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In Internet of things (IoT) and Social Internet of things (SIoT), how to select or recommend suitable smart objects from an ocean of smart objects has become an increasingly critical issue. In this paper, we propose a novel neural network model called BLA (BERT and Bi-LSTM with attention) for smart objects scoring tasks to make recommendations in social Internet of things. The model uses a BERT network to obtain the sentence vectors for a smart object related text, and then uses Bi-LSTM with two types of attention mechanisms to extract representations of the smart object vectors. The devised attention mechanism contains a self-attention (SA) layer and a global-attention (GA) layer. The SA layer is able to estimate the importance of sentences or fields, which in a certain sense can substitute for manually defined features at the sentence and field level. The GA layer can measure the relationships between sentences (or fields) and user requirements, which further helps the model obtain more effective smart object vectors. The experimental results on the datasets demonstrate that our model outperforms other baseline methods.

E-learning sites are useful for improving the skills and awareness of the academic backbone, such as instructors, students, administrative staff, and those who are searching for current information about various educational institutes. Despite all the benefits of an online learning platform, users face some challenges and complexities, such as selecting appropriate learning material and courses based on their needs and preferences. Hence, the provision of quality resources during the training phases is their central responsibility, the lack of online assistance offered by service providers is known to be the key cause of many difficulties. There is a need to create a system that can intelligently propose courses while considering a variety of viewpoints to enhance the learners' skills and knowledge. This research proposes an architecture that builds semantic recommendations with the aid of virtual agents based on user requirements and preferences, assisting academia in seeking appropriate courses in a real-world setting. The experimental and statistical results show that, when compared with existing techniques, the virtualized agent-based recommendation system not only improved user learning skills but also made course selection easier, depending on users’ interests and preferences.

Chapter 13 led us into the “front end” of the product development process, with a perspective that focused on the market. Readers should have left that chapter understanding how firms can interpret market needs and come up with a concise description of the product and of the market segment to address.

This research was specifically aiming to understand the current travel behavior of individuals in five different locations related to e-micromobility. The basis of the analysis was a well-designed survey built to extract objective trip information when using e-micromobility, and subjective information of individual perspectives towards the service. The survey was mainly focusing on service usage, customer satisfaction, and trip combinations, with a specific focus on knowledge about regulations. In general, travelers are familiar with e-micromobile services and regulations, but they primarily use them for leisure trips as short-term renting, not on a regular basis. It seems that most users would shift from walking and public transport modes. The main benefits of e-micromobility are its flexibility and speed, while the concerns cover potential conflicts with other road users, safety issues, and incorrect parking of e-micromobility vehicles. Comparing and analyzing the results among the chosen cities helped understanding the strengths and weaknesses of e-micromobility, as well as the potential of new mobility services. We also aimed to analyze future implications, which supports long-term policy making and potential effects on the transportation network and city structure.

In a nursing home, the elderly gets health services to support their daily life. These services are documented and reported periodically to elderly families. In addition to managing information about nursing services, there is other information that must also be managed properly to help the smooth operation of the nursing home. To support the information management process, reliable software is needed to have the functions and benefits that are in accordance with the needs. One of the supporting components that contribute to building good software is interface design. This study will discuss the design of nursing home service application interfaces that have fields, characteristics, and functions that are different from other fields, especially the field of special health services for the elderly. The purpose of this study is to provide an overview and insight to desktop, mobile, and web application developers regarding aspects of designing an interface that is acceptable to system users in nursing homes. This will certainly make it easier for developers to produce good and acceptable software. The design of the interface is carried out using the Human-Centered Design (HCD) method which applies a user-focused design approach so that it makes it easy to understand what their needs are. There are several stages in HCD, namely the stage of identifying and determining the context of the user (Understand and specifying the context of use), the stage of identifying user requirements (Specifying the user requirements), the stage of producing design solutions (Producing design solutions) and the stage of evaluating the design (Evaluating the design). This research produces an interactive and easy-to-use interface design because the testing process uses a prototype as a demonstration tool. The test results using the End User Computing Satisfaction (EUCS) method show that 88.25% of users are satisfied with the design made and in line with the needs of users in a nursing home.

In this article, Ms Yihang Chen with her supervisor, Prof Lihong Zhou, reports on her MA in Library Science study aimed to identify user requirements of library research support services (RSS) at the universities of Traditional Chinese Medicine (TCM) in China. This study adopted an inductive qualitative approach, employed as a case study and 14 TCM researchers and academic librarians using semi-structured interviews. The research findings point to 28 RSS requirements in five main themes: mastering, planning, project, publication and electronic preservation stages. Although this research is situated in China, it has implications for libraries worldwide in supporting research into holistic and indigenous medicine. F.J.

Haptic prohibition is one of the most common limitations when interacting with museum artefacts. This restriction aims quite logically at preventing damages while safeguarding the integrity of the cultural reserve, which is primarily characterised by its uniqueness. Nevertheless, in cases where museum visitors are visually impaired, the inability to touch the artefacts makes the whole experience incomplete as the haptic perception of an artefact’s morphology is the primary substitute of sight. In this paper, we work towards a low-cost haptic ban removal by an initial establishment of a range of requirement specifications focused on the concept of a smart exhibit which is defined as a physical object that replicates the morphological features of an actual artefact while belonging in an ICT infrastructure that exploits features common in Internet of Things devices. We present a set of high level specifications and functionalities that could be offered by a smart exhibit and objectively justify them through a process of gaining feedback from individuals with and without visual impairments. More specifically, we performed an interview-based questionnaire which in combination with a custom-built haptic performance assessment object composed a sustainable environment to collect user requirements and preferences. The questionnaire itemises user portraying in relation to museum visit experiences and accessibility tools, smart exhibit interaction and recorded narrations preferences, cultural heritage haptic exploration experiences and 3D printing derivatives. On the other hand, the haptic assessment object contributes on evaluating the suitability of reference design elements, when producing low-cost (fused filament fabrication) tactile-enabled artefacts and maps. We present the various results and indicators that contribute in composing a set of requirements specifications and good practices that will enable their exploitation in the Epigraphic Museum (Athens,Greece) by following three implementation approaches. The paper contributes in presenting aspects of designing systems that exploit the proposed smart exhibit concept to provide haptic access to cultural heritage thesaurus.

The evaluation of the volumetric accuracy of a machine tool is an open challenge in the industry, and a wide variety of technical solutions are available in the market and at research level. All solutions have advantages and disadvantages concerning which errors can be measured, the achievable uncertainty, the ease of implementation, possibility of machine integration and automation, the equipment cost and the machine occupation time, and it is not always straightforward which option to choose for each application. The need to ensure accuracy during the whole lifetime of the machine and the availability of monitoring systems developed following the Industry 4.0 trend are pushing the development of measurement systems that can be integrated in the machine to perform semi-automatic verification procedures that can be performed frequently by the machine user to monitor the condition of the machine. Calibrated artefact based calibration and verification solutions have an advantage in this field over laser based solutions in terms of cost and feasibility of machine integration, but they need to be optimized for each machine and customer requirements to achieve the required calibration uncertainty and minimize machine occupation time. This paper introduces a digital twin-based methodology to simulate all relevant effects in an artefact-based machine tool calibration procedure, from the machine itself with its expected error ranges, to the artefact geometry and uncertainty, artefact positions in the workspace, probe uncertainty, compensation model, etc. By parameterizing all relevant variables in the design of the calibration procedure, this simulation methodology can be used to analyse the effect of each design variable on the error mapping uncertainty, which is of great help in adapting the procedure to each specific machine and user requirements. The simulation methodology and the analysis possibilities are illustrated by applying it on a 3-axis milling machine tool.

Network forensic tools enable security professionals to monitor network performance and compromises. These tools are used to monitor internal and external network attacks. Technological improvements have enabled criminals to wipe out tracks of cybercrime to elude alterations. Network forensics procedures use processes to expedite investigation by tracking each original packet and event that is generated in the network. There are many network forensic tools, both open source and commercial versions available in the market. In this work, the result of a survey participated by different experts in open source network forensic tools have been presented. The advantages, challenges, and necessities have been identified for network forensic investigation of such tools. A few open source network forensic tools have been studied and performed a comparative analysis based on six key parameters. Further, two malware datasets are analyzed using open source tools to perform investigation and present a comprehensive network forensic analysis comprising IO graphs, Flow graphs, TCP stream, UDP multicast stream, mac-based analysis, and operating system analysis.

This chapter examines the technical capabilities of orbital earth observation sensors and considers associated geomorphic user requirements between 1957 and 2000. Early photography from space provides much promise, which is followed by successive dedicated satellite missions. These produce data at ever-greater spatial and spectral resolution, as well as frequency, starting with Landsat 1 in 1972. Users especially in the arid and polar community are drawing on this new technology. However, the wider uptake of data derived from passive systems such as Landsat and other such sensors by geomorphologists is sporadic due to the mismatch between data requirements and systems specifications. Limitations to most geomorphologists would have included data cost, given that even Landsat data were not always freely available, as well as data volume and processing capabilities, which favoured governmental scientists. Active radar data on some levels fulfilled the geomorphic requirements such as retrieval of form and texture, as well as height. Unfortunately, the processing of such image data required significant technical capabilities and was not easy to interpret, given the numerous variables associated with the backscatter of the microwave signal. Early Earth observation missions were deployed at a time when the full extent of global change, driven by anthropogenic activity, had not been fully comprehended. However, older legacy data are now of profound value, since they provide a comparative baseline against which change can be quantified. The study period also saw the gradual transfer of military GPS capabilities to the civilian sector, which facilitated field activities and geometric correction of imagery.

This study provides empirical evidence to the body of knowledge in Agile methods adoption in small, medium and large organizations in international context. This research explores the factors involved in the adoption of Agile methods in software development organizations. A survey was conducted among Agile professionals to gather survey data from 52 software organizations in seven countries across the world. Statistical techniques are applied towards empirical assessment. Organizational culture, team structure and management support are found to be crucial success factors whereas lack of management support, a large organization size and traditional organizational culture are found to be detrimental for the adoption of Agile approach in an organization. The selection of an appropriate Agile method depends on the project size and, for each size, there are specific methods preferred by different enterprises. Providing better control over the work is viewed as the primary advantage of the Agile methods within large and small organizations, while for the medium-size organizations, the priority is switched to coping with changing user requirements. Majority of the respondents did not consider embracing agile methods as a reason for project failure which indicates that Agile methods are, indeed, beneficial.

Cognitive-physical exercises can reduce the progression of dementia. However, traditional methods often induce problems (e.g., lack of motivation), whereas the success of recent virtual reality (VR) exergames such as Beat Saber may provide a playful, motivational, and immersive alternative. Yet, until now, it remains unclear which game mechanics, concepts, and designs work best for people with dementia, and how to implement exergames for and with this user group. In this paper, we adapted a human-centered design approach to address the specifics of developing VR exergames for people with dementia. This includes semi-structured interviews with stakeholders and contextual inquiries to better analyze the user requirements. Based on our analysis, we present Memory Journalist VR - a novel VR exergame specifically designed for people with dementia in a participatory design process. We report the qualitative evaluation based on the feedback gathered in five focus group sessions. Finally, we discuss the lessons learned, which provide important insights for the design of future VR exergames for people with dementia: (i) creating social gaming activities with a focus on shared aspects, (ii) support of an inverse game flow channel addressing decline and variance in cognitive-physical abilities, and (iii) ensuring a safe VR exergame experience.

The study of Electroencephalogram (EEG)-based biometric has gained the attention of researchers due to the neurons’ unique electrical activity representation of an individual. However, the practical application of EEG-based biometrics is not currently widespread and there are some challenges to its implementation. Nowadays, the evaluation of a biometric system is user driven. Usability is one of the concerning issues that determine the success of the system. The basic elements of the usability of a biometric system are effectiveness, efficiency and user satisfaction. Apart from the mandatory consideration of the biometric system’s performance, users also need an easy-to-use and easy-to-learn authentication system. Thus, to satisfy these user requirements, this paper proposes a reasonable acquisition period and employs a consumer-grade EEG device to authenticate an individual to identify the performances of two acquisition protocols: eyes-closed (EC) and visual stimulation. A self-collected database of eight subjects was utilized in the analysis. The recording process was divided into two sessions, which were the morning and afternoon sessions. In each session, the subject was requested to perform two different tasks: EC and visual stimulation. The pairwise correlation of the preprocessed EEG signals of each electrode channel was determined and a feature vector was formed. Support vector machine (SVM) was then used for classification purposes. In the performance analysis, promising results were obtained, where EC protocol achieved an accuracy performance of 83.70–96.42% while visual stimulation protocol attained an accuracy performance of 87.64–99.06%. These results have demonstrated the feasibility and reliability of our acquisition protocols with consumer-grade EEG devices.

We propose a method to collect data on user requirements of medical equipment shared by different users and services, relate those requirements with the equipment's technical features, and rank the most important features to be considered when procuring the equipment, leading to more effective procurement decision making. Our method is structured in three phases: (i) elicit the device's technical characteristics, (ii) determine user requirements, and (iii) relate technical characteristics to user requirements. The method is applied to rank the most relevant features of a hospital recliner used by seven services and three types of users. Our results indicate the 10 most relevant factors (requirements) for an “ideal” hospital recliner with potential impact on outputs (importance scores). A final list of 32 items was useful for comparing user requirements and identifying key features that address the most relevant requirements. User-centered approaches to requirements elicitation in medical equipment procurement promote healthcare benefits, safety, and end-user satisfaction. Potential use of our approach goes beyond our application case study into many other categories of procurement decisions and into other industry and business applications, wherever multiple stakeholders' requirements should be considered in decisions with multiple value dimensions of value.

In a cloud computing environment, there are many providers offering various services of different quality attributes. Selecting a cloud service that meets user requirements from such a large number of cloud services is a complex and time-consuming process. At the same time, user requirements are sometimes described as uncertain (sets or intervals), something which should be taken into account while selecting cloud services. This paper proposes an efficient method for ranking cloud services while accounting for uncertain user requirements. For this purpose, a requirement interval is defined to fulfill uncertain user requirements. Since there are a large number of cloud services, the services falling outside the requirement interval are filtered out. Finally, the analytic hierarchy process is employed for ranking. The results evaluate the proposed method in terms of optimality of ranking, scalability, and sensitivity analyses. According to the test results, the proposed method outperforms the previous methods.

Over the past decades, technological advancement and the mass digitization of information resources have led to the development of a range of digital resources for academic scholarship. Understanding the needs of scholars when employing digital resources for their work can lead to the building of digital infrastructure that not only enables access to the required information but also has the potential to transform scholarship through having a positive effect on the whole scholarly workflow. Through this article, we show how the design of digital libraries and resources can be improved to enhance information discovery and use in art history, while also benefiting other key areas of the research process. By employing an ethnographic approach to the study of scholarly practices, we developed a sound understanding of art historians’ behaviour when interacting with information at different stages of the scholarly workflow. Our results show that scholars exhibited highly creative behaviour when conducting core scholarly activities, such as information seeking and use. Yet, the challenges they often encountered showed that there is still more work to be done to improve digital infrastructure and tools for scholarship in the field. Part of this article will focus on the user requirements for designing systems that facilitate discovery, encourage creative use of information, and trigger inspiration.

Cloud-based services introduce a paradigm shift in how users access, process and analyse Big Earth data. A key challenge is to align the current state of how users access, process and analyse the d...

Designing and developing a mobile health intervention that focuses on menopausal symptom management and emotional support for women should be grounded by some knowledge about their problems and needs. Therefore, to gather information about the issues surrounding women in their menopausal phase, review of literatures pertaining to the topic was conducted, followed by a brief preliminary investigation (PI) using online survey method which was administered to Malaysian women for two weeks. The purpose of PI was to examine their awareness about menopause, namely its phases and symptoms management, as well as methods of information searching on menopause. Respondents were also inquired about their requirements from mobile app to support management of menopause. A total of 30 respondents answered the survey, with majority of them were between the ages of 40 and 59 years old. It was discovered that menopausal women had experienced variety of symptoms, some could be intense more often than the others, and they use diary or book to record these symptoms, which is deemed ineffective. It is imperative to help Malaysian women to manage this unavoidable phase of their lives in a more convenient approach. Therefore, a mobile app that supports symptoms management, and provides educational and motivational tips in Malay language is proposed.

PurposeThe engineering education accreditation (EEA) is a principal quality assurance mechanism. However, at many education institutions, the most labor-intensive work of EEA process is accomplished manually. Without the support of computer and information technology, the EEA process leads to high labor intensity, low work efficiency and poor management level. The purpose of this paper is to build a complex network model and realize an information management system of talent training program for supporting the EEA process.Design/methodology/approachBased on polychromatic graph (PG), this paper builds a network model of talent training program for engineering specialty. The related information and data are organized and processed in this network model. From the bidirections of top-down and bottom-up, the user requirements are retrieved automatically in logic layer. Together with the specialty of mechanical engineering, the proposed PG-based network modeling method is applied and the corresponding information management system is realized.FindingsThe study results show that the PG-based network modeling method takes full advantages of the strong simulation ability of PG to model the complex network system and has some unique merits in formal expression of problem, efficient processing of information and lightweight realization of system. Further, the information management system of talent training program can reduce the tedious human labor and improve the management level of EEA process dramatically.Originality/valueThis paper proposes a PG-based network modeling method, in which the nodes and the edges can be painted by some unified colors to describe the different kinds of activities and the various types of interactions. Theoretically, this modeling method does not distinguish the activities, the interactions and their properties in graphic symbol and the problem size is diminished about a half. Furthermore, this paper provides an effective experience and idea to the education institutions for implementing the engineering education accreditation, increasing the education management efficiency and promoting the talent training quality.

Causal consistency has attracted considerable attention in distributed systems because it meets the high availability and high-performance requirements in the presence of network partitions. Existing causal consistency models seldom pay attention to hot data governance and run the data stabilization process periodically and thus fail to meet the user requirements of real-time data and high concurrency. In response to this problem, this study proposes a model based on thermal data governance, the Horae model, which simplifies causal sequence verification by sorting, accelerates data stability, and optimizes model update visibility and read response latency. Furthermore, the Horae model stores hot data, reduces the number of partition loads, increases operation parallelism, and ultimately improves throughput. Theoretical analysis and simulation experiments show that the proposed model outperforms existing models in terms of throughput, read response time, and update visibility.

Mobile-edge computing (MEC) and nonorthogonal multiple access (NOMA) have been regarded as promising technologies for beyond fifth-generation (B5G) and sixth-generation (6G) networks. This study aims to reduce the computational overhead (weighted sum of consumed energy and latency) in a NOMA-assisted MEC network by jointly optimizing the computation offloading policy and channel resource allocation under dynamic network environments with time-varying channels. To this end, we propose a deep reinforcement learning algorithm named ACDQN that utilizes the advantages of both actor–critic and deep $Q$ -network methods and provides low complexity. The proposed algorithm considers partial computation offloading, where users can split computation tasks so that some are performed on the local terminal while some are offloaded to the MEC server. It also considers a hybrid multiple access scheme that combines the advantages of NOMA and orthogonal multiple access to serve diverse user requirements. Through extensive simulations, it is shown that the proposed algorithm stably converges to its optimal value, provides approximately 10%, 27%, and 69% lower computational overhead than the prevalent schemes, such as full offloading with NOMA, random offloading with NOMA, and fully local execution, and achieves near-optimal performance.

Web API/service technology has been attracting considerable attention and the REST (REpresentational State Transfer) architecture is now widely accepted as mainstream technology. Nonetheless, developing the means by which to discover RESTful Web APIs/services is crucial to the further development of this technology. Unfortunately, existing search engines for RESTful Web APIs/services provide only keyword-based or tag-based search functions. A failure to take into account the semantics and/or characteristics (e.g., their interface compatibility) greatly hampers the ability to find suitable APIs/services. In this study, we propose a novel approach to the discovery of RESTful Web API/services, referred to as Test-Oriented API Search with Semantic Interface Compatibility (TASSIC). This scheme involves expanding the terms of Web API/service documents based on DBpedia and WordNet. Unsuitable APIs/services are then filtered out using a systematic process, as follows: 1) calculation of semantic similarity between a set of candidate APIs/services and a user query, 2) analysis of interface compatibility between candidate APIs/services using the Hungarian Algorithm, 3) invocation of candidate APIs/services to verify functionality and availability, and 4) analysis of similarity between the actual response of the candidate services and the expected response specified in the user query. The proposed TASSIC increases the likelihood of matching APIs/services that are semantically equivalent or similar to user queries. Unit test and acceptance test are used to verify that a set of candidate APIs/services are actually available and that they actually meets user requirements. Experiment results demonstrate the efficacy of TASSIC, the accuracy of which is superior to that of existing methods.

Background - Health services are one of the most widely used public services, administered by BPJS Health reaching 222.5 million people as of December 31, 2020. This figure is equivalent to 81.3% of the total population in Indonesia. The Doku application is an application that will help level I Health Facilities and Hospitals to manage BPJS patient services. The Doku application will replace the conventional BPJS patient services at Level I Health Facilities and Hospitals to online. This business opportunity is quite large, even though there are threats from existing applications, with more brands and users, but based on the results of QSPM is product development strategy, Doku will always update features and add according to market needs. Method - Product design operational management approach. Result - This product design helps companies to implement user requirements in the form of user interface. Keywords: Application, Doku, Feature Update, Business opportunity.

The paper draws on two cases of learning settings that were converted to meet up-to-date educational requirements within these learning contexts. The authors address the role of stakeholder perspectives. Focusing on the learning situation, they present an articulation tool to aid dialogue between key stakeholder perspectives in a (re)design process. Dialogue is a way to figure out relevant issues and to establish the common ground between participants. The goal of a redesign process is that user requirements are well understood, and the design is embedded into local practices, informed of constraints and aware of potential opportunities regarding educational technology.

A big problem with the chemistry literature is that it is not standardized with respect to precise operational parameters, and real time corrections are hard to make without expert knowledge. This lack of context means difficult reproducibility because many steps are ambiguous, and hence depend on tacit knowledge. Here we present the integration of online NMR into an automated chemical synthesis machine (CSM aka. “Chemputer” which is capable of small‐molecule synthesis using a universal programming language) to allow automated analysis and adjustment of reactions on the fly. The system was validated and benchmarked by using Grignard reactions which were chosen due to their importance in synthesis. The system was monitored in real time using online‐NMR, and spectra were measured continuously during the reactions. This shows that the synthesis being done in the Chemputer can be dynamically controlled in response to feedback optimizing the reaction conditions according to the user requirements., A universal chemical synthesis platform was extended by online NMR to allow adjustments of the encoded reactions on the fly. The approach was demonstrated on the class of Grignard reactions showing robust analytical results under harsh conditions. Real‐time process analytics and the use of straightforward feedback control algorithm enhance the usability of available synthesis formula considering existing deviations.

Over the decades, there has been a sustained effort to use fashion as a medium for delivering digital functionality. The goal is to integrate information technology (IT) into clothing to provide users with functions to assist them in their tasks. Regarding the direction of previous efforts, this study developed a multifunctional smart outdoor jacket prototype that senses, recognizes, responds, and manages various safety risks and potentially hazardous situations and identifies environmental factors that are difficult to predict. The prototype’s research and development (R & D) was carried out through the following steps. First, to determine functions that can practically assist users in outdoor environments and help ensure their health and safety, a user requirement survey subject to expert evaluation was conducted. Six functions were selected: (1) Bluetooth hands-free calling and audio streaming, (2) heart rate monitoring for self-health care, (3) emergency calls to request assistance, (4) temperature-reactive heating to retain body heat for survival, (5) fall detection and automatic emergency calls, and (6) ultraviolet monitoring for self-health care. Next, a wearable system and its garment platform were developed, containing detachable device modules for washability and ease of maintenance. Lastly, a dedicated smartphone application was developed for extended functionality. By exploring the use of clothing in diversifying wearable health care and HAR systems, the study could be used to diversify wearable healthcare and safety platforms.

Automated insulin delivery (AID) is the most recent advance in type 1 diabetes (T1D) management. It has the potential to achieve glycemic targets without disabling hypoglycemia, to improve quality of life and reduce diabetes distress and burden associated with self-management. Several AID systems are currently licensed for use by people with T1D in Europe, United States, and the rest of the world. Despite AID becoming a reality in routine clinical practice over the last few years, the commercially hybrid AID and other systems, are still far from a fully optimized automated diabetes management tool. Implementation of AID systems requires education and support of healthcare professionals taking care of people with T1D, as well as users and their families. There is much to do to increase usability, portability, convenience and to reduce the burden associated with the use of the systems. Co-design, involvement of people with lived experience of T1D and robust qualitative assessment is critical to improving the real-world use of AID systems, especially for those who may have greater need. In addition to this, information regarding the psychosocial impact of the use of AID systems in real life is needed. The first commercially available AID systems are not the end of the development journey but are the first step in learning how to optimally automate insulin delivery in a way that is equitably accessible and effective for people living with T1D.

Recommender systems, which are used to predict user requirements precisely, play a vital role in the modern internet industry. As an effective tool with rich semantics, knowledge graphs have recently attracted growing research attention in enhancing recommendation results. By mining multihop relations (i.e., paths) between user-item interactions within a knowledge graph, implicit user preferences and other side information can be clearly revealed. Nevertheless, existing knowledge graph-based recommendation methods have two fundamental limitations. First, the indiscriminate utilization of user-item path sets conveys unclear information and negatively influences explainability. Moreover, obtaining reliable recommendation results with these methods requires large amounts of prior knowledge, which indicates that they show poor performance in terms of accuracy and handling cold-start issues. To address these issues, we propose a novel model called the Path-enhanced Recurrent Network (PeRN). Specifically, PeRN integrates a recurrent neural network encoder with a metapath-based entropy encoder to increase explainability and accuracy and reduce cold-start costs. The recurrent network encoder has a strong ability to represent sequential path semantics in a knowledge graph, while the entropy encoder, as an efficient statistical analysis tool, leverages metapath information to differentiate paths in a single user-item interaction. A path extraction algorithm with a bidirectional scheme is also proposed to make PeRN more feasible. The experimental results on two real-world datasets demonstrate our significant improvements with reasonable explanations, promising accuracy and a minimal amount of prior knowledge compared with several state-of-the-art baselines.

Future vehicular Internet-of-Things (IoT) systems feature a large number of devices and multi-access environments where different types of communication, computing, and storage resources must be efficiently utilized. At the same time, novel services such as cooperative autonomous driving and intelligent transportation systems (ITS), that demand unprecedented high accuracy, ultra-low latency, and large bandwidth, are emerging. These services also have an extreme variance in user requirements and resource demands with respect to time, location, and context. Hence, current research is no longer confined to improving reliable communication and system operation in the presence of highly mobile vehicles, which has been the main focus in the past. It is therefore important to empower future vehicular IoT systems with advanced features, such as real-time reactive and proactive cooperation and coordination among different agents (or decision makers), including vehicles, roadside units, base stations, pedestrians, and other entities.

This article deals with reconfigurable uniprocessor systems powered by a renewable energy source under real-time and resource sharing constraints. A reconfigurable system is defined as a set of implementations, each of which is encoded by real-time periodic software tasks. Reconfiguration is a flexible runtime scenario that adapts the current system’s implementation to any related environment evolution under well-defined conditions. A task is characterized by an effective calculated deadline that should be less than a maximum deadline defined in user requirements. The main problem is how to calculate the effective deadlines of the different periodic tasks in the different implementations under possibly the predicted renewable energy source and the sharing of resource constraints. We propose an offline method based on three solutions to calculate the deadlines of tasks. The first serves to compute the deadlines ensuring the real-time system feasibility and also minimizes the number of context switches by assigning the highest priority to the task with the smallest maximum deadline. The second computes the deadlines ensuring the respect of energy constraints, and the third computes the deadlines ensuring the respect of resource sharing constraints. These three solutions calculate the possible deadlines of each task in the hyperperiod of the corresponding implementations. We develop a new simulator called DEAD-CALC, that integrates a new tool called RANDOM-TASK for applying and evaluating the proposed solutions. The conducted experimentation proves that this methodology provides deadlines with affecting neither the load nor the processor speed while reducing the calculation time. Note to Practitioners —Real-time software is particularly difficult to design since, in addition to ever more complex functional constraints, it has to satisfy a set of stringent nonfunctional requirements, such as deadlines. In fact, the violation of deadlines can lead to breakdowns, data loss, and so on, which can be catastrophic for critical applications. This article presents the DEAD-CALC project for computing efficiently the deadlines of reconfigurable real-time devices to run possibly under energy and resource sharing constraints in all the system implementations. A device, in the software level, is a superset of implementations, each of which (i.e., a set of periodic software tasks) is activated and executed at a particular time according to user requirements. DEAD-CALC reduces the development time by computing the deadlines to be certainly respected without any additional feasibility analysis of the device. The calculation can only consider the real-time aspects, or both the harvesting energy and resource sharing constraints, giving the user the ability to configure the system under different conditions. DEAD-CALC is a visual environment that can be simply used by designers to compute and display these deadlines, with a few clicks, in arranged tables, and in a short time. This project can be a future reference for industrial partners who will be focusing on various real-time applications design, such as the intelligent manufacturing industry, intelligent transportation systems, embedded systems, wireless sensor networks, smart grids, medical control devices, and military platforms.

Libraries should explore the marketing strategies to be used to promote their services among users, to entice new users and retain existing users. The objectives of this study were to find out the marketing techniques used in Sri Lankan university libraries and identify the challenges that university librarians face when marketing their services. The study involved 130 academic staff members of the libraries in 15 state universities established under the purview of the University Grants Commission in Sri Lanka. The total population was considered as the sample and the data were collected through self-administered questionnaire. The data were analyzed using the SPSS software package considering the mean and standard deviation. There were 105 valid questionnaires among returns, and the response rate was 80.8%. As per the results, library websites, user orientation seminars, notice boards, and e-mail notifications were most frequently used to promote library services. Mobile applications, blogs and podcasts were rarely used to promote library services in Sri Lankan universities. The mean ratings of perceived challenges in the marketing of library services by university librarians in Sri Lanka were considered. Lack of networking among librarians (3.54) was identified as a significant challenge faced by Sri Lankan university librarians when marketing their services. Other significant challenges were unawareness of library user requirements, insufficient funds for marketing, increased cost of marketing and lack of skills in marketing library services. This concludes that Sri Lankan university librarians market their library services using an array of techniques and come across various challenges while adopting marketing techniques to their services. To overcome these challenges libraries should consider appointing a marketing librarian for each university library and establish a collaboration between them, develop a unique marketing strategy for each library, and allocation of funds for marketing library services.

Models used for the design and service delivery of Augmentative and Alternative Communication (AAC) systems are limited. There are no standardized protocols for gathering user requirements beyond clinical/diagnostic information relating to AAC access needs (i.e., physical and cognitive capabilities). Nonetheless, information on the social, cultural, and psychological aspects of technology orientation and use are important to understanding how an AAC system will complement the user's lifestyle, personal goals, values, and activities. Persona development is a user-centered design method that creates descriptive user models of different segments of a user population. Personas describe users' personal characteristics, and the ways in which they think, behave, and engage in activities (with or without technology). The objective of this study is to investigate the utility of user personas as a supplementary tool to aid SLPs in AAC assessment and service delivery.Three personas of individuals with Amyotrophic Lateral Sclerosis (ALS) were developed and validated in our prior research (Subrahmaniyan, 2014; Subrahmaniyan, Bisantz & Higginbotham, 2018). Twelve SLPs engaged in mock AAC assessments of the three ALS case studies under two conditions: with or without the use of personas as a supplemental informational tool. By and large, there were no statistically significant differences between groups across objective measures, however, interview sessions with the SLP participants revealed benefits to using personas during clinical decision-making, particularly for training novice SLPs. Discussion also focuses on ways in which user personas can be adapted and improved to mitigate some of the challenges and risks identified.

A modern model long-term composed service (LCS) with a group recommendation system has an indefinite lifespan. An LCS is used as a long-term business goal, and for a business committed to its customers, support will be provided to customers enabling them to book, e.g. an automotive service through online web services by providing information that the LCS then uses to offer more support. However, identifying the exact service to meet the user requirement is essential. Service composition has been identified as the key task in achieving various QoS performances. There exist various approaches that involve service composition according to the throughput and popularity. However, they fail to achieve the expected performance. Towards improving the performance of the LCS, a novel LCS that is based on the user queries of a group of persons is developed to give the best business services based on previous travel details and services. The method carries out service selection and composition according to the ratings provided by users towards any service. Additionally, the method considers the user-to-service rating and service-to-service rating, which are measured according to the coupling quality. Therefore, the proposed novel LCS provides better services based on the user ratings for particular business queries. The method ranks the services according to the rating values to perform service composition, with consideration of the detection of similar user groups and utilization of the rating values in service selection. We aim to propose a novel LCS work based on group ratings and a group of services. This work is intended to reduce the time complexity of changes in the LCS network using the group recommendation system.

The availability of office stationery is very important to make the required work smooth. In order for ATK management to be handled properly, an application is needed to manage ATK inventory data using a technology-based information system so that it becomes a complete information system. The method used by the author in conducting this research is the Waterfall model system development method starting from the specification of user requirements, planning, modeling, and coding. The method of specification of user requirements includes interviews, observations, literature studies, and documentation studies. The planning method includes the tasks to be carried out including the risks that may occur and the work schedule. Modeling methods include the design of flow documents, DFD, data dictionary, and ERD. The coding includes a program designer with the VB.Net programming language with SQL Server 2008 database and application testing using black box testing, namely this test is intended to determine whether the functions, inputs and outputs of the software are in accordance with the required specifications. To simplify reporting and recording so that errors do not occur, it is necessary to design and implement a system that can facilitate inter-related functions within the company by using Microsoft Visual Studio 2010 (VB.Net) and Microsoft SQL Server 2008. With the implementation of this system, it is expected will be useful for the company in its operations in the future.

With the advent of cloud computing, the affinity between business and technology had increased manifold, allowing users to access IT resources at their convenience through the pay-per-use scheme. With such huge demand surging day to day, the cloud environment must cater to the user requirements flawlessly and also should be rewarding to the providers of cloud service. To maintain its high level of efficiency, there are several challenges that the cloud environment should tackle. One amongst those challenges is the balancing of load. It is one of the primary features of cloud computing that focuses on avoiding the overloading of nodes where there may be idle nodes or nodes with lesser load present at the same juncture. By keeping an effective check on the load several the Quality of Service (QoS) parameters including response time, throughput, resource utilization, energy consumption, cost etc., can be improved, adding to better performance of the entire cloud environment. Even distribution of load among datacenters will contribute to optimal energy consumption and keeps a check on carbon emissions. In this paper we have presented a methodical review on literature pertaining to load balancing strategies that had been proposed in the cloud environment. We had made in-depth analyses of available load balancing techniques and had come up with their advantages, limitations along with the challenges to be addressed by researchers for developing efficient load balancing strategies in the near future. We had also suggested prospective insights about the aspects in load balancing that could be applied in the cloud environment.

Cloud data centers provide services for an increasing number of applications. The virtual machines (VMs) that perform the corresponding application tasks need to be allocated to physical machines (PMs). For VM allocation, cloud service centers consider both energy consumption and quality of service (QoS), while cloud users are primarily concerned with their own needs, such as throughput and reliability. This paper proposes an allocation scheme for optimization based on user requirements in a cloud data center. First, various application requests from mobile phones and devices, which are regarded as a group of VM lists in the data center, are submitted to the cloud platform. Our method first allocates these arriving VMs to appropriate PMs based on their usage of hardware resources and the current throughput of the PMs in the data center. Second, due to dynamic workloads, the loads of the PMs that host these VMs may become very high. CPU utilization thresholds are set to determine whether migration is required, and the energy consumption before and after allocation is used to choose which VMs are reallocated. A suitable strategy for VM migration and PM shutdown can improve reliability and reduce energy consumption. Finally, it is shown through experimental simulations that compared with two existing algorithms, on the premise that the user requirements are met, the proposed method offers good performance in terms of total energy consumption, CPU utilization, number of PMs used and number of service-level agreement (SLA) violation.

When specifying user requirements, not only is it critical to ensure correct and unambiguous specification of functional requirements, but also that of Non-Functional Requirements (NFRs). A critical success factor in Requirements Engineering (RE) involves recognizing conflicts among NFRs specified by multiple stakeholders having differing concerns, priorities, and responsibilities. There indeed are numerous attempts made in the literature to resolve the conflicts between two NFRs, with the traditional view of considering the two NFRs different from each other e.g. security conflicting with the availability. In this paper, however, we propose that to introduce fine-grained conflict resolution – by also focusing on those situations where one NFR conflicts with another NFR of the same type. For ease of understanding, we propose to differentiate such conflicts by coining the term intra-conflicts. Thus, we propose fine-grained conflict resolution – by focusing on the notion of resolving conflicts between two NFRs of the same type. Needless to say, non-detection of any conflict between two NFRs – whether the NFRs are of the same type or not – at an early stage of RE, leads to higher costs for changes. The process of conflict resolution is essentially intuitive and hence is iterative. Our proposal hence is motivated by a view that differentiating the inter-conflicts with intra-conflicts, helps one in better focusing on the conflict resolution. We also propose an approach that allows a requirements analyst to semi-automatically identify intra-conflicts among NFRs at an early stage of RE using natural language processing, machine learning, and ontology-based semantic analysis. The controlled experiments, conducted on five publicly available datasets, achieve an average recall, precision, and F-measure of 0.57, 0.77, and 0.65 respectively.

Gathering information for an early, proactive integration of ergonomic user requirements is challenging due to the unstructured character of available knowledge. Knowledge acquisition and processing is therefore costly and time-consuming. This contribution presents and evaluates InProCo, an approach for structured ergonomic guidance that aims to improve accessibility and clarity of ergonomic requirements in early design phases by providing interaction-based ergonomic properties. InProCo reduces the complexity of gathering knowledge and provide a novel way to describe interactions. Within a three-stage evaluation process, a survey assessed standard interactions for completeness, the output given by the graphical user interface of the approach (GUI) was evaluated for correctness and the knowledge base was validated by comparing the approaches output with properties identified by participants within a one-day workshop. The results showed that there are enough predefined standard interactions, the output of the GUI is valid and the knowledge base contains high quality data. Practitioner Summary: InProCo is an approach that provides structured interaction-based ergonomic properties to improve accessibility and clarity of ergonomic requirements in early design phases. This contribution presents and evaluates InProCo building the prerequisite for further use in an industrial context.

Information and communication technologies are well thought-out as probable assets for the development of socioeconomics in developing countries. Studies have shown that enhanced infrastructure of telecommunication has facilitated means for underserved population development by various ways. Among the existing applications of ICT, the digital library systems provide with better solutions and respond to a variety of unmet needs of research institutions, scientific communities, and developments. With the development of digital library technology, the parallel database system has become the main tool for efficient information processing in the digital library system. On this basis, based on the parallel environment of the computer cluster, by coordinating the communication in the parallel environment, the coordinator, the collection machine, and the query processor can complete the operation of distribution, load, and maintenance, which has high efficiency and saves much precious time, supports the digital library to meet user requirements effectively, and meets the digital library’s performance requirements for data, and also, the key problem in the parallel algorithm has been solved. The experimental results show that this parallel technique has very good performance and efficiency.

Active aging technologies are increasingly designed to support an active lifestyle. However, the way in which they are designed can raise different barriers to acceptance of and use by older adults. Their designers can adopt a negative stereotype of aging. Thorough understanding of user requirements is central to this problem. This paper investigates user requirements for technologies that encourage an active lifestyle and provide older people with the means to self-manage their physical, mental, and emotional health. This requires consideration of the person and the sociotechnical context of use. We describe our work in collecting and analyzing older adults' requirements for a technology which enables an active lifestyle. The main contribution of the paper is a model of user requirements for inclusive technology for older people.

Planning driving routes is a common yet challenging task. Previous solutions that often suggest the shortest or time-dependent fastest paths for drivers are incompatible with the diversity of user requirements. Recent years are witnessing an increasing need of utility gained along the driving path and more advanced pathplanners are developed correspondingly, such as the safest and the most beautiful paths. Similar to the travel time on the edge, the utility score actually changes with the time as well. In this paper, targeting a more realistic path planning system, we allow both time cost and utility on the edge to vary from time to time. Over such two-fold time-dependent road network, we aim to discover the optimal driving path for the given user query. To address this NP-hard problem, we propose an approximated algorithm called 2TD Path-Planner, which mainly consists of three components, i.e., edge reachability computing, chromosome encoding, and chromosome decoding.

Redesigns of public transport networks are complex undertakings requiring a careful balancing of several conflicting perspectives (e.g., user requirements vs system performance) and aims (e.g., increasing spatial coverage, increasing frequency). Current assessment tools omit an explicit focus on navigability, often identified as a key aspect of the user perspective. For understanding the multidimensional perspective of navigability, this research introduces an assessment framework with both system and journey-level measures. The system-level measures provide an overview of redesigns based on static network representations. The journey-level measures are based on journey trajectories generated with a customized routing algorithm, assessing the distributive effects of the redesign. The framework is applied to public transport networks from nine cities with recently implemented redesigns, namely Amsterdam, Auckland, Austin, Baltimore, Columbus, Helsinki, Houston, Indianapolis, and Wellington. Results indicate that the redesigns have improved navigability both from a system-level and user perspective in general. However, in some cases, improvements in navigability come at the cost of increased travel time and number of transfers. Furthermore, the results suggest that the redesigns have differing emphasis within the regions, for different times of day, and for different aspects of network structure. The results are discussed both from the perspective of the case findings and for drawing more general planning and policy recommendations. Finally, this research provides a basis for further transdisciplinary approaches, encouraging connections between transport modeling and complex networks approaches.

Resource management (RM) is a challenging task in a cloud computing environment where a large number of virtualized, heterogeneous, and distributed resources are hosted in the datacentres. The uncertainty, heterogeneity, and the dynamic nature of such resources affect the efficiency of provisioning, allocation, scheduling, and monitoring tasks of RM. The most existing RM techniques and strategies have insufficiency in handling such cloud resources dynamic behaviour. To resolve these limitations, there is a need for the design and development of intelligent and efficient autonomic RM techniques to ensure the Quality-of-Service (QoS) of cloud-based applications, satisfy the cloud user requirements, and avoid a Service-Level Agreement (SLA) violations. This paper presents a comprehensive review along with a taxonomy of the most recent existing autonomic and elastic RM techniques in a cloud environment. The taxonomy classifies the existing autonomic and elastic RM techniques into different categories based on their design, objective, function, and applications. Moreover, a comparison and qualitative analysis is provided to illustrate their strengths and weaknesses. Finally, the open issues and challenges are highlighted to help researchers in finding significant future research options.

There are enormous software applications which are developed for the usage of the software users. The software user may be categorized as public users who use online services through internet, and the private users who use the specific software inside a specific organization only. The private users can be the business organizations, Educational institutions, Health care centers and other government organizations. Each organization has a specific requirement on the base of which the software and the customer relationship management frame work has to be designed. Organization specific software are developed, tested and delivered to the service users by the software development companies and where under maintenance by the development team in the timely manner. At times, when these registered users are in need of alterations and modifications in the software which are used, then the business process reengineering is required to be done. Thus business process reengineering plays a vital role in the maintainability and the sustainability of the software product based on the user requirement. To create an effective Business process Re-engineering Framework, the user (or) the stakeholder requirements are considered as the prerequisite. Based on the requirement the software product would be re-engineering, the stakeholders requirements has to be initially preprocessed and the stake holders has to be grouped and prioritized with the ranking of the requirement modules that has to be implemented. Finally the risk assessment has to be done to estimate the critical conditions or the changes that would be faced while re- engineering and the requirements will be clustered for effective execution.

In this paper seven of the most important issues in software systems development have been investigated. These issues address two aspects, namely: software development productivity and the final overall quality. For the productivity aspect, an approach has been devised relying on using scripts. Built as a result of an analyst-user collaboration, these scripts, upon interpretation, transform given user requirements into code. This prototyping approach, in addition to being rapid, involves the user in order to ensure his overall satisfaction with the final product. For the quality aspect, a two-layered repository of thoroughly tested and verified reusable software components has been built. The first layer contains the kernels to interpret the scripts. This is independent of the physical implementation of the functional components in the second layer. Using the repository, the care data manipulations of virtually any application can be automatically generated. Five applications covering five different domains have been designed and implemented to investigate the merits of the above described framework.

When developing a novel technological system, it is important to meet the users’ needs and expectations to ensure that the product will be accepted and applied by future users. To achieve that, a broadly based qualitative user-requirements analysis is essential. Following a user-centered design approach, a qualitative analysis was conducted to identify users’ needs and expectations for a future TV system. A prototype of the system has been developed with a focus on accessibility for deaf consumers by providing sign language via a virtual interpreter inserted into the traditional TV picture. The requirements analysis based on three different methods: the user interviews, the online questionnaire and the workshop. The statements given in the different studies handle similar topics. The respective detailed expectations by young and elder signers are mostly complementary, but partly even contrary. The results highlight the importance to set a user-requirements analysis on a broad database when developing technological systems. Only asking individual representatives of the user group and only applying individual methods would give very limited insight into users’ expectations and needs toward a technical system. To gain a detailed and representative picture for the whole community, a multimethod approach should be followed allowing for a feedback of several subgroups of the targeted population.

Business process simulation marks an essential technique for analyzing business processes and for reasoning about process improvement. With first contributions dating back to the mid-1990s, computerized business process simulation has been a continuing research focus and is widely acknowledged as foundational to Business Process Management research and practice. Reviewing contributions to the field published between 1990 and 2018, the authors assess the state of research on business process simulation and develop an organizing overview of research contributions discussing simulation approaches, tool support, results visualization, use context, application purposes, and adoption barriers. Findings inform future research on business process simulation by discussing paths for behavioral research on the use of business process simulation, user requirements, and adoption barriers as well as complementary paths for design science research addressing limitations of present approaches and simulation tool support.