Electronic Records Management System Adoption Readiness Framework for Higher Professional Education Institutions in Yemen

Electronic records (e-records) are used to provide proof of organizational activities. E-records are crucial in complementing business functions, essential tool to assess organizational performance and are the core of good governance. E-records in Higher Professional Education (HPE) institutions contain valuable information in running the education business in an efficient and effective manner, supplying services consistently and in supporting effective performance evaluation and decisions. There are serious consequences and risk awaiting when the administrators of HPE are not based on information contained in e-records in making decisions. Well-informed decision makings would thus be impossible if electronic records are not efficiently and effectively managed using system. Therefore, Electronic Records Management System (ERMS) is an effective and efficient tool to hinder such a problem. Voluminous electronic records are created every day in HPE. The record keepers inclusive of records managers, archivists, administrators and IT personnel, who are the people essentially involved in creating, maintaining and preserving the contents of the e-records.  Thus, these personnel participatinginthe records keeping should identify the readiness of the HPE institutions to adopt ERMS. Therefore, the aim of this paper is to investigate the readiness of the Yemeni HPE institutions to adopt the ERMS. The study involves interviewing 20 specialists from Yemeni HPE institutions who are involved in ERMS. The findings showed that in order to promote effective ERMS readiness in the HPE institutions, there should be a framework to be used as guidance in such process

A Machine Learning-Based Intelligence Approach for Multiple-Input/Multiple-Output Routing in Wireless Sensor Networks

Computational intelligence methods play an important role for supporting smart networks operations, optimization, and management. In wireless sensor networks (WSNs), increasing the number of nodes has a need for transferring large volume of data to remote nodes without any loss. These large amounts of data transmission might lead to exceeding the capacity of WSNs, which results in congestion, latency, and packet loss. Congestion in WSNs not only results in information loss but also burns a significant amount of energy. To tackle this issue, a practical computational intelligence approach for optimizing data transmission while decreasing latency is necessary. In this article, a Softmax-Regressed-Tanimoto-Reweight-Boost-Classification- (SRTRBC-) based machine learning technique is proposed for effective routing in WSNs. It can route packets around busy locations by selecting nodes with higher energy and lower load. The proposed SRTRBC technique is composed of two steps: route path construction and congestion-aware MIMO routing. Prior to constructing the route path, the residual energy of the node is determined. After that, the residual energy level is analyzed using softmax regression to determine whether or not the node is energy efficient. The energy-efficient nodes are located, and numerous paths between the source and sink nodes are established using route request and route reply. Following that, the SRTRBC technique is used for congestion-aware routing based on buffer space and bandwidth capability. The path that requires the least buffer space and has the highest bandwidth capacity is picked as the optimal route path among multiple paths. Finally, congestion-aware data transmission is used to minimize latency and data loss along the route path. The simulation considers a variety of performance metrics, including energy consumption, data delivery rate, data loss rate, throughput, and delay, in relation to the amount of data packets and sensor nodes.publishedVersio

Improving the decision-making process in the higher learning institutions via electronic records management system adoption

This is an accepted manuscript of an article published by KSII in KSII Transactions on Internet and Information Systems on 31/01/2021, available online: http://itiis.org/digital-library/24232 The accepted version of the publication may differ from the final published version.Electronic Records Management System (ERMS) is a computer program or set of applications that is utilized for keeping up to date records along with their storage. ERMS has been extensively utilized for enhancing the performance of academic institutions. The system assists in the planning and decision-making processes, which in turn enhances the competencies. However, although ERMS is significant in supporting the process of decision-making, the majority of organizations have failed to take an initiative to implement it, taking into account that are some implementing it without an appropriate framework, and thus resulted in the practice which does not meet the accepted standard. Therefore, this study identifies the factors influencing the adoption of ERMS among employees of HLI in Yemen and the role of such adoption in the decision-making process, using the Unified Theory of Acceptance and Use of Technology (UTAUT) along with Technology, Organization and Environment (TOE) as the underpinning theories. The study conducts a cross-sectional survey with a questionnaire as the technique for data collection, distributed to 364 participants in various Yemeni public Higher Learning Institutions (HLI). Using AMOS as a statistical method, the findings revealed there are significant and positive relationships between technology factors (effort expectancy, performance expectancy, IT infrastructure and security), organizational factors (top management support, financial support, training, and policy),environmental factors (competitiveness pressure, facilitating conditions and trust) and behavioral intention to adopt ERMS, which in return has a significant relationship with the process of decision-making in HLI. The study also presents a variety of theoretical and empirical contributions that enrich the body of knowledge in the field of technology adoption and the electronic record’s domain

A hybrid method for iris segmentation

Advance development in security technology has caused many major corporations and governments to start employing modern techniques in identifying the identity of the individuals. Among the common biometric identification methods are facial recognition, fingerprint recognition, speaker verification and so on, present a new solution for applications that require a high degree of security. Among these biometric methods, iris recognition becomes an important topic in pattern recognition, and it depends on the iris which is located in a place that still stable through human life. Furthermore, the probability to find two identical iris's approaching to zero value is quite easy. The identification system consists of several stages, and segmentation is the most crucial step. The current segmentation methods still have limitation in localizing the iris due to circular shape consideration of the pupil. Therefore, in this research, two segmentation methods of iris are suggested: Daugman method and Gupta method to investigate the feasibility of these segmentations in iris recognition. An enhanced method based on the techniques of the mentioned two methods is proposed, which can guarantee the accuracy of the iris identification system. The proposed method takes into account the elliptical shape of the pupil and iris. Eyelid detection is another step that has been included in this study as a part of segmentation stage. The dataset which is used for the study is CASIA v3 including the three subsets: Interval, Lamp and Twin. The performance measurement of the proposed method is done by determining the number of success images. The results of the study are very promising with an accuracy of 99.9% compared to the related existing methods

Modified Method of PAPR Reduction Using Clipping and Filtering for Image Transmission with OFDM

Due to the capability of OFDM (Orthogonal Frequency Division Multiplexing) to handle difficult channels, the most agreeable modulation for the multi-carrier scheme in present wireless communications is to improve an all-purpose modulation scheme, especially with high data rates. The image in this research article was transmitted and received on a noisy channel using an OFDM simulation technique. Since the average peak power ratio (PAPR) is one of the main disadvantages of OFDM, a new method has been proposed to reduce the PAPR using the clipping and filtering (CF) method. When the OFDM signal has a high PAPR, it means that many subcarrier components will be added through the operation of IFFT. Also, choosing the type of modulation to examine and getting a perfect type of OFDM system that is used for transmitting the image. Furthermore, signal-to-noise ratio (SNR) was considered to find the PAPR effect on the OFDM signal. The new method was tested to get a reduction of PAPR concerning CF and without CF. This method depends on clipping the signal before transmitting it, by using a method to overcome a nonlinear distortion, and therefore, decrease the bit error rate (BER). Then a filter with multi-stages was used to minimize the noise. This whole process was repeated several times to overcome the difficulties of transmitting/receiving the signal including PAPR. BER and SNR show wonderful outcomes when BPSK is chosen. Control over transmission and reception is also considered to be the type of modulation. All simulation results were defined using an Additive White Gaussian Noise (AWGN) channel

Knowledge management system adoption to improve decision-making process in higher learning institutions in the developing countries: a conceptual framework

Currently, higher learning institutions (HLIs) are facing their most challenging problem in inefficient information management. The knowledge management system (KMS) application calls for providing several benefits to lecturers and students, producing daily information, documenting records for evidence of a transaction, and eventually improving the decision-making process. Knowledge management can be coupled with fuzzy logic to deal with imprecision and uncertainty of data in a KMS. The ICT dynamic development has shifted the HLI operations from manual to electronic-based handling of related information. KMS is one of the systems that are of significant consideration in this regard. Nevertheless, such a system has not been extensively adopted as expected due to users’ rejection of its use. In the present paper, the factors affecting the decision to adopt/reject KMS are highlighted. The study is qualitative and entails a critical review of the related literature concerning the topic, backed by interviews. KMS experts working with highly reputable HLI were interviewed. A total of 11 factors were focused on in light of their effect on the decision to adopt/reject KMS, as argued by the technological adoption theories and literature review. All the factors were validated and placed in ranks by the experts. From the results, a novel conceptual framework of KMS adoption was developed for Libyan HLIs to bring about technology adoption and improved decision-making