGcompressionandGaussianNoise.Theobtainedresultsrevealthat theproposedschemeexhibitsapromisingperformancewith95.05%precision,94.05%recall,94.05% truepositiverate,and98.197%accuracy.Moreover,theobtainedresultsshowthesuperiorityofthe proposedschemecomparedtootherrecentsplicingdetectionmethod. KeywoRDS Color Filter Array, Deep Belief Network, Deep Learning, Digital Image Forgery, Splicing Forgery","PeriodicalId":13656,"journal":{"name":"Int. J. Sociotechnology Knowl. Dev.","volume":"98 1","pages":"31-44"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78576533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Effect of Controlling Parameters of Tone Reservation Based on Null Subcarriers (TRNS) on the Performance of OFDM Systems","authors":"Mohamed Mounir, M. B. Mashade","doi":"10.4018/ijskd.2020040103","DOIUrl":"https://doi.org/10.4018/ijskd.2020040103","url":null,"abstract":"High data rate communication systems usually implement Orthogonal Frequency Division Multiplexing(OFDM)tofacefrequencyselectivity.HighPeaktoAveragePowerRatio(PAPR)isan OFDMdisadvantagethatcausesBitErrorRate(BER)degradationandout-of-band(OOB)radiation whenOFDMsignalpassthroughnonlinearPowerAmplifier(PA).Inordertoovercomethisproblem largerInputBack-Off(IBO)isrequired.However, largeIBOdecreases thePAefficiency.PAPR reductiontechniquesareusedtoreducetherequiredIBO,sothatPAefficiencyissaved.Several PAPRreductionmethodsareintroducedinliterature,amongthemToneReservationbasedonNull Subcarriers(TRNS)isdownwardcompatibleversionofToneReservation(TR)withsmallexcessin theaveragepowerandlowcomputationalcomplexitycomparedtoothers.Aswillbeshown,TRNS is the best practical one of the four downward compatible techniques. Performance of TRNS is controlledbythreeparameters;numberofpeakreductiontones(PRTs),predefinedthreshold(Amax), andnumberofiterations(Itr).InordertoincreasePAPRreductiongain,enhanceBERperformance, andreducetherequiredIBOtofollowthegivenpowerspectraldensity(PSD),wehavetochoosethe valuesoftheseparametersadequately.Resultsshowedthat,wehavetoreducethethresholdvalue totheaverage(i.e.Amax=0dB).Also,wehavetoincreasenumberofPRTs.However,wehaveto maintainthespectrumshape.Finally,wehavetochoosemoderatenumberofiterations(e.g.Itr≈50), asexcessiveincreaseinnumberofiterationsisnotuseful,especiallyathighPAPRvalues. KEywORDS Orthogonal Frequency Division Multiplexing (OFDM), Peak To Average Power Ratio (PAPR), Tone Reservation Based On Null Subcarriers (TRNS) International Journal of Sociotechnology and Knowledge Development Volume 12 • Issue 2 • April-June 2020","PeriodicalId":13656,"journal":{"name":"Int. J. Sociotechnology Knowl. Dev.","volume":"2 1","pages":"45-62"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84776819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.4018/ijskd.2020010106
Hanaa Ibrahim Abu Zahra, Shaker El-Sappagh, Tarek El-Shishtawy
Most frequent itemset mining algorithms (FIMA) discover hidden relationships from unrelated items. They find the most frequent itemsets depending only on the frequency of the item's existence in the dataset. These algorithms give all items the same importance, and neglect the differences in importance of the items. They assume the full certainty of data, but in most cases, real word data may be uncertain. As a result, the data could be incomplete and/or imprecise. These two problems are the most common challenges that face FIMA algorithms. Some new algorithms proposed some solutions to face these two issues separately. In other words, some algorithms handle item importance only, and others handle uncertainty only. Few algorithms dealt with the two issues together. In this article, the single scan for weighted itemsets over the uncertain database (SSU-Wfim) is proposed. It depends on the single scan frequent itemsets algorithm (SS_FIM), and enhances it to deal with weighted items in an uncertain database. SSU_WFIM deals with the uncertainty of data by giving each item in a transaction an additional value to indicate occurrence likelihood. It gives the items different values to define the weight of them. It uses a table called Ptable to save the items and their probability values. This table is used to generate all possible candidates itemsets. The results indicate the high performance in aspects of runtime, memory consumption and scalability of SSU-Wfim comparing with the UApriori algorithm. The proposed algorithm saves time and memory with a percentage exceeds 70% for all tested datasets.
{"title":"A Proposed Frequent Itemset Discovery Algorithm Based on Item Weights and Uncertainty","authors":"Hanaa Ibrahim Abu Zahra, Shaker El-Sappagh, Tarek El-Shishtawy","doi":"10.4018/ijskd.2020010106","DOIUrl":"https://doi.org/10.4018/ijskd.2020010106","url":null,"abstract":"Most frequent itemset mining algorithms (FIMA) discover hidden relationships from unrelated items. They find the most frequent itemsets depending only on the frequency of the item's existence in the dataset. These algorithms give all items the same importance, and neglect the differences in importance of the items. They assume the full certainty of data, but in most cases, real word data may be uncertain. As a result, the data could be incomplete and/or imprecise. These two problems are the most common challenges that face FIMA algorithms. Some new algorithms proposed some solutions to face these two issues separately. In other words, some algorithms handle item importance only, and others handle uncertainty only. Few algorithms dealt with the two issues together. In this article, the single scan for weighted itemsets over the uncertain database (SSU-Wfim) is proposed. It depends on the single scan frequent itemsets algorithm (SS_FIM), and enhances it to deal with weighted items in an uncertain database. SSU_WFIM deals with the uncertainty of data by giving each item in a transaction an additional value to indicate occurrence likelihood. It gives the items different values to define the weight of them. It uses a table called Ptable to save the items and their probability values. This table is used to generate all possible candidates itemsets. The results indicate the high performance in aspects of runtime, memory consumption and scalability of SSU-Wfim comparing with the UApriori algorithm. The proposed algorithm saves time and memory with a percentage exceeds 70% for all tested datasets.","PeriodicalId":13656,"journal":{"name":"Int. J. Sociotechnology Knowl. Dev.","volume":"39 1","pages":"98-118"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84606761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.4018/ijskd.2020010102
M. R. Mouhamed, Mona M. Soliman, A. Darwish, A. Hassanien
This article presents a robust 3D mesh watermarking approach, which adopts an optimization method of selecting watermark vertices for 3D mesh models. The proposed approach can enhance the imperceptibility of the watermarked model without affecting the robustness and capacity factors. The proposed watermark approach depends on an embedding algorithm that use a clustering strategy, based on K−means clustering algorithm in conjunction with the particle swarm optimization to divide the mesh model vertices into groups. Points of interest set (POIs) are selected from these clustered groups and mark it as watermark vertices where the (POIs) are invariant to most of the geometrical and connectivity attacks. Then, the proposed approach inserts the watermark bit stream in the decimal part of spherical coordinates for these selected watermark vertices. The experimental results confirm that the proposed approach proves its superiority compared with state-of-the-art techniques with respect to imperceptibility and robustness.
{"title":"A Robust and Blind 3D Mesh Watermarking Approach Based on Particle Swarm Optimization","authors":"M. R. Mouhamed, Mona M. Soliman, A. Darwish, A. Hassanien","doi":"10.4018/ijskd.2020010102","DOIUrl":"https://doi.org/10.4018/ijskd.2020010102","url":null,"abstract":"This article presents a robust 3D mesh watermarking approach, which adopts an optimization method of selecting watermark vertices for 3D mesh models. The proposed approach can enhance the imperceptibility of the watermarked model without affecting the robustness and capacity factors. The proposed watermark approach depends on an embedding algorithm that use a clustering strategy, based on K−means clustering algorithm in conjunction with the particle swarm optimization to divide the mesh model vertices into groups. Points of interest set (POIs) are selected from these clustered groups and mark it as watermark vertices where the (POIs) are invariant to most of the geometrical and connectivity attacks. Then, the proposed approach inserts the watermark bit stream in the decimal part of spherical coordinates for these selected watermark vertices. The experimental results confirm that the proposed approach proves its superiority compared with state-of-the-art techniques with respect to imperceptibility and robustness.","PeriodicalId":13656,"journal":{"name":"Int. J. Sociotechnology Knowl. Dev.","volume":"10 1","pages":"24-48"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87822975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.4018/ijskd.2020010105
Youssef Ahmed, Walaa Medhat, Tarek El Shishtawi
Big Data management is trending research that seeks to find a framework that will give support to decision makers in governments and enterprises organizations. For the rapid growth of data, dealing with Big Data with respect to management and finding new values has drawn attention recently. Strategies should be established together with the goals, vision, and objectives of an organization to manage Big Data. Big data management frameworks are the main components for the implementation of Big Data service. Many organizations that deals with Big Data have three critical problems, how to manage Big Data, how can Big Data create new values reference to its strategies and business needs, and how it can take the correct decision in the correct time. In this article, the authors propose a Big Data management framework that will handle all Big Data operation beginning with collecting data until making analysis and how new value can be created. The proposed framework also takes care of other factors such as organization strategies, governance, and security.
{"title":"A Framework for Managing Big Data in Enterprise Organizations","authors":"Youssef Ahmed, Walaa Medhat, Tarek El Shishtawi","doi":"10.4018/ijskd.2020010105","DOIUrl":"https://doi.org/10.4018/ijskd.2020010105","url":null,"abstract":"Big Data management is trending research that seeks to find a framework that will give support to decision makers in governments and enterprises organizations. For the rapid growth of data, dealing with Big Data with respect to management and finding new values has drawn attention recently. Strategies should be established together with the goals, vision, and objectives of an organization to manage Big Data. Big data management frameworks are the main components for the implementation of Big Data service. Many organizations that deals with Big Data have three critical problems, how to manage Big Data, how can Big Data create new values reference to its strategies and business needs, and how it can take the correct decision in the correct time. In this article, the authors propose a Big Data management framework that will handle all Big Data operation beginning with collecting data until making analysis and how new value can be created. The proposed framework also takes care of other factors such as organization strategies, governance, and security.","PeriodicalId":13656,"journal":{"name":"Int. J. Sociotechnology Knowl. Dev.","volume":"82 1","pages":"84-97"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76056149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.4018/ijskd.2020010104
R. Mahmoud, M. Selim, Omar A. Muhi
In the present study, a multimodal biometric authentication method is presented to confirm the identity of a person based on his face and iris features. This method depends on multiple biometric techniques that combine face and iris (left and right) features to recognize. The authors have designed and applied a system to identify people. It depends on extracting the features of the face using Rectangle Histogram of Oriented Gradient (R-HOG). The study applies a feature-level fusion using a novel fusion method which employs both the canonical correlation process and the proposed serial concatenation. A deep belief network was used for the recognition process. The performance of the proposed systems was validated and evaluated through a set of experiments on SDUMLA-HMT database. The results were compared with others, and have shown that the fusion time has been reduced by about 34.5%. The proposed system has also succeeded in achieving a lower equal error rate (EER), and a recognition accuracy up to 99%.
{"title":"Fusion Time Reduction of a Feature Level Based Multimodal Biometric Authentication System","authors":"R. Mahmoud, M. Selim, Omar A. Muhi","doi":"10.4018/ijskd.2020010104","DOIUrl":"https://doi.org/10.4018/ijskd.2020010104","url":null,"abstract":"In the present study, a multimodal biometric authentication method is presented to confirm the identity of a person based on his face and iris features. This method depends on multiple biometric techniques that combine face and iris (left and right) features to recognize. The authors have designed and applied a system to identify people. It depends on extracting the features of the face using Rectangle Histogram of Oriented Gradient (R-HOG). The study applies a feature-level fusion using a novel fusion method which employs both the canonical correlation process and the proposed serial concatenation. A deep belief network was used for the recognition process. The performance of the proposed systems was validated and evaluated through a set of experiments on SDUMLA-HMT database. The results were compared with others, and have shown that the fusion time has been reduced by about 34.5%. The proposed system has also succeeded in achieving a lower equal error rate (EER), and a recognition accuracy up to 99%.","PeriodicalId":13656,"journal":{"name":"Int. J. Sociotechnology Knowl. Dev.","volume":"26 1","pages":"67-83"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86104682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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