Hasil untuk "Management information systems"

Wassim J. Aloulou, Rahaf Fahad Almarshedi, Shuayyi Sameer Alharbi et al.

This study investigates the relationships between proactive personality, psychological capital, work engagement, work well-being, and innovative work behavior among employees in Saudi public authorities, based on the conservation of resources theory and the job demands-resources model. Using a sequential mediation model, data from 457 public employees were analyzed through structural equation modeling. The results show that a proactive personality and psychological capital significantly predict work engagement, but neither is significantly related to work well-being. Notably, while a proactive personality does not directly impact innovative work behavior, psychological capital does. Additionally, work well-being partially mediates the relationship between work engagement and innovative work behavior. These findings suggest that enhancing psychological capital and fostering engagement are key to promoting innovation. The mediating role of well-being highlights the importance of employee welfare in this process. This study provides practical implications for HR managers in the Saudi public sector and emphasizes strategies for building internal psychological resources. However, as data were collected from a single source, future research should include multiple key informants to enhance generalizability. This study builds on theory by demonstrating how proactive personality and psychological capital jointly stimulate innovative behavior through engagement and well-being, enriching the job demands-resources model with personal resource dynamics in public sector organizations.

Emanuela Podda, Pol Hölzmer, Alexandre Amard et al.

The recent amendment to the European eIDAS Regulation has established the European Digital Identity Framework, which introduces electronic attestations of attributes. Technically, these attestations involve auxiliary information to ensure their verifiability, leading to the generation, processing, and storage of more than just personal data. In particular, this auxiliary information contains globally unique information that can be misused as personal identifiers and poses risks to the privacy of individuals engaging in transactions using a European Digital Identity Wallet. As such, they create tension with the principle of data minimisation under the General Data Protection Regulation (GDPR). On the positive side, privacy-enhancing technologies, especially zero-knowledge proofs (ZKPs), are rapidly advancing and capable of addressing this tension. In this paper, we analyse the impact of the availability of these techniques on legal compatibility in the European electronic identification context and explore the tension field between the technical requirements of the digital identity wallet and the GDPR’s data minimisation principle. We illustrate this dynamic through the specific examples of cryptographic data processed to ensure the authenticity and integrity of attributes' electronic attestations and shed light on how ZKPs can support legal compliance. This paper contributes to the privacy-oriented electronic identity management literature by providing policy and technical recommendations for achieving data minimisation compliance. We emphasise the necessity for regulatory bodies to enforce the use of advanced solutions like ZKPs to achieve unlinkability and unobservability. Accelerating the standardisation of these technologies is crucial for safeguarding user privacy and achieving seamless regulatory compliance in digital identity systems.

Elia Gabarron, Dillys Larbi, Octavio Rivera-Romero et al.

BackgroundArtificial intelligence (AI) has the potential to enhance physical activity (PA) interventions. However, human factors (HFs) play a pivotal role in the successful integration of AI into mobile health (mHealth) solutions for promoting PA. Understanding and optimizing the interaction between individuals and AI-driven mHealth apps is essential for achieving the desired outcomes. ObjectiveThis study aims to review and describe the current evidence on the HFs in AI-driven digital solutions for increasing PA. MethodsWe conducted a scoping review by searching for publications containing terms related to PA, HFs, and AI in the titles and abstracts across 3 databases—PubMed, Embase, and IEEE Xplore—and Google Scholar. Studies were included if they were primary studies describing an AI-based solution aimed at increasing PA, and results from testing the solution were reported. Studies that did not meet these criteria were excluded. Additionally, we searched the references in the included articles for relevant research. The following data were extracted from included studies and incorporated into a qualitative synthesis: bibliographic information, study characteristics, population, intervention, comparison, outcomes, and AI-related information. The certainty of the evidence in the included studies was evaluated using GRADE (Grading of Recommendations Assessment, Development, and Evaluation). ResultsA total of 15 studies published between 2015 and 2023 involving 899 participants aged approximately between 19 and 84 years, 60.7% (546/899) of whom were female participants, were included in this review. The interventions lasted between 2 and 26 weeks in the included studies. Recommender systems were the most commonly used AI technology in digital solutions for PA (10/15 studies), followed by conversational agents (4/15 studies). User acceptability and satisfaction were the HFs most frequently evaluated (5/15 studies each), followed by usability (4/15 studies). Regarding automated data collection for personalization and recommendation, most systems involved fitness trackers (5/15 studies). The certainty of the evidence analysis indicates moderate certainty of the effectiveness of AI-driven digital technologies in increasing PA (eg, number of steps, distance walked, or time spent on PA). Furthermore, AI-driven technology, particularly recommender systems, seems to positively influence changes in PA behavior, although with very low certainty evidence. ConclusionsCurrent research highlights the potential of AI-driven technologies to enhance PA, though the evidence remains limited. Longer-term studies are necessary to assess the sustained impact of AI-driven technologies on behavior change and habit formation. While AI-driven digital solutions for PA hold significant promise, further exploration into optimizing AI’s impact on PA and effectively integrating AI and HFs is crucial for broader benefits. Thus, the implications for innovation management involve conducting long-term studies, prioritizing diversity, ensuring research quality, focusing on user experience, and understanding the evolving role of AI in PA promotion.

Роман Пантюшенко, Юлія Чайка

The relevance of the study is due to the need for effective protection of information systems in the face of ever-growing cyber threats. In the modern digital world, where cyberattacks are becoming increasingly complex and widespread, the use of artificial intelligence in cybersecurity is extremely relevant. The problem of cybersecurity is becoming increasingly important and conducting relevant research is becoming a necessary aspect of ensuring security in the digital space. In this context, we propose an article that examines the role of artificial intelligence, innovations, challenges, and prospects of its development in the sphere of cybersecurity. Additionally, it explores the utilization of artificial intelligence for automating processes of detecting, analysing, and responding to cyber threats, and its practical significance for enhancing security levels in the digital space and the effectiveness of cyber threat protection. The main approaches for this study are trend analysis and expert assessments, which allow for a comprehensive review of the directions of artificial intelligence development in the field of cybersecurity, the benefits and challenges of its implementation, as well as potential opportunities and threats to information security. The article discusses advanced security information and event management systems designed to collect, analyse and respond to cyber threats and other systems aimed at specific aspects of protection and expanding automation capabilities to improve the security level of information systems. The materials of the article are of theoretical value for further scientific research on the use of artificial intelligence in the sphere of cybersecurity and reflect important features of its influence on this area. This research can contribute not only to deepening the understanding of the theoretical aspects of the use of artificial intelligence in cybersecurity but also to identifying specific practical applications and innovations that will help improve protection against cyber threats in the future.

Kedi Zheng, Hongye Guo, Qixin Chen

This paper studies the pool strategy for price-makers under imperfect information. In this occasion, market participants cannot obtain essential transmission parameters of the power system. Thus, price-makers should estimate the market results with respect to their offer curves using available historical information. The linear programming model of economic dispatch is analyzed with the theory of rim multi-parametric linear programming (rim-MPLP). The characteristics of system patterns (combinations of status flags for generating units and transmission lines) are revealed. A multi-class classification model based on support vector machine (SVM) is trained to map the offer curves to system patterns, which is then integrated into the decision framework of the price-maker. The performance of the proposed method is validated on the IEEE 30-bus system, Illinois synthetic 200-bus system, and South Carolina synthetic 500-bus system.

S. Erengüç, N. Simpson, A. Vakharia

Junzhuo Li, Wenyong Li, Guan Lian

A low-cost, timely, and durable long-term approach to resident travel surveys is crucial for authorities to understand the city’s transportation systems and formulate transportation planning and management policies. This paper summarizes commonly used wireless positioning technologies and uses the STDBSCAN method to identify travel endpoints based on the characteristics of trajectory location information. It uses Shenzhen cellular signaling data to visually analyze the spatial and temporal distribution of urban traffic demand, traffic correlation, and asymmetry of traffic flow between different traffic zones. The results confirm that mobile internet information represented by cellular signaling information can effectively reflect the traffic status of urban areas, which, compared to traditional travel survey methods, has the advantages of lower cost, more timely feedback, and can be durably carried out in the long term.

Aldiansah Prayogi, Rizal Fathoni Aji

The Covid-19 pandemic has kept almost everyone at home and forced them to perform online activities using their mobile gadgets. Penetration of the Internet and mobile use is increased as lockdowns or restrictions on meeting face to face are getting used to. This has become a new market for cyber criminals to carry out their actions, such as spreading Social Engineering, sending Phishing, doing Account Takeover, and ending in theft of money in Financial Mobile Applications. Application protection with OTP SMS and Magic Link SMS still has vulnerabilities, with several examples of cases that have occurred. For this reason, this problem was raised to find a solution using the Mobile Network Infrastructure. The method used is to compare the congruence between the phone numbers registered in the application and the phone numbers used. Every time a user signs in or signs up, the Financial Mobile Application will perform Mobile Network Verification to cellular operators via API. Verification is carried out by utilizing the header enrichment in the background of the application process that was installed on the user's smartphone or tablet to the Mobile Network Verification Server. The Financial Mobile Applications can then determine whether the user is using a valid or invalid telephone number. Therefore, the target account cannot be taken over because the cyber criminal's mobile device does not have the phone number attached to the victim’s mobile device. This proof is carried out with four test case scenarios with the sign-up and sign-in processes on the same phone number and different phone numbers between devices and applications. It is hoped that this kind of protection model can reduce losses experienced by users of Financial Mobile Applications due to Account Takeover.

Manuela Daniela Danu, George Marica, Sanjeev Kumar Karn et al.

Among all the sub-sections in a typical radiology report, the Clinical Indications, Findings, and Impression often reflect important details about the health status of a patient. The information included in Impression is also often covered in Findings. While Findings and Impression can be deduced by inspecting the image, Clinical Indications often require additional context. The cognitive task of interpreting medical images remains the most critical and often time-consuming step in the radiology workflow. Instead of generating an end-to-end radiology report, in this paper, we focus on generating the Findings from automated interpretation of medical images, specifically chest X-rays (CXRs). Thus, this work focuses on reducing the workload of radiologists who spend most of their time either writing or narrating the Findings. Unlike past research, which addresses radiology report generation as a single-step image captioning task, we have further taken into consideration the complexity of interpreting CXR images and propose a two-step approach: (a) detecting the regions with abnormalities in the image, and (b) generating relevant text for regions with abnormalities by employing a generative large language model (LLM). This two-step approach introduces a layer of interpretability and aligns the framework with the systematic reasoning that radiologists use when reviewing a CXR.

Muhammad Shoaib Farooq, Rana Muhammad Nadir, Furqan Rustam et al.

Several smart city ideas are introduced to manage various problems caused by overpopulation, but the futuristic smart city is a concept based on dense and artificial-intelligence-centric cities. Thus, massive device connectivity with huge data traffic is expected in the future where communication networks are expected to provide ubiquity, high quality of service, and on-demand content for a large number of interconnected devices. The sixth-generation (6G) network is considered the problem-solving network of futuristic cities, with huge bandwidth and low latency. The expected 6G of the radio access network is based on terahertz (THz) waves with the capability of carrying up to one terabit per second (Tbps). THz waves have the capability of carrying a large amount of data but these waves have several drawbacks, such as short-range and atmospheric attenuation. Hence, these problems can introduce complications and hamper the performance of the 6G network. This study envisions futuristic smart cities using 6G and proposes a conceptual terrestrial network (TN) architecture for 6G. The nested Bee Hive is a scalable multilayer architecture designed to meet the needs of futuristic smart cities. Moreover, we designed the multilayer network infrastructure while considering the expectations from a network of futuristic smart cities and the complications of THz waves. Extensive simulations are performed using different pathfinding algorithms in the 3D multilayer domain to evaluate the performance of the proposed architecture and set the dynamics of futuristic communication of 6G.

I Made Dananjaya Priyatama, Ridwansyah Ridwansyah

Anak Tunagrahita ialah anak yang memiliki perbedaan dari anak yang lain yang dapat dilihat secara signifikan dengan kasat mata kita, karena mereka merupakan anak berkebutuhan khusus baik secara mental, fisik mereka maupun dapat di lihat dari psikologi mereka. Intelektual  anak tunagrahita secara sosial lebih lambat melakukan segala hal dalam mencapai tujuan yang mereka inginkan secara maksimal. Anak Tunagrahita biasanya mempunyai gangguan seperti gangguan tidak bisa berbicar atau cacat fisik dan mental, serta emosional yamg tidak terkendali. Permasalahan yang ada dengan para pengajar anak berkebutuhan khusus karena banyak nya tenaga pengajar yang belum mengetahui ciri – ciri dari anak tunagrahita dan cara penanganannya melalui tingkat IQ dan beberapa faktor lain nya. Dalam penyelesaian masalah untuk anak berkebutuhan khusus maka anak-anak tersebut perlu di klasifikasikan yang dikarenakan perbedaan mereka satu orang dengan orang  lainnya dalam keterlambatan perkembangan dan kondisi fisik yang mereka alami, sehingga perlu membedakan strategi pendidikan ataupun pengajaran yang di rancang dan di programkan untuk mereka. Dengan metode Algoritma C4.5 yang dapat mengklasifikasikan anak berkebutuhan khusus berdasarkan ciri-ciri yang ada dengan data yang di uji dengan model yang di gunakan cross validation dan di evaluasi dengan confusion matrix. Berdasarkan hasil pengujian dengan metode tersebut akurasi yang didapat sangat tinggi sehingga dapat di gunakan oleh para tenaga pengajar dari informasi yang akurat tersebut.

Javed Iqbal, Usman Illahi, Muhammad Abbas Khan et al.

In this research article, a single-fed dual-band circular polarized (CP) dielectric resonator antenna (DRA) for dual-function communication, such as GPS and WLAN, was made. Initially, the proposed design process was initiated by designing a linearly polarized singly fed-DRA. To attain CP fields, the cross-shape conformal metal strip was optimized to excite the fundamental and the high-order mode in the two frequency bands. The metallic strip (parasitic) was utilized on top of the rectangular DRA to improve and widen the impedance and axial ratio (AR) bandwidth. This step led to a 2.73% improvement on the lower band and an impact of 6.5% on the upper band while on the other side a significant improvement was witnessed in the AR bandwidth in both frequency bands. A prototype was designed and fabricated in order to validate its operations. The measurement outcomes of the proposed antennas authenticated wideband impedance bandwidths of 6.4% and 25.26%, and 3-dB axial ratios (AR) of 21.26% and 27.82% respectively. The prototype is a decent candidate for a global positioning system (GPS) and wireless local area network (WLAN).

Alireza Farimani, Omid Pourheidari, Ahmad Khodamipour

Subject and purpose of the article: The main purpose of the research is to identify the indicators of interactive and diagnostic approaches in the use of management control systems in order to accept the new management accounting activities using the content analysis approach and provide a favorable structural model.Research method: The statistical population is experts and the number of samples is determined through the snowball method. Field method using library studies and interviews is used to collect data in order to identify indicators. Data is analysed through the theme analysis method. MAXQDA software is used for qualitative content analysis.Research findings: Finally, 17 criteria are determined: identifying strategic uncertainty and developing operational plans, face-to-face meetings between senior and operational managers, valuate managers' interactions, producer of information that forms important goals, track progress towards goals and monitor results, planning in line with strategic goals, performance review and consequenses assessment, Management Based Activity (MBA).Conclusion, originality and its contribution to the knowledge: According to the proposed model, the criteria for identifying strategic uncertainty, time and cost management and communication management are the main criteria of the interactive and diagnostic approaches model in using management control systems in order to accept the new management accounting activities. Considering the goal of modern public management in transforming public sector organizations into organizations with more customer focus and more quality focus, this research is done to identify the indicators of interactive and diagnostic approaches in the use of management control systems in order to accept the new management accounting activities.

Michael Petraglia, Nicole Boivin, Eregzen Gelegdorj et al.

Background: The archaeological and ethnographic heritages of Mongolia reflect a multi-millennial continuity of typically mobile-pastoral occupations across sparsely populated, environmentally diverse landscapes, but the threats of modernisation and industrialisation to those heritages are nevertheless present and substantial. The construction of the Erdeneburen Hydroelectric Dam on the Khovd River in western Mongolia is planned to submerge hundreds of archaeological features and jeopardise at least another thousand. Methods: The Mongolian Archaeology Project: Surveying the Steppes, in collaboration with the Mongolian Institute of Archaeology, integrates a variety of digital techniques including GIS (geographic information systems), Machine Learning automated site detection, drone mapping, and Structure-from-Motion LiDAR scanning to document the endangered archaeology. This paper presents the resulting dataset of archaeological features across three different impact zones associated with the dam construction and evaluates the degree of efficacy of the initial data integration strategy through informal partner feedback and self-assessment. Results: While only approximately 20% of the documented sites fall within the planned flood zone, the remaining sites will be subjected to collateral threats such as industrial and infrastructural development that will necessitate extended monitoring, both temporally and spatially. In consideration of these results, this paper argues that a ‘responsive’ mode of heritage disaster intervention can bridge the gap between ‘reactive’ and ‘proactive’ modes, but requires development of an integrated (digital) methodology. Conclusions: The paper concludes by offering a new, more interconnected ‘transmethodology’ that addresses spatiality, sub-sampling, data reuse, and community input across multiple disciplines such as cultural heritage preservation, salvage archaeology, computer vision, and community archaeology. The authors developed this ‘transmethodology’ and the resulting workflows out of a theoretical framework that considers principles of Symmetrical Archaeology, Resilience Humanitarianism, and the CARE standard for inclusive data management (Collective benefit, Authority to control, Responsibility, and Ethics).

Monosi Andries Bolowe, Ketshephaone Thutwa, Phetogo Ineeleng Monau et al.

The aim of this study was to describe the indigenous Tswana sheep production systems, their management and farmers’ preferred selection traits when selecting breeding rams in four southern districts of Botswana. A total of 105 households; Kgatleng (<i>n</i> = 30), Kweneng (<i>n</i> = 27), southern (<i>n</i> = 24) and south–east (<i>n</i> = 24) districts were interviewed using structured questionnaire. An index-based approach was used to rank farmers’ most preferred traits for their production systems. Data were analyzed using Statistical Package for Social Sciences. The Chi-square test was used to assess the statistical significance among categorical variables. The results indicated that indigenous Tswana sheep are mainly kept by males, single people, aged between 51 and 60 years possessing primary and secondary education. Management practices across the districts include castration, health care and supplementation mostly during the dry season. Superior fitness traits of indigenous Tswana rams over exotic rams were considered more important when selecting breeding rams in Kgatleng, Kweneng and south–east while in the southern district, rams were mainly selected based on body size. Most farmers kept breeding rams while those who did not keep rams depended on communal rams for service. This information is important in designing successful breeding programs and strategies for the conservation and sustainable utilization of indigenous Tswana sheep genetic resources.

Hasala Gallolu Kankanamalage, Yuandan Lin, Yuan Wang

Motivated by the regulator theory and adaptive controls, several notions on output stability in the framework of input-to-state stability (iss) were introduced for finite-dimensional systems. It turned out that these output stability notions are intrinsically different, reflecting different manners of how state variables may affect the transient behavior of output variables. In this work, we consider these output stability properties for delay systems. Our main objective is to illustrate how the various notions are related for delay systems and to provide the Razumikhin criteria for the output stability properties. The main results are also critical in developing the converse Lyapunov theorems of the output stability properties for delay systems

Zhifeng Tang, Nan Yang, Parastoo Sadeghi et al.

We analytically decide whether the broadcast transmission scheme or the unicast transmission scheme achieves the optimal age of information (AoI) performance of a multiuser system where a base station (BS) generates and transmits status updates to multiple user equipments (UEs). In the broadcast transmission scheme, the status update for all UEs is jointly encoded into a packet for transmission, while in the unicast transmission scheme, the status update for each UE is encoded individually and transmitted by following the round robin policy. For both transmission schemes, we examine three packet management strategies, namely the non-preemption strategy, the preemption in buffer strategy, and the preemption in serving strategy. We first derive new closed-form expressions for the average AoI achieved by two transmission schemes with three packet management strategies. Based on them, we compare the AoI performance of two transmission schemes in two systems, namely, the remote control system and the dynamic system. Aided by simulation results, we verify our analysis and investigate the impact of system parameters on the average AoI. For example, the unicast transmission scheme is more appropriate for the system with a large number UEs. Otherwise, the broadcast transmission scheme is more appropriate.

Peng Gao, Xiaoyuan Liu, Edward Choi et al.

Open-source cyber threat intelligence (OSCTI) has become essential for keeping up with the rapidly changing threat landscape. However, current OSCTI gathering and management solutions mainly focus on structured Indicators of Compromise (IOC) feeds, which are low-level and isolated, providing only a narrow view of potential threats. Meanwhile, the extensive and interconnected knowledge found in the unstructured text of numerous OSCTI reports (e.g., security articles, threat reports) available publicly is still largely underexplored. To bridge the gap, we propose ThreatKG, an automated system for OSCTI gathering and management. ThreatKG efficiently collects a large number of OSCTI reports from multiple sources, leverages specialized AI-based techniques to extract high-quality knowledge about various threat entities and their relationships, and constructs and continuously updates a threat knowledge graph by integrating new OSCTI data. ThreatKG features a modular and extensible design, allowing for the addition of components to accommodate diverse OSCTI report structures and knowledge types. Our extensive evaluations demonstrate ThreatKG's practical effectiveness in enhancing threat knowledge gathering and management.

M. Abernethy, A. Lillis

Svitlana Vakulenko, Evangelos Kanoulas, Maarten de Rijke

Conversational search is a relatively young area of research that aims at automating an information-seeking dialogue. In this paper we help to position it with respect to other research areas within conversational Artificial Intelligence (AI) by analysing the structural properties of an information-seeking dialogue. To this end, we perform a large-scale dialogue analysis of more than 150K transcripts from 16 publicly available dialogue datasets. These datasets were collected to inform different dialogue-based tasks including conversational search. We extract different patterns of mixed initiative from these dialogue transcripts and use them to compare dialogues of different types. Moreover, we contrast the patterns found in information-seeking dialogues that are being used for research purposes with the patterns found in virtual reference interviews that were conducted by professional librarians. The insights we provide (1) establish close relations between conversational search and other conversational AI tasks; and (2) uncover limitations of existing conversational datasets to inform future data collection tasks.