This study examines diverse information media in order to identify those formats that are most suitable for consumption via handheld mobile devices, namely, smartphones and tablets. The preferences of the users are measured objectively by analyzing actual data of their relative use of handheld mobile devices and personal computing (PC) desktop devices, including laptops and notebooks, for consumption of information presented in various formats. Our findings are based on Google Analytics pageview data of five course Websites during a period of three semesters, by 11,557 undergraduate students. M-learning contexts were chosen, since in a learning environment the interests of information providers (i.e., the instructors) are in accord with those of the information consumers (i.e., the students), whereas in commercial settings there may be conflicts of interests. Our findings demonstrate that although about 90% of the pageviews were via PC devices, the rate of smartphone use for consuming learning content in diverse information media is gradually increasing as time goes by, whereas the rate of tablet use for these purposes is stagnant. The most promising direction for smartphone development, emanating from the findings, is online video content.

This paper compares the effect of social isolation on students enrolled in online courses versus students enrolled in on campus courses (called in this paper Face-to-Face or F2F). Grade data was collected from one online section and two F2F sections of a computer literacy course that was recently taught by one of the authors of this study. The same instructor taught all sections thereby providing a controlled comparison between the two forms of teaching (F2F and online). This paper first introduces the plan and the limitation of this study. It provides a literature review and notes the trend of social isolation found in online courses. This paper then presents a summary of the collected data; and offers a conclusion based on the collected data.

Though the field of management information systems, as a sector and a discipline, is the inventor of many guidelines and models, it appears to be a slow runner on practical implications of interface usability. This usability can influence end users’ attitude and behavior to use IT. The purpose of this paper was to examine the interface usability of a popular Enterprise Resource Planning (ERP) software system, SAP, and to identify related issues and implications to the Technology Acceptance Model (TAM). A survey was conducted of 112 SAP ERP users from an organization in the heavy metal industry in Bangladesh. The partial least squares technique was used to analyze the survey data. The survey findings empirically confirmed that interface usability has a significant impact on users’ perceptions of usefulness and ease of use which ultimately affects attitudes and intention to use the ERP software. The research model extends the TAM by incorporating three criteria of interface usability. It is the first known study to investigate usability criteria as an extension of TAM.

Aim/Purpose: 5G and IoT are two path-breaking technologies, and they are like wall and climbers, where IoT as a climber is growing tremendously, taking the support of 5G as a wall. The main challenge that emerges here is to secure the ecosystem created by the collaboration of 5G and IoT, which consists of a network, users, endpoints, devices, and data. Other than underlying and hereditary security issues, they bring many Zero-day vulnerabilities, which always pose a risk. This paper proposes a security solution using network slicing, where each slice serves customers with different problems. Background: 5G and IoT are a combination of technology that will enhance the user experience and add many security issues to existing ones like DDoS, DoS. This paper aims to solve some of these problems by using network slicing and implementing an Intrusion Detection System to identify and isolate the compromised resources. Methodology: This paper proposes a 5G-IoT architecture using network slicing. Research here is an advancement to our previous implementation, a Python-based software divided into five different modules. This paper’s amplification includes induction of security using pattern matching intrusion detection methods and conducting tests in five different scenarios, with 1000 up to 5000 devices in different security modes. This enhancement in security helps differentiate and isolate attacks on IoT endpoints, base stations, and slices. Contribution: Network slicing is a known security technique; we have used it as a platform and developed a solution to host IoT devices with peculiar requirements and enhance their security by identifying intruders. This paper gives a different solution for implementing security while using slicing technology. Findings: The study entails and simulates how the IoT ecosystem can be variedly deployed on 5G networks using network slicing for different types of IoT devices and users. Simulation done in this research proves that the suggested architecture can be successfully implemented on IoT users with peculiar requirements in a network slicing environment. Recommendations for Practitioners: Practitioners can implement this solution in any live or production IoT environment to enhance security. This solution helps them get a cost-effective method for deploying IoT devices on a 5G network, which would otherwise have been an expensive technology to implement. Recommendation for Researchers: Researchers can enhance the simulations by amplifying the different types of IoT devices on varied hardware. They can even perform the simulation on a real network to unearth the actual impact. Impact on Society: This research provides an affordable and modest solution for securing the IoT ecosystem on a 5G network using network slicing technology, which will eventually benefit society as an end-user. This research can be of great assistance to all those working towards implementing security in IoT ecosystems. Future Research: All the configuration and slicing resources allocation done in this research was performed manually; it can be automated to improve accuracy and results. Our future direction will include machine learning techniques to make this application and intrusion detection more intelligent and advanced. This simulation can be combined and performed with smart network devices to obtain more varied results. A proof-of-concept system can be implemented on a real 5G network to amplify the concept further.

Aim/Purpose: This study focuses on two targeting strategies of out-store Location-Based Mobile Advertising (LBMA): the geo-fencing strategy (i.e., targeting customers who are near the focal store) and the geo-conquesting strategy (i.e., targeting those who are near competitors’ stores to visit the focal store). To the authors’ knowledge, no previous studies have compared the perceived intrusiveness of advertisements (ads) in geo-fencing and geo-conquesting settings, despite the accumulating literature on out-store LBMA. Hence, the aim of this study is to determine which targeting strategy is more effective in terms of reducing the perception of ads’ intrusiveness and increasing positive customers’ attitudes and purchase intention. Background: The intrusive nature of LBMA is perceived negatively by some customers, impacting their attitudes toward the ad, purchase intention, and even their perception of the brand. Therefore, identifying the targeting strategy under which ads are perceived as less intrusive is essential. Additionally, brick-and-mortar clothing stores in Jordan are facing challenges due to the rise of online shopping and increased competition from nearby stores. Thus, examining geo-fencing and geo-conquesting might tackle these challenges and encourage local clothing retailers to adopt these strategies. Methodology: A quantitative method was used in this study. A between-subjects experimental design was used to collect the data using a scenario-based survey distributed to Jordanians aged 18 to 45. A total of 531 responses were collected. After excluding those who do not belong to the targeted age group and those who did not pass the manipulation check, 406 responses were analyzed using the Statistical Package for the Social Sciences (SPSS) software version 28 and the Analysis of Moment Structures (AMOS) software version 26 to conduct Structural Equation Modeling (SEM). Contribution: This work offers valuable contributions by investigating the impact of the perceived intrusiveness of ads on purchase intention in the contexts of geo-fencing and geo-conquesting, which has not been studied before. Additionally, it fills a gap by examining this phenomenon in Jordan, a developing country in which attitudes toward LBMA have not been previously explored. Findings: The results revealed that location-based mobile ads sent under a geo-fencing strategy are perceived as less intrusive than those sent under a geo-conquesting strategy. In addition, customers’ attitudes fully mediate the relationship between intrusiveness and purchase intention only under the geo-fencing strategy. Ultimately, neither of the strategies is more effective in terms of increasing positive customer attitudes and purchase intentions in the context of clothing retail stores in Jordan. Recommendations for Practitioners: Clothing retailers in Jordan should consider adopting geo-fencing and geo-conquesting strategies to boost purchase intentions and tackle industry challenges. Additionally, to increase purchase intentions with geo-fencing, practitioners should focus on fostering positive customer attitudes toward ads, as simply perceiving them as less intrusive is not sufficient to drive purchase intention without the mediating effect of positive attitudes. Recommendation for Researchers: This research is crucial for academics and researchers as geolocation technology and LBMA are expected to advance significantly in the future. Researchers can investigate this topic through a randomized field experiment, followed by a research questionnaire to collect data from a real-world setting. Impact on Society: Utilizing LBMA is essential for local clothing retail stores that are trying to effectively reach and connect with their customers because searching the Internet for local goods and services is done primarily on mobile devices. Indeed, this study revealed that customers in both settings (i.e., geo-fencing and geo-conquesting) reported a high intention to visit the promoting store and to purchase from the advertised product category. Future Research: Future research can apply this topic to different industries and cultural contexts, as the results may vary across industries and regions. Moreover, future research could build on this study by investigating additional constructs, such as product category involvement, customization, and content type of the message (e.g., informative, entertaining).

With the continuous growth and importance of data, the need for strong data protection becomes crucial. Encryption plays a vital role in preserving the confidentiality of data, and attribute-based encryption (ABE) offers a meticulous access control system based on attributes. This study investigates the integration of Fernet encryption with initialisation vector (IV) and ABE, resulting in a hybrid encryption approach that enhances both security and flexibility. By combining the advantages of Fernet encryption and IV-based encryption, the hybrid encryption scheme establishes an effective and robust mechanism for safeguarding data. Fernet encryption, renowned for its simplicity and efficiency, provides authenticated encryption, guaranteeing both the confidentiality and integrity of the data. The incorporation of an initialisation vector (IV) introduces an element of randomness into the encryption process, thereby strengthening the overall security measures. This research paper discusses the advantages and drawbacks of the hybrid encryption of Fernet and IV with ABE.

Empowered by and tethered to ubiquitous technologies, the current generation of youth yearns for opportunities to engage in self-expression and information sharing online with personal disclosure no longer governed by concepts of propriety and privacy. This raises issues about the unsafe online activities of teens and young adults. The following paper presents the findings of a study examining the social networking activities of undergraduate students and also highlights a program to increase awareness of the dangers and safe practices when using and communicating, via social media. According to the survey results, young adults practice risky social networking site (SNS) behaviors with most having experienced at least one negative consequence. Further, females were more likely than males to engage in oversharing as well as to have experienced negative consequences. Finally, results of a post-treatment survey found that a targeted program that includes flyers, posters, YouTube videos, handouts, and in-class information sessions conducted at a Mid-Atlantic Historically Black College or University (HBCU) increased student awareness of the dangers of social media as well as positively influenced students to practice more prudent online behaviors.

Personalization is one of the most expected features in the current educational systems. User modeling is supposed to be the first stage of this process, which may incorporate learning style as an important part of the model. Learning style, which is a non-stable characteristic in the case of children, differentiates students in learning preferences. This paper identifies a new hybrid method to initiate and update the information of children’s learning style in an educational system. At the start-up phase, children’s learning style information is gathered through the modified Murphy-Meisgeier Type Indicator for Children (MMTIC) questionnaire, which is based on the well-known Myers-Briggs Type Indicator (MBTI). This primary information will be tuned by tracking children’s behaviors during the learning process. Analytical data mining helped us to cluster these behaviors and find their patterns. The proposed method was applied on 81 fourth grade children in elementary school. Delivering results suggest that this method provides a good precision in recognizing children learning style and may be an appropriate solution for non-stability problems in their preferences.

Aim/Purpose: As online video lectures rapidly gain popularity in formal and informal learning environments, one of their main challenges is student retention. This study investigates the influence of adding interactivity to online video lectures on students’ attention span. Background: Interactivity is perceived as increasing the attention span of learners and improving the quality of learning. However, interactivity may be regarded as an interruption, which distracts students. Furthermore, adding interactive elements to online video lectures requires additional investment of various resources. Therefore, it is important to investigate the impact of adding interactivity to online video lectures on the attention span of learners. Methodology: This study employed a learning analytics approach, obtained data from Google Analytics, and analyzed data of two Massive Open Online Courses (MOOCs) that were developed by the Open University of Israel in order to make English for academic purposes (EAP) courses freely accessible. Contribution: The paper provides important insights, based on quantitative empirical research, on: integrating interactive elements in online videos; the impact of video length; and differences between two groups of advanced and basic learners. Furthermore, it demonstrates how learning analytics may be used for improving instructional design. Findings: The findings suggest that interactivity may increase the attention span of learners, as measured by the average online video lecture viewing completion percentage, before and after the addition of interactivity. However, when the lecture is longer than about 15 minutes, the completion percentages decrease, even after adding interactive elements. Recommendations for Practitioners: Adding interactivity to online video lectures and controlling their length is expected to increase the attention span of learners. Recommendation for Researchers: Learning analytics is a powerful quantitative methodology for identifying ways to improve learning processes. Impact on Society: Providing practical insights on mechanisms for increasing the attention span of learners is expected to improve social inclusion. Future Research: Discovering further best practices to improve the effectiveness of online video lectures for diverse learners.

Aim/Purpose: This paper presents the preliminary findings of a pilot survey that sought to examine the technology uses, backgrounds, needs, interests, career goals, and professional expectations of Generation Z students enrolled at a minority serving institution in the United States Mid-Atlantic region. Background: Students entering college today are part of Generation Z born in the late 90’s through 2016. Known for their short attention spans and heightened ability to multi-task, they already outnumber millennials and are the first true digital natives born during the age of smart phone. Methodology: In the fall of 2017, an online student perception survey was piloted with stu-dents enrolled at a mid-Atlantic minority serving institution. The survey included a combination of dichotomous, Likert-scaled, and ranking questions. The survey was administered electronically using the Survey Monkey system to students following completion of core computer concepts courses and explored their technology backgrounds, skills, perceived computing self-efficacy, and the role they predict technology will play in their future career. The data was subsequently exported to Microsoft Excel and SPSS where descriptive statistical analyses were conducted. Contribution: As Generation Z descends on college campuses, with their technology domi-nated backgrounds and different communications, learning, and social prefer-ences, it is important to better understand this generation whose needs and expectations will help shape the future of higher education. Additionally, this study also provides research on a population (first-generation minority college students) that is expanding in numbers in higher education and that the litera-ture, reports is impacted negatively by the digital divide and educational inequalities. This paper is timely and relevant and helps to extend our understanding of Generation Z. Findings: The findings show that Generation Z learners enrolled in a minority-serving institution enjoy computer classes, feel that using computers comes easy to them; and perceive themselves as experts in the use of social media, mobile operating systems, using a smart phone, searching the Web, and email. Participants also reported that they want to be more technologically literate, want to be more skilled in computer software applications, and are interested in learning about cyber security. In terms of the future, most respondents also believe that their career will require them to analyze information to inform decision making. Additionally, most stated that information security will be important to their future career. Finally, the results affirmed that college computing courses remain important and that college students recognize that technology will play a crucial role in their career with employers wanting to see job applicants with strong technology skills. Recommendations for Practitioners: Generation Z learners enrolled in higher education need, and want, a wide range of technology courses available to them in order to help them meet the rapidly evolving demands of tomorrow’s workplace. Students in this study overwhelmingly see the value in enhancing their technology skills especially in such areas as computer software applications, information management, and cyber security. Recommendation for Researchers: Institutions of higher education should invest in thorough and ongoing examinations of the information and technology literacy skills, needs, and perceptions of students. Impact on Society: Understanding the interests and needs of Generation Z learners is imperative to the future of higher education. Future Research: This survey is a work in progress that is part of a pilot study that is being used to help guide a much more sizable examination of Generation Z learners.

Based on the diffusion of innovation (DOI) theory (Rogers, 2003), the uses and gratifications (U&G) theory, and trust theory, this study investigated the factors that influence the use of Twitter among the Kuwaiti community. The study surveyed Twitter users in Kuwait. A structured online questionnaire was used to collect data, and 463 respondents who provided complete answers participated. Multiple regression analysis was used to examine the effect of three theoretical perspectives on Twitter usage. The result of the analysis showed that Twitter usage is better explained by DOI constructs than by U&G constructs. The findings indicated that the perceived relative advantage from DOI, and the need for information, need to pass time, and need for interpersonal utility from the U&G approach, have a direct positive significant effect on the use of Twitter. None of the trust theory constructs was found to be significant in predicting the general use of Twitter. The study results help Twitter providers and users in individual or organizational contexts to understand what factors generally affect the usage of the Twitter service.

The all-pervasive Internet has created serious problems, such as Internet overuse, which has triggered considerable debate over its relationship with addiction. To further explore its genetic susceptibilities and alternative explanations for Internet overuse, we proposed and evaluated four hypotheses, each based on existing knowledge of the biological bases of addiction, inattention, novelty-seeking, and harm-avoidance. Four genetic loci including DRD4 VNTR, DRD2 Taq1A, COMT Val158Met and 5-HTTLPR length polymorphisms were screened from seventy-three individuals. Our results showed that the DRD4 4R/4R individuals scored significantly higher than the 2R or 7R carriers in Internet Addiction Test (IAT). The 5-HTTLPR short/short males scored significantly higher in IAT than the long variant carriers. Bayesian analysis showed the most compatible hypothesis with the observed genetic results was based on attention (69.8%), whereas hypotheses based harm-avoidance (21.6%), novelty-seeking (7.8%) and addiction (0.9%) received little support. Our study suggests that carriers of alleles (DRD4 2R and 7R, 5-HTTLPR long) associated with inattentiveness are more likely to experience disrupted patterns and reduced durations of Internet use, protecting them from Internet overuse. Furthermore, our study suggests that Internet overuse should be categorized differently from addiction due to the lack of shared genetic contributions.

Aim/Purpose: This review paper aims to unveil some underlying machine-learning classification algorithms used for political election predictions and how stack ensembles have been explored. Additionally, it examines the types of datasets available to researchers and presents the results they have achieved. Background: Predicting the outcomes of presidential elections has always been a significant aspect of political systems in numerous countries. Analysts and researchers examining political elections rely on existing datasets from various sources, including tweets, Facebook posts, and so forth to forecast future elections. However, these data sources often struggle to establish a direct correlation between voters and their voting patterns, primarily due to the manual nature of the voting process. Numerous factors influence election outcomes, including ethnicity, voter incentives, and campaign messages. The voting patterns of successors in regions of countries remain uncertain, and the reasons behind such patterns remain ambiguous. Methodology: The study examined a collection of articles obtained from Google Scholar, through search, focusing on the use of ensemble classifiers and machine learning classifiers and their application in predicting political elections through machine learning algorithms. Some specific keywords for the search include “ensemble classifier,” “political election prediction,” and “machine learning”, “stack ensemble”. Contribution: The study provides a broad and deep review of political election predictions through the use of machine learning algorithms and summarizes the major source of the dataset in the said analysis. Findings: Single classifiers have featured greatly in political election predictions, though ensemble classifiers have been used and have proven potent use in the said field is rather low. Recommendation for Researchers: The efficacy of stack classification algorithms can play a significant role in machine learning classification when modelled tactfully and is efficient in handling labelled datasets. however, runtime becomes a hindrance when the dataset grows larger with the increased number of base classifiers forming the stack. Future Research: There is the need to ensure a more comprehensive analysis, alternative data sources rather than depending largely on tweets, and explore ensemble machine learning classifiers in predicting political elections. Also, ensemble classification algorithms have indeed demonstrated superior performance when carefully chosen and combined.

Lihan TONG,Weijia LI,Qingxia YANG,Liyuan CHEN,Peng CHEN, Vol.E107-D, No.11, pp.1472-1475
We present Ksformer, utilizing Multi-scale Key-select Routing Attention (MKRA) for intelligent selection of key areas through multi-channel, multi-scale windows with a top-k operator, and Lightweight Frequency Processing Module (LFPM) to enhance high-frequency features, outperforming other dehazing methods in tests.
Publication Date: 2024/11/01

Hierarchy is a reality of group life, for humans as well as for most other group-living species. And yet, there remains considerable debate about whether and when hierarchy can promote group performance and member satisfaction. We suggest that progress in this debate has been hampered by a lack of clarity about hierarchy and how to conceptualize it. Whereas prevailing conceptualizations of hierarchy in the group and organization literature focus on inequality in member power or status (i.e., centralization or steepness), we build on the ethological and social network traditions to advance a view of hierarchy as cascading relations of dyadic influence (i.e., acyclicity). We further suggest that hierarchy thus conceptualized is more likely to capture the functional benefits of hierarchy whereas hierarchy as inequality is more likely to be dysfunctional. In a study of 75 teams drawn from a wide range of industries, we show that whereas acyclicity in influence relations reduces conflict and thereby enhances both group performance and member satisfaction, centralization and steepness have negative effects on conflict, performance, and satisfaction, particularly in groups that perform complex tasks. The theory and results of this study can help to clarify and advance research on the functions and dysfunctions of hierarchy in task groups.

Growing workforce diversity increases the likelihood that supervisors and subordinates will differ along demographic lines, a situation that has important implications for their relationship quality and individual outcomes. In a sample of 1,253 employees from 54 work-units, we investigate the effects of differences in disability status between supervisors and subordinates on leader-member-exchange (LMX) quality and subsequent performance ratings, and find that incongruence in general is related to lower LMX quality and lower performance. In addition, we propose and find an asymmetrical effect of disability incongruence, such that LMX quality is worse in dyads in which the supervisor has a disability than in dyads in which the subordinate has a disability. Furthermore, we investigate the moderating role of unit-level climate for inclusion on this relationship and find support for a buffering effect of inclusive climates on the negative incongruence-LMX relationship for scenarios in which the supervisor, but not the subordinate, has a disability. We build relevant theory for the relational demography, disability, LMX, and organizational climate literatures by predicting these effects on the basis of status mechanisms. These findings have important practical implications, as they provide companies with a feasible way to manage their diverse workforce.

Management scholars have noted that leader departures often foreshadow higher turnover intentions (or lower organizational attachment) by subordinates left behind, especially when relationships between the departing leader and the subordinates, or leader-member exchanges (LMX), had been of high quality. In this paper, we posit that the quality of subordinates' relationships with all members of their relational system, not only their leader, must be considered to better understand how leader departures affect subordinates' organizational attachment. Our proposed relationships are illustrated in a theoretical model that includes phenomena at the individual-level (i.e., a subordinate's identification with the departing leader and with his/her organization), at the group-level (i.e., turnover contagion), and at the organizational level (i.e., organization-wide developmental climate). As such, we propose that elucidating how leader-departures affect organizational attachment requires multi-level theorizing and constructs. Theoretical and practical implications of such a 360-degree relational perspective on leader-departure effects are discussed.

Many online are raising questions about a recent spate of public violence, as officials continue to censor discussion.

TOY manufacturer Mattel have removed thousands of its ‘Wicked’-branded dolls off the shelves after discovering a x-rated printing error on the packaging.

The dolls were made in collaboration with the movie adaptation of the award-winning musical ‘Wicked’, fashioned after the characters.

CNBC reported that the website link printed on the dolls’ packaging lead to a pornographic website instead of the ‘Wicked’ movie adaptation’s official website.

Quoting Mattel’s apology statement, the company stated it was “aware” of a misprint on the doll’s packaging, mainly sold in US, intended to direct consumers to the movie’s landing page.

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“We deeply regret this unfortunate error and are taking immediate action to remedy this. Parents are advised that the misprinted, incorrect website is not appropriate for children,” Mattel was quoted as saying.

The company also advised consumers who have already purchased the dolls with the misprint to throw away the packaging or “obsure”, as quoted, the website link.

Following the misprint revelation, several online retailers across the US have pulled the dolls off their shelves as of Monday (Nov 11).

However, it is unclear if the toy manufacturing company will release the dolls with the correct print details or provide stickers to cover the mistakenly printed link.

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Hyundai Rotem, a subsidiary of South Korea’s Hyundai Group, has announced a pioneering development for the Republic of Korea (ROK) Army: a hydrogen-powered K3 main battle tank. Set to be among the most advanced military vehicles in the world, the K3 aims to redefine future warfare by leveraging eco-friendly fuel cells, autonomous technologies, and advanced firepower.

Hyundai Rotem’s K3 project is a collaborative effort with South Korea’s Agency for Defence Development and other national research institutions, with production tentatively scheduled to begin by 2040. The shift to hydrogen marks a historic step in South Korea’s commitment to reduce reliance on traditional combustion engines in defence equipment. The K3’s hydrogen fuel cell will eventually replace the diesel engines of the ROK’s K-series tanks, beginning with hybrid prototypes that combine hydrogen and diesel power.

In an online statement, Hyundai Rotem described the K3 as “a next-generation main battle tank that surpasses all capabilities of today’s MBTs (main battle tanks), optimised for evolving battlefield demands.” Key enhancements to the K3 include autonomous driving, AI-based fire control, and a 130-mm smoothbore main gun for increased preemptive strike capabilities. Additionally, the tank will feature improved stealth capabilities, a reduced heat signature, and the deployment of slave drones to enhance reconnaissance and support combat operations.

Fuel cell technology offers multiple advantages, including quieter operation, faster acceleration, superior fuel efficiency, and reduced maintenance due to fewer moving parts. With minimal heat output and sound, the tank achieves heightened stealth, making it less detectable in combat scenarios. Mobility is also improved, allowing the K3 to maneuver through steep and rugged terrains more effectively.

Designed to operate with a streamlined crew of three—a driver, commander, and gunner—the crew will be secured within a reinforced armoured capsule at the front of the tank. This layout ensures enhanced protection and operational efficiency.

The hydrogen-powered K3 demonstrates South Korea’s commitment to integrating sustainable, high-performance technologies into its military arsenal, setting a benchmark for modern warfare with cleaner and more capable military assets.

Random Photo: CatTaturday

‘Standup Girl’ actor says she has no qualms about beau playing romantic roles

Social media did not disappoint when it came to satirical coverage of the event

Fallen tracks and rubble from the bridge blocking the road below being cleared by authorities

If you ever had the app, odds are you were reading some barely coherent narrative about One Direction or Harry Potter

In a viral interview clip, Khan mentions Bollywood actors he’d like to work with in the future.

The actress shared the news of her husband’s passing on Instagram.

European Commission initially accused Apple of receiving "illegal" tax benefits from Ireland over two decades

The new technology could potentially reduce the weight of laptops by half, make mobile phones as thin as a credit card

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This video tutorial shows how to get the image (attachment) ID to use it in the shortcode for WordPress templates.

The post WordPress. How to get the image (attachment) ID to use it in the shortcode appeared first on Template Monster Help.

Ben Affleck, Matt Damon uncover surprising reason behind business venture

Matt Damon and Ben Affleck revealed the bromantic reason behind starting their business partnership, Artists Equity.

In a recent chat with Deadline, Damon recalled the inspiration behind his partnership...