Reviewerly/exHarmony huggingface dataset:
Strategic Effects of Service Innovation on Financial and Market Performance

The reason for the emphasis on innovation and strategy was the need for organizations to be successful in performance criteria and growth aspirations against competitors. The fact that the competition continues to increase day by day and the entrance to the market is becoming more difficult in every sector shows the fact that companies need to improve their innovation skills in order to ensure sustainability in national or international activities. In the research, the effects of service innovation activities on financial and market performance, as well as strategic analysis and strategic orientation, are examined in banks which have a significant position in the service sector. The surveys were collected from 358 (white-collar) employees at the expert level, after the research model and the sector to be researched were determined. SPSS 25 and AMOS programs were used in the analysis, and the Sobel Test and Hayes process were used for mediation variable analysis. According to survey data, service innovation has a positive impact on both strategic orientation and strategic analysis, as well as financial and market performance. In addition, it is understood that strategic analysis and the mediation effect of strategic orientation variables exist.
Development of a Robotic Palpation System with Suppressing an Influence of Trocar

In this paper, a laparoscopic surgical robot equipped with a new palpation system which can identify the location of an imitation tumor under use of a trocar was developed based on our previous studies. In robotic surgery, when palpation is performed under use of the trocar, it is difficult to realize haptic or tactile sense of the contacted object because the forceps is affected by the trocar. Therefore, suppression of an influence of the trocar on the forceps was attempted by using the Neural Network. In order to verify an effectiveness of the developed palpation system, location identification experiments were carried out, in which identification of the imitation tumor location was attempted for 4 kinds of sample with each different tumor location. The results showed the effectiveness of the neural network, and an error of identification of the imitation tumor location was less than 1mm.
Visual Storytelling with Hierarchical BERT Semantic Guidance

Visual storytelling, which aims at automatically producing a narrative paragraph for photo album, remains quite challenging due to the complexity and diversity of photo album content. In addition, open-domain photo albums cover a broad range of topics and this results in highly variable vocabularies and expression styles to describe photo albums. In this work, a novel teacher-student visual storytelling framework with hierarchical BERT semantic guidance (HBSG) is proposed to address the above-mentioned challenges. The proposed teacher module consists of two joint tasks, namely, word-level latent topic generation and semantic-guided sentence generation. The first task aims to predict the latent topic of the story. As there is no ground-truth topic information, a pre-trained BERT model based on visual contents and annotated stories is utilized to mine topics. Then the topic vector is distilled to a designed image-topic prediction model. In the semantic-guided sentence generation task, HBSG is introduced for two purposes. The first is to narrow down the language complexity across topics, where the co-attention decoder with vision and semantic is designed to leverage the latent topics to induce topic-related language models. The second is to employ sentence semantic as an online external linguistic knowledge teacher module. Finally, an auxiliary loss is devised to transform linguistic knowledge into the language generation model. Extensive experiments are performed to demonstrate the effectiveness of HBSG framework, which surpasses the state-of-the-art approaches evaluated on the VIST test set.
New Perspectives on Thomas Kyd’s Restored Canon

In this note, I explore probabilistic assumptions in the field of early modern authorship attribution studies. I reveal some significant findings concerning the distribution of linguistic items in uncontested plays, which will hopefully lead to more precise approaches towards examining texts for which the authorship is contested. As a case study, I offer new perspectives on the ‘enlarged’ sole-authored Thomas Kyd canon proposed by Brian Vickers: The Spanish Tragedy, Soliman and Perseda, King Leir, Arden of Faversham, Fair Em, and Cornelia.1 Utilizing Pervez Rizvi’s electronic corpus of 527 plays, ‘Collocations and N-grams’,2 MacDonald P. Jackson argues that other plays by the same author tend to share larger numbers of unique formal trigram matches than do plays by different authors.3 The n-gram, ‘I swear by heaven’, which co-occurs with Arden and Cornelia, contains two three-word phrases, ‘I swear by’ and...
Secure and Smart Monitoring of Sensitive Data in Cloud Computing using Effective Cryptographic Scheme

The advantage of storing infinite data without giving any attentiontothe available storage restrictions and the liberty that one possesses to use those data when needed from anywhere in the globe, makes cloud environment the most ideal technology. Cloud hadalso became the preferred platform for storing and transferring the intendeddata. Both individuals and organizations were much comfortable in letting their sensitive data across their own generated cloud environments. But apart from the advantages that the cloud environments have imparted, it also have its own limitations. Limitations like risk of maintaining user’s data privacy, integrity, confidentiality and safety were normally existing while using the cloud environments. Besides allof the above said challenges, transferring of data from organization to cloud servers was considered with major importancein many evolving works. Several algorithms and encryption techniques have been developed currently for securing the operation of data transmission. Along this way, this paper proposes a design for thecloud framework that guarantees secured data transmission to serverfrom the source. This paper utilizes an approach called Honey Bee algorithm for encrypting and decrypting the datato be transmitted to the server. This algorithm is basically an encryption scheme which provides flexibility againstthe potential attacks by delivering a reasonable-looking text. But, the reasonable-looking text is a kind ofplain text generated for every wrong key used by an attacker for decrypting the message. Here a count of five keys will be generatedby the PRNG algorithmright after matching the OTP keys, which will be thenrandomly sent to users. The generated five keys aredeployed to promote additional security by the operation of anonymizationagainst the intruderstrying to access the data while under transmission. Here, in this proposed methodology,user cannot view all of his/her information, whereas the admin can have the full privilege of viewing all information about a user.Furthermore, performance metrics such as Key generation time, Encryption time, Decryption time and Message time were taken for the performance analysis to validate the performance of this proposed methodology with the existing considered methodologies.
Question Answering over Knowledge Base Embeddings with Triples Representation Learning

Question answering based on knowledge graph aims to help users answer natural language questions through the facts in the knowledge graph without the user needing to understand its data structure. This is a challenging task because it is difficult for machines to correctly understand the semantics of the question. For machines to understand semantics correctly, we need to face two challenges. One is that different entities connected by the same predicate. The other one is entity ambiguity. The entity usually has different expressions which makes the number of candidate answers become huge. To solve these problems, we propose an elegant method named TRL-KEQA. It doesn’t directly infer its subject and predicate, but restores the vector representation of the subject and predicate of the problem in KG embedding space. And syntactic analysis is used to construct the connection between the predicate and the entity. This connection is aggregated into the vector representation of the predicate. According to a well-designed joint distance metric, the fact which has learned vector is closest in KG will be returned as the answer. Experiments conducted on widely adopted benchmarks show that the proposed model is superior to the latest KBQA method.
How I Impress Others with My Cantonese

COVER FEATURE HONG KONG How I Impress Others with My Cantonese by Eddie Tay At a dim sum restaurant you’ll need to ask for la jiu jeong (chili sauce), la jiu yeow (chili oil), or dao ban jeong (bean paste sauce) depending on your preference. Try not to use Cantonese after saying hi if you’re paranoid and unsure because that’s a rude word in Cantonese. Siu mei is not siu mai. San fu (priest), san fu (new pants), san fu (uncomfortable/difficult). If you’re not sure just ask for har gow, siu mai, and char siu bao and certainly not phoenix claws unless you like unmanicured chicken feet (which I do, actually). I’m usually given a Chinese menu because I’m visibly Chinese, because I speak Mandarin (though it’s called Putonghua in Hong Kong) better than Cantonese I may be mistaken for a mainland Chinese person but because I took Chinese as a second language in school and scraped by to get into university, I can barely recognize the traditional Chinese characters because in Singapore we use the simplified script. It’s too complicated to explain all these to the confused/irritated waiter in Cantonese or Putonghua so I usually go with har gow, siu mai, and char siu bao. Siu mei is not siu mai. San fu (priest), san fu (new pants), san fu (uncomfortable/difficult). Eddie Tay is a street photographer and poet. He teaches in the Department of English, Chinese University of Hong Kong. He has written four volumes of poetry. His recent book, Anything You Can Get Away With: Creative Practices, plays with the language of poetry, street photography, and creative-writing scholarship. Press Doorbell Please. Photo: Eddie Tay Visit worldlit.org to read Eddie Tay’s poem “Choices.” 64 WLT SPRING 2019 ...
Research on the Construction of Function Model of Smart Sports Venues

In order to improve the utilization rate and service quality of traditional sports venues, this paper adopts field survey method and semi-structured interview method to investigate the construction scheme of new smart sports venues. It is found that the functions of smart stadiums should include three functional modules, smart buildings, smart management and smart services, which respectively solve the three core requirements of automation of building equipment, digitization of daily management and intelligence of mass services. Based on this, this paper attempts to construct the functional structure model of smart stadiums, which has important value and significance for effectively improving the utilization rate of stadiums and improving service quality.
Diagnosis of Alzheimer’s Disease: Methods and Challenges

To explore Alzheimer’s disease, there were many classical machine learning techniques have been used, growing from image decomposition techniques such as principal component analysis through high-complexity algorithms. With the appearance of the deep learning methods, the extraction of high-level abstract features directly from MRI images has become promising to describe the distribution of data in low-dimensional space. Our approach includes training sparse autoencoder (SAE) approach to perform unsupervised feature leaning and prediction of AD. We spot the light on developing a SAE model to learn effective features from the AD dataset and then perform classification using the learned features.
Objectifying Subjectivity

The subjectivity of assessment is a reality that cannot be ignored. It is well understood that this subjectivity is due to the fact that the actors involved in the assessment are human beings, which is to say thinkers. The problem with assessment is not its subjectivity but its potential arbitrariness. To avoid this, the assessing process should be made as transparent as possible, explicit both for the assessors and for the students. It is also mandatory to establish concrete benchmarks allowing systematization and control of the assessment functions, criteria and indicators to be used, as well as the adopted approach. Objectives Both teachers and students should look critically at the subjectivity of the assessment process, regardless of the discipline, functions and procedures under consideration. To propose ways to control this subjectivity and to objectify the assessment process.
DIGITAL INNOVATIONS IN THE EDUCATION BACHELORS PROFESSIONAL TRAINING AS A NEW UKRAINIAN SCHOOLS REQUIREMENT

The article highlights that digital innovations in the training of future teachers is a characteristic of such an organization of educational activities, when consciously, purposefully and effectively uses digital equipment, modern software, technical and information equipment that provides active use of information and communication and multimedia technologies in the educational process; when future teachers are radically different in their willingness to work at school in the new digital educational environment.
Adaptive weight assignment scheme for multi-task learning

Deep learning based models are used regularly in every applications nowadays. Gen- erally we train a single model on a single task. However, we can train multiple tasks on a single model under multi-task learning (MTL) settings. This provides us many beneﬁts like lesser training time, training a single model for multiple tasks, reducing overﬁtting, and improving performances. To train a model in multi-task learning settings we need to sum the loss values from different tasks. In vanilla multi-task learning settings we assign equal weights but since not all tasks are of similar difﬁculty we need to allocate more weight to tasks which are more difﬁcult. Also improper weight assignment reduces the performance of the model. We propose a simple weight assignment scheme in this paper which improves the performance of the model and puts more emphasis on difﬁcult tasks. We tested our methods performance on both image and textual data and also compared performance against two popular weight assignment methods. Empirical results suggest that our proposed method achieves better results compared to other popular methods.
Handling of Krueng Jantho Riverbed Degradation with Groundsill Planning

Krueng Jantho river has an important role in the utilization of water resources, watershed conservation, and control of water damage. Dredging of river material has resulted in damage to the ecological factors of the Krueng Jantho river, specifically the degradation of the riverbed which can trigger the collapse of river banks and bridge pillars. The location under review is located in Alue Gintung Village, Seulimuem District, Aceh Besar Regency. Data and maps collected are watershed maps, river discharge data from the Krueng Aceh water level measurement post (AWLR), and topographical and river cross-section data. The method of calculating the generation of discharge data is used the Markov Chain method, the analysis of flood discharge plans using the Pearson Log type III distribution method, and the groundsill building planning for river bottom management and security. The groundsill building for the 25 yearly discharge is planned to be 80.00 m wide, groundsill 1,00 m high and 4.00 m thick groundsill lighthouse.
Featherweight assisted vulnerability discovery

Predicting vulnerable source code helps to focus the attention of a developer, or a program analysis technique, on those parts of the code that need to be examined with more scrutiny. Recent work proposed the use of function names as semantic cues that can be learned by a deep neural network (DNN) to aid in the hunt for vulnerability of functions. Combining identifier splitting, which we use to split each function name into its constituent words, with a novel frequency-based algorithm, we explore the extent to which the words that make up a function’s name can be used to predict potentially vulnerable functions. In contrast to the lightweight prediction provided by a DNN considering only function names, avoiding the need for a DNN provides featherweight prediction. The underlying idea is that function names that contain certain “dangerous” words are more likely to accompany vulnerable functions. Of course, this assumes that the frequency-based algorithm can be properly tuned to focus on truly dangerous words. Because it is more transparent than a DNN, which behaves as a “black box” and thus provides no insight into the rationalization underlying its decisions, the frequency-based algorithm enables us to investigate the inner workings of the DNN. If successful, this investigation into what the DNN does and does not learn will help us train more effective future models. We empirically evaluate our approach on a heterogeneous dataset containing over 73 000 functions labeled vulnerable, and over 950 000 functions labeled benign. Our analysis shows that words alone account for a significant portion of the DNN’s classification ability. We also find that words are of greatest value in the datasets with a more homogeneous vocabulary. Thus, when working within the scope of a given project, where the vocabulary is unavoidably homogeneous, our approach provides a cheaper, potentially complementary, technique to aid in the hunt for source-code vulnerabilities. Finally, this approach has the advantage that it is viable with orders of magnitude less training data.
PrACTiC: A Predictive Algorithm for Chemoradiotherapy-Induced Cytopenia in Glioblastoma Patients

Chemotherapy-induced cytopenia is the most frequent side effect of chemoradiotherapy in glioblastoma patients which may lead to reduced delivery of treatment. This study aims to develop a predictive model that is able to forecast the cytopenia induced by temozolomide (TMZ) during concomitant chemoradiotherapy.Medical records of 128 patients with newly diagnosed glioblastoma were evaluated to extract the baseline complete blood test before and during the six weeks of chemoradiotherapy to create a dataset for the development of ML models. Using the constructed dataset, different ML algorithms were trained and tested.Our proposed algorithm achieved accuracies of 85.6%, 88.7%, and 89.3% in predicting thrombocytopenia, lymphopenia, and neutropenia, respectively.The algorithm designed and developed in this study, called PrACTiC, showed promising results in the accurate prediction of thrombocytopenia, neutropenia, and lymphopenia induced by TMZ in glioblastoma patients. PrACTiC can provide valuable insight for physicians and help them to make the necessary treatment modifications and prevent the toxicities.
The effect of chemicals on decorative inserts made of minerals and rocks

The decoration of ceremonial clothing is due to the careful choice of decorative materials, especially if it concerns such a specific material as mineral raw materials. Many minerals have physical properties and features of the internal structure, because of which it should be used with caution in the decorative decoration of clothing. The choice of materials mainly depends on the exploitation conditions. Decorative elements of clothing are exposed to friction, impact, and the influence of light weather when worn. The care of clothing can also be affected by mineral raw materials. Cleaning agents can change the appearance and physical properties of decorative inserts. Mineral raw materials have a wide range of mineral varieties that are used as decorative materials, based on this, you can choose a material that meets your requirements.
EU UPDATE OF THE COMPUTER LAW &amp; SECURITY REVIEW

Enterprise (large organisation) computing workloads are moving from ‘on-prem’ to ‘in-cloud’ increasingly quickly, and the cloud is forecast to account for almost half of enterprise IT by 2026, up from 10% today. But the benefits of the enterprise cloud need to be weighed against increasingly burdensome duties around cloud and data security. This comment piece provides a checklist of the sources of enterprise cloud security duties and a checklist of best practices to manage them.
An Overview of Compliance Management

Compliance management seems to supersede all the management functions that an organisation carries out for accomplishment of its objectives. Compliances are basically organizational, legal, social, environmental, ethical and financial standards that aim to protect an organization’s integrity and accountability. Compliance is a high priority issue, failing of which may entail a cost, implicit and/or explicit. A general awareness discussion is attempted here towards compliance and its necessity and benefits including the practical aspects of managing the compliance activities.
AUTOMATIC DETECTION OF ACCESS CONTROL VULNERABILITIES VIA API SPECIFICATION PROCESSING

Objective. Insecure Direct Object Reference (IDOR) or Broken Object Level Authorization (BOLA) are one of the critical type of access control vulnerabilities for modern applications. As a result, an attacker can bypass authorization checks leading to information leakage, account takeover. Our main research goal was to help an application security architect to optimize security design and testing process by giving an algorithm and tool that allows to automatically analyze system API specifications and generate list of possible vulnerabilities and attack vector ready to be used as security non-functional requirements. Method. We conducted a multivocal review of research and conference papers, bug bounty program reports and other grey sources of literature to outline patterns of attacks against IDOR vulnerability. These attacks are collected in groups proceeding with further analysis common attributes between these groups and what features compose the group. Endpoint properties and attack techniques comprise a group of attacks. Mapping between group features and existing OpenAPI specifications is performed to implement a tool for automatic discovery of potentially vulnerable endpoints. Results and practical relevance. In this work, we provide systematization of IDOR/BOLA attack techniques based on literature review, real cases analysis and derive IDOR/BOLA attack groups. We proposed an approach to describe IDOR/BOLA attacks based on OpenAPI specifications properties. We develop an algorithm of potential IDOR/BOLA vulnerabilities detection based on OpenAPI specification processing. We implemented our novel algorithm using Python and evaluated it. The results show that algorithm is resilient and can be used in practice to detect potential IDOR/BOLA vulnerabilities.
Large-aperture collimated wavefront evaluation based on sparse subaperture

针对300 mm口径波长调谐干涉仪的准直波前，提出了基于稀疏子孔径的波前评价方法。该方法利用稀疏孔径的波前数据，构建均匀、等间隔的子孔径排布模型，运用同步拟合算法实现全口径准直波前的重构；通过数值计算分析子孔径间隔、子孔径大小对重构精度的变化规律，得到优化的子孔径排布方式；采用子孔径口径大小为10.8 mm、相邻子孔径中心间距为9.72 mm的优化子孔径排布对300 mm口径准直波前进行稀疏子孔径评价。仿真结果表明：优化后的稀疏子孔径评价波前残差峰谷值（peak valley，PV）为0.001 6<inline-formula><tex-math id="M1">\begin{document}${\rm{\lambda}}$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="9739_M1.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="9739_M1.png"/></alternatives></inline-formula>、残差均方根值（root meam square，RMS）为1.689 3e−4<inline-formula><tex-math id="M2">\begin{document}${\rm{\lambda}}$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="9739_M2.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="9739_M2.png"/></alternatives></inline-formula>。