-
An Approach to Improve the Availability of a Traffic Light System
Olajide Blessing Olajide,
Oke Alice Olufunke,
Odeniyi Olufemi Ayodeji,
Olabiyisi Stephen Olatunde,
Adeosun Olusegun Olajide
Issue:
Volume 10, Issue 4, August 2021
Pages:
37-43
Received:
13 April 2021
Accepted:
30 April 2021
Published:
6 July 2021
Abstract: Traffic Light System (TLS) is a standalone safety-critical infrastructure that is used to avert traffic congestion and accidents at a road intersection. It is pertinent that its service must be dependable because any failure could result to loss of lives or resources. The existing fail-safe TLS often experience downtime as a result of inevitable fault developed frequently by its Traffic Light Controller Unit (TLCU) due to harsh weather and other environmental factors exposed to on the roads. Hence, the need for a fault-tolerant TLS that will optimize TLS service delivery even at the event of a faulty TLCU initiated this work. In developing the fault-tolerant TLS, three TLCUs were interfaced using the concept of triple modular redundancy architecture. A disagreement detector was configured to test the viability of the primary TLCU using stationarity process. Markovian process was used to switch a faulty primary TLCU to a good one using majority voter mechanism. The fault-tolerant TLS and existing TLS were simulated using MATLAB R2015a. The performance of the fault-tolerant TLS was evaluated by comparing with that of existing TLS using availability as performance metric. The simulation results revealed that the fault-tolerant TLS yielded 99.9474% availability while simulation results of the existing TLS yielded 97.6199% availability. This work has therefore developed a fault-tolerant TLS that performed better than the existing fail-safe TLS.
Abstract: Traffic Light System (TLS) is a standalone safety-critical infrastructure that is used to avert traffic congestion and accidents at a road intersection. It is pertinent that its service must be dependable because any failure could result to loss of lives or resources. The existing fail-safe TLS often experience downtime as a result of inevitable f...
Show More
-
IT-based Knowledge, Adaptive Behavior and Service Performance Improvement
Issue:
Volume 10, Issue 4, August 2021
Pages:
44-49
Received:
26 July 2021
Accepted:
13 August 2021
Published:
24 August 2021
Abstract: The continuing investment in IT applications in business operations by enterprises worldwide has generated interest and research among the academia pertaining to whether and how IT applications can enhance employees work performance. Within such a context, it is the objective of this paper to hypothesize and illustrate how service employees can utilize the IT-based knowledge to improve their service performance and achieve customer satisfaction. A model is developed based upon the literature of categorization and adaptive behavior, conceptualizing a IT-knowledge driven process in which employees categorize customers and adapt to them by modifying service delivery and customizing service options. Five hypotheses are thus proposed within the theoretical framework of this model to justify the causal relationship in-between IT-knowledge and service performance, mediated by employees’ adaptive behavior. It is argued in this paper that IT-based knowledge enables employees to assign the prospective customers to customers categories so as to anticipate their expectations and preferences. Accordingly, employees adjust their interpersonal behavior in their interactions with customers and customize service options to customers’ preferences. With the introduction of IT-based knowledge as an antecedent to adaptive behavior, this paper enriches the extant literature in IT support for employees performance and offers new insight to business management when motivating their service employees to elevate the level of customer satisfaction with the service quality.
Abstract: The continuing investment in IT applications in business operations by enterprises worldwide has generated interest and research among the academia pertaining to whether and how IT applications can enhance employees work performance. Within such a context, it is the objective of this paper to hypothesize and illustrate how service employees can uti...
Show More
-
Development of Artificial Intelligence for Industrial and Social Robotization
Issue:
Volume 10, Issue 4, August 2021
Pages:
50-59
Received:
5 August 2021
Accepted:
16 August 2021
Published:
24 August 2021
Abstract: The intellectual robotization of industry and the social sphere takes on an international scale. The creation of smart robots for various spheres of human life is associated with high technology and artificial intelligence. Currently, the development of artificial intelligence for industrial and social robotics is carried out by information technology, cognitive robots, digital twins and artificial intelligence systems. The ensembles of intelligent mobile diversifiable agents with strong artificial intelligence are central to the development of artificial intelligence for industrial and social robotics through the recurring development of professional skills, increasing their visual, sound, subject, spatial and temporal sensitivity. Working with big data, diversify and transform the high-tech industry and the social sphere. The cognitive ensembles of mobile diversifiable agents, technology platforms and analytical systems allow you to quickly and efficiently solve the tasks of collecting, analyzing and visualizing large amounts of data. Effective collection and analysis of big data, their rapid updating using strong artificial intelligence will accelerate industrial and social robotics by teaching new skills. Intelligent robotization based on large ensembles of intelligent agents processing big data requires faster supercomputers. Communication and control of the robot through the mental neurointerface accelerates the training of industrial and social communicative-associative robots, the development of their intelligence, and makes them natural assistants in improving the life of society. Rapid technological development and rapid change of professions requires a client of project-oriented training of personnel.
Abstract: The intellectual robotization of industry and the social sphere takes on an international scale. The creation of smart robots for various spheres of human life is associated with high technology and artificial intelligence. Currently, the development of artificial intelligence for industrial and social robotics is carried out by information technol...
Show More
-
Blockchain Traceability to Ensure the Veracity of Diplomas
Issue:
Volume 10, Issue 4, August 2021
Pages:
60-68
Received:
6 May 2021
Accepted:
16 June 2021
Published:
24 August 2021
Abstract: Higher education institutions are considered one of the most important pillars and the greatest starting points from which the wheels of development and civilized advancement are launched, as well as their important role in instilling the values of society and preserving its moral and value system. In performing the role entrusted to it in achieving sustainable development and the comprehensive renaissance of society in various field and sectors. Thus; the accreditation systems are frequently used to verify which institutions are recognized and authorized to giveeducational or professional skills. However, these systems are not always efficient in countries where recognized higher education establishments cannot rally the demand for certified professionals required by the employment market. This generates a fertile argument for the “certificate factories” to sell false diplomas to unskilled people who are trying to catchbenefit of this deficit. In this regard, the digitization of diploma granting’s and verification’s processes, is becomingincreasingly important in order to guarantee the identity of diplomas, and that companies recruit the right qualified people. For that reason, an efficient management system for the control of diploma creation processes is immediatelymandatory. The Blockchain methodology provides efficient ways to examine the data information management systems. It is designed to make confidence techniques that can revolutionize information management methods. The major purpose of this paper is to develop a “BlockDipls” system based on Blockchain technology. This BlockDipls system is planned to support diploma traceability and smart contract functions, and can be used to address the problems of diploma falsification and diploma record fraud.
Abstract: Higher education institutions are considered one of the most important pillars and the greatest starting points from which the wheels of development and civilized advancement are launched, as well as their important role in instilling the values of society and preserving its moral and value system. In performing the role entrusted to it in achievin...
Show More
-
User Centric Social Opinion and Clinical Behavioural Model for Depression Detection
Ayodeji Olusegun Ibitoye,
Rantiola Fidelix Famutimi,
Dauda Odunayo Olanloye,
Ehisuoria Akioyamen
Issue:
Volume 10, Issue 4, August 2021
Pages:
69-73
Received:
28 July 2021
Accepted:
20 August 2021
Published:
31 August 2021
Abstract: In more recent time, depression as a lingering mental illness as continued to affect the way people act, and behave consciously or otherwise. Though it remained an undiagnosed disease globally without prejudice to age, gender, color or race; a lot of people never know implicitly or explicitly when they are depressed until it begins to affect their health conditions. While depression can be deciphered through text analysis in opinion mining, oftentimes, changes in human body also provides a convincing status of a depressed individual. No doubt, each data source can independently predict human depression status; however, the exclusive mutual relationship between both data sources has not been studied for depression detection. Therefore, in identifying meaningful correlations between clinical and behavioural data, this research detected depression by analyzing and matching mined patterns in users’ behavioural opinion through tweets with trackable changes in clinical body vitals using wearable device for effective therapy in depressed patient management. Thus, by using a 5-fold cross validation on the clustered data, Random Forest ensemble model was used to build the Social-Health Depression Detection Model (SH2DM) after data preprocessing and optimal feature extraction. The dual data sourced user-centric model produced a better predictive result in accuracy, precision and recall values when compared and evaluated with single data depression detection instances of clinical and behavioural records.
Abstract: In more recent time, depression as a lingering mental illness as continued to affect the way people act, and behave consciously or otherwise. Though it remained an undiagnosed disease globally without prejudice to age, gender, color or race; a lot of people never know implicitly or explicitly when they are depressed until it begins to affect their ...
Show More
-
Extracting Structured Data from Text in Natural Language
Zheni Mincheva,
Nikola Vasilev,
Ventsislav Nikolov,
Anatoliy Antonov
Issue:
Volume 10, Issue 4, August 2021
Pages:
74-80
Received:
6 August 2021
Accepted:
20 August 2021
Published:
31 August 2021
Abstract: Nowadays, the amount of information in the web is tremendous. Big part of it is presented as articles, descriptions, posts and comments i.e. free text in natural language and it is really hard to make use of it while it is in this format. Whereas, in the structured form it could be used for a lot of purposes. So, the main idea that this paper proposes is an approach for extracting data which is given as a free text in natural language into a structured data for example table. The structured information is easy to search and analyze. The structured data is quantitative, while the unstructured data is qualitative. Overall such tool that enables conversion of a text into a structured data will not only provide automatic mechanism for data extraction but will also save a lot of resources for processing and storing of the extracted data. The data extraction from text will also provide automation of the process of extracting useful insights from data that is usually processed by people. The efficiency of the process as well as its accuracy will increase and the probability of human error will be minimized. The amount of the processed data will no longer be limited by the human resources.
Abstract: Nowadays, the amount of information in the web is tremendous. Big part of it is presented as articles, descriptions, posts and comments i.e. free text in natural language and it is really hard to make use of it while it is in this format. Whereas, in the structured form it could be used for a lot of purposes. So, the main idea that this paper propo...
Show More
